Search

Insulated gate bipolar transistor (IGBT) module is one of the most prone-to-fail components in the wind power converter (WPC). The reduction of the junction temperature swing by thermal management can improve the reliability of a WPC. Due to the lack of an applicable selection criterion, not many studies on the control target of junction temperature swing were reported. This article proposes a thermal management strategy to find the control target of junction temperature swing. The proposed strategy considers the return on investment (ROI) of thermal management as a quantitative indicator to guide the control target selection. The selected control target enables optimal benefit of the thermal management. Results show that a 1% increase in the total harmonic distortion would extend the lifetime of IGBT module by 0.144 years. Success of the proposed scheme lies in the efficient regulation of the junction temperature swing. Case studies with different mission profiles and experimental tests on a three-phase two-level inverter are presented to validate the proposed method. [ABSTRACT FROM AUTHOR]

Emerging 5G systems will need to seamlessly guarantee novel types of services in a multi-do-main ecosystem. New methodologies of network and infrastructure sharing facilitate the cooperation among the operators, exploiting the core and access sections of the system architecture. Network slicing (NS) is the operators' best technique for building and managing a network. Without NS, the 5G requirements in terms of flexibility, optimal resource utilization, and investment returns cannot materialize. Before slicing is commercially available, different sections of the 5G architecture should be modified to include NS. In this work, we present a novel dynamic radio access network slicing resource sharing method aimed to guarantee optimal service level agreements through the monitoring of each slice tenant's key performance indicators. The experiments are conducted following the 3GPP specifications, and the solution is validated using a testbed based on the main 5G functionalities. [ABSTRACT FROM AUTHOR]

The smart meters installed at the customer premises are one of the main apparatuses promoting the modernization of the distribution systems. These devices collect a huge amount of data, demanding the development of analytic techniques to transform these data into useful information. In addition, by proposing new applications to data supplied by smart meters, more value is added to this equipment, allowing higher return on the associated investments. Utilities can have a business case by increasing their operational efficiency if smart meters are used, for instance, to identify non-technical losses, which represent an important cause of revenue losses. This paper presents a new data analytic technique for detection and location of non-technical losses caused by illegal connections of loads to distribution systems in the presence of smart meters. The data analytic technique relies on bad data analysis, similar to the ones used in state estimation methods, developed specifically for this application. A real 34-bus low voltage system is used to illustrate the main concepts of the proposed algorithm. Systematic tests are also conducted on a real 1682-bus distribution system to evaluate the method performance considering electricity theft caused by medium and low voltage customers. [ABSTRACT FROM AUTHOR]

Dual-channel retailers are increasingly adopting a typical cross-channel return option (CC) to allow online consumers to return their unsatisfied items at physical stores. It is important for retailers to determine whether to introduce this option in addition to the same-channel return option (SC) that requires online purchases to be returned online. To address such challenging issue, we consider a dual-channel retailer and develop theoretical models to derive the optimal return strategy and pricing decisions. To this end, two scenarios, i.e., the SC and CC scenarios, are considered. In the latter scenario, the SC is also allowed. We show that the retailer cannot always benefit from adopting the CC. Specifically, given that consumer online purchase hassle cost is sufficiently low, when the cross-selling profit is sufficiently high, the retailer is better off adopting this option, and vice versa. Adopting this option cannot always help increase the demand, but always increases the return quantity. We also find that the retailer is not always better off adopting a uniform or differential pricing scheme. Interestingly, the retailer benefits from offering a relatively low return service charge, especially when adopting the CC. Our numerical results further show that, the retailer benefits from adopting the CC when the return rate is relatively low or moderate, and vice versa. [ABSTRACT FROM AUTHOR]

The rapid increase in global IP traaffic and the adoption of mobile devices have challenged network service providers to scale and improve infrastructure to meet this new demand. To improve return on investment for scaling networking infrastructure and capitalize on advancements in virtualization technologies, Network Function Virtualization (NFV) has been proposed. NFV does present some newfound security challenges, however, by combining elements of networking and virtualization technology. These challenges include protecting against attacks like remote hypervisor attacks, Denial of Service (DoS) attacks, Virtual Machine (VM) Hopping, and port scanning. Software- Defined Perimeter (SDP) is proposed as a framework to provide logical perimeters around these services, restricting network access and connections to the SDP-enabled Virtual Network Functions (VNFs) to trusted clients only. Several security benefits present themselves as a result of a combined NFV-SDP architecture. The deployment and access control are customize-able, catering to a wide array of user needs. The aforementioned proposed architecture was tested within a virtual environment. The test results show that the combined architecture is indeed resistant to DoS attacks. Additionally, the results lead to a discussion regarding future research and implementation potentials for this architecture. [ABSTRACT FROM AUTHOR]

