Information Systems Offshore Outsourcing: An Exploratory Study of Motivations and Risks in Large Spanish Firms

Prior research has documented that IT investment increases market returns. Economic theories predict such returns to be recognized in accounting profitability; this relationship remains ambiguous in prior literature. We reexamine the relationship between IT investment and firm profitability. Our approach is unique in that we examine complementarities between distinct IT components. We document that a firm’s investments in IT components exhibit different impacts on its profitability conditional on the level of investments in complementary components.     

A socio-technical analysis of functional properties in a joint cognitive system: a case study in an aircraft cockpit

Abstract

In a socio-technical work domain, humans, device interfaces and artefacts all affect transformations of information flow. Such transformations, which may involve a change of auditory to visual information & vice versa or alter semantic approximations into spatial proximities from instruments readings, are generally not restricted to solely human cognition. This paper applies a joint cognitive system approach to explore a socio-technical system. A systems ergonomics perspective is achieved by applying a multi-layered division to transformations of information between, and within, human and technical agents. The approach uses the Functional Resonance Analysis Method (FRAM), but abandons the traditional boundary between medium and agent in favour of accepting aircraft systems and artefacts as agents, with their own functional properties and relationships. The joint cognitive system perspective in developing the FRAM model allows an understanding of the effects of task and information propagation, and eventual distributed criticalities, taking advantage of the functional properties of the system, as described in a case study related to the cockpit environment of a DC-9 aircraft.

Practitioner Summary: This research presents the application of one systemic method to understand work systems and performance variability in relation to the transformation of information within a flight deck for a specific phase of flight. By using a joint cognitive systems approach both retrospective and prospective investigation of cockpit challenges will be better understood.

Abbreviations: ATC: air traffic control; ATCO: air traffic controller; ATM: air traffic management; CSE: cognitive systems engineering; DSA: distributed situation awareness; FMS: flight management system; FMV: FRAM model visualize; FRAM: functional resonance analysis method; GF: generalised function; GW: gross weight; HFACS: human factors analysis and classification system; JCS: joint cognitive systems; PF: pilot flying; PNF: pilot not flying; SA: situation awareness; SME: subject matter expert; STAMP: systems theoretic accident model and processes; VBA: visual basic for applications; WAD: work-as-done; WAI: work-as-imagined; ZFW: zero fuel weight     

Software quality assurance economics

ContextSoftware companies invest in quality assurance in order to lower software development and maintenance cost, and to increase revenue and profit margins. To contribute to increase of net income, a quality assurance organization has to consider cost and value of the testware involved in assuring quality of software artifacts, such as requirements, specifications, designs, and code.ObjectiveThis paper proposes a set of economic metrics: testware return on investment, inflation, and cost and value sensitivity to artifact changes and time passage. The paper proposes a set of guidelines on lowering testware cost, on increasing value, on maximizing return on investment, and on when to release.MethodThis paper presents an industrial case study data on the relation between test case cost and value, and on cost and value sensitivity to time passage and artifact changes.ResultsThe industrial case study showed return on investment on test cases of up to 200%, deflation of up to −2% per month, undesirable economic effects, such as test case cost outpacing test case value and rapid test case value depreciation based on time passage.ConclusionA viable QA organization should measure and improve test case return on investment, inflation, and cost and value sensitivity to artifact changes and time passage.     

回归—聚类联合框架下的手写文本行提取

目的 手写文本行提取是文档图像处理中的重要基础步骤,对于无约束手写文本图像,文本行都会有不同程度的倾斜、弯曲、交叉、粘连等问题。利用传统的几何分割或聚类的方法往往无法保证文本行边缘的精确分割。针对这些问题提出一种基于文本行回归-聚类联合框架的手写文本行提取方法。方法 首先,采用各向异性高斯滤波器组对图像进行多尺度、多方向分析,利用拖尾效应检测脊形结构提取文本行主体区域,并对其骨架化得到文本行回归模型。然后,以连通域为基本图像单元建立超像素表示,为实现超像素的聚类,建立了像素-超像素-文本行关联层级随机场模型,利用能量函数优化的方法实现超像素的聚类与所属文本行标注。在此基础上,检测出所有的行间粘连字符块,采用基于回归线的k-means聚类算法由回归模型引导粘连字符像素聚类,实现粘连字符分割与所属文本行标注。最后,利用文本行标签开关实现了文本行像素的操控显示与定向提取,而不再需要几何分割。结果 在HIT-MW脱机手写中文文档数据集上进行文本行提取测试,检测率DR为99.83%,识别准确率RA为99.92%。结论 实验表明,提出的文本行回归-聚类联合分析框架相比于传统的分段投影分析、最小生成树聚类、Seam Carving等方法提高了文本行边缘的可控性与分割精度。在高效手写文本行提取的同时,最大程度地避免了相邻文本行的干扰,具有较高的准确率和鲁棒性。     

