‘Mind the Gap’: diagnosing the relationship between the IT organisation and the rest of the business

The senior management of many organisations are continually disappointed with the benefits and value which they perceive they are getting from their investments in IT. This frustration with IT, and in particular with the IT function, has seen many organisations choose to rid themselves of the ‘problem’ altogether by outsourcing IT activities to a third party. The fact that there is a separate organisational unit responsible for IT activities has led to the emergence of gap between this so called IT organisation and the rest of the business. Culture is often used to explain the gap as if this somehow justifies an organisations inability to effectively leverage IT. However, the premise underlying this article is that culture is an excuse for rather than a cause of ineffective application of IT for business benefits and value. The clear message from this article is that achieving high performance from IT is not just about the IT function's ability to build, maintain and deliver systems, but is an organisational wide activity requiring a strong business/IT partnership. A framework grounded in the research literature, which identifies the elements to manage in creating high performance from IT, is developed and operationalised. The findings of an exploratory survey are presented and research and practitioner implications developed.     

What Do the Sun and the Sky Tell Us About the Camera?

As the main observed illuminant outdoors, the sky is a rich source of information about the scene. However, it is yet to be fully explored in computer vision because its appearance in an image depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. In this paper, we analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. By fitting a model of the predicted sun position to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. Similarly, we show how we can extract the same parameters by fitting a physically-based sky model to the sky appearance. In short, the sun and the sky serve as geometric calibration targets, which can be used to annotate a large database of image sequences. We test our methods on a high-quality image sequence with known camera parameters, and obtain errors of less that 1% for the focal length, 1° for azimuth angle and 3° for zenith angle. We also use our methods to calibrate 22 real, low-quality webcam sequences scattered throughout the continental US, and show deviations below 4% for focal length, and 3° for the zenith and azimuth angles. Finally, we demonstrate that by combining the information available within the sun position and the sky appearance, we can also estimate the camera geolocation, as well as its geometric parameters. Our method achieves a mean localization error of 110 km on real, low-quality Internet webcams. The estimated viewing and illumination geometry of the scene can be useful for a variety of vision and graphics tasks such as relighting, appearance analysis and scene recovery.     

A Note on the Difference between the Camera Resection and the PnP Problem

The camera resection and the PnP problem are both of great importance in computer vision field.However,these two fundamentally different problems are often mistaken one another in the literature.In this short note,the essential differences of these two problems are clarified,and such a clarification seems helpful for those who are working on the problems.     

Respond to the input equipment in the VC

The ways to program the respond to the input equipment in Visual C++ program language are introduced in this paper. It also presents all the examples for keyboard, mouse, and joystick.     

Shaping the drivers’ interaction: how the new vehicle systems match the technological requirements and the human needs

Although it is not always possible to derive from statistics the causes of an accident, data clearly show that they are mostly due to a lack of driver’s perception, with high direct and indirect social costs for society (Hutchinson in Road accidents statistics, Rumsby Scientific Publishing, 1987; Kawai in Convergence 1994, Conference Proceedings, 1994; Boussuge in Bilan et perspectives, Revue Gen. des Routes et des Aerodromes, N. 726, 1995). Therefore, a strong integration among all the actors involved (i.e., the drivers, the vehicle or technical system in general and the driving environment) is quite necessary. From the beginning of 1980s, there has been a shift in system concept design, moving from a technological approach towards a human-centred design approach (Norman and Draper 1986; Rouse 1991). Firstly this approach was applied to the human–computer interaction domain, and has also been extended towards complex and automated technological systems (Sheridan in Telerobotics, automation, and human supervisory control, MIT Press, 1992; Scerbo in Human performance in automated systems: theory and applications, Lawrence Erlbaum Associates, 1996) in several domains as, among the others, automotive (Michon in Generic intelligent driver support, Taylor & Francis, 1994) and industrial plants (Cacciabue in Giuseppe mantovani ergonomia, II Mulino, 2000). According to these perspectives, the role of user’s needs in the design process of a certain system becomes crucial; nevertheless, the technological requirements, i.e., the so-called “machine needs” should maintain a role of which the designer should be totally aware. Otherwise, the risk is to fail the design process making a system incoherent and ineffective. Thus, this paper aims at presenting such types of needs, the mutual interaction between machine and users, as well as the interaction of both with the surrounding environment. The work is based on several experiences conducted in the automotive domain.

Crossing the Line or Making the Case?

