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Summary

The law of evidence is a fascinating subject which covers a range of controversial and complex topics, from the admissibility of confessions and other evidence obtained as a result of police brutality or trickery, to the dangers presented by mistaken visual identification evidence, and the impact of a defendant's refusal to answer questions or the admissibility of his previous convictions on the verdict. Much of the study of the law of evidence focuses on the admissibility of certain types of evidence: the law seeks to control the admissibility of evidence to ensure that the tribunal of fact has access to evidence that is relevant and reliable. The rules governing admissibility are often complicated and nuanced, requiring a solid understanding of more general principles relating to the purpose of the trial process, due process, justice, fairness and legitimacy.

The first two chapters of the book provide an introduction to the subject and to these preliminary principles. Chapter 3 explores matters concerning proof, including the burden and standard of proof in criminal and civil proceedings. Chapters 4 to 6 cover the investigative stage of evidence gathering and focus on the impact of the defendant's silence in the police station on the trial and the admissibility of illegally or improperly obtained evidence, including confession evidence. Chapters 7 and 8 deal with the admissibility of hearsay evidence and character evidence respectively. Chapters 9 and 10 cover the rules relating to the competence and compellability of different categories of witnesses and the testimony given by witnesses, such as the different types of questioning permitted in examination-in-chief and cross-examination. They also deal with the rules relating to the cross-examination of a complainant regarding their sexual history and the measures which may be used to assist an intimidated or vulnerable witness to improve the quality of the evidence that they give. Chapter 11 examines the safeguards provided by the law where the prosecution seeks to rely on hazardous evidence.

Summary

1.1 INTRODUCTION

This book is concerned with the law of evidence which governs the presentation of evidence in criminal and civil proceedings. Rules of evidence transcend all aspects of the trial stage of proceedings. They govern who has to prove what in a trial (the burden of proof) and the level to which those facts have to be proved (the standard of proof). They govern what evidence can go before the court (by the rules relating to relevance and admissibility), the format in which it is presented to the tribunal of fact and the reasons why it may be adduced (i.e. what the evidence goes towards proving or disproving). They ensure that members of the tribunal of fact are provided with guidance (usually by way of a direction from the judge) as to how they should approach their deliberations and what certain evidence may go to prove or disprove. The law of evidence provides rules as to who can be called as a witness (and by which party in proceedings) to give evidence (competence) and who must give evidence if called to do so (compellability). The rules of evidence also dictate the type of questions which may be asked of a particular witness depending upon the party calling them. The law provides safeguards for the protection of vulnerable witnesses in order to maximise the quality of their evidence. The law safeguards against miscarriages of justice by providing rules of evidence and discretionary powers to exclude certain types of evidence or evidence which has been improperly obtained.

1.2 WHAT IS EVIDENCE?

Evidence is information which may be used to prove the existence of a fact in issue or a collateral fact or to disprove a fact in issue or collateral fact. These terms will be explored in paragraphs 1.3.1 and 1.3.3 below.

There are many different types of evidence including the testimony from a witness given in the witness box, forensic evidence, the evidence of identification, evidence in documentary form, and objects (e.g. a weapon).

Summary

14.1 INTRODUCTION

When a witness is called to give evidence and answers questions in examination-in-chief, he opens himself up to cross-examination by other parties in the case, and, as a general rule, he must answer any question put to him. However, the law acknowledges that there may be circumstances in which a witness should be permitted to refuse to answer certain questions: for instance, a lawyer should not be required to answer questions about the details of conversations he had with his client, a witness should not be required to answer questions if he might incriminate himself, and the prosecution should not be required to disclose information which might jeopardise national security or police operations. Thus, the law provides privileges for witnesses which protect the witness against such questioning. The circumstances mentioned above and many others are protected by the law of privilege. This chapter explores the law of privilege. It begins with an examination of legal professional privilege, and more specifically, the two categories of legal professional privilege, namely, legal advice privilege and litigation privilege. Other forms of privilege are then considered, including ‘without prejudice’ communications, the privilege against self-incrimination and public interest immunity.

14.2 LEGAL PROFESSIONAL PRIVILEGE

The relationship between a lawyer and his client is a protected one. The law provides that communications between a lawyer and his client are confidential and they are protected by legal professional privilege. Thus, a lawyer cannot be compelled to testify about the details of communications with his client. Legal professional privilege has been held to be an absolute privilege; there are no exceptions to the privilege and the court should not conduct a balancing exercise to weigh up the interests of the client in keeping the communications confidential and the interests of the public in disclosing the communications to the other party.

