Deep learning in food category recognition

Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent of big data and the development of data-oriented fields like deep learning have provided advancements in food category recognition. With increasing computational power and ever-larger food datasets, the approach’s potential has yet to be realized. This survey provides an overview of methods that can be applied to various food category recognition tasks, including detecting type, ingredients, quality, and quantity. We survey the core components for constructing a machine learning system for food category recognition, including datasets, data augmentation, hand-crafted feature extraction, and machine learning algorithms. We place a particular focus on the field of deep learning, including the utilization of convolutional neural networks, transfer learning, and semi-supervised learning. We provide an overview of relevant studies to promote further developments in food category recognition for research and industrial applicationsMRC (MC_PC_17171)Royal Society (RP202G0230)BHF (AA/18/3/34220)Hope Foundation for Cancer Research (RM60G0680)GCRF (P202PF11)Sino-UK Industrial Fund (RP202G0289)LIAS (P202ED10Data Science Enhancement Fund (P202RE237)Fight for Sight (24NN201);Sino-UK Education Fund (OP202006)BBSRC (RM32G0178B8

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Evaluation of the ingestive behaviour of the dairy cow under two systems of rotation with slope

The ingestive behaviour of grazing animals is modulated by the vegetation characteristics, topography and the type of stocking method. This research was carried out in 2019, at the Rumipamba CADER-UCE. It aimed to evaluate the impact of two contrasting stocking methods of dairy cows grazing a pasture with an average of slope >8.5%. Four dairy cows were set to graze a 0.4 ha paddock for 5 days for continuous stocking methods, while for the electric fence methods the dairy cows were restricted to 0.2 ha and the fence was moved uphill every 3 hours, repeating this process four times a day. Cow were equipped with activity sensors for 12 h per day. The whole procedure was repeated 2 times after realizing an equalization cuts and both paddocks, a rest time of 30 days and a random reassignment of paddocks to one of the treatments. The cows showed a difference in terms of the percentage of grazing P=0.0072, being higher with the electric fence (55% of the measurement time). From rising-plate-meter estimates of available biomass along the grazing periods, we calculated despite similar forage allowances (electric fence = 48.06 kg DM/cow/d and continuous = 48.21 DM/cow/d) a higher forage intake was obtained in the electric fence treatment (17.5 kg DM/cow/d) compared the continuous stocking (15.7 kg DM/cow/d) (P=0.006). In terms of milk production animals grazing under the differences electrical fence stocking method tended (P=0.0985) to produce more milk (17.39 kg/d) than those grazing in the continuous system (15.16 kg/d) due to the influence of the slope (P=0.05), while for milk quality the protein content was higher for the electric fence (33.7 g/l) than the continuous method (30.5 g/l) (P=0.039). None of the other milk properties differed between methods (P>0.05)

Bibliography of Lewis Research Center technical publications announced in 1977

This compilation of abstracts describes and indexes over 780 technical reports resulting from the scientific and engineering work performed and managed by the Lewis Research Center in 1977. All the publications were announced in the 1977 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Documents cited include research reports, journal articles, conference presentations, patents and patent applications, and theses

Dipterocarps protected by Jering local wisdom in Jering Menduyung Nature Recreational Park, Bangka Island, Indonesia

Apart of the oil palm plantation expansion, the Jering Menduyung Nature Recreational Park has relatively diverse plants. The 3,538 ha park is located at the north west of Bangka Island, Indonesia. The minimum species-area curve was 0.82 ha which is just below Dalil conservation forest that is 1.2 ha, but it is much higher than measurements of several secondary forests in the Island that are 0.2 ha. The plot is inhabited by more than 50 plant species. Of 22 tree species, there are 40 individual poles with the average diameter of 15.3 cm, and 64 individual trees with the average diameter of 48.9 cm. The density of Dipterocarpus grandiflorus (Blanco) Blanco or kruing, is 20.7 individual/ha with the diameter ranges of 12.1 – 212.7 cm or with the average diameter of 69.0 cm. The relatively intact park is supported by the local wisdom of Jering tribe, one of indigenous tribes in the island. People has regulated in cutting trees especially in the cape. The conservation agency designates the park as one of the kruing propagules sources in the province. The growing oil palm plantation and the less adoption of local wisdom among the youth is a challenge to forest conservation in the province where tin mining activities have been the economic driver for decades. More socialization from the conservation agency and the involvement of university students in raising environmental awareness is important to be done