Anyone who has searched the Internet for products and services has experienced the wonderful assortment of products, services and resources that can be found online. We are witnessing the rapid growth of truly global commerce with unparalleled opportunity for choice and selection, competition and more. However, when criminals operating in another nation attack, the operators of E-commerce systems confront one of the most serious downsides of global operations since there is little or no commonality on how police officials in various nations will respond. Possible conflicts can arise in the absence of common codes of criminal conduct, standards of collaboration and consensus as to how the “civilized” forces of law and order will proceed against the denizens of the “dark side”.     

Naturality of the conditional and the recursion ∗

In a class of categories, including E. Manes's assertional ones, the control structures if-then-else and repeat-until are modeled as natural transformations of suitable functors. This context show how the three basic pieces of any structured programming language (concatenation, conditional and recursion) share naturality.     

EFTPoS– the engine of the card business

The slow but increasing spread of chip-based payment cards, the introduction of the euro and the recent flurry of panic over the security of the smart card payment system in France offers new opportunities to point-of-sale terminal manufacturers.     

On the Formalization of the Modal μ-Calculus in the Calculus of Inductive Constructions

We present a natural deduction proof system for the propositional modal μ-calculus and its formalization in the calculus of inductive constructions. We address several problematic issues, such as the use of higher-order abstract syntax in inductive sets in the presence of recursive constructors, and the formalization of modal (sequent-style) rules and of context sensitive grammars. The formalization can be used in the system Coq, providing an experimental computer-aided proof environment for the interactive development of error-free proofs in the modal μ-calculus. The techniques we adopt can be readily ported to other languages and proof systems featuring similar problematic issues.     

A system for recognizing online handwritten mathematical expressions by using improved structural analysis

A system for recognizing online handwritten mathematical expressions (MEs), by applying improved structural analysis, is proposed and experimentally evaluated on two databases. With this system, MEs are represented in the form of stochastic context-free grammar (SCFG), and the Cocke–Younger–Kasami (CYK) algorithm is used to parse two-dimensional (2D) structures of online handwritten MEs and select the best interpretation in terms of the results of symbol segmentation and recognition as well as structural analysis. A concept of “body box” is proposed, and two SVM models are applied for learning and analyzing structural relations from training patterns without the need for any heuristic decisions. Stroke order is used to reduce the complexity of the parsing algorithm. Even though SCFG does not resolve ambiguities in some cases, the proposed system still gives users a list of candidates that contains the expected result. The results of experimental evaluations of the proposed system on the CROHME 2013 and CROHME 2014 databases and on an in-house (“Hand-Math”) database show that the recognition rate of the proposed system is improved, while the processing time on a common CPU is kept to a practical level.     

Synthetic Data Generation and Shuffled Multi-Round Training Based Offline Handwritten Mathematical Expression Recognition

Offline handwritten mathematical expression recognition is a challenging optical character recognition (OCR) task due to various ambiguities of handwritten symbols and complicated two-dimensional structures. Recent work in this area usually constructs deeper and deeper neural networks trained with end-to-end approaches to improve the performance. However, the higher the complexity of the network, the more the computing resources and time required. To improve the performance without more computing requirements, we concentrate on the training data and the training strategy in this paper. We propose a data augmentation method which can generate synthetic samples with new LaTeX notations by only using the official training data of CROHME. Moreover, we propose a novel training strategy called Shuffled Multi-Round Training (SMRT) to regularize the model. With the generated data and the shuffled multi-round training strategy, we achieve the state-of-the-art result in expression accuracy, i.e., 59.74% and 61.57% on CROHME 2014 and 2016, respectively, by using attention-based encoder-decoder models for offline handwritten mathematical expression recognition.     

Machine learning models for mathematical symbol recognition: A stem to stern literature analysis

Given the ubiquity of handwriting and mathematical content in human transactions, machine recognition of handwritten mathematical text and symbols has become a domain of great practical scope and significance. Recognition of mathematical expression (ME) has remained a challenging and emerging research domain, with mathematical symbol recognition (MSR) as a requisite step in the entire recognition process. Many variations in writing styles and existing dissimilarities among the wide range of symbols and recurring characters make the recognition tasks strenuous even for Optical Character Recognition. The past decade has witnessed the emergence of recognition techniques and the peaking interest of several researchers in this evolving domain. In light of the current research status associated with recognizing handwritten math symbols, a systematic review of the literature seems timely. This article seeks to provide a complete systematic analysis of recognition techniques, models, datasets, sub-stages, accuracy metrics, and accuracy details in an extracted form as described in the literature. A systematic literature review conducted in this study includes pragmatic studies until the year 2021, and the analysis reveals Support Vector Machine (SVM) to be the most dominating recognition technique and symbol recognition rate to be most frequently deployed accuracy measure and other interesting results in terms of segmentation, feature extraction and datasets involved are vividly represented. The statistics of mathematical symbols-related papers are shown, and open problems are identified for more advanced research. Our study focused on the key points of earlier research, present work, and the future direction of MSR.