Retailers are increasingly implementing an online-to-store channel, i.e., buy online and pick up in stores (BOPS), to better target different segments of consumers. It is important for retailers to determine whether to implement such channel in addition to traditional brick-and-mortar (BM) channel or both BM and online channels [double channels (DC)] in a competitive market. To address such a challenging issue, we develop theoretical models to derive the optimal channel strategy for BM and DC retailers, respectively. To this end, we assume that two competing retailers sell two substitutable products to the same group of consumers, and consider two scenarios, i.e., no retailer and both retailers offering BOPS channel. We then extend our analysis to an asymmetric competition case where only one retailer offers such channel. We find that BM retailers and DC retailers need to be cautious when implementing this BOPS channel in a competitive market. Specifically, we present the conditions under which retailers can benefit from implementing BOPS channel. Interestingly, products with a relatively high return rate are not suitable for BOPS option for BM retailers, but may benefit DC retailers. This provides an important insight that retailers should carefully choose the right products to sell through BOPS channel. [ABSTRACT FROM AUTHOR]

Probabilistic representations of movement primitives open important new possibilities for machine learning in robotics. These representations are able to capture the variability of the demonstrations from a teacher as a probability distribution over trajectories, providing a sensible region of exploration and the ability to adapt to changes in the robot environment. However, to be able to capture variability and correlations between different joints, a probabilistic movement primitive requires the estimation of a larger number of parameters compared to their deterministic counterparts, which focus on modeling only the mean behavior. In this article, we make use of prior distributions over the parameters of a probabilistic movement primitive to make robust estimates of the parameters with few training instances. In addition, we introduce general purpose operators to adapt movement primitives in joint and task space. The proposed training method and adaptation operators are tested in a coffee preparation and in robot table tennis task. In the coffee preparation task we evaluate the generalization performance to changes in the location of the coffee grinder and brewing chamber in a target area, achieving the desired behavior after only two demonstrations. In the table tennis task we evaluate the hit and return rates, outperforming previous approaches while using fewer task specific heuristics. [ABSTRACT FROM AUTHOR]

The European directive “Clean Energy for All Europeans” depicts for 2030 a new scenario for low-voltage distribution grids, where each end user will have the right to trade energy and offer demand response in the electrical market either individually or in aggregation with others. This creates a new perspective for renewable energy sources (RESs) and energy storage systems (ESSs), which become key elements to allow end users playing a substantial role in the electrical market. While many distributed RESs are already in place in low-voltage grids, the ESSs are still in infancy and will become a crucial asset of future microgrids. The optimal selection of ESS ratings and location within an energy network is still an open problem, and its solution can impact considerably the grid performance and return of investment for energy sources and distribution infrastructure. This paper presents a general methodology to select the best location and ratings of energy storage units complying with the needs of local area energy networks. The aim is to support end users and aggregators to plan their investments and operate the grid so as to attain the role and functionality envisioned by the European directive. [ABSTRACT FROM AUTHOR]

The rapid development of bike-sharing systems has brought people enormous convenience during the past decade. On the other hand, high transport flexibility gives rise to problems for both users and operators. For users, dynamic distribution of shared bikes caused by uneven user demand often leads to the check in or check out service unavailable at some stations. For operators, unbalanced bike usage comes with more bike broken and growing maintenance cost. In this paper, we consider enhancing user experiences and rebalance bicycle utilization by directing users to different stations with a higher success rate of rental and return. For the first time, we devise a trip advisor that recommends bike check-in and check-out stations with joint consideration of service quality and bicycle utilization. To ensure service quality, we firstly predict the user demand of each station to obtain the success rate of rental and return in the future. Experiments indicate that the precision of our method is as much as 0.826, which has raised by 25.9 percent as compared with that of the historical average method. To rebalance bike usage, from historical data, we identify that biased bike usage is rooted from circumscribed bicycle circulation among few active stations. Therefore, with defined station activeness, we optimize the bike circulation by leading users to shift bikes between highly active stations and inactive ones. We extensively evaluate the performance of our design through real-world datasets. Evaluation results show that the percentage of frequently used bikes decreases by 33.6 percent on usage number and 28.6 percent on usage time. [ABSTRACT FROM AUTHOR]

