The Decision-Support Characteristics of ERP Systems

Enterprise Resource Planning (ERP) systems have been widely adopted in large organizations. These systems store critical knowledge used to make the decisions that drive an organization's performance. However, ERP systems are known primarily for their transactional rather than their decision-support characteristics. This study examines the extent to which adopters of ERP systems perceive characteristics typically associated with decision-support systems. It also examines the importance that adopters place on such characteristics. The major findings are that ERP adopters perceive substantial levels of decision-support characteristics in their ERP systems and that they consider such characteristics to be important. The study also examines differences in decision-support perceptions among demographic groups. By delineating the current state of ERP systems as they pertain to decision support, the results establish areas that vendors and adopters can focus on to improve the level of decision support provided by their ERP systems.     

Challenges for intelligent systems in biology

Biological processes have produced the ultimate intelligent system (humans), and now we are trying to understand biology (and ourselves) by building intelligent systems. Intelligent systems research in biology strives to understand how living systems perform difficult tasks routinely (ranging from molecular phenomena such as protein-folding to organism-level phenomena such as cognition). The definition of intelligent systems in biology can lead to hours of debate. Some say that all high-performance systems that do something difficult with (or to) biological data should be considered intelligent systems. Others insist that the term intelligent system should be reserved for systems using the methods typically associated with modem AI.     

The impact of artificial intelligence in accounting work: Expert systems use in auditing and tax

This paper uses Perrow’s sociological framework as a basis for a comparative organisation analysis of the impact of expert systems on organisational issues. The study analyses the relative impact of expert systems on two different types of accounting work: auditing and tax. The results indicate an impact on factors that ultimately improve productivity. The aggregate results indicate that expert systems are found to allow the user substantial control of search for solutions and discretion on whether to follow system recommendations, increased access to top management, and a decrease in the need for supervision. The systems allow the user the ability to solve a broader range of problems, while allowing the user the ability to perform more work. The comparison of auditing and tax expert systems indicates that audit systems seem to allow for greater control over search. Tax systems seem to allow more work to be done without supervision, make more decisions immediately, and allow the user to make a wider range of decisions.     

Information Filtering: Overview of Issues,Research and Systems

An abundant amount of information is created and delivered over electronic media. Users risk becoming overwhelmed by the flow of information, and they lack adequate tools to help them manage the situation. Information filtering (IF) is one of the methods that is rapidly evolving to manage large information flows. The aim of IF is to expose users to only information that is relevant to them. Many IF systems have been developed in recent years for various application domains. Some examples of filtering applications are: filters for search results on the internet that are employed in the Internet software, personal e-mail filters based on personal profiles, listservers or newsgroups filters for groups or individuals, browser filters that block non-valuable information, filters designed to give children access them only to suitable pages, filters for e-commerce applications that address products and promotions to potential customers only, and many more. The different systems use various methods, concepts, and techniques from diverse research areas like: Information Retrieval, Artificial Intelligence, or Behavioral Science. Various systems cover different scope, have divergent functionality, and various platforms. There are many systems of widely varying philosophies, but all share the goal of automatically directing the most valuable information to users in accordance with their User Model, and of helping them use their limited reading time most optimally. This paper clarifies the difference between IF systems and related systems, such as information retrieval (IR) systems, or Extraction systems. The paper defines a framework to classify IF systems according to several parameters, and illustrates the approach with commercial and academic systems. The paper describes the underlying concepts of IF systems and the techniques that are used to implement them. It discusses methods and measurements that are used for evaluation of IF systems and limitations of the current systems. In the conclusion we present research issues in the Information Filtering research arena, such as user modeling, evaluation standardization and integration with digital libraries and Web repositories.     

Comparison of necessary conditions for typical Takagi-Sugeno andMamdani fuzzy systems as universal approximators

Both Takagi-Sugeno (TS) and Mamdani fuzzy systems are known to be universal approximators. We investigate whether one type of fuzzy approximators is more economical than the other. The TS fuzzy systems are the typical two-input single-output TS fuzzy systems. We first establish necessary conditions on minimal system configuration of the TS fuzzy systems as function approximators. We show that the number of the input fuzzy sets and fuzzy rules needed by the TS fuzzy systems depend on the number and locations of the extrema of the function to be approximated. The resulting conditions reveal the strength of the TS fuzzy approximators. The drawback, though, is that a large number of fuzzy rules must be employed to approximate periodic or highly oscillatory functions. We then compare these necessary conditions with the ones that we established for the general Mamdani fuzzy systems in our previous papers. Results of the comparison unveil that the minimal system configurations of the TS and Mamdani fuzzy systems are comparable. Finally, we prove that the minimal configuration of the TS fuzzy systems can be reduced and becomes smaller than that of the Mamdani fuzzy systems if nontrapezoidal or nontriangular input fuzzy sets are used. We believe that all the results in present paper hold for the TS fuzzy systems with more than two input variables but the proof seems to be mathematically difficult. Our new findings are valuable in designing more compact fuzzy systems, especially fuzzy controllers and models which are two most popular and successful applications of the fuzzy approximators     

