320 research outputs found
Belief Tree Search for Active Object Recognition
Active Object Recognition (AOR) has been approached as an unsupervised
learning problem, in which optimal trajectories for object inspection are not
known and are to be discovered by reducing label uncertainty measures or
training with reinforcement learning. Such approaches have no guarantees of the
quality of their solution. In this paper, we treat AOR as a Partially
Observable Markov Decision Process (POMDP) and find near-optimal policies on
training data using Belief Tree Search (BTS) on the corresponding belief Markov
Decision Process (MDP). AOR then reduces to the problem of knowledge transfer
from near-optimal policies on training set to the test set. We train a Long
Short Term Memory (LSTM) network to predict the best next action on the
training set rollouts. We sho that the proposed AOR method generalizes well to
novel views of familiar objects and also to novel objects. We compare this
supervised scheme against guided policy search, and find that the LSTM network
reaches higher recognition accuracy compared to the guided policy method. We
further look into optimizing the observation function to increase the total
collected reward of optimal policy. In AOR, the observation function is known
only approximately. We propose a gradient-based method update to this
approximate observation function to increase the total reward of any policy. We
show that by optimizing the observation function and retraining the supervised
LSTM network, the AOR performance on the test set improves significantly.Comment: IROS 201
The Relations Between Phenylalanine–Ammonia Lyase, Glutathione-s-Transferase Activities and the Concentrations of Total Tannins, Phytochelatins, Glutathione, and Peroxidation in two Cultivars of Sorghum (Sorghum bicolor (L.) Moench) Exposed to Aluminum
Interlanguage Pragmatic Learning Strategies (IPLS) as Predictors of L2 