Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Intelligent task-level grasp mapping for robot control

In the future, robots will enter our everyday lives to help us with various tasks.For a complete integration and cooperation with humans, these robots needto be able to acquire new skills. Sensor capabilities for navigation in real humanenvironments and intelligent interaction with humans are some of the keychallenges.Learning by demonstration systems focus on the problem of human robotinteraction, and let the human teach the robot by demonstrating the task usinghis own hands. In this thesis, we present a solution to a subproblem within thelearning by demonstration field, namely human-robot grasp mapping. Robotgrasping of objects in a home or office environment is challenging problem.Programming by demonstration systems, can give important skills for aidingthe robot in the grasping task.The thesis presents two techniques for human-robot grasp mapping, directrobot imitation from human demonstrator and intelligent grasp imitation. Inintelligent grasp mapping, the robot takes the size and shape of the object intoconsideration, while for direct mapping, only the pose of the human hand isavailable.These are evaluated in a simulated environment on several robot platforms.The results show that knowing the object shape and size for a grasping taskimproves the robot precision and performance

On high-rate full-diversity 2x2 space-time codes with low-complexity optimum detection

The 2×2 MIMO profiles included in Mobile WiMAX specifications are Alamouti’s space-time code (STC) fortransmit diversity and spatial multiplexing (SM). The former hasfull diversity and the latter has full rate, but neither of them hasboth of these desired features. An alternative 2×2 STC, which is both full rate and full diversity, is the Golden code. It is the best known 2×2 STC, but it has a high decoding complexity. Recently, the attention was turned to the decoder complexity, this issue wasincluded in the STC design criteria, and different STCs wereproposed. In this paper, we first present a full-rate full-diversity2×2 STC design leading to substantially lower complexity ofthe optimum detector compared to the Golden code with only a slight performance loss. We provide the general optimized form of this STC and show that this scheme achieves the diversitymultiplexing frontier for square QAM signal constellations. Then, we present a variant of the proposed STC, which provides a further decrease in the detection complexity with a rate reduction of 25% and show that this provides an interesting trade-off between the Alamouti scheme and SM.

Using qualia information to identify lexical semantic classes in an unsupervised clustering task

Acquiring lexical information is a complex problem, typically approached by relying on a number of contexts to contribute information for classification. One of the first issues to address in this domain is the determination of such contexts. The work presented here proposes the use of automatically obtained FORMAL role descriptors as features used to draw nouns from the same lexical semantic class together in an unsupervised clustering task. We have dealt with three lexical semantic classes (HUMAN, LOCATION and EVENT) in English. The results obtained show that it is possible to discriminate between elements from different lexical semantic classes using only FORMAL role information, hence validating our initial hypothesis. Also, iterating our method accurately accounts for fine-grained distinctions within lexical classes, namely distinctions involving ambiguous expressions. Moreover, a filtering and bootstrapping strategy employed in extracting FORMAL role descriptors proved to minimize effects of sparse data and noise in our task.

Automatic Lexical Semantic Classification of Nouns

The work we present here addresses cue-based noun classification in English and Spanish. Its main objective is to automatically acquire lexical semantic information by classifying nouns into previously known noun lexical classes. This is achieved by using particular aspects of linguistic contexts as cues that identify a specific lexical class. Here we concentrate on the task of identifying such cues and the theoretical background that allows for an assessment of the complexity of the task. The results show that, despite of the a-priori complexity of the task, cue-based classification is a useful tool in the automatic acquisition of lexical semantic classes.