Online advertising delivers promotional marketing messages to consumers through online media. Advertisers often have the desire to optimize their advertising spending strategies in order to gain the highest return on investment and maximize their key performance indicator. To build accurate advertisement performance predictive models, it is crucial to detect the change-points in the historical data and apply appropriate strategies to address a data pattern shift problem. However, with sparse data, which is common in online advertising and some other applications, online change-point detection is very challenging. We present a novel collaborated online change-point detection method in this paper. Through efficiently leveraging and coordinating with auxiliary time series, we can quickly and accurately identify the change-points in sparse and noisy time series. Simulation studies as well as real data experiments have justified the proposed method’s effectiveness in detecting change-points in sparse time series. Therefore, it can be used to improve the accuracy of predictive models. [ABSTRACT FROM AUTHOR]

In order to maintain a competitive edge in the face of increasing global competition in the semiconductor memory market, device makers in the IC memory industry need to continuously improve their productivity by implementing novel manufacturing strategies that are applicable to the rapid market changes characteristic of the industry. Conventional wafer productivity strategies typically only focus on maximizing gross die out, a strategy which does not address wafer productivity for profitability, i.e., return on investment (ROI), with respect to current market situations, since ROI is significantly influenced not only by the number of gross die out, but also by other factors both within the manufacturing line, for example by the number of photolithography shots per wafer, and also by external factors, most importantly the market price of the memory devices being produced. In this paper, we propose a novel productivity model based on ROI and use the ROI-based model to evaluate wafer maps and thereby to determine optimal chip sizes for maximizing fab productivity. To evaluate wafer productivity accurately, we predicted yields from various wafer map configurations using deep neural networks, and, to search for productivity-maximal wafer maps in extremely large search spaces, we adopted differential evolution as the optimization technique. Comparison results have demonstrated that our proposed method effectively improved wafer productivity by up to 7.96%, in contrast with the old method. By incorporating these market-oriented indicators into standard yield models, we offer a new way for memory device manufacturers to maximize productivity and maintain competitive advantage for their semiconductor fabrication lines. [ABSTRACT FROM AUTHOR]

Using several factors essential to determine the income of a knowledge organization, we formulate a mathematical programming problem for allocating the firm's capital budget between organizational and physical capitals. We solve this problem to obtain an analytically tractable and easy to implement decision rule to enhance the firm's expected income and, subsequently, value. The model applies interconnections of these capitals and their constituent variables in the context of the firm's valuation through the growth of its operating income. Finally, we illustrate our findings by studying the capital allocations of IBM, Microsoft, Oracle, SAP, Symantec, EMC Corporation, Hewlett-Packard, and CA Technologies, which constitute eight of the ten of the world's largest software companies. We use the data from their financial statements covering the period 1991–2015, and find that the companies that had a stable policy setting higher priority on their budget for organizational capital enjoyed superior financial performance over the 25 years of our study. Professionals in the field of engineering and technology management can benefit greatly from the findings of this study as they can use it to justify the firm's capital investment budget for organizational capital, because it typically includes items of greater interest to them such as the intangibles, intellectual property, and human capital. The paper gives directions for future research in the relatively new area of organizational capital. [ABSTRACT FROM AUTHOR]

This paper will present a new approach that is advantageous to medium-voltage (MV) distribution design configurations for large industrial and power distribution system configurations [specifically main-tie-main (MTM)] for large industrial and power station installations. Sixty years of traditional low-cost design approaches (typical MTM and operated with open tiebreaker) are re-evaluated to demonstrate that traditional low capital cost design may miss improvement opportunities. Those opportunities can be major capital expenditure reduction, power quality improvement, MV motor soft starter deletion, and improved system stability to name a few. Many designers may not have considered the component interrelationships and/or their tradeoffs when in an integrated system. The designer and/or user should consider the advantages of higher short-circuit capacity (SCC) systems by integrating fault current limiters and MV switchgear. Utilizing higher SCC systems permits power system designer optimization opportunities not possible before using conventional design methods. This paper will provide documentation of substantial savings of capital investment and energy under higher SCC conditions. The savings in one system component will offset another's increased cost. An obvious benefit of stiffer systems is ease of direct-on-line starting of large motor-driven compressor trains. The future need for motor soft starters minimizing system impact will be challenged. This paper may change fundamental system design methodology for system designers by removing several performance tradeoffs. This paper, in its original version, was previously presented at the 2010 IEEE/IAS/Petroleum Chemical Industry Conference. It was expanded with new sections for the 2017 IEEE/Industry Applications Society (IAS)/Pulp, Paper Forestry Industries Conference to include pre-emptive prefault adjustable power quality and multisourced networked power systems. [ABSTRACT FROM PUBLISHER]

R3 has built a global consortium to focus on the application of distributed-ledger technology (DLT), which can help banks combat low return on equity and alleviate pressure on their operating costs. The authors explain the conditions that led to interest in DLT and introduce Corda, R3’s shared ledger for recording and managing financial agreements. [ABSTRACT FROM AUTHOR]

