Is information systems a discipline? Foucauldian and Toulminian insights

Following the Kleinian spirit, this study takes a critical view of the existing orthodoxy within information systems (IS) and reframes the ongoing discussion concerning the intellectual core, identity and disciplinary status of IS using the disciplinary analysis of Michel Foucault and Stephen Toulmin. Instead of limiting the discussion to specific paradigms, topics, subjects or content, it focuses on the characteristics, rules and goals of IS as an academic field. A disciplinary lens is used to frame what it means to be a field, discipline and science, and in the process the study uncovers four doxas that have shaped the development of the IS field: (1) the IS research community sees no difference between fields, disciplines or sciences; (2) IT changes so rapidly, and thus the IS field needs to change to remain relevant; (3) disciplines are by definition rigid, inflexible and uni-theoretical and (4) because IS is pluralistic, IS should not become a discipline. This study's analyses of the IS field's discursive formation and intellectual ideals offer novel perspectives that allow for the integration of the IS field's plurality and diversity. To transform the IS field from its multimodal existence into a vibrant, diverse, academically and socially relevant and influential discipline, the study proposes actionable strategies that include (1) agreeing on the intellectual ideals for IS, (2) focusing on conceptual formation, (3) focusing on theory construction, (4) erecting genealogical boundaries and (5) fostering the development of professional bodies.     

A study of the impact of the willingness-to-learn of CAD novice users on their competence development

The notion that ‘attitude drives behavior’ manifests itself in a variety of ways in educational and occupational settings. As applied to CAD competence development, industrial training of novice CAD users on their way to becoming competent CAD users consume a lot of corporate resources. This paper is the third paper in the line of research that attempts to answer the question having to do with what it takes to make a competent CAD user. Specifically, we examine the CAD-specific factors revolving around the trainees’ willingness-to-learn CAD.These factors are analyzed in two stages. At the start of the training, trainees’ initial attitude towards CAD is established by means of a short questionnaire. Afterwards, throughout the training, trainees’ behavior (online and offline practice) is gauged and, in turn, a relation is established to illustrate how this practice leads to the development of CAD-specific skills. For this purpose, another short questionnaire was utilized. Strong correlations were established relating the trainees’ CAD-specific behavior with the CAD-specific outcomes of learning CAD syntax.Furthermore, and in order to assess the quality of the trainees’ learning of CAD, overall competence was monitored throughout the study via performance measures that describe the time it took the trainees to build test models (speed), which reflects upon the ability to learn the syntax of the CAD tool (declarative knowledge). The sophistication of the models is also used as another measure. Correlating the trainees’ character attributes with these assessed measures, it was found that the stronger is the trainees’ will to learn CAD, the stronger is the likelihood to learn faster. Perhaps more importantly, trainees with initial favorable attitude toward CAD were shown to develop increasingly positive behavior that manifested through additional practice and other forms of visible effort.     

Application of neural-fuzzy controller for streaming video over Bluetooth 1.2

This paper is to introduce an application of Computational Intelligence (CI) to Moving Picture Expert Group-4 (MPEG-4) video compression over IEEE.802.15.1 wireless communication, known as Bluetooth 1.2, in order to improve picture quality. The 2.4 GHz Industrial, Scientific and Medical frequency band is used for the IEEE.802.15.1 standard. IEEE.802.15.1 can be affected by noise and interference due to other neighboring wireless devices sharing the same frequency carrier. The noise and interference create difficulties in ascertaining an accurate real-time transmission rate at the receiving end. Furthermore, the MPEG-4 codec is an object-oriented compression system and demands a high bandwidth. It is therefore difficult to avoid excessive delay, image quality degradation and/or data loss during MPEG-4 video transmission over standard systems. A new buffer entitled ‘buffer added’ has been introduced at the input of the Bluetooth 1.2 device. This buffer is controlled by a Rule-Based Fuzzy (RBF) logic controller at the input and a neural-fuzzy controller (NFC) at the output. The two new fuzzy rules manipulate and supervise the flow of video over the Bluetooth 1.2 standard. The computer simulation results illustrate the comparison between a non-CI video transmission over Bluetooth 1.2 and the proposed design, confirming that the applications of RBF and NFC do improve the image quality, reduce data loss and reduce time delay.     

High-gain observers in the presence of measurement noise: A switched-gain approach

This paper considers output feedback control using high-gain observers in the presence of measurement noise for a class of nonlinear systems. We study stability in the presence of measurement noise and illustrate the tradeoff when selecting the observer gain between state reconstruction speed and robustness to model uncertainty on the one hand versus amplification of noise on the other. Based on this tradeoff we propose a high-gain observer that switches between two gain values. This scheme is able to quickly recover the system states during large estimation error and reduce the effect of measurement noise in a neighborhood of the origin of the estimation error. We argue boundedness and ultimate boundedness of the closed-loop system under switched-gain output feedback.     

