Building trustworthy software agents

As agents become more active and sophisticated, the implications of their actions become more serious. With today's GUIs, user and software errors can often be easily fixed or undone. An agent performing actions on behalf of a user could make errors that are very difficult to "undo", and, depending on the agent's complexity, it might not be clear what went wrong. Moreover, for agents to operate effectively and truly act on their users' behalf, they might need confidential or sensitive information. This includes financial details and personal contact information. Thus, along with the excitement about agents and what they can do, there is concern about the resulting security and privacy issues. It is not enough to assume that well-designed software agents will provide the security and privacy users need; assurances and assumptions about security and privacy need to be made explicit. This article proposes a model of the factors that determine agent acceptance, based on earlier work on user attitudes toward e-commerce transactions, in which feelings of trust and perceptions of risk combine in opposite directions to determine a user's final acceptance of an agent technology.     

Pervasive computing goes to work: interfacing to the enterprise

The paperless office is an idea whose time has come, and come, and come again. To see how pervasive computing applications might bring some substance to this dream, the author spoke recently with key managers and technologists at McKesson Corporation (San Francisco), a healthcare supplier, service, and technology company with US$50 billion in sales last year, and also at AvantGo (Hayward, Calif.), a provider of mobile infrastructure software and services. For the past several years, McKesson has used mobility middleware developed by AvantGo to deploy major supply chain applications with thousands of pervasive clients and multiple servers that replace existing paper-based tracking systems. According to McKesson's managers, their system greatly reduced errors and associated costs caused by redelivery or loss of valuable products, giving McKesson a solid return on its investment.     

Using human error information for error prevention

Developing error-free software requirements is of critical importance to the success of a software project. Problems that occur during requirements collection and specification, if not fixed early, are costly to fix later. Therefore, it is important to develop techniques that help requirements engineers detect and prevent requirements problems. As a human-centric activity, requirements engineering can be influenced by psychological research about human errors, which are the failings of human cognition during the process of planning and executinge a task. We have employed human error research to describe the types of problems that occur during requirements engineering. The goals of this research are: (1) to evaluate whether understanding human errors contributes to the prevention of errors and concomitant faults during requirements engineering and (2) to identify error prevention techniques used in industrial practice. We conducted a controlled classroom experiment to evaluate the benefits that knowledge of errors has on error prevention. We then analyzed data from two industrial surveys to identify specific prevention and mitigation approaches employed in practice. The classroom study showed that the better a requirements engineer understands human errors, the fewer errors and concomitant faults that engineer makes when developing a new requirements document. Furthermore, different types of Human Errors have different impacts on fault prevention. The industry study results identified prevention and mitigation mechanisms for each error type. Human error information is useful for fault prevention during requirements engineering. There are practices that requirements engineers can employ to prevent or mitigate specific human errors.     

Observations of Fallibility in Applications of Modern Programming Methodologies

Errors, inconsistencies, or confusing points are noted in a variety of published algorithms, many of which are being used as examples in formulating or teaching principles of such modern programming methodologies as formal specification, systematic construction, and correctness proving. Common properties of these points of contention are abstracted. These properties are then used to pinpoint possible causes of the errors and to formulate general guidelines which might help to avoid further errors. The common characteristic of mathematical rigor and reasoning in these examples is noted, leading to some discussion about fallibility in mathematics, and its relationship to fallibility in these programming methodologies. The overriding goal is to cast a more realistic perspective on the methodologies, particularly with respect to older methodologies, such as testing, and to provide constructive recommendations for their improvement.     

Decision making under uncertainty in a decision support system for the Red River

Decision support systems (DSSs) are increasingly being used in water management for the evaluation of impacts of policy measures under different scenarios. The exact impacts generally are unknown and surrounded with considerable uncertainties. It may therefore be difficult to make a selection of measures relevant for a particular water management problem. In order to support policy makers to make a strategic selection between different measures in a DSS while taking uncertainty into account, a methodology for the ranking of measures has been developed. The methodology has been applied to a pilot DSS for flood control in the Red River basin in Vietnam and China. The decision variable is the total flood damage and possible flood reducing measures are dike heightening, reforestation and the construction of a retention basin. The methodology consists of a Monte Carlo uncertainty analysis employing Latin Hypercube Sampling and a ranking procedure based on the significance of the difference between output distributions for different measures. The mean flood damage in the base situation is about 2.2 billion US$ for the year 1996 with a standard deviation due to parameter uncertainty of about 1 billion US$. Selected applications of the measures reforestation, dike heightening and the construction of a retention basin reduce the flood damage by about 5, 55 and 300 million US$, respectively. The construction of a retention basin significantly reduces flood damage in the Red River basin, while dike heightening and reforestation reduce flood damage, but not significantly.     