This paper assesses the feasibility of three-phase pulse-width modulated (PWM) three-level voltage-source converters (VSC), namely neutral-point-clamped (3L-NPC) and T-type (3L-T) as alternatives to two-level converter (2L-VSC) for low-voltage multimegawatt renewable energy grid-connected converter applications. For this purpose, a novel design algorithm that takes switching frequency, capacity factor, modulation index, PWM scheme(s), and converter topology(ies) as input is unveiled to provide the design steps and performance benchmark for the specified topologies and modulation methods. Design of the LCL filter is also addressed, and equivalent output ripple performance criteria is used to benchmark the converter performances for a set of selected filter parameters. Main contribution of this algorithm is that it covers cost and operating factors of the design during the hardware design phase by introducing/modifying the terms of total cost of ownership (TCO) and return on investment (ROI) time considering the major energy markets. The design is detailed for 1-MVA system, and the results are summarized for 0.5 and 2-MVA systems. The study shows that 3L topologies perform more efficiently than 2L-VSC (T-type being the most prominent—with the shortest ROI), whereas the difference becomes much more prominent at the multimegawatt range, provided that all three yield equivalent outputs fulfilling the stringent grid codes. [ABSTRACT FROM PUBLISHER]

Prosperity of the online keyword auctions greatly facilitates the penetration of search-engine marketing in various industries. However, the current operation rules of the search engine make it very difficult for those inexperienced advertisers to make sound bids without the support of powerful tools. Therefore, many studies have been conducted to help advertisers understand such dynamic, infinite, and opaque auction situation, and obtain as good as possible bidding result. This paper, focusing on predicting the return on investment (ROI) of a keyword portfolio, develops a hierarchical Bayesian network (BN) model to forecast keyword auctions’ performance. Few papers directly predict the ROI of a keyword portfolio. This approach effectively echoes advertisers’ expectation for a keyword auction by choosing the right keywords and bids to achieve the desired outcome. The building blocks of the prediction model, such as bid and rank, are organized in a tree-shaped structure with a set of joint conditional probabilities. To infer the posterior probabilities of the predictors, a Bayesian parameter-learning algorithm is conducted after validating the network's structural relationships. The empirical study demonstrates that the prediction model is appropriate and effective for keyword auctions. Moreover, the proposed hierarchical BN model shows a higher accuracy than the popular prediction approach—the back-propagation artificial neural network. [ABSTRACT FROM PUBLISHER]

In this paper, a new automated approach for the extraction of aboveground circular storage structures from near-nadir very high resolution satellite imagery is proposed. The approach focuses on the cast shadows of the circular structures and splits the boundaries of the shadow regions into curved segments using the chord-to-point distance accumulation technique. Thereafter, the curved segments are tested with newly developed constraints for being a part of a circular structure, and the ones that pass all of the constraints are considered as candidates. The reciprocal relations between the candidate segments are assessed by a developed mutual evidence test, and for the candidates that expose a relation, a robust circle fitting is applied. For the candidates having no such relations, an approach that further validates the circle evidence is developed. The approach consists in introducing regions-of-interest (ROIs) for each candidate segment and applying a circular Hough transform in each ROI, where the parameters of the transform are self-controlled. Experiments performed on 12 challenging Geoeye-1 test images selected from industrial areas reveal that the proposed approach accurately detects aboveground circular structures in complex industrial environments. Besides, the comparison of the results of the proposed approach with the results of two different circle detection approaches verifies the success and the robustness of the approach developed. [ABSTRACT FROM PUBLISHER]

Over the past decade, virtualization technology has taken the world over by storm. This explosion has led the industry to market already existing virtualization technology, also known as infrastructure as a service, with the buzz word cloud computing. There has been much promise for return on investment, leading to significant research and a myriad of innovations in this domain. Despite the best efforts of industry leaders, there are still challenges with respect to enterprise security and policy management. In this article, we present the fundamentals of machine virtualization and simple network virtualization. We then provide a brief overview of network policy management throughout the evolution of virtualization. We then segue into current industry trends and some of its novel innovations. Throughout the article we discuss the challenges with respect to policy management. We finalize by analyzing existing solutions and building on them and those of the Distributed Management Task Force. [ABSTRACT FROM PUBLISHER]

