Browsing by Issue Date, starting with "2022-12-27"
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- Anomaly detection of consumption in Hotel Units: A case study comparing isolation forest and variational autoencoder algorithmsPublication . Mendes, Tomás; Cardoso, Pedro; Monteiro, Jânio; Raposo, JoãoBuildings are responsible for a high percentage of global energy consumption, and thus, the improvement of their efficiency can positively impact not only the costs to the companies they house, but also at a global level. One way to reduce that impact is to constantly monitor the consumption levels of these buildings and to quickly act when unjustified levels are detected. Currently, a variety of sensor networks can be deployed to constantly monitor many variables associated with these buildings, including distinct types of meters, air temperature, solar radiation, etc. However, as consumption is highly dependent on occupancy and environmental variables, the identification of anomalous consumption levels is a challenging task. This study focuses on the implementation of an intelligent system, capable of performing the early detection of anomalous sequences of values in consumption time series applied to distinct hotel unit meters. The development of the system was performed in several steps, which resulted in the implementation of several modules. An initial (i) Exploratory Data Analysis (EDA) phase was made to analyze the data, including the consumption datasets of electricity, water, and gas, obtained over several years. The results of the EDA were used to implement a (ii) data correction module, capable of dealing with the transmission losses and erroneous values identified during the EDA’s phase. Then, a (iii) comparative study was performed between a machine learning (ML) algorithm and a deep learning (DL) one, respectively, the isolation forest (IF) and a variational autoencoder (VAE). The study was made, taking into consideration a (iv) proposed performance metric for anomaly detection algorithms in unsupervised time series, also considering computational requirements and adaptability to different types of data. (v) The results show that the IF algorithm is a better solution for the presented problem, since it is easily adaptable to different sources of data, to different combinations of features, and has lower computational complexity. This allows its deployment without major computational requirements, high knowledge, and data history, whilst also being less prone to problems with missing data. As a global outcome, an architecture of a platform is proposed that encompasses the mentioned modules. The platform represents a running system, performing continuous detection and quickly alerting hotel managers about possible anomalous consumption levels, allowing them to take more timely measures to investigate and solve the associated causes.
- Application of In Vitro plant tissue culture techniques to halophyte species: A reviewPublication . L, Custódio; Charles, Gilbert; Magné, Christian; Barba-Espín, Gregorio; Piqueras, Abel; Hernández, José A.; Ben Hamed, Karim; Castañeda-Loaiza, Viana; Fernandes, Eliana; Rodrigues, Maria JoãoHalophytes are plants able to thrive in environments characterized by severe abiotic conditions, including high salinity and high light intensity, drought/flooding, and temperature fluctuations. Several species have ethnomedicinal uses, and some are currently explored as sources of food and cosmetic ingredients. Halophytes are considered important alternative cash crops to be used in sustainable saline production systems, due to their ability to grow in saline conditions where conventional glycophyte crops cannot, such as salt-affected soils and saline irrigation water. In vitro plant tissue culture (PTC) techniques have greatly contributed to industry and agriculture in the last century by exploiting the economic potential of several commercial crop plants. The application of PTC to selected halophyte species can thus contribute for developing innovative production systems and obtaining halophyte-based bioactive products. This work aimed to put together and review for the first time the most relevant information on the application of PTC to halophytes. Several protocols were established for the micropropagation of different species. Various explant types have been used as starting materials (e.g., basal shoots and nodes, cotyledons, epicotyls, inflorescence, internodal segments, leaves, roots, rhizomes, stems, shoot tips, or zygotic embryos), involving different micropropagation techniques (e.g., node culture, direct or indirect shoot neoformation, caulogenesis, somatic embryogenesis, rooting, acclimatization, germplasm conservation and cryopreservation, and callogenesis and cell suspension cultures). In vitro systems were also used to study physiological, biochemical, and molecular processes in halophytes, such as functional and salt-tolerance studies. Thus, the application of PTC to halophytes may be used to improve their controlled multiplication and the selection of desired traits for the in vitro production of plants enriched in nutritional and functional components, as well as for the study of their resistance to salt stress.