Prototyping networked embedded systems

Sophisticated consumer devices that support multimedia-personal digital assistants, network computers, and mobile communication devices-pose challenges for embedded systems designers. The low-cost, consumer-oriented, fast time-to-market mentality that dominates embedded system design today forces design teams to use hardware-software codesign to cope with growing design complexities. New codesign methodologies and tools must support a key characteristic of next-generation embedded systems: the capability to communicate over networks and adapt to different operating environments. The paper discusses two emerging classes of embedded systems: multifunction systems and multimode systems     

The surface of emergence in systems development: agency,institutions, and large-scale information systems

There is a strong tendency in the systems development literature to focus primarily on the system under development and to underemphasize the role of pre-existing information systems. Pre-existing information systems are treated largely as black boxes that serve as resources or constraints on development. A case study of a large-scale information system within a major university system in the U.S. is used to explore the role of pre-existing information systems in the development and emergence of a new system. The case study develops the argument that pre-existing information systems are active forces in systems development. Their influence occurs both through the material constraints and directions inherent in existing systems and through the experiences and learning from previous systems, which shape developers' approaches to building the new system. The study also develops a theoretical framework that integrates elements of structuration theory and actor-network theory to provide a more fine-grained analysis of how information technologies and institutional features interact in the structuring of organizational information systems. This study offers several theoretical and practical implications for IS development.     

People are not computers: (most) thought processes are not computational procedures

The computational conception of the mind that dominates cognitive science assumes that thought processes involve the computation of algorithms or the execution of functions. Human minds turn out to be automatic formal systems or physical syntax-processing systems. The objection has often been posed that systems of this kind do not possess sufficient conditions for mentality, because the syntax they process may be meaningless for those systems. That problem concerns their semantic content. Here an additional objection is posed that systems of this kind, as normatively-directed, problem-solving causal systems, impose conditions that are not necessary for mentality, because many if not most human thought processes violate them. This problem concerns their causal character. The computational conception reflects an overgeneralization about human thought processes based on special kinds of thinking and thus seems to be trivial or false.     

Canonical forms for stochastic nonlinear systems

In this paper, we obtain necessary and sufficient conditions for the existence of diffeomorphisms that transform stochastic nonlinear systems to various canonical forms. The main tool in our analysis is the so called invariance under transformation rule that directly relates the coordinate transformation for stochastic nonlinear systems to that for deterministic uncertain nonlinear systems. This invariance rule allows the utilization of the existing necessary and sufficient conditions for deterministic nonlinear systems in associated stochastic nonlinear systems.     

An Integrated Approach to Scheduling in Safety-Critical Embedded Control Systems

This paper describes an approach that has been developed over a number of years for the job of scheduling systems and providing evidence that timing requirements are met. The approach has been targeted at the safety-critical systems domain, and more specifically the development of control systems for jet engines. The work provides a usable computational model that supports the reuse of legacy systems. In addition, timing analysis has been developed that features low pessimism, low computational complexity and that is robust to change. The contributions of this paper are to show how standard timing analysis is often insufficient for real systems, presenting extensions to the standard analysis to give an integrated approach to verification, and providing a case study that demonstrates the appropriateness and benefits of the overall technique.     

The reachable set of a linear endogenous switching system

In this work, switching systems are named endogenous when their switching pattern is controllable. Linear endogenous switching systems can be considered as a particular class of bilinear control systems. The key idea is that both types of systems are equivalent to polysystems, i.e. to systems whose flow is piecewise smooth. The reachable set of a linear endogenous switching system can be studied consequently. The main result is that, in general, it has the structure of a semigroup, even when the Lie algebra rank condition is satisfied since the logic inputs cannot reverse the direction of the flow. The adaptation of existing controllability criteria for bilinear systems is straightforward.     

一类具有不确定性的非线性相似组合系统的鲁棒镇定

描述了两个控制系统间的相似性概念,讨论了一类具有不确定性的非线性相似组合系统的鲁棒镇定问题.结果表明,作者构造的控制器具有结构相似性.相似结构确实可以简化组合系统鲁棒镇定的判据.这说明,在一定程度上,具有相似结构的组合系统其相似结构具有稳固系统的特性.     

A comparison of four microcomputer operating systems

This article describes a comparative study of four operating systems for IBM-PC compatible microcomputers. The assessment concentrated on the suitability of the operating systems for use in real-time applications, and on their use as development environments for real-time systems. The study evaluated the predictability and the performance of the operating systems in several areas critical in real-time systems by using comparative benchmarks. In addition, a small-scale simulation of a process control system was developed for each of the systems. The operating systems that were studied were UNIX, OS/2, QNX and FlexOS. These operating systems represent a broad spectrum of systems from general purpose operating systems to small, specialized real-time operating systems. The details of the evaluation process are given and a summary of the results is presented.     