This work develops a stochastic optimization model for the creation of a bidding strategy for a generator in an energy call option auction similar to Brazil's, i.e., where the bidder can offer both the premium and the strike price. The objective of the model is to maximize the bidder's competitiveness while ensuring that the project's target rate of return is achieved with a given probability, for example 95%. The problem's complexity is compounded by uncertainties in fuel supply and the need to switch between fuels. The generators face the conundrum of bidding a single strike price to cover the expenses generated by using multiple types of fuels. We address the problem of finding bidding strategies which, taking into account uncertainty in fuel supply and risk constraints, set the combination of strike price and option premium that ensure a desired risk-adjusted return for greenfield dual-fuel thermal plants. [ABSTRACT FROM PUBLISHER]

The article details a proposal for an object recognition processor with neuro-fuzzy controller (NFC) that mimics human visual system resulting in intelligent Return on Investment (ROI) estimates and reduced processor's power consumption. The six-engineer team from the Korea Advanced State of Science and Technology proposes a single instruction, multiple data (SIMD) processor for object recognition, using NEC's IMAP-CE and NXP's XETAL II. For descriptor generation and database matching processing, the team proposes a multiple instruction, multiple data (MIMD) processor that employs coarse-grained processing elements and a memory-centric network-on-chip (NOC). It also details the NFC's design that include a neuro-fuzzy visual predictor (NF-VP) and task/power management unit.

Prognostics and Health Management (PHM) provides opportunities for lowering sustainment costs, improving maintenance decision-making, and providing product usage feedback into the product design and validation process. However, support for PHM is predicated on the articulation of clear business cases that quantify the expected cost and benefits of its implementation. The realization of PHM requires implementation at different levels of scale, and complexity. The maturity, robustness, and applicability of the underlying predictive algorithms impact the overall efficacy of PHM within an enterprise. The utility of PHM to inform decision-makers within tight scheduling constraints, and under different operational profiles likewise affects the cost avoidance that can be realized. This paper discusses the calculation of Return on Investment (ROl) for PHM activities, and presents a study conducted using a stochastic discrete event simulation model to deter- mine the potential ROl offered by electronics PHM. The case study of a multifunctional display in a Boeing 737 compares the life cycle costs of a system employing unscheduled maintenance to the same system using a precursor to failure PHM approach. [ABSTRACT FROM AUTHOR]

This paper presents a new and improved solution for random yield improvement at the post-routing stage. The proposed solution is better suited for current processes, where a clustering effect has been observed resulting in differing particle densities in the metal and empty regions of the chip. To account for this clustering effect, we introduce the concept of weighted critical area to serve as a proxy for random yield loss. A new algorithm for weighted critical area minimization is also introduced. The proposed optimization solution derives a weighted critical area based on the user-specified particle densities. It then uses this weighted critical area information to dynamically select the appropriate critical area reduction technique in each local region to guarantee a reduction of the weighted critical area in both the local region and the whole layer. This makes the algorithm flexible and readily applicable to different process lines. It consistently improves the random yield irrespective of the particle densities in the metal and empty regions of the chip. [ABSTRACT FROM AUTHOR]

The issue of developing a model to estimate field reliability from process yield has received a growing interest in recent years. Thus far, only Poisson and negative binomial relationships have been obtained, assuming that the number of yield defects is independent of the number of reliability defects in a device. In this paper, we derived explicit yield-reliability relationships for various defect density, such as Erlang, uniform, and triangle distributions, using a multinomial distribution to consider a correlation between the number of yield defects, and the number of reliability defects. The proposed model has advantages over previous models for any defect density distribution to determine the optimal burn-in time. [ABSTRACT FROM AUTHOR]

The article discusses the impact of recommendation technology on electronic commerce. The approach applies complex algorithm that evaluates volumes of data and products that consumers might want to purchase in accordance with their preferences and online shopping options. Several technology vendors including AgentArts, Google Inc., and Amazon.com Inc., have created new revenue opportunities and improved customer retention. However, investing in recommendation systems incurs high hardware and software installation costs, while return on investment is difficult to measure.

The cost of reticles is growing twice as fast as the overall cost of new process development for technologies beyond the 100-nm node [1], [2]. In order for the integrated circuit design to continuously benefit from the shrinkpath in alignment with Moore's law [3], the industry should explore cost-effective approaches for the mask data [(intellectual property (IP)] placement alternative to the standard methodology of one mask for one layer of one product [4]. The implementation of multi-IP placements, using multilayer or multiproduct (shuttle) masks, is based on complex technical and economical analysis to maximize mask return on investment (ROI) over the product lifetime. The key criteria include the ability to match layers or products on one plate with respect to the CD control and pattern density and the expected time or fab volume prior to the conversion to the dedicated mask set for successful products. This work analyzes the links between the IP content of the mask, the product market price, and the wafer volume. As an example, by taking into account the cost of the exposure and of the mask, one can show that for 100-nm technology, positive ROI would be achieved for a product or test vehicle with volume depending on the architecture of the multi- layer mask set. We compare the key challenges of the two basic multi-IP mask approaches, the multilayer and the multiproduct masks, and discuss the best conditions for their implementation. Directions for future research are also proposed. [ABSTRACT FROM AUTHOR]

