How can one amplify the effect of e-learning? An examination of high-tech employees’ computer attitude and flow experience

While numerous studies have focused on the effectiveness and benefits of e-learning, this study elicits the determinants of the IT professionals’ e-learning outcomes by investigating the effect of IT professionals’ computer attitudes on two personal outcomes: self-perceived flow experience and learning outcomes. Data collected from 50 technological companies which located in Hsinchu Science Parks in Taiwan (N = 239) were analyzed using structural equation modeling. Results confirm that both computer attitude and flow experience generate positive and direct influence on learning outcome. Specially, the effect of personal computer attitude is amplified on learning outcome through experience of flow in an e-learning environment. Managerial implications are proposed and research limitations are discussed.     

A vehicle routing improvement algorithm comparison of a “greedy” and a matching implementation for inventory routing

Given an initial solution to a vehicle routing problem—(VRP)—we present three heuristic route improvement schemes based on the concept of node interchange between different routes. Three algorithms are presented together with their computational performance when applied to an inventory routing problem for 12 consecutive weekly periods. All three procedures improve the initial solution constructed by a modified Clark and Wright algorithm by over 50% as measured by the change in the value of the objective function. In two of the algorithms a minimum weight matching problem is solved repetitively.     

How can proteomics elucidate the complexity of multiple sclerosis?

Multiple sclerosis affects more than 2.5 million people worldwide. Although multiple sclerosis was described almost 150 years ago, there are many knowledge gaps regarding its etiology, diagnosis, prognosis, and pathogenesis. Multiple sclerosis is an inflammatory, demyelinating, neurodegenerative disease of the CNS. During the last several decades, experimental models of multiple sclerosis have contributed to our understanding of the inflammatory disease mechanisms and have aided drug testing and development. However, little is known about the neurodegenerative mechanisms that operate during the evolution of the disease. Currently, all therapeutic approaches are primarily based on the inflammatory aspect of the disease. During the last decade, proteomics has emerged as a promising tool for revealing molecular pathways as well as identifying and quantifying differentially expressed proteins. Therefore, proteomics may be used for the discovery of biomarkers, potential drug targets, and new regulatory mechanisms. To date, a considerable number of proteomics studies have been conducted on samples from experimental models and patients with multiple sclerosis. These data form a solid base for further careful analysis and validation.     

Are digital natives a myth or reality? University students’ use of digital technologies

This study investigated the extent and nature of university students’ use of digital technologies for learning and socialising. The findings show that students use a limited range of mainly established technologies. Use of collaborative knowledge creation tools, virtual worlds, and social networking sites was low. ‘Digital natives’ and students of a technical discipline (Engineering) used more technology tools when compared to ‘digital immigrants’ and students of a non-technical discipline (Social Work). This relationship may be mediated by the finding that Engineering courses required more intensive and extensive access to technology than Social Work courses. However, the use of technology between these groups is only quantitatively rather than qualitatively different. The study did not find evidence to support popular claims that young people adopt radically different learning styles. Their attitudes to learning appear to be influenced by lecturers’ teaching approaches. Students appear to conform to traditional pedagogies, albeit with minor uses of tools delivering content. The outcomes suggest that although the calls for transformations in education may be legitimate it would be misleading to ground the arguments for such change in students’ shifting patterns of learning and technology use.     

How far we can go with extractive text summarization? Heuristic methods to obtain near upper bounds

Extractive text summarization is an effective way to automatically reduce a text to a summary by selecting a subset of the text. The performance of a summarization system is usually evaluated by comparing with human-constructed extractive summaries that are created in annotated text datasets. However, for datasets where an abstract is written for reader purpose, the performance of a summarization system is evaluated by comparing with an abstract that is created by human who uses his own words. This makes it difficult to determine how far the state-of-the-art extractive methods are away from the upper bound that an ideal extractive method might achieve. In addition, the performance of an extractive method is always different in each domain, which make it difficult to benchmark. Previous studies construct an ideal sentence-based extract of a document that provides the best score of a given metric by exhaustive search of all possible sentence combinations of a given length. They then use the performance of the extract as the sentence-based upper-bound. However, this only applies to short texts. For long texts and multiple documents, previous studies rely on manual effort, which is expensive and time consuming. In this paper, we propose nine fast heuristic methods to generate the near ideal sentence-based extracts for long texts and multiple documents. Furthermore, we propose an n-gram construction method to construct the word-based upper-bound. A percentage ranking method is used to benchmark different extractive methods across different corpora. In the experiments, five different corpora are used. The results show that the near upper bounds constructed by the proposed methods are close to that using exhaustive search, but the proposed methods are much faster. Six general extractive summarization methods were also assessed to demonstrate the difference between the performance of the methods and the near upper bounds.     