A new approach to bootstrap inference in functional coefficient models

To infer on functional dependence of regression parameters, a new, factor based bootstrap approach is introduced, that is robust under various forms of heteroskedastic error terms. Modeling the functional coefficient parametrically, the bootstrap approximation of an F-statistic is shown to hold asymptotically. In simulation studies with both parametric and nonparametric functional coefficients, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach, according to its rejection frequencies under the null hypothesis. Applying the functional coefficient model to a cross sectional investment regression on savings, the saving retention coefficient is found to depend on third variables as the population growth rate and the openness ratio.     

Toward automated feature model configuration with optimizing non-functional requirements

ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in [1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders.     

Effect of seat thickness on peak femoral vein velocity

IntroductionThis study aimed to investigate the effects of different seat thicknesses on lower limb momentum and lower limb blood flow in a narrow enclosed space simulating public places.MethodsWe enrolled 15 female volunteers. We measured the maximum venous blood flow velocity (peak velocity [PV]) of the superficial femoral vein, the range of knee joint movements, and the number of knee joint movements while the subjects sat on the thicker- or thinner-tip seat for 140 min.ResultsThere was a difference in the change rate of PV after 140 min of sitting: thinner-tip seat groups: 22.3% (−31.1 − −13.5%); thinner-tip seat groups: 6.9% (−16.5 − 2.8%) (P < 0.001). There was a significant difference in the range of knee joint motion between the two seats: thicker-tip seat: 24.5° (19.9°–29.1°); thinner-tip seat: 36.6° (29.1°–44.1°) (P = 0.01). There was a significant positive correlation between the change rates of PV and the knee joint range of motion (r = 0.41, P = 0.03).ConclusionsOur findings suggest that a seat structure that does not restrict lower limb movement may help inhibit reductions in lower limb blood flow when sitting for long periods.     

Modeling and simulation of the open-end equity mutual fund market in Taiwan by using self-organizing map

This research applies artificial intelligence (AI) of unsupervised learning self-organizing map neural network (SOM-NN) to establish a model to select the superior funds. This research period is from year 2000 to 2010 and picks 100 domestic equity mutual funds as study object. This research used 30 days prior to the beginning of each month’s prior 30 days, 60 days, 90 days on fund’s net asset value and the Taiwan Weighted Stock Index (TAIEX) return as the fund’s relative performance evaluation indicators classified by month. Finally, based on the superior rate or the average return rate, this research select the superior funds and simulate investment transactions according to this model.The empirical results show that using the mutual fund’s net asset value and the TAIEX’s relative return as SOM-NN input variables not only finds out the superior fund but also has a good predictive ability. Applying this model to simulate investment transactions will be better than the random trading model and market. The experiments also found that the investment simulation of a three-month interval has the highest profitability. The model operation suggests that it is more suitable for short-term and medium-term investment. This research can assist investors in making the right investment decisions while facing rapid financial environment changes.     

多目标粒子群优化PCNN参数的图像融合算法

目的 脉冲耦合神经网络（PCNN）在图像融合上往往因为参数设置问题而达不到最佳效果,为了提高图像融合的质量,提出了一种基于多目标粒子群优化PCNN参数的图像融合算法。方法 首先用多目标粒子群对PCNN模型参数进行优化得到最优PCNN参数模型,然后利用双复树小波（DTCWT）对图像多尺度分解,将高频分量通过优化好的PCNN模型进行高频融合,低频分量通过拉普拉斯分量绝对和（SML）来进行低频融合,最后通过DTCWT逆变换实现图像的融合。结果 分别与DTCWT,拉普拉斯金字塔变换（LP）以及非下采样Contourlet变换（NSCT）进行实验对比,融合图像Clock,Lab的融合结果在客观指标上的互信息（8.062 3,7.908 5）、图像的品质因数（0.716 2,0.714 2）和标准差（51.213,47.671）都优于其他方法,熵和其他方法差不多,融合结果能够获得更好的视觉效果以及较大的互信息值和边缘信息保留值。结论 该方法有较好融合图像的能力,可适用于计算机视觉、医学、遥感等领域。     