Card production breaks 10 billion

New statistics have revealed that the total number of plastic cards manufactured worldwide in 2002 hit 10.7 billion, just over 10% more than in 2001, when 9.7 billion cards were produced. This rise wasn’t reflected in the revenue picture, however, as extreme price pressure in 2002 meant that the market rose by just US$100 million from US$4.7 billion in 2001 to US$4.8 billion.Visit www.compseconline.com for the latest computer security industry news     

A knowledge centric methodology for dental implant technology assessment using ontology based patent analysis and clinical meta-analysis

The medical equipment industry has been one of the fastest growing sectors of the decade with predicted global sales reaching US$ 430 billion in 2017 [22]. During the period from 1995 to 2008, the patent applications in medical technology increased rapidly worldwide (World Intellectual Property Organization, 2012). Patent analysis, although useful in forecasting technology development trends, has posed a challenging analysis task since the volume and diversity of new patent applications has surpassed the ability of regular firms and research teams to process and identify relevant information. Further, medical related technologies rely on clinical trials to validate and gain regulatory approval for patient treatment even though patents, protecting the intellectual property rights of inventors, have been granted. This research focuses on developing a knowledge centric methodology and system to analyze and assess viable medical technology innovations and trends considering both patents and clinical reports. Specifically, the design innovations of dental implant connections are used as a case study. A novel and generic methodology combining ontology based patent analysis and clinical meta-analysis is developed to analyze and identify the most effective patented techniques in the dental implant field. The research establishes and verifies a computer supported analytical approach and system for the strategic prediction of medical technology development trends.     

Phishing attacks rising, but dollar losses down

New research suggests that phishing attacks, although increasing rapidly, aren't proliferating on a wildfire basis. Instead, they might actually he controlled by a small number of criminal organizations, and dollar losses once estimated at more than US$1 billion might be just above one tenth of that. However, the psychological toll phishing scams place on both service providers and end users can still cripple e-commerce     

An auditing protocol for spreadsheet models

Errors are prevalent in spreadsheets and can be extremely difficult to find. A number of audits of existing spreadsheets have been reported, but few details have been given about how the audits were performed. We developed and tested a new spreadsheet auditing protocol designed to find errors in operational spreadsheets. Our work showed which auditing procedures, used in what sequence and combination, were most effective across a wide range of spreadsheets. It also provided useful information on the size and complexity of operational spreadsheets, as well as the frequency with which certain types of errors occur.     

India's software industry

India today has a distinct identity as a software superpower. With the world's second largest pool of English-speaking scientific and technical professionals, India boasts a US$5.7 billion software industry with an annual growth rate of more than 50 percent. As the software industry increasingly becomes a major driver of the nation's economy and policy makers devise ways to fuel its growth, India's software industry is poised for massive expansion. As a matter of fact, policy makers and industry leaders envision this industry's growing to more than US$80 billion by 2005 (with US$50 billion worth of software exports). The author considers India's competitive advantage and software competence. He gives a financial snapshot of India's software powerhouses     

Introduction of affinity set and its application in data-mining example of delayed diagnosis

At least 44,000 people die in hospitals each year as a result of medical errors, and these deaths are becoming the eighth-leading cause of death in the United States. Thus, medical providers have the responsibility to pay attention for reducing avoidable medical errors and improve patient safety as best as they can. It requires the rapid evaluation and prioritisation of life threatening injuries in the primary survey followed by a detailed secondary survey in the emergency room. However, time is always valuable and limited such that some important vital signs may be delayed and ignored. This research explores delayed diagnosis problem and uses the affinity set by Topology concept to classify/focus on key attributes causing delayed diagnosis (missed injury) in order to reduce error risk. Results interestingly indicate that when a patient can breathe normally, but his (or her) blood-pressure or pulse is abnormal, a high probability of delayed diagnosis exists. This affinity work also compares the performance with the model of rough set (Rosetta), neural network, support vector machine and logistic regression. And our affinity model shows its advantage by prediction accuracy and explanation power.     

Learning to make errors: evidence from a driving task simulation

Human errors represent a mismatch between the demands of an operational system and what the operator does. If they cannot be reversed, their consequences may be severe. Errors are frequently classified as design-or operator-induced. A third class of errors may also be identified, namely process-induced errors. Such errors arise out of on-going processes which typically extend over time. One such process is that of learning. In relation to the acquisition of skills, for example, learning frequently involves a trial-and-error component. Accidents by inexperienced drivers may represent a severe consequence of such errors. Errors may also arise out of particular learning experiences which provide a distorted underestimate of objective risk and/or motivate high risk behaviour. These phenomena are investigated in a computer simulation of the driving task. The relationship is discussed between various kinds of learning experience and the development of situations in which the possibility of error recovery declines. Some suggestions for reducing the frequency of irreversible errors and for increasing the data base for human error in vehicle driving are made.     