Excuse me, but your accent is very unusual. The complexity of establishing third languages in Inglourious Basterds. Applying a model of translation analysis to dubbing

The growing multilingual trend in movie production comes with a challenge for dubbing translators since they are increasingly confronted with more than one source language. The main purpose of this master’s thesis is to provide a case study on how these third languages (see CORRIUS and ZABALBEASCOA 2011) are rendered. Another aim is to put a particular focus on their textual and narrative functions and detect possible shifts that might occur in translations. By applying a theoretical model for translation analysis (CORRIUS and ZABALBEASCOA 2011), this study describes how third languages are rendered in the German, Spanish, and Italian dubbed versions of the 2009 Tarantino movie Inglourious Basterds. A broad range of solution-types are thereby revealed and prevalent restrictions of the translation process identified. The target texts are brought in context with some sociohistorical aspects of dubbing in order to detect prevalent norms of the respective cultures andto discuss the acceptability of translations (TOURY 1995). The translatability potential of even highly complex multilingual audiovisual texts is demonstrated in this study. Moreover, proposals for further studies in multilingual audiovisual translation are outlined and the potential for future investigations in this field thereby emphasised.

Organisational Values as "Attractors of Chaos": An Emerging Cultural Change to Manage Organisational Complexity

Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.

Cognitive stimulation through task-oriented telerobotics

The project presented, iCognos, consists of a flexible platform to assist end-users in performing a series of mental tasks with a sensitized mobile telerobotic platform aimed at mitigating the problems associated to cognitive disorders with an ecological cognition approach.

Organisational values as "attractors of chaos": An emerging cultural change to manage organisational complexity

Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.

Deciding analytically or trusting your intuition? The advantadges and disadvantadges of analytic and intuitive thought

Recent research has highlighted the notion that people can make judgmentsand choices by means of two systems that are labeled here tacit(or intuitive) and deliberate (or analytic). Whereas most decisionstypically involve both systems, this chapter examines the conditions underwhich each system is liable to be more effective. This aims to illuminatethe age-old issue of whether and when people should trust intuition or analysis. To do this, a framework is presented to understand how thetacit and deliberate systems work in tandem. Distinctions are also madebetween the types of information typically used by both systems as wellas the characteristics of environments that facilitate or hinder accuratelearning by the tacit system. Next, several experiments that havecontrasted intuitive and analytic modes on the same tasks are reviewed.Together, the theoretical framework and experimental evidence leads tospecifying the trade-off that characterizes their relative effectiveness.Tacit system responses can be subject to biases. In making deliberate systemresponses, however, people might not be aware of the correct rule to dealwith the task they are facing and/or make errors in executing it. Whethertacit or deliberate responses are more valid in particular circumstancesrequires assessing this trade-off. In this, the probability of making errorsin deliberate thought is postulated to be a function of the analytical complexityof the task as perceived by the person. Thus the trade-off is one of bias (inimplicit responses) versus analytical complexity (when tasks are handled indeliberate mode). Finally, it is noted that whereas much attention has beenpaid in the past to helping people make decisions in deliberate mode, effortsshould also be directed toward improving ability to make decisions intacit mode since the effectiveness of decisions clearly depends on both. Thistherefore represents an important frontier for research.

Outcomes from studies of Antineutrophil Cytoplasm Antibody Associated Vasculitis: a systematic review by the European League Against Rheumatism systemic vasculitis task force.

Objectives: We undertook a systematic literature review as a background to the European League Against Rheumatism (EULAR) recommendations for conducting clinical trials in anti-neutrophil cytoplasm antibody associated vasculitis (AAV), and to assess the quality of evidence for outcome measures in AAV. Methods: Using a systematic Medline search, we categorised the identified studies according to diagnoses. Factors affecting remission, relapse, renal function and overall survival were identified. Results: A total of 44 papers were reviewed from 502 identified by our search criteria. There was considerable inconsistency in definitions of end points. Remission rates varied from 30% to 93% in Wegener granulomatosis (WG), 75% to 89% in microscopic polyangiitis (MPA) and 81% to 91% in Churg¿Strauss syndrome (CSS). The 5-year survival for WG, MPA and CSS was 74¿91%, 45¿76% and 60¿97%. Relapse (variably defined) was common in the first 2 years but the frequency varied: 18% to 60% in WG, 8% in MPA, and 35% in CSS. The rate of renal survival in WG varied from 23% at 15 months to 23% at 120 months. Methods used to assess morbidity varied between studies. Ignoring the variations in definitions of the stage of disease, factors influencing remission, relapse, renal and overall survival included immunosuppressive therapy used, type of organ involvement, presence of ANCA, older age and male ender. Conclusions: Factors influencing remission, relapse, renal and overall survival include the type of immunosuppressive therapy used, pattern of organ involvement, presence of ANCA, older age and male gender. Methodological variations between studies highlight the need for a consensus on terminology and definitions for future conduct of clinical studies in AAV.