多级实时数据库的安全性策略

实时数据库根本目标就是使满足截止时间的事物数量为最大,因而,管理和支持优先考虑时间的事务处理是非常重要的。然而,随着实时计算的迅速发展,安全成了许多实时应用另一个必须考虑的问题。因此,在多级实时数据库系统中,提出一种结合实时性和安全性的方法是非常必要的。本文陈述了实时系统设计者应该考虑的实时性和安全性,描述了一种规范语言允许设计者在适当的级别设定数据库的重要属性以支持部分安全并探讨了一种自适应方法以达此目的。     

Beamforming techniques for massive MIMO systems in 5G: overview,classification, and trends for future research

Massive multiple-input multiple-output (MIMO) systems combined with beamforming antenna array technologies are expected to play a key role in next-generation wireless communication systems (5G), which will be deployed in 2020 and beyond. The main objective of this review paper is to discuss the state-of-the-art research on the most favourable types of beamforming techniques that can be deployed in massive MIMO systems and to clarify the importance of beamforming techniques in massive MIMO systems for eliminating and resolving the many technical hitches that massive MIMO system implementation faces. Classifications of optimal beamforming techniques that are used in wireless communication systems are reviewed in detail to determine which techniques are more suitable for deployment in massive MIMO systems to improve system throughput and reduce intra- and inter-cell interference. To overcome the limitations in the literature, we have suggested an optimal beamforming technique that can provide the highest performance in massive MIMO systems, satisfying the requirements of next-generation wireless communication systems.     

Synthesizing User Centered and Designer Centered IS Development Approaches Using General Systems Theory

This paper uses general systems theory to provide an expanded view of information systems in organizations. Three general viewpoints and corresponding approaches to information systems development are identified. The designer centered or American approach to information systems development is based on a functionalist perspective of information systems and a problem solving orientation. The user centered or European approach to information systems development takes an expanded view of information systems that specifically considers humans and recognizes their aspirations and goals and uses a democratic, participative approach to develop systems in an effort to produce an improved workplace and a better quality of worklife for users. A third viewpoint on information systems development, business process centering, is identified that further expands the components of the system to include the set of integrated tasks that provide value to the customer. We define a new development approach that combines the strengths of these approaches based on general systems theory, business process centering, and a measurement and control system.     

A View on Human Goal-Directed Activity and the Construction of Artificial Intelligence

Although activity aimed at the construction of artificial intelligence started about 60 years ago however, contemporary intelligent systems are effective in very narrow domains only. One of the reasons for this situation appears to be serious problems in the theory of intelligence. Intelligence is a characteristic of goal-directed systems and two classes of goal-directed systems can be derived from observations on animals and humans, one class is systems with innately and jointly determined goals and means. The other class contains systems that are able to construct arbitrary goals and means. It is suggested that the classes (that implicitly underlie most models of artificial intelligence) are insufficient to explain human goal-directed activity. A broader approach to goal-directed systems is considered. This approach suggests that humans are goal-directed systems that jointly synthesize arbitrary goals and means. Neural and psychological data favoring this hypothesis and its experimental validation are considered. A simple computer model based on the idea of joint synthesis to simulate goal-directed activity is presented. The usage of the idea of joint synthesis for the construction of artificial intelligence is discussed.     

Robust switching adaptive control of multi-input nonlinear systems

During the last decade a considerable progress has been made in the design of stabilizing controllers for nonlinear systems with known and unknown constant parameters. New design tools such as adaptive feedback linearization, adaptive back-stepping, control Lyapunov functions (CLFs) and robust control Lyapunov functions (RCLFs), nonlinear damping and switching adaptive control have been introduced. Most of the results developed are applicable to single-input feedback-linearizable systems and parametric-strict-feedback systems. These results, however, cannot be applied to multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. In this paper, we develop a general procedure for designing robust adaptive controllers for a large class of multi-input nonlinear systems. This class of nonlinear systems includes as a special case multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. The proposed approach uses tools from the theory of RCLF and the switching adaptive controllers proposed by the authors for overcoming the problem of computing the feedback control law when the estimation model becomes uncontrollable. The proposed control approach has also been shown to be robust with respect to exogenous bounded input disturbances     

Satisfaction with employee relationship management systems: the impact of usefulness on systems quality perceptions

The ability to effectively manage external customer satisfaction through IT-based Customer Relationship Management systems (CRM) is well documented in the literature. The concept of applying such technologies in Business to Employee relationships to manage the firm's relationships with its employees is not. By extending the CRM paradigm to consider the service of internal customers, we characterize the emergent concept of Employee Relationship Management systems (ERM) for investigation. We find that employee satisfaction with ERM systems designed to provide access to benefits and other important employee services is largely a function of systems quality perceptions, as moderated by employee perceptions of system usefulness. Specifically, we believe our results suggest that high-quality systems implementations will not produce high degrees of employee satisfaction with ERM systems unless such systems are also found by the employee to be highly useful for their intended purpose. This highlights the critical role of accurate assessments of user requirements matched to specific needs from human resources-based systems support in the analysis phase of system design.     

Guest Editors' Introduction: Dependable Agent Systems

It is well known that building dependable software systems for dynamic environments is difficult. It is also well known that building large-scale distributed software systems is difficult. The relatively few attempts to combine these two tasks confirm that successfully building large-scale distributed systems with predictable dependability properties is exceptionally difficult. The articles in this special issue of IEEE Intelligent Systems deal with this issue and discuss an emerging and exciting new approach to building these most challenging kinds of systems.