ESCOLA SUPERIOR DE TECNOLOGIA E GESTÃO DE VISEU
Permanent URI for this community
Browse
Browsing ESCOLA SUPERIOR DE TECNOLOGIA E GESTÃO DE VISEU by Field of Science and Technology (FOS) "Ciências Naturais"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Contribution to the knowledge of hierarchical clustering algorithms and consensus clustering. Studies applied to personal recognition by hands biometricsPublication . Sousa, Lúcia; Gama, João; Faceli, KattiIn exploratory data analysis, hierarchical clustering algorithms with its features can provide different clusterings when applied to the same data set. In the presence of several clusterings, each one identifying a specific data structure, consensus clustering provide a contribution to deal with this issue. The work reported here is composed by two parts: In the first part, we intend to explore the profile of base hierarchical clusterings, according to their variabilities, to obtain the consensus clustering. As a first result of our researches, we identified the consensus clustering technique as having better performance than the others, depending on the characteristics of hierarchical clusterings used as base. This result allows us to identify a sufficient condition for the existence of consensus clustering, as well as define a new strategy to evaluate the consensus clustering. It also leads to study a new property of hierarchical clustering algorithms. In the second part, we explore a real-world application. In a first analysis, we use data sets derived by biometrics extracted from hands for personal recognition. We show that the hierarchical clusterings obtained by SEP/COP algorithms, can provide results with great accuracy when applied to these data sets. Furthermore, we found an increased 100% of recognition rate, comparing to the ones found in literature. In a second analysis, we consider the application of consensus clustering techniques to the problem of the identification of people's parenting by the hands biometrics. The results obtained indicate that hand’s photography has information that allows the identification of people’s family members but, according to our data, we didn't have very positive results (we observed a probability of 95% of the parents, and 94% of a sibling to be in the half of the more similar hands) that we believe it’s due to the poor quality of the photographs we used. However, the results indicate that the technique has potential, and if the collection of photographs is made using a scanner with fixed pins, the hand may be an interesting alternative for the identification of parenting of missing children when it is applied the consensus clustering.
- Environmental and Economic Assessment of Desktop vs. Laptop Computers: A Life Cycle ApproachPublication . Domingos Ferreira, Miguel; Domingos, idalina; Leite dos Santos, Lenise Maria; Barreto Ana; Ferreira, JoséThis study evaluates and compares the environmental and economic implications of desktop and laptop computer systems throughout their life cycles using screening life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The functional unit was defined as the use of one computer system for fundamental home and small-business productivity tasks for over four years. The analysis considered the production, use, and end-of-life phases. The results showed the desktop system had a higher overall carbon footprint (679.1 kg CO2eq) compared to the laptop (286.1 kg CO2eq). For both systems, manufacturing contributed the largest share of the emissions, followed by use. Desktops exhibited significantly higher use phase emissions, due to greater energy consumption. Life cycle cost analysis revealed that laptops had slightly lower total costs (EUR 593.88) than desktops (EUR 608.40) over the 4-year period, despite higher initial investment costs. Sensitivity analysis examining different geographical scenarios highlighted the importance of considering regional factors in the LCA. Manufacturer-provided data generally showed lower carbon footprint values than the modeled scenarios. This study emphasizes the need for updated life cycle inventory data and energy efficiency improvements to reduce the environmental impacts of computer systems. Overall, laptops demonstrated environmental and economic advantages over desktops in the defined usage cases.