Summary

13.1 INTRODUCTION

This chapter explores the provisions that govern the process of pre-trial disclosure. The law on disclosure has been the subject of extensive discussion amongst academics and practitioners. This is a controversial area, and the arguments balancing the interests of all the parties in a case are well rehearsed. The concept of pre-trial prosecution disclosure supports the defendant's right to a fair trial or fair hearing under Article 6 of the European Convention on Human Rights by ensuring that the defendant is aware of the evidence against him before trial. The rules on disclosure also assist in the administration of justice by ensuring that the issues that will arise at trial are identified at an early stage; this reduces the length of court hearings and ensures that the justice system is more cost efficient. Brief consideration will be given to the civil disclosure process before a more detailed examination of disclosure in the criminal justice system. The chapter will provide an overview of the disclosure process in criminal proceedings before looking at the two different types of disclosure: disclosure of ‘used’ material, where the prosecution discloses to the defence any material on which it intends to rely, and disclosure of ‘unused’ material, which is governed by the Criminal Procedure and Investigations Act 1996. The Criminal Procedure and Investigations Act 1996 (as amended by the Criminal Justice Act 2003) lays down a framework for the disclosure of unused material. The 1996 Act also first introduced the concept of defence disclosure into the criminal justice system, requiring that the defence disclose its case in advance of trial through the service of a defence statement. Finally, the chapter will consider the non-disclosure of material which is subject to public interest immunity (PII), the secretive manner in which some PII applications are made and the effect of this on the defendant's right to a fair trial under Article 6.

Summary

Part I provides prerequisite information for using optimization in practice. Specifically, we need to use software and we need to have some basic knowledge of mathematics. This book uses Matlab as a computational tool. If you are new to Matlab or do not know it yet, Chapter 1 will provide you with the preparatory information to get started. If your mathematics knowledge is a bit rusty, Chapter 2 will provide you with the preparatory knowledge for optimization application.

Specifically, the topics presented, with the chapter numbers, are given below:

Summary

In the first part of the book, we dealt with some material that prepared us to begin learning optimization. Specifically, we learned about Matlab and about some basic mathematics. In this next portion of the book, we start to understand what optimization is all about. In particular, (i) we will be introduced to the fascinating world of optimization, (ii) we will differentiate optimization from other engineering activities (e.g., analysis and modeling), and, finally, (iii) we will provide an important classification of optimization, which is important to know in practice.

Specifically, the topics presented, with the chapter numbers, are given below:

3. Welcome to the Fascinating World of Optimization

4. Analysis, Design, Optimization, and Modeling

5. Introducing Linear and Nonlinear Programming

Summary

Part IV of the book explains what is inside the code and how it works. This knowledge will make it possible to use the optimization code with more confidence, and more reliably. It will also help you know what to do when things do not work. The material presented will also be great preparation for further studies in optimization. With this more advanced knowledge, it will be possible to understand such things as the code error messages. The material examined in this part of the book will reinforce and advance the knowledge of optimization that was previously learned.

Metaphorically, the material up to this point taught us how to drive the design from a bad state to an optimal state. We did so without understanding how the car we are driving works, how to fix it, design it, or actually build it. However, we have sufficient practical knowledge to drive from a bad to a good design. The following material will teach us how the car works, how to fix it, how to make it perform very well, and even prepare us venture into the advanced world of designing cars (if that is our interest). That is, building optimization codes and algorithms. Interestingly, most of us want to use the power of optimization, without having to become expert in the intricate details of the inner-workings of the optimization code. This book provides the breadth of presentation to suit these diverse objectives. More advanced topics will be presented beyond Part IV.

Summary

1.1 Overview

Optimization can be viewed as a process that searches methodically for better answers, better solutions, or better designs that a human being may not be able to find through experience, intuition, or courageous trial-and-error. Optimization can be defined as the art of making things better. Interestingly, optimization very often does not simply allow us to do something better, but it may also make it possible to do something that we did not otherwise know how to do. To take full advantage of the power of optimization in practice, there is no choice but to use a computer.

The study of optimization typically takes a theoretical and/or computational approach. The theoretical approach is highly useful when the objective is to develop new optimization methods or to assess how the current methods work [1]. Additionally, the study of optimization often focuses on the understanding of various search algorithms for optimization. A book by Reklaitis and co-authors [2] is an example of methods-based optimization presentation. While these books play an important role in the general study of optimization, we pursue a different approach. The objective of this book takes on a practical perspective. The current interest is in the immediate ability to apply optimization in practice. In order to reach this objective, and to have the ability to apply optimization to real world problems, we use the approach that is almost always required in the application of optimization. We use the power of the computer, in conjunction with the study of different important practical aspects of optimization.

In order readily apply optimization in practice, the focus will be on the computational application of what we will learn, as we learn it. To do so, we use a computational modeling and coding tool that is powerful, easy to use, and one that is widely applied in engineering and other fields. Matlab is an excellent tool choice and will be used in this book. Matlab has arguably become the most popular tool for computational modeling worldwide.

