Application of different heuristic classes in memory-based and stimulus-based decisions

This paper studies the drivers of heuristic application in different decision types. The study compares differences in frequencies of heuristic classes' such as recognition, one-reason choice and trade-off applied in, respectively, memory-based and stimulus-based choices as well as in high and low involvement decisions. The study has been conducted online among 205 participants from 28 countries.

Write-erase and read paper memory transistor

Applied Physics Letters, Vol.93, issue 20

Burrows-wheeler transform in secondary memory

Master’s Thesis in Computer Engineering

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Speculative execution by using software transactional memory

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.

Cooperative memory and database transactions

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Developing Libraries Using Software Transactional Memory

Software transactional memory is a promising programming model that adapts many concepts borrowed from the databases world to control concurrent accesses to main memory (RAM) locations. This paper discusses how to support apparently irreversible operations, such as memory allocation and deallocation, within software libraries that will be used in (software memory) transactional contexts, and propose a generic and elegant approach based on a handler system, which provide the means to create and execute compensation actions at key moments during the life-time of a transaction.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Vibration control with shape-memory alloys in civil engineering structures

Dissertação apresentada à Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Doutor em Engenharia Civil

Type-based protocol conformance and aliasing control in concurrent java programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A modular distributed transactional memory framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Effect of surfactant on PDLC films with and without permanent memory effect

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Maintaining the correctness of transactional memory programs

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Help-seeking for 'memory loss' by older adults in India : patient, caregiver and health providers' perspectives

ABSTRACT: Background. In India, prevalence rates of dementia and prodromal amnestic Mild Cognitive Impairment (MCI) are 3.1% and 4.3% respectively. Most Indians refer to the full spectrum of cognitive disorders simply as ‘memory loss.’ Barring prevention or cure, these conditions will rise rapidly with population aging. Evidence-based policies and practices can improve the lives of affected individuals and their caregivers, but will require timely and sustained uptake. Objectives. Framed by social cognitive theories of health behavior, this study explores the knowledge, attitudes and practices concerning cognitive impairment and related service use by older adults who screen positive for MCI, their primary caregivers, and health providers. Methods. I used the Montreal Cognitive Assessment to screen for cognitive impairment in memory camps in Mumbai. To achieve sampling diversity, I used maximum variation sampling. Ten adults aged 60+ who had no significant functional impairment but screened positive for MCI and their caregivers participated in separate focus groups. Four other such dyads and six doctors/ traditional healers completed in-depth interviews. Data were translated from Hindi or Marathi to English and analyzed in Atlas.ti using Framework Analysis. Findings. Knowledge and awareness of cognitive impairment and available resources were very low. Physicians attributed the condition to disease-induced pathology while lay persons blamed brain malfunction due to normal aging. Main attitudes were that this condition is not a disease, is not serious and/or is not treatable, and that it evokes stigma toward and among impaired persons, their families and providers. Low knowledge and poor attitudes impeded help-seeking. Conclusions. Cognitive disorders of aging will take a heavy toll on private lives and public resources in developing countries. Early detection, accurate diagnosis, systematic monitoring and quality care are needed to compress the period of morbidity and promote quality of life. Key stakeholders provide essential insights into how scientific and indigenous knowledge and sociocultural attitudes affect use and provision of resources.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.