Software quality trade-offs: A systematic map

BackgroundSoftware quality is complex with over investment, under investment and the interplay between aspects often being overlooked as many researchers aim to advance individual aspects of software quality.AimThis paper aims to provide a consolidated overview the literature that addresses trade-offs between aspects of software product quality.MethodA systematic literature map is employed to provide an overview of software quality trade-off literature in general. Specific analysis is also done of empirical literature addressing the topic.ResultsThe results show a wide range of solution proposals being considered. However, there is insufficient empirical evidence to adequately evaluate and compare these proposals. Further a very large vocabulary has been found to describe software quality.ConclusionGreater empirical research is required to sufficiently evaluate and compare the wide range of solution proposals. This will allow researchers to focus on the proposals showing greater signs of success and better support industrial practitioners.     

能量泛函正则化模型在图像恢复中的应用分析

目的 能量泛函正则化模型是图像恢复研究的热点。为使更多工程领域的研究者对正则化技术进行探索和应用,推动不适定问题的研究,对能量泛函正则化模型的进展进行了分析。方法 首先建立图像整体坐标与局部坐标的关系,分析图像恢复正则化模型的基本原理,给出并证明正则化模型各向同性与各向异性扩散定理。然后结合函数空间、图像分解和紧框架,评述能量泛函正则化模型国内外发展现状,并对正则化模型解的适定性进行分析。结果 推导出图像恢复正则化模型扩散基本原理,给出正则化模型通用表达式,讨论正则化模型存在的问题及未来的发展方向。结论 正则化技术在解决图像恢复、修复等反问题起着重要作用。目前,国内外学者对该问题的研究取得了一些成果,但许多理论问题有待进一步研究。     

Acute biomechanical responses to a prolonged standing exposure in a simulated occupational setting

Prolonged occupational standing has previously been associated with low back pain (LBP) development. The immediate effects of a bout of prolonged standing on subsequent functional movement performance have not been investigated. It is possible that including a period of prolonged standing may have acute, detrimental effects. The purpose of the study is to investigate the impact of a prolonged standing exposure on biomechanical profiles (trunk muscle activation, joint stiffness and kinematics) during three functional movements. A total of 23 volunteers without history of LBP performed lumbar flexion, single-leg stance and unloaded squat movements pre- and post 2 h of standing exposure. It was found that 40% of the participants developed LBP during the standing exposure. There was a decrease in vertebral joint rotation stiffness in lateral bending and increased centre of pressure excursion during unilateral stance following standing exposure. There may be adverse effects to prolonged standing if followed by activities requiring precise balance or resistance of side loads.

Statement of Relevance: Prolonged standing may result in decreases in balance reactions during narrow base conditions as well as in the capacity to effectively resist side-loads at the trunk. Consideration should be given when prolonged standing is included in the workplace.     

A teamwork model for understanding an agile team: A case study of a Scrum project

ContextSoftware development depends significantly on team performance, as does any process that involves human interaction.ObjectiveMost current development methods argue that teams should self-manage. Our objective is thus to provide a better understanding of the nature of self-managing agile teams, and the teamwork challenges that arise when introducing such teams.MethodWe conducted extensive fieldwork for 9 months in a software development company that introduced Scrum. We focused on the human sensemaking, on how mechanisms of teamwork were understood by the people involved.ResultsWe describe a project through Dickinson and McIntyre’s teamwork model, focusing on the interrelations between essential teamwork components. Problems with team orientation, team leadership and coordination in addition to highly specialized skills and corresponding division of work were important barriers for achieving team effectiveness.ConclusionTransitioning from individual work to self-managing teams requires a reorientation not only by developers but also by management. This transition takes time and resources, but should not be neglected. In addition to Dickinson and McIntyre’s teamwork components, we found trust and shared mental models to be of fundamental importance.     

Developing recommender systems with the consideration of product profitability for sellers

In electronic commerce web sites, recommender systems are popularly being employed to help customers in selecting suitable products to meet their personal needs. These systems learn about user preferences over time and automatically suggest products that fit the learned model of user preferences. Traditionally, recommendations are provided to customers depending on purchase probability and customers’ preferences, without considering the profitability factor for sellers. This study attempts to integrate the profitability factor into the traditional recommender systems. Based on this consideration, we propose two profitability-based recommender systems called CPPRS (Convenience plus Profitability Perspective Recommender System) and HPRS (Hybrid Perspective Recommender System). Moreover, comparisons between our proposed systems (considering both purchase probability and profitability) and traditional systems (emphasizing an individual’s preference) are made to clarify the advantages and disadvantages of these systems in terms of recommendation accuracy and/or profit from cross-selling. The experimental results show that the proposed HPRS can increase profit from cross-selling without losing recommendation accuracy.     