Summary

Overview

This chapter covers the practice of optimization in diverse technical areas. What has been learned thus far is the practical knowledge that is needed to apply optimization to different types of designs or systems. We will explore optimizing systems/designs in the following disciplines: chemistry, mechanics, aerospace, automotive, mathematics (data fitting), nuclear, electrical, portfolio management, and business (Ref. [1]). Our ability to optimize these various designs provides us with the skills to apply optimization beyond the confines of this book or of the class you might be taking, and successfully venture into the real world!

Mechanical Engineering Example

Structural Example

Figure 10.1 represents a ten-bar truss. The members are connected to each other at six nodes, numbered 1 to 6. The truss is assumed to be planar, and every node has two degrees of freedom (i.e., it is free to move both in the x and y directions). The left edge of the truss is fixed to the wall. The displacements u1 to u8 are specified at the specific non-fixed nodes. F1 to F8 represent loads applied to these nodes. The variables by x1 to x10 denote the cross sectional areas of the truss members. The Young's modulus of the material is E = 1 × 106N/mm2. The maximum allowable stress in each bar is σult = ±100N/mm2 (i.e., tension/compression), and the maximum allowable deflection is δmax = ±2 mm. We note that the unit of length in the figure and in this problem is mm, and that of force is N. While the current example is commonly used in the literature, the reader is also encouraged to review the topology optimization survey by Rozvany in Ref. [2].

Imagine you are hired as the optimization expert for the ten-bar truss project. The structural engineer working on the project provides you with a program blackbox−10bar.m, which allows you to enter the loads at the nodes and the area of each member, and obtain the corresponding nodal displacements and stresses in the members. Figure 10.2 illustrates this task. The ten-bar truss is subjected to 10 different loading conditions given in Table 10.1.

Summary

In Part I, we presented some prerequisite material for our study of optimization: and introduction to Matlab, and some elementary mathematics. In Part II, we learned what we needed to explore what optimization is all about, and the important role it can play in your life as and engineer, scientist, business person, or anyone dealing with improving things quantitatively (e.g., performance and cost). In Part III, we get into the thick of things! We learn what we need to know to credibly address optimization problems in practice.

Specifically, the topics presented, with the chapter numbers, are given below:

6. Multiobjective Optimization

7. Numerical Essentials

8. Global Optimization Basics

9. Discrete Optimization Basics

10. Practicing Optimization—Larger Examples

Summary

Overview

In this chapter, we introduce efficient mathematical approaches to model the behavior of complex systems in the context of optimizing the system. Specifically, complex systems often involve a large number of design parameters (to be tuned), and the optimization of these systems often demand large scale computational simulations or experiments to quantify the system behavior. The resulting high dimensionality of the design space, the prohibitive computation time (or expense), or the lack of mathematical models present important challenges to the quantitative optimization of these complex systems. This chapter introduces traditional and contemporary approaches, such as design variable linking and surrogate modeling, to address the modeling challenges encountered in solving complex optimization problems.

Section 15.2 discusses the generic challenges in complex optimization problems. The impact of problem dimension is addressed in Sec. 15.3, where design variable linking and design of experiments are introduced. Section 15.4 presents surrogate modeling, where the discussion includes: the process, the polynomial response surface methodology, the radial basis function method, the Kriging method, and the artificial neural network method. The chapter concludes with a summary provided in Section. 15.5.

Modeling Challenges in Complex Optimization Problems

Modeling is one of the primary activities in optimization. Leveraging computational tools and models, as opposed to purely depending on experiments, can be considered the way forward in the area of system optimization. The design of complex systems, such as aircrafts, cars, and smart-grid networks, are increasingly performed using simulation-based design and analysis tools such as Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD). The incorporation of these tools has dramatically transformed modern engineering design and optimization approaches.

These changes, however, are not free of challenges. For example, modern aerospace systems present significantly complex design requirements [1], where design objectives generally involve improving performance, reducing costs, and maximizing safety. Another example is the optimization of a vehicle structure to absorb crash energy, maintain adequate passenger space, and control crash deceleration pulse during collisions [2].

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Contents

Preface

Summary

List of figures and tables

1 - Introduction to the law of evidence

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14 - Privilege and public interest immunity

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9 - Witnesses

13 - Disclosure

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Index

PART I - HELPFUL PRELIMINARIES

Summary

List of Tables

17 - Methods for Pareto Frontier Generation/Representation

PART II - USING OPTIMIZATION–THE ROAD MAP

Summary

2 - Mathematical Preliminaries

5 - Introducing Linear and Nonlinear Programming

Frontmatter

PART IV - GOING DEEPER: INSIDE THE CODES AND THEORETICAL ASPECTS

Summary

1 - MATLAB® as a Computational Tool

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10 - Practicing Optimization—Larger Examples

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PART III - USING OPTIMIZATION—PRACTICAL ESSENTIALS

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15 - Modeling Complex Systems: Surrogate Modeling and Design Space Reduction

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