Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

A survey of human motion analysis using depth imagery

Analysis of human behaviour through visual information has been a highly active research topic in the computer vision community. This was previously achieved via images from a conventional camera, but recently depth sensors have made a new type of data available. This survey starts by explaining the advantages of depth imagery, then describes the new sensors that are available to obtain it. In particular, the Microsoft Kinect has made high-resolution real-time depth cheaply available. The main published research on the use of depth imagery for analysing human activity is reviewed. Much of the existing work focuses on body part detection and pose estimation. A growing research area addresses the recognition of human actions. The publicly available datasets that include depth imagery are listed, as are the software libraries that can acquire it from a sensor. This survey concludes by summarising the current state of work on this topic, and pointing out promising future research directions.

Dimensions of perception and recognition of danger

Despite abundant literature on human behaviour in the face of danger, much remains to be discovered. Some descriptive models of behaviour in the face of danger are reviewed in order to identify areas where documentation is lacking. It is argued that little is known about recognition and assessment of danger and yet, these are important aspects of cognitive processes. Speculative arguments about hazard assessment are reviewed and tested against the results of previous studies. Once hypotheses are formulated, the reason for retaining the reportory grid as the main research instrument are outlined, and the choice of data analysis techniques is described. Whilst all samples used repertory grids, the rating scales were different between samples; therefore, an analysis is performed of the way in which rating scales were used in the various samples and of some reasons why the scales were used differently. Then, individual grids are looked into and compared between respondents within each sample; consensus grids are also discussed. the major results from all samples are then contrasted and compared. It was hypothesized that hazard assessment would encompass three main dimensions, i.e. 'controllability', 'severity of consequences' and 'likelihood of occurrence', which would emerge in that order. the results suggest that these dimensions are but facets of two broader dimensions labelled 'scope of human intervention' and 'dangerousness'. It seems that these two dimensions encompass a number of more specific dimensions some of which can be further fragmented. Thus, hazard assessment appears to be a more complex process about which much remains to be discovered. Some of the ways in which further discovery might proceed are discussed.

Recognition of human activities through eSteps insoles

Recognition of everyday human activity through mobile personal sensing technology plays a central role in the field of pervasive healthcare. The Bologna-based American company eSteps Inc. addresses the growing motor disability of the lower limbs by offering pre-, during and post-hospitalisation monitoring solutions with biomechanics and telerehabilitation protocol. It has developed a smart, customised and sustainable device to monitor motor activity, fatigue and injury risk for patients and a special app to share data with caregivers and medical specialists. The objective of this study is the development of an Artificial Intelligence model to recognize the activity performed by a person with Multiple Sclerosis or a healthy person through eSteps devices.

Exploring Change in Neanderthal Behavioural Complexity: An Innovative Approach to the Study of Neanderthal Behaviour

Diachronic approaches provide potential for a more sophisticated framework within which to examine change in Neanderthal behavioural complexity using archaeological proxies such as symbolic artefacts, faunal assemblages and technology. Analysis of the temporal appearance and distribution of such artefacts and assemblages provide the basis for identifying changes in Neanderthal behavioural complexity in terms of symbolism, faunal extraction and technology respectively. Although changes in technology and faunal extraction were examined in the wider study, only the results of the symbolic study are presented below to illustrate the potential of the approach.

Human activity data discovery based on accelerometry

Dissertation to Obtain Master Degree in Biomedical Engineering

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

A framework to understand human action

This paper consists in an analysis of two explanatory models of human behaviour which play a prominent role in the contemporary literature on human action. The first model - the causalist - aims at explaining action in terms of causes and general laws. The second model - the intentionalist - explains human action in terms of intentions and practical syllogism. The difficulties of both models are presented and in the last part of the essay we propose one alternative model, based on the notion of retroduction.

Le potentiel des technologies de l’information et des communications pour le renforcement de la résilience organisationnelle lors des opérations d’évacuation : é́tude de cas de la ville de New York