     

Recognition of online handwritten mathematical expressions

This paper aims at automatic understanding of online handwritten mathematical expressions (MEs) written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. Combination of two different classifiers have been used to achieve high accuracy for the recognition of symbols. Several online and offline features are used in the structural analysis phase to identify the spatial relationships among symbols. A context-free grammar has been designed to convert the input expressions into their corresponding T(E)X strings which are subsequently converted into MathML format. Contextual information has been used to correct several structure interpretation errors. A new method for evaluating performance of the proposed system has been formulated. Experiments on a dataset of considerable size strongly support the feasibility of the proposed system.     

基于凸壳和模糊识别的数学公式识别

根据数学公式中字符或符号间空间关系特点,并针对目前用于数学公式字符空间关系判别的区域和质心方法所存在的不足,提出了基于字符凸壳和模糊识别的字符空间关系判别方法.首先,对数学公式中的字符或符号进行分类,对每一类运用字符凸壳判别其正上和正下关系,然后应用模糊识别的方法对常见关系进行识别.实验结果表明,运用该方法能明显提高字符空间关系判别的识别率,识别的正确率可达到93.5%.     

An expert system for general symbol recognition

An expert system for analysis and recognition of general symbols is introduced. The system uses the structural pattern recognition technique for modeling symbols by a set of straight lines referred to as segments. The system rotates, scales and thins the symbol, then extracts the symbol strokes. Each stroke is transferred into segments (straight lines). The system is shown to be able to map similar styles of the symbol to the same representation. When the system had some stored models for each symbol (an average of 97 models/symbol), the rejection rate was 16.1% and the recognition rate was 83.9% of which 95% was recognized correctly. The system is tested by 5726 handwritten characters from the Center of Excellence for Document Analysis and Recognition (CEDAR) database. The system is capable of learning new symbols by simply adding their models to the system knowledge base.     

基于模糊理论的数学公式上下标关系判别

上下标关系数学公式中出现频繁又难于解决的特殊结构,容易与其它关系混淆.提出了基于模糊理论的数学公式上下标关系判别.运用模糊理论对数学公式中符号的空间区域关系进行划分,然后应用模糊识别的方法对上下标关系进行判别.实验结果表明,运用该方法能明显提高符号空间关系判别的识别率,尤其是能很好地判别手写数学公式中的空间关系,识别的正确率可达到96.4%.     

面向联机手写数学表达式的实时识别方法

数学表达式识别一般分为字符识别和结构分析两部分,而且大多数现有的方法是先进行字符识别然后将字符识别的结果作为结构分析的输入再进行结构分析,在这种分步识别的过程中,字符识别的错误会被继承到结构分析阶段,最终导致识别错误。关于数学表达式结构分析的问题,现有的方法大多是在假设所有的符号已经识别的基础上进行的。为了解决上述问题,提出了一种实时识别联机手写数学表达式的方法。该方法基于字符识别和结构分析的结合,动态地构建一棵数学表达式结构树来识别该数学表达式。在构建数学表达式树的过程中,采用了影响区域定位的方法,免去了其他不受影响区域的重复识别过程,因而提高了再次识别的效率,同时还弥补了现有实时识别方法不能乱序输入的缺陷。实验结果表明提出的方法可以得到比较满意的识别结果。     

手绘电路图形符号识别技术的研究

特征提取和分类器设计是手绘电路图形符号识别系统的关键环节。针对手绘图形不规则性的特点,提出了一种基于视觉的特征提取方法,并利用自适应学习速率的改进型BP神经网络进行分类识别。通过对10种手绘电路图形符号的分类实验,验证了文中设计的识别系统具有很好的分类效果和较强的实用性。     

印刷体数学公式的识别

介绍了一个印刷体数学公式识别系统,它由公式字符识别和结构分析两部分组成。在公式字符识别中,采用了一些适用于公式字符的特殊处理方法;在结构分析中,根据数学公式的结构布局,采用了一种将“自顶向下”和“自底向上”策略相结合的数学公式结构分析方法,实现了数学公式的重用,实验表明,这种方法能取得较好的识别效果。