The most recognized return-on-investment (ROI) drivers include the value to users; the cost of development, maintenance, upgrades, and customer support; and the risks of project failure, budget overrun, and revenue shortfall. This article focuses on ROl issues related to positioning software in the marketplaces. Rather than discuss contracted software development for specific customers or open-source software efforts, the author emphasizes the uncertainties and strategic issues that suppliers encounter in selling or licensing software in the general marketplace. These issues are categorized by the standard ROI measures of revenue, cost, and risk. Revenue is affected by many factors, including pricing strategies and unit sales. All these factors strongly depend on design decisions affecting customer-perceived value and customer-incurred costs, as well as the status of competition. Increasing value and satisfaction for customers is critical for remaining competitive but often isn't sufficient to take market share away from an established competitor. Encouraging complementary solutions from other vendors increases value, although with little differentiation from competitors who can exploit the same complements. INSET: Further Reading..

In most organizations, proposed investments in software dependability compete for limited resources with proposed investments in software and system functionality, response time, adaptability, speed development, ease of use, and other system capabilities. The lack of good return on-investment (ROI) models for software dependability makes determining the overall business case for dependability investments difficult. So, with a weak business case, investments in software dependability and resulting system dependability are frequently inadequate. Because different stakeholders depend on different system capabilities in different situations, the business case for dependability must deal with multiple situation-dependent attribute values. Dependability models will need to support stakeholders in determining their desired levels for each dependability attribute and estimating the cost, value, and ROI for achieving those. those. At the University of Southern California, researchers have developed software cost-and quality-estimation models, a value-based software engineering process methods, and used these models and the value-based approach to develop an Information Dependability Attribute Value Estimation model. INSET: Related Work..

Software process improvement (SPI) has been on the agenda of both academics and practitioners. Many companies have invested large sums of money in improving their software processes, and several research papers document SPI's effectiveness. SPI aims to create more effective and efficient software development and maintenance by structuring and optimizing processes. SPI assumes that a well-managed organization with a defined engineering process is more likely to produce products that consistently meet the purchaser's requirements within schedule and budget than a poorly managed organization with no such engineering process. Like any change in an organization, SPI is an investment for which the benefits should exceed the cost. One frequent argument in software practice is that measuring SPI's benefits is impossible, or at least difficult. Organizations find it relatively easy to measure cost by measuring effort but have trouble measuring benefits. However, this is owing to a serious misunderstanding of cost measurement: costs are much broader than effort alone. Making explicit return on investment (ROI) calculations is therefore crucial for SPI because it's an investment with significant cost and sometimes invisible benefits. The ROI should therefore be visible as well to avoid incorrect intuitive evaluations.

Product line engineering has become an important and widely used approach for efficiently developing portfolios of software products. The idea is to develop a set of products as a single, coherent development task from a core asset base, a collection of artifacts specifically designed for use across a portfolio. This approach produces order-of-magnitude economic improvements compared to one-at-a-time software system development. Because the product line approach isn't limited to specific technical properties of the planned software but rather focuses on economic characteristics, high return on investment has become the anthem of the approach's protagonists. Despite this focus on ROl, most of the economic arguments for the product line community are based on singular data points derived from case studies or on reasonableness and simplistic cost curves. A manager must describe the situations in which the model can be applied. Almost all product line adoption scenarios involve fielding a set of existing or planned products as one or more product lines.

This article focuses on the significance of return on investment (ROI) policy in the computer software industry. On the contrary, ROI analysis aim to achieve clarity in the decision-making process. A robust economic and strategic analysis can help answer these questions. If a firm strategy to achieve competitive advantage based on higher customer satisfaction at corresponding higher prices, then it can argue for a certain level and type of investment in quality. A competitive strategy based on lower production costs and low prices might lead to targeting the investment in quality to specific parts of the software product or service. In this way, the value of increasing software quality is framed in terms that senior management can understand and use to make informed decisions. The ROl calculation organizes a project's costs and benefits, into a useful profitability measure. But this measure alone doesn't capture two essential ingredients of any serious economic analysis: time and risk.