How mild can slow controls be?

For a linear control system, if a state can be steered to zero in some time, then it can be steered to zero in any larger time and it is expected that, as the time grows, the norm of the corresponding control to be smaller. We study here the behavior of the minimum \(L^p\) -control, \(p\in (1,+\infty ]\) , as time duration goes to infinity.     

An algorithm of contact problems for forming process of thin plates—a numerical analysis for the seaming process of a can

An algorithm of contact problems for processing thin plates is presented. In the seaming process of a can, two thin plates, an end and flange of a can slip each other and repeat contacting and separating, and are deformed by a roll. To analyse such a complex contact problem, an algorithm using penalty forces and maximum displacement control is proposed. A trial analysis of the seaming process with this algorithm is shown in this paper.     

Robust fault isolation for a class of non-linear input?output systems

The design and analysis of fault diagnosis methodologies for non-linear systems has received significant attention recently. This paper presents a robust fault isolation scheme for a class of non-linear systems with unstructured modelling uncertainty and partial state measurement. The proposed fault diagnosis architecture consists of a fault detection and approximation estimator and a bank of isolation estimators. Each isolation estimator corresponds to a particular type of fault in the fault class. A fault isolation decision scheme is presented with guaranteed performance. If at least one component of the output estimation error of a particular fault isolation estimator exceeds the corresponding adaptive threshold at some finite time, then the occurrence of that type of fault can be excluded. Fault isolation is achieved if this is valid for all but one isolation estimator. Based on the class of non-linear systems under consideration, fault isolability conditions are rigorously investigated, characterizing the class of non-linear faults that are isolable by the proposed scheme. Moreover, the non-conservativeness of the fault isolability conditions is illustrated by deriving a subclass of nonlinear systems and faults for which this condition is also necessary for fault isolability. A simulation example of a simple robotic system is used to show the effectiveness of the robust fault isolation methodology.     

How can a complex square root be computed in an optimal way?

We give an optimality analysis for computations of complex square roots in real arithmetic by certain computation tress that use real square root operations. Improving standard elementary geometric constructions Schönhage suggests better methods which will be shown to be unimprobable. The iteration of such a procedure for 2 ^k -th roots is however improvable, and an improved version of it can also be shown to be unimprovable. In particular, repeated usage of an optimal square root procedure does not yield an optimal one for 2 ^k -th roots.To answer this kind of questions about resolution by real radicals we apply methods of real algebra which lead into the theory of real field, ring, and integral ring extensions.     

How can we learn leadership? The vision of the Europe-wide University

In the view of many students, business and engineering education in Europe today do not sufficiently take into account complex problems, tendencies of chaos and uncontrollable business behaviour, and the lack of mutual trust in business transactions. Additionally, universities seem to fail in creating leaders, instead focusing on educating future managers. Therefore, the student-run international organisation the European Students of Industrial Engineering and Management (ESTIEM) offers a whole series of educational activities and programmes in parallel to their own university courses. It is based on the concept of experiential learning. Through ESTIEM, we, students of Industrial Engineering Management, learn and practise working in teams with shared and rotating leadership among ourselves. These experiences are to be described in the paper in some more detail, as a model for university education in industrial engineering and management. Furthermore, the following questions will be tackled: What does leadership mean today? How are problems handled by leaders and managers in industry nowadays? How can leadership to solve complex problems be taught in the university? As a consequence, it is suggested to develop out of the ESTIEM programmes, a series of university-equivalent ESTIEM courses. In the long term, the goal might be to realise the vision of a genuine Europe-wide “ESTIEM University” in its own right, similar to normal universities which will help in shaping new leadership generation in Europe.     

How can a sparse representation be made applicable for very low-dimensional data?