Throughput analysis of STS-based CDMA system with variable spreading factor in non-frequency selective Rayleigh fading channel

The throughput enhancement of space-time spreading (STS)-based code division multiple access (CDMA) system is investigated in this paper. Variable spreading factor (VSF) is utilized to improve the data throughput of the system in non-frequency selective Rayleigh fading channel. In this contribution, an analytical approach is proposed to compute a new expression for the bit error rate (BER) performance of the STS-based CDMA system against pre-despreading signal-to-noise-ratio (SNR) for different values of spreading factor. The other contribution of the paper is deriving a new analytical expression for the throughput enhancement of the VSF STS-based CDMA system in non-frequency selective Rayleigh fading channel. Simulation and analytical results demonstrate that using VSF method in STS-based CDMA system improves the throughput of the system by keeping the BER performance at a target level.     

New oscillation criteria for second order linear difference equations with positive and negative coefficients

The oscillation of second order neutral difference equations with positive and negative coefficients of the form

is investigated. We obtain many new results using the comparison between both first order and second order difference equations. An example is given to show the strength of the obtained results.     

An enhanced Web page change detection approach based on limiting similarity computations to elements of same type

This paper describes an efficient Web page detection approach based on restricting the similarity computations between two versions of a given Web page to the nodes with the same HTML tag type. Before performing the similarity computations, the HTML Web page is transformed into an XML-like structure in which a node corresponds to an open-closed HTML tag. Analytical expressions and supporting experimental results are used to quantify the improvements that are made when comparing the proposed approach to the traditional one, which computes the similarities across all nodes of both pages. It is shown that the improvements are highly dependent on the diversity of tags in the page. That is, the more diverse the page is (i.e., contains mixed content of text, images, links, etc.), the greater the improvements are, while the more uniform it is, the lesser they are.     

Modelling of palm oil production using fuzzy expert system

The production of crude palm oil and palm kernel is a complex problem due to the influence of processing variables and environmental factors. These processing variables influence the amount of crude palm oil and palm kernel losses during processing. Instead of mathematical model, fuzzy logic approach provides a simpler and easier mechanism to describe the relationships between the processing variables and the amount of crude palm oil and palm kernel losses. In this study, four fuzzy expert system models were developed for each palm oil processing station. An approximation of centre of gravity method for defuzzification is also proposed to enable the development of the model using Microsoft^®Excel. For comparison purpose, the models were also developed using MATLAB^®. Results obtained from the Excel model are found to be very close to the results from MATLAB.     

Short-term and long-term memory analysis of learning using 2D and 3D educational contents

ABSTRACT

The effect of 2D and 3D educational content learning on memory has been studied using electroencephalography (EEG) brain signal. A hypothesis is set that the 3D materials are better than the 2D materials for learning and memory recall. To test the hypothesis, we proposed a classification system that will predict true or false recall for short-term memory (STM) and long-term memory (LTM) after learning by either 2D or 3D educational contents. For this purpose, EEG brain signals are recorded during learning and testing; the signals are then analysed in the time domain using different types of features in various frequency bands. The features are then fed into a support vector machine (SVM)-based classifier. The experimental results indicate that the learning and memory recall using 2D and 3D contents do not have significant differences for both the STM and the LTM.     

A new combination of artificial neural network and <Emphasis Type="Italic">K</Emphasis>-nearest neighbors models to predict blast-induced ground vibration and air-overpressure

Blasting operation is widely used method for rock excavation in mining and civil works. Ground vibration and air-overpressure (AOp) are two of the most detrimental effects induced by blasting. So, evaluation and prediction of ground vibration and AOp are essential. This paper presents a new combination of artificial neural network (ANN) and K-nearest neighbors (KNN) models to predict blast-induced ground vibration and AOp. Here, this combination is abbreviated using ANN-KNN. To indicate performance of the ANN-KNN model in predicting ground vibration and AOp, a pre-developed ANN as well as two empirical equations, presented by United States Bureau of Mines (USBM), were developed. To construct the mentioned models, maximum charge per delay (MC) and distance between blast face and monitoring station (D) were set as input parameters, whereas AOp and peak particle velocity (PPV), as a vibration index, were considered as output parameters. A database consisting of 75 datasets, obtained from the Shur river dam, Iran, was utilized to develop the mentioned models. In terms of using three performance indices, namely coefficient correlation (R ²), root mean square error and variance account for, the superiority of the ANN-KNN model was proved in comparison with the ANN and USBM equations.