Why ADR must be a mandatory subject in the law degree : A cheat sheet for the willing and a primer for the non-believer

The profession of law is deeply steeped in tradition and conservatism, which influences the content and pedagogy employed in law faculties across Australia. Indeed, the practice of law and the institutions of legal education are in a relationship of mutual influence; a dénouement which preserves the best aspects of the common law legal system, but also leaves the way we educate, practice and think about the role of law resistant to change. In this article, the authors lay down a challenge to legal education orthodoxy and a call to arms for legal academic progressivists: that alternative dispute resolution (ADR) should be a compulsory, stand alone subject in the law degree. The authors put forward 10 simple arguments as to why every law student should be exposed to a semester-long course of ADR instruction.

Out of their minds: legal theory in neural networks

This paper examines the use of connectionism (neural networks) in modelling legal reasoning. I discuss how the implementations of neural networks have failed to account for legal theoretical perspectives on adjudication. I criticise the use of neural networks in law, not because connectionism is inherently unsuitable in law, but rather because it has been done so poorly to date. The paper reviews a number of legal theories which provide a grounding for the use of neural networks in law. It then examines some implementations undertaken in law and criticises their legal theoretical naïvete. It then presents a lessons from the implementations which researchers must bear in mind if they wish to build neural networks which are justified by legal theories.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

Reasoning paradigms in legal decision support systems

In this paper we discuss the strengths and weaknesses of a range of artificial intelligence approaches used in legal domains. Symbolic reasoning systems which rely on deductive, inductive and analogical reasoning are described and reviewed. The role of statistical reasoning in law is examined, and the use of neural networks analysed. There is discussion of architectures for, and examples of, systems which combine a number of these reasoning strategies. We conclude that to build intelligent legal decision support systems requires a range of reasoning strategies.

Near knowledge : inductive learning systems in law

Induction is an interesting model of legal reasoning, since it provides a method of capturing initial states of legal principles and rules, and adjusting these principles and rules over time as the law changes. In this article I explain how Artificial Intelligence-based inductive learning algorithms work, and show how they have been used in law to model legal domains. I identify some problems with implementations undertaken in law to date, and create a taxonomy of appropriate cases to use in legal inductive inferencing systems. I suggest that inductive learning algorithms have potential in modeling law, but that the artificial intelligence implementations to date are problematic. I argue that induction should be further investigated, since it has the potential to be an extremely useful mechanism for understanding legal domains.

Deductive, inductive and analogical reasoning in legal decision support systems

In this paper we provide an overview of a number of fundamental reasoning formalisms in artificial intelligence which can and have been used in modelling legal reasoning. We describe deduction, induction and analogical reasoning formalisms, and show how they can be used separately to model legal reasoning. We argue that these formalisms can be used together to model legal reasoning more accurately, and describe a number of attempts to integrate the approaches.

The IHR (2005), disease surveillance, and the individual in global health politics

Since the revisions to the International Health Regulations (IHR) in 2005, much attention has turned to two concerns relating to infectious disease control. The first is how to assist states to strengthen their capacity to identify and verify public health emergencies of international concern (PHEIC). The second is the question of how the World Health Organization (WHO) will operate its expanded mandate under the revised IHR. Very little attention has been paid to the potential individual power that has been afforded under the IHR revisions – primarily through the first inclusion of human rights principles into the instrument and the allowance for the WHO to receive non-state surveillance intelligence and informal reports of health emergencies. These inclusions mark the individual as a powerful actor, but also recognise the vulnerability of the individual to the whim of the state in outbreak response and containment. In this paper we examine why these changes to the IHR occurred and explore the consequence of expanding the sovereignty-as-responsibility concept to disease outbreak response. To this end our paper considers both the strengths and weaknesses of incorporating reports from non-official sources and including human rights principles in the IHR framework.

Do spoken nonword and sentence repetition tasks discriminate language impairment in children with an ASD?

The primary aim of this paper was to investigate heterogeneity in language abilities of children with a confirmed diagnosis of an ASD (N = 20) and children with typical development (TD; N = 15). Group comparisons revealed no differences between ASD and TD participants on standard clinical assessments of language ability, reading ability or nonverbal intelligence. However, a hierarchical cluster analysis based on spoken nonword repetition and sentence repetition identified two clusters within the combined group of ASD and TD participants. The first cluster (N = 6) presented with significantly poorer performances than the second cluster (N = 29) on both of the clustering variables in addition to single word and nonword reading. The significant differences between the two clusters occur within a context of Cluster 1 having language impairment and a tendency towards more severe autistic symptomatology. Differences between the oral language abilities of the first and second clusters are considered in light of diagnosis, attention and verbal short term memory skills and reading impairment.