Lorsque les ouragans entrent en contact avec l'environnement bâti et naturel, les autorités publiques n'ont parfois d'autre choix que de déclarer l'évacuation obligatoire de la population située en zone à risque. En raison de l'imprévisibilité du déroulement d'une catastrophe et des comportements humains, les opérations d'évacuation sont confrontées à une incertitude significative. Les expériences passées ont montré que les technologies de l'information et des communications (TIC) ont le potentiel d'améliorer l'état de l'art en gestion des évacuations. Malgré cette reconnaissance, les recherches empiriques sur ce sujet sont à ce jour limitées. La présente étude de cas de la ville de New York explore comment l'intégration des TIC dans la planification opérationnelle des organisations ayant des responsabilités en matière de transport peut améliorer leurs réponses aux événements et influencer le succès global du système de gestion des catastrophes. L'analyse est basée sur les informations recueillies au moyen d'entretiens semi-dirigés avec les organisations de transport et de gestion des catastrophes de la ville de New York ainsi qu’avec des experts du milieu universitaire. Les résultats mettent en lumière le potentiel des TIC pour la prise de décision en interne. Même s’il est largement reconnu que les TIC sont des moyens efficaces d'échanger de l'information en interne et entre les organisations, ces usages sont confrontés à certaines contraintes technologique, organisationnelle, structurelle et systémique. Cette observation a permis d'identifier les contraintes vécues dans les pratiques usuelles de gestion des systèmes urbains.

Translation Invariance in Object Recognition, and Its Relation to Other Visual Transformations

Human object recognition is generally considered to tolerate changes of the stimulus position in the visual field. A number of recent studies, however, have cast doubt on the completeness of translation invariance. In a new series of experiments we tried to investigate whether positional specificity of short-term memory is a general property of visual perception. We tested same/different discrimination of computer graphics models that were displayed at the same or at different locations of the visual field, and found complete translation invariance, regardless of the similarity of the animals and irrespective of direction and size of the displacement (Exp. 1 and 2). Decisions were strongly biased towards same decisions if stimuli appeared at a constant location, while after translation subjects displayed a tendency towards different decisions. Even if the spatial order of animal limbs was randomized ("scrambled animals"), no deteriorating effect of shifts in the field of view could be detected (Exp. 3). However, if the influence of single features was reduced (Exp. 4 and 5) small but significant effects of translation could be obtained. Under conditions that do not reveal an influence of translation, rotation in depth strongly interferes with recognition (Exp. 6). Changes of stimulus size did not reduce performance (Exp. 7). Tolerance to these object transformations seems to rely on different brain mechanisms, with translation and scale invariance being achieved in principle, while rotation invariance is not.

A review of palaeoclimates and palaeoenvironments in the Levant and Eastern Mediterranean from 25,000 to 5000 years BP: setting the environmental background for the evolution of human civilisation

The southern Levant has a long history of human habitation and it has been previously suggested that climatic changes during the Late Pleistocene-Holocene stimulated changes in human behaviour and society. In order to evaluate such linkages, it is necessary to have a detailed understanding of the climate record. We have conducted an extensive and up-to-date review of terrestrial and marine climatic conditions in the Levant and Eastern Mediterranean during the last 25,000 years. We firstly present data from general circulation models (GCMs) simulating the climate for the last glacial maximum (LGM), and evaluate the output of the model by reference to geological climate proxy data. We consider the types of climate data available from different environments and proxies and then present the spatial climatic "picture" for key climatic events. This exercise suggests that the major Northern Hemisphere climatic fluctuations of the last 25,000 years are recorded in the Eastern Mediterranean and Levantine region. However, this review also highlights problems and inadequacies with the existing data. (c) 2006 Elsevier Ltd. All rights reserved.

A little learning is a dangerous thing: an experimental demonstration of ignorance-driven inference

Studies of ignorance-driven decision making have been employed to analyse when ignorance should prove advantageous on theoretical grounds or else they have been employed to examine whether human behaviour is consistent with an ignorance-driven inference strategy (e. g., the recognition heuristic). In the current study we examine whether-under conditions where such inferences might be expected-the advantages that theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgements, participants reliably use recognition as a basis for their judgements. Their wealth judgements under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all of the names (a "less-is-more effect"). These results are consistent across a number of variations: the number of options given to participants and the nature of the wealth judgement. A basic model of recognition-based inference predicts these effects.

Multicamera trajectory analysis for semantic behaviour characterisation

In this paper we propose an innovative approach for behaviour recognition, from a multicamera environment, based on translating video activity into semantics. First, we fuse tracks from individual cameras through clustering employing soft computing techniques. Then, we introduce a higher-level module able to translate fused tracks into semantic information. With our proposed approach, we address the challenge set in PETS 2014 on recognising behaviours of interest around a parked vehicle, namely the abnormal behaviour of someone walking around the vehicle.

A framework to understand human action

O trabalho consiste numa análise de dois modelos explicativos do comportamento humano considerados fundamentais na literatura contemporânea sobre teoria da ação. O primeiro modelo, o causalista, tenta explicar as ações em termos de causas e leis gerais. O segundo explica a ação em termos de intenções e silogismos práticos. As dificuldades e problemas de ambos modelos são apresentadas e na última parte do ensaio propomos um modelo alternativo baseado na noção de retrodução.