Many contemporary markets, particularly markets of information technology products and information services, are characterized by increasing returns, including those resulting from bandwagon and network effects. At the same time, in larger firms, innovation often takes place in distinct units that are semi-autonomous and that have the responsibility for more than one phase in the product development process. In the most extreme case, a separate profit center is created within which research and development (R&D), production, marketing, and related activities are fully integrated and that has its own responsibility for external relations: an internal innovative venture. The central issue in this paper is the relation between the way firms organize their innovative activities and the market dynamics caused by bandwagon and network effects. We focus on the decision-making actors and we propose a categorization of causes of increasing returns and definitions of bandwagon and network effects that are consistent with this aim. We investigate the extent of internal autonomy of the unit, the extent of the integration of R&D, marketing and other activities in the product development process, and the extent of external autonomy. Three cases of projects creating software products, two of them in the same firm, demonstrate that the organization of innovation and the dynamics of the market are mutually dependent. More in particular, we hold that higher autonomy of teams, particularly in managing external relations, is important to cope with and manage bandwagon and network effects. [ABSTRACT FROM AUTHOR]

Presents an adaptive supervised learning decision (ASLD) trading system to optimize an expected returns of investment without considering risks. Overview of a standard Markowian portfolio optimization (SMPO); List of training and operation procedures of the proposed ASLD systems; Comparison of the system and SMPO.

The article discusses why software development corporations have to increase speed and reduce cycle time to remain competitive. A first to market advantage gains customers and increases market share if a solution is introduced faster into the market, from a technology perspective. From a financial viewpoint, the earlier a product is introduced into the market, the sooner the return on investment is realized. From a marketing view, a company able to move idea to product faster is commonly seen as a market leader and can command a premium on its goods.

The article offers updates on an article titled "Measuring the Return on Investment (ROI) of Software Process Improvement (SPI)" which appeared in the May/June 2004 issue of "IEEE Software." In the 2004 article, the author made three contributions with regard to cost measurements and financial benefits of SPI. After five years, the author stresses on finding ways to measure the financial value and quantify the intangible benefits of SPI. He suggests adoption of Six Sigma strategy for software engineering.

The article discusses the importance of subjective quality issues in software development process. It was believed that quantified quality requirements have a clear return on investment (ROI) for increasing stakeholder value. However, in most project teams worldwide, quantified quality requirements are obviously missing from the results. The project's failure was a basic process failure and that most projects succeed or fail due to three main factors, lack of good sponsor, lack of interaction with real users and lack of qualified lead designer. In addition, many quality requirements cannot be known until users review the system.

This column discusses the irony of government funding of science--that is, that governments tend to fund scientific research in areas where returns are believed to be high, but where there's little data to confirm or refute this belief. The author illustrates these concepts using the example of the server software Apache. [ABSTRACT FROM PUBLISHER]

The article introduces a series of articles on prognostics and health management, which were presented at the 1st International Institute of Electrical and Electronics Engineers (IEEE) Prognostics and Health Management (PHM) 2008 Conference. They include the precursor parameters to develop a physics-of-failure approach, a methodology to build a damage model, and the calculation of return on investment (ROI) for PHM activities.

The article presents information on system concepts that assists one in designing more innovative software systems. By using system concepts one can simplify the way one determine, handle, and communicate the requirements during software development. The system concept both binds the problem, requirements, and possible solutions and functions. If one don't have time for comprehensive requirements work, try to figure out the system concept. Creating something simple and tangible to help you understand and communicate what your project is all about is often the shortcut that you need. This should be a skill in an requirements engineer's repertoire. The concise description synthesizes the problem's essence, requirements, projected solution, cost and return on investment. System concepts may provide an analogy or metaphor to capture the idea. System concept acts as a project's gist. System concept is a stating point to engineers in many fields. Thus, searching for system concept may be integral to any software development project.

The article discusses the problem of return on Information Technology investment (ROI). It discusses ROI in reference to the article "IT Doesn't Matter," published by Nicholas G. Carr on May 2003. Besides this it also discusses the effects of ROI on software engineering. Software project cost estimation is major part however, so are Information Technology (IT) assessments. Other relevant areas include IT governance, auditing, due diligence, outsourcing, portfolio management, productivity, value, project business impact assessment, and project adoption impact assessment. IEEE International Conference on Exploring Quantifiable Information on Technology Yields as planned. The conference's broad objective was to promote the development and dissemination of software engineering and IT-centered approach. This was not only limited to new projects but also to existing software projects. In 2003, Chris Verhoef of Vrije University, in its speech at the IEEE International Workshop on Source Code Analysis and Manipulation, claimed that there was little evidence of a positive correlation between IT investment and return on shareholders' investment.