Bridging the cognitive-cellular neuroscience gap empirically: a study combining physiology,modelling and fMRI

In this article, we present a mixed qualitative and quantitative approach for evaluation of information technology (IT) security investments. For this purpose, we model security scenarios by using defense trees, an extension of attack trees with countermeasures and we use economic quantitative indexes for computing the defender's return on security investment and the attacker's return on attack. We show how our approach can be used to evaluate economic profitability of countermeasures and their deterrent effect on attackers, thus providing decision makers with a useful tool for performing better evaluation of IT security investments during the risk management process.     

Control of investment portfolio based on complex quantile risk measures

Combined measures of financial risks, which are convex combinations of known measures VaR and CVar and their analogues for right-hand tails of investment portfolio profitability distribution functions, are considered. Two-stage optimization procedure is developed for estimation of efficiency of proposed measures. Results of numerical experiment are presented.     

Effects of backpack load on critical changes of trunk muscle activation and lumbar spine loading during walking

This study investigated the effects of carrying a backpack while walking. Critical changes featuring the disproportionality of increases in trunk muscle activation and lumbar joint loading between light and heavy backpack carriage weight may reveal the load-bearing strategy (LBS) of the lumbar spine. This was investigated using an integrated system equipped with a motion analysis, a force platform and a wireless surface electromyography (EMG) system to measure the trunk muscle EMG amplitudes and lumbar joint component forces. A predictive goal programming model was developed to determine the most critical changes in trunk muscle activation and lumbar joint loading. Results suggested that lightweight backpack carriage at approximately 3% of body weight (BW) might reduce the peak lumbosacral compression force by 3% during walking compared with no load condition. The most critical changes in both trunk muscle activation and lumbosacral joint loading were found at a backpack load of 10% of BW.

Practitioner Summary: This study investigated the effects of backpack load on the LBS of lumbar spine while walking. A backpack load of 3% of BW might reduce the peak lumbosacral compression force by 3 and 10% of BW induced the most critical changes in LBS of lumbar spine.     

A Unifying Model for Statistical Arbitrage: Model Assumptions and Empirical Failure

Statistical arbitrage refers to a suite of quantitative investment strategies employed chiefly by hedge funds and proprietary trading firms. The arbitrageur can draw on a number of different approaches to identify and exploit an arbitrage opportunity, though the literature is broadly segmented by the canonical distance, cointegration and time series perspectives. Since the initial academic investigation of statistical arbitrage, its profitability has continued to diminish thanks largely to the increasing proportion of non-convergent opportunities. This paper surveys the existing literature, with particular emphasis given to evidence of statistical arbitrage failure, before unifying the distance, cointegration and time series perspectives under a single explicit model. The failure of statistical arbitrage opportunities is shown to be the direct consequence of implicit model assumptions that are inconsistent with the empirical literature. An alternative model is proposed, and evidence of its relative performance discussed.

     

Software defect prediction using ensemble learning on selected features

ContextSeveral issues hinder software defect data including redundancy, correlation, feature irrelevance and missing samples. It is also hard to ensure balanced distribution between data pertaining to defective and non-defective software. In most experimental cases, data related to the latter software class is dominantly present in the dataset.ObjectiveThe objectives of this paper are to demonstrate the positive effects of combining feature selection and ensemble learning on the performance of defect classification. Along with efficient feature selection, a new two-variant (with and without feature selection) ensemble learning algorithm is proposed to provide robustness to both data imbalance and feature redundancy.MethodWe carefully combine selected ensemble learning models with efficient feature selection to address these issues and mitigate their effects on the defect classification performance.ResultsForward selection showed that only few features contribute to high area under the receiver-operating curve (AUC). On the tested datasets, greedy forward selection (GFS) method outperformed other feature selection techniques such as Pearson’s correlation. This suggests that features are highly unstable. However, ensemble learners like random forests and the proposed algorithm, average probability ensemble (APE), are not as affected by poor features as in the case of weighted support vector machines (W-SVMs). Moreover, the APE model combined with greedy forward selection (enhanced APE) achieved AUC values of approximately 1.0 for the NASA datasets: PC2, PC4, and MC1.ConclusionThis paper shows that features of a software dataset must be carefully selected for accurate classification of defective components. Furthermore, tackling the software data issues, mentioned above, with the proposed combined learning model resulted in remarkable classification performance paving the way for successful quality control.