The sparse representation has achieved notable performance in the field of pattern classification, and has been adopted in many expert and intelligent applications such as access control and surveillance. However, sparse representation does not work as well for low-dimensional data as it does for high-dimensional data. For data of very low dimensionality, sparse representation methods usually have severe drawbacks; consequently, wider applications of sparse representations are seriously restricted. In this paper, we focus on this challenging problem and propose a very effective method for using sparse representations with low-dimensional data. Compared with the conventional sparse representation method, the proposed method achieves considerable improvement of classification accuracy by increasing the dimensionality of the data. Moreover, the proposed method is mathematically tractable and quite computationally efficient.     

How do monetary incentives influence giving? An empirical investigation of matching subsidies on kiva

Information Systems and e-Business Management - Matching subsidies, through which third-party institutions provide a dollar-for-dollar match of private contributions made through selected...     

Clinical application of antibody microarray in chronic kidney disease: How far to go?

Chronic kidney disease (CKD) that affects about 10% of the adult population has been shown as a worldwide public health problem in recent years. Both basic and clinical investigations have identified complex disease-associated protein networks involved in the pathophysiologic processes of CKD. The traditional single-assay approach and proteomic analysis of those related proteins have given birth to a steadily increasing panel of molecules that may have the potential to serve as biomarkers for CKD. However, both approaches suffered from some shortcomings from a technological point of view. Antibody microarray (AbM) is characterized by high sensitivity, specificity, and quantitative ability for a particular set of known proteins. However, its application in CKD has been very limited so far. The objective of this review, therefore, is to address the potential applications of AbM in studying of CKD. We will briefly discuss the proteins involved in the development of CKD, future directions in which AbM approaches would probably display its potential and also some key issues that need to be considered in application of this novel technique.     

How does a backrest work?

After discussing the distribution of forces in the stable upright posture and illustrating the importance of the lumbar lordosis for minimising muscular effort in this position, the loadings on the spine and muscles of the back are outlined during upright sitting. It is shown that the backrest locates the lumbar spine so that the CG of the superincumbent body parts can be positioned above the vertebrae, permitting the gravity load to be transmitted to the seat without the counteracting torques which muscles would have to provide if this position was not adopted. The forces arising from other sitting positions are then discussed, and some conclusions drawn for seat design.     

How to Guard a Graph?

We initiate the study of the algorithmic foundations of games in which a set of cops has to guard a region in a graph (or digraph) against a robber. The robber and the cops are placed on vertices of the graph; they take turns in moving to adjacent vertices (or staying). The goal of the robber is to enter the guarded region at a vertex with no cop on it. The problem is to find the minimum number of cops needed to prevent the robber from entering the guarded region. The problem is highly non-trivial even if the robber’s or the cops’ regions are restricted to very simple graphs. The computational complexity of the problem depends heavily on the chosen restriction. In particular, if the robber’s region is only a path, then the problem can be solved in polynomial time. When the robber moves in a tree (or even in a star), then the decision version of the problem is NP-complete. Furthermore, if the robber is moving in a directed acyclic graph, the problem becomes PSPACE-complete.     

The digital agenda of virtual currencies: Can BitCoin become a global currency?

This paper identifies and analyzes BitCoin features which may facilitate BitCoin to become a global currency, as well as characteristics which may impede the use of BitCoin as a medium of exchange, a unit of account and a store of value, and compares BitCoin with standard currencies with respect to the main functions of money. Among all analyzed BitCoin features, the extreme price volatility stands out most clearly compared to standard currencies. In order to understand the reasons for such extreme price volatility, we attempt to identify drivers of BitCoin price formation and estimate their importance econometrically. We apply time-series analytical mechanisms to daily data for the 2009–2014 period. Our estimation results suggest that BitCoin attractiveness indicators are the strongest drivers of BitCoin price followed by market forces. In contrast, macro-financial developments do not determine BitCoin price in the long-run. Our findings suggest that as long as BitCoin price will be mainly driven by speculative investments, BitCoin will not be able to compete with standard currencies.     

Finding the key length of a Vigenère cipher: How to improve the twist algorithm

Abstract

A Vigenère cipher applies a single short key repeatedly to encrypt a plaintext. If a cryptanalyst correctly finds out the key length, the ciphertext can be divided into multiple instances of shift cipher and be broken by frequency analysis. To determine the key length, the twist algorithm, an alternate method to the standard Kasiski and Friedman tests, was recently proposed. In this article, we propose the twist⁺ algorithm, an improved twist algorithm, which can estimate the key length more accurately than the original twist algorithm.