In a cloud computing environment, dynamic resource allocation and reallocation are keys for accommodating unpredictable demands and, ultimately, contribute to investment return. This article discusses this process in the context of distributed clouds, which are seen as systems where application developers can selectively lease geographically distributed resources. This article highlights and categorizes the main challenges inherent to the resource allocation process particular to distributed clouds, offering a stepwise view of this process that covers the initial modeling phase through to the optimization phase. [ABSTRACT FROM PUBLISHER]

The security of the international maritime supply chain and United States ports is vital to the nation?s economy. Terrorists may exploit this supply chain to smuggle illicit people or material into the United States. This scenario, the terrorist transfer threat, has potentially catastrophic consequences. Lewis?s Model Based Risk Assessment software applies network theory to analyze terrorist threats against critical infrastructure systems. This article adapts MBRA to model the terrorist transfer threat?s propagation through the maritime supply chain. MBRA originally applied fault trees to model the inherited vulnerability of a network node based on the logic gate between it and lower layers of nodes (De Morgan?s Law). The author adapts MBRA to incorporate the organic vulnerability for each transfer threat network node in addition to the inherited vulnerability in order to model the decreased likelihood of the transfer threat propagating through the (supply chain) network. This adaptation produces recommendations for optimizing budget allocations across nodes to minimize overall network risk (measured in dollars). It can also show how subsequent manual budget reallocation can change network risk. The MBRA application uses emergent behavior to allocate money at random until equilibrium is reached and network risk is minimized. Return on investment for each network node is also calculated, representing how much network risk is reduced per dollar spent at that node. MBRA networks are indifferent as to whether intermediate or target nodes have maritime locations. Thus, the adapted approach has utility for both maritime and non-maritime homeland security authorities. [ABSTRACT FROM PUBLISHER]

One can evaluate software process imrovement's (SPI) return on investment (ROI) by dividing a financial representation of benefits by a financial representation of the cost. A limited number of publications contain concrete data for calculating ROI of SPI. This article presents a statistical table, which shows that organizations report an ROI of SPI ranging from 1.5 to 19, for every invested dollar. The average ROI is 7 and the median of the data is 6.6. Although any SPI undertaking's ROI depends on many influencing factors, it appears that a proper estimation of for an SPI ROI lies between 4 and 10. However the literature contains limited evidence that these ROIs will occur, when one uses a specific SPI. The best one can obtain, with studies focusing only on process factors, is strong evidence that SPI is associated with some benefits or that organizations could benefit from SPI activities. Although the publications, on SPI's costs and benefits are written by respected researchers and have been through severe reviewing processes, one must consider some limitations to the reported data.

Basic financial and economic concepts underlying ROI appear in introductory corporate finance books. For example, relevant chapters on capital budgeting and risk and return in the book "Fundamentals of Corporate Finance." The article "Annals of Software Engineering, provides a concise introduction to these concepts and the fundamentals of option pricing theory in the software engineering context. The book "Competitive Strategy," by Michael Porter, presents a standard text on competitive strategy. "Value-Based Software Engineering," by Barry Boehm, is a comprehensive reference on software engineering economics, which provides a solid foundation for understanding the concept of return on investment, in the software context. An excellent reference on ROI, for software quality is Haled El-Embalm's book "The ROI From Software Quality: An Executive Briefing," includes several ROI calculation examples for inspection, risk assessment, test-driven development and defect detection. Most existing literature on software engineering economics focuses on process or business decisions, so works that address technical decisions are scarce.

This article presents a brief information on several articles, related to the computer software industry, published in the May 2004 issue of the periodical "IEEE Software." One article deals with calculating return on investment (ROI) for software product lines. The product line engineering approach can improve the ROl from a set of products. Because product lines emphasize economic optimization, the need for ROl calculations is particularly important. In the current IT environment, organizations are no longer willing to invest in software development without clear expectations for returns, and they're demanding those returns in much less time. This clearly challenges the development community to change the way of doing business. In another article, authors describe Information Dependability Attribute Value Estimation model, which helps users reason about the ROl of software dependability investments. The relative ROl for achieving the desired values for dependability attributes is measured and helps select the most effective software dependability strategies.

This article presents the author's note on the current buyer trend in the software market. The author, who also happens to be newly elected Editor-in-Chief (EiC), of the journal IEEE Network, first introduces himself and extends his heartiest thanks to the previous EiCs for their services to the magazine. He intimates about the marketplace being more service oriented as there is more emphasis on return on investment among the buyers of information technology. The buyers are moving away from merely purchasing the services for the sake of technology itself, instead they focus on service oriented end-to end solutions that provide tangible added value to their bottomline and their customers.