From local groups to early states: the development of complexity in protohistoric Catalonia

La recerca sobre la protohistoria de Catalunya s'ha fonamentat tradicionalment en la historia cultural, pero el treba11 deIs darrers vint-i-cinc anys ha comenat a donar 11um sobre aspectes crucials com el canvi social i la formació de l'Estat arcaico Aquest article és una visió general sobre aquests temes. S'hi analitza particularment el paper del creixement demogrMic com a element crucial del canvi social, pero també s'hi té en compte el paper que eventualment hi hagin pogut tenir els moviments de població i el comerç colonial.

Training referential communicative skills to individuals with autism spectrum disorder: a pilot study

Summary. The present study reports the effects of referential communication training in individuals formally diagnosed with autism spectrum disorder (ASD). Participants were 20 children with ASD (M age = 14.3 yr., SD = 4.2; 6 girls, 14 boys) in the role of speakers and 20 control children, who acted as listeners. They were all enrolled in mainstream compulsory education. Inclusion/exclusion criteria were defined according to the clinical diagnosis of ASD, the presence or absence of additional or associated disability, previous training in referential communication, and any drug treatment. Speakers were randomly assigned to one of two groups (trained vs untrained). Linguistic age, cognitive level, and autistic symptoms were analyzed, respectively, with the Peabody Picture Vocabulary Test (PPVT), the Wechsler Intelligence Scale (WISCR or WAISIII), and the Autistic Behavior Checklist (ABC). Communicative abilities were analyzed through two indexes related to message complexity and self-regulation. The trained group was trained in referential communication tasks (task analysis, role taking, and task evaluation), while the untrained group took part in a communicative game but without any specific communicative training. The results showed that the complexity of emitted messages had improved statistically significantly in the trained group as an effect of training. Ecological referential communication is shown to be an appropriate paradigm for studying the communicative process and its products and could be used to develop and implement a training program focused on those skills in which individuals with ASD are most deficient.

Dissecting the role of low-complexity regions in the evolution of vertebrate proteins

Low-complexity regions (LCRs) in proteins are tracts that are highly enriched in one or a few aminoacids. Given their high abundance, and their capacity to expand in relatively short periods of time through replication slippage, they can greatly contribute to increase protein sequence space and generate novel protein functions. However, little is known about the global impact of LCRs on protein evolution. We have traced back the evolutionary history of 2,802 LCRs from a large set of homologous protein families from H.sapiens, M.musculus, G.gallus, D.rerio and C.intestinalis. Transcriptional factors and other regulatory functions are overrepresented in proteins containing LCRs. We have found that the gain of novel LCRs is frequently associated with repeat expansion whereas the loss of LCRs is more often due to accumulation of amino acid substitutions as opposed to deletions. This dichotomy results in net protein sequence gain over time. We have detected a significant increase in the rate of accumulation of novel LCRs in the ancestral Amniota and mammalian branches, and a reduction in the chicken branch. Alanine and/or glycine-rich LCRs are overrepresented in recently emerged LCR sets from all branches, suggesting that their expansion is better tolerated than for other LCR types. LCRs enriched in positively charged amino acids show the contrary pattern, indicating an important effect of purifying selection in their maintenance. We have performed the first large-scale study on the evolutionary dynamics of LCRs in protein families. The study has shown that the composition of an LCR is an important determinant of its evolutionary pattern.

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process