Pedestrian dynamics in real and simulated world

The paper examines the knowledge of pedestrian movements, both in real scenarios, and from more recent years, in the virtual 4 simulation realm. Aiming to verify whether it is possible to learn from the study of virtual environments how people will behave in real 5 environments, it is vital to understand what is already known about behavior in real environments. Besides the walking interaction among 6 pedestrians, the interaction between pedestrians and the built environment in which they are walking also have greatest relevance. Force-based 7 models were compared with the other three major microscopic models of pedestrian simulation to demonstrate a more realistic and capable 8 heuristic approach is needed for the study of the dynamics of pedestrians.

Long-term experiments with an adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

Detection of rain in acoustic recordings of the environment

Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

Exploring location-dependency in process modeling

Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

Identifying team style in soccer using formations learned from spatiotemporal tracking data

To the trained-eye, experts can often identify a team based on their unique style of play due to their movement, passing and interactions. In this paper, we present a method which can accurately determine the identity of a team from spatiotemporal player tracking data. We do this by utilizing a formation descriptor which is found by minimizing the entropy of role-specific occupancy maps. We show how our approach is significantly better at identifying different teams compared to standard measures (i.e., shots, passes etc.). We demonstrate the utility of our approach using an entire season of Prozone player tracking data from a top-tier professional soccer league.

Impact of simulated hyperopia on academic-related performance in children

Purpose: To investigate the impact of simulated hyperopia and sustained near work on children’s ability to perform a range of academic-related tasks. Methods: Fifteen visually normal children (mean age: 10.9 ± 0.8 years; 10 males and 5 females) were recruited. Performance on a range of standardised academic-related outcome measures was assessed with and without 2.50 D of simulated bilateral hyperopia (administered in a randomised order), before and after 20 minutes of sustained near work, at two separate testing sessions. Academic-related measures included a standardised reading test (the Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (the Developmental Eye Movement test). Results: Simulated bilateral hyperopia and sustained near work each independently impaired reading, visual information processing and reading-related eye movement performance (p<0.001). A significant interaction was also demonstrated between these factors (p<0.001), with the greatest decrement in performance observed when simulated hyperopia was combined with sustained near work. This combination resulted in performance reductions of between 5% and 24% across the range of academic-related measures. A significant moderate correlation was also found between the change in horizontal near heterophoria and the change in several of the academic-related outcome measures, following the addition of simulated hyperopia. Conclusions: A relatively low level of simulated bilateral hyperopia impaired children’s performance on a range of academic–related outcome measures, with sustained near work further exacerbating this effect. Further investigations are required to determine the impact of correcting low levels of hyperopia on academic performance in children.

Simulated hyperopic anisometropia and reading, visual information processing, and reading-related eye movement performance in children

Purpose: This study investigated the impact of simulated hyperopic anisometropia and sustained near work on performance of academic-related measures in children. Methods: Participants included 16 children (mean age: 11.1 ± 0.8 years) with minimal refractive error. Academic-related outcome measures included a reading test (Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (Developmental Eye Movement test). Performance was assessed with and without 0.75 D of imposed monocular hyperopic defocus (administered in a randomised order), before and after 20 minutes of sustained near work. Unilateral hyperopic defocus was systematically assigned to either the dominant or non-dominant sighting eye to evaluate the impact of ocular dominance on any performance decrements. Results: Simulated hyperopic anisometropia and sustained near work both independently reduced performance on all of the outcome measures (p<0.001). A significant interaction was also observed between simulated anisometropia and near work (p<0.05), with the greatest decrement in performance observed during simulated anisometropia in combination with sustained near work. Laterality of the refractive error simulation (ocular dominance) did not significantly influence the outcome measures (p>0.05). A reduction of up to 12% in performance was observed across the range of academic-related measures following sustained near work undertaken during the anisometropic simulation. Conclusion: Simulated hyperopic anisometropia significantly impaired academic–related performance, particularly in combination with sustained near work. The impact of uncorrected habitual anisometropia on academic-related performance in children requires further investigation.