Where the big money is

Someone once told the author that toy manufacturers had greater influence over computer design than computer scientists and this is true-the really big bucks are in consumer software products (about $90 billion per year), not information processing ($30-40 billion), client/server software (a few billion), scientific computing (maybe $2 billion), or multimedia (tens of billions). The author discusses the reasons for this and makes some predictions about the future of the computing industry     

A Note on High-Precision Approximation of Asymptotically Decaying Solution and Orthogonal Decomposition

In some physical applications, the decaying rate of asymptotically decaying solution is more important than the solution magnitude itself in understanding the physical system such as the late-time behavior of decaying fields in black hole space-time. In Khanna (J Sci Comput 56(2):366–380, 2013), it was emphasized that high-precision arithmetic and high-order methods are required to capture numerically the correct decaying rate of the late-time radiative tails of black-hole system in order to prevent roundoff errors from inducing a wrong power-law decay rate in the numerical approximation. In this paper, we explain how roundoff errors induce a wrong decay mode in the numerical approximation using simple linear differential equations. Then we describe the orthogonal decomposition method as a possible technique to remove wrong decaying modes induced by roundoff errors in the numerical approximation.     

Schlumberger IPO on the cards?

The financial press has been speculating that Schlumberger’s smart card division will be sold off in an IPO in the second half of 2003. The move would be an attempt to reduce the parent company’s debt which reached US$5 billion in 2002.This is a short news story only. Visit www.compseconline.com for the latest computer security industry news     

Accountability and automation bias

Although generally introduced to guard against human error, automated devices can fundamentally change how people approach their work, which in turn can lead to new and different kinds of error. The present study explored the extent to which errors of omission (failures to respond to system irregularities or events because automated devices fail to detect or indicate them) and commission (when people follow an automated directive despite contradictory information from other more reliable sources of information because they either fail to check or discount that information) can be reduced under conditions of social accountability. Results indicated that making participants accountable for either their overall performance or their decision accuracy led to lower rates of “automation bias”. Errors of omission proved to be the result of cognitive vigilance decrements, whereas errors of commission proved to be the result of a combination of a failure to take into account information and a belief in the superior judgement of automated aids.     

Improving cooperative trajectory mapping applications with encounter-based error correction

Cooperative trajectory mapping is an emerging technique that allows users to create such a map by using data that are collected from each other's mobile phones. This technique has been proposed for many applications, such as people localisation, public transportation tracking and traffic monitoring. Unlike the traditional Global Positioning System, cooperative trajectory mapping only requires information about the departure distance and moving direction from the previously reported position. This avoids problems such as the high-energy consumption of GPS and weak GPS signals in indoor conditions. However, the new technique also brings about other problems, such as measurement errors in cooperative trajectory mapping, which is when a measurement error causes the spatial relations among users to be wrong. We propose an encounter-based error correction algorithm to efficiently reduce measurement errors. Extensive simulation experiments are carried out to validate our solutions.     

Estimating friction errors in MOC analyses of unsteady pipe flows

Errors arising from the numerical treatment of friction in unsteady flows in small pipe networks are assessed for fixed-grid, method of characteristics analyses (MOC) with no interpolation. Although the results of the study are targeted at general unsteady flows, the underpinning analytical development is based on the behaviour of standing waves. This enables quantitative conclusions to be drawn about the sensitivity of MOC solutions to frequency. The development is undertaken first for a single pipe and then for networks, with and without a loop. The performance of MOC solutions is modelled with the aid of polynomial transfer matrices that are analogous to transfer function matrices available directly from partial differential equations of water hammer. It is found that, in a single pipe, the numerical errors tend to increase damping at all frequencies, but that, in networks, either increased or decreased damping may occur. The errors place both higher and lower limits on the frequencies that can propagate along a pipe in a numerical analysis. This contrasts with the physical case where only a lower limit exists. The work presented is part of a wider project with the long-term aim of automating the selection of numerical grid sizes in MOC analyses of unsteady flows.     

E-commerce and corporate strategy: an executive perspective

Despite the recent downturn in Internet-based business, the dollar value of electronic commerce (EC) transactions is increasing at an astounding rate. In consumer-to-business applications, the amount of money spent by online shoppers is nearly doubling every year and is expected to approach US$ 100 billion by 2004 while business-to-business sales is expected to reach US$ 1.3 trillion by 2003. These opportunities, powered by the evolving computing and communication technologies, enable companies to gain tremendous operational efficiencies, personalization, and information based products and services. More and more conventional brick and mortar firms see e-commerce initiatives as offering strategic opportunities to transcend their normal operations. This study proposes that e-commerce initiatives are important strategic initiatives and that firms with a stronger EC market orientation will be more successful. Content analysis of CEO’s letter to shareholders of 145 Fortune 500 firms was conducted to evaluate the importance of EC and strategic orientation. The results provide support to the study’s propositions and indicate that EC must be pursued carefully as a strategic initiative rather than as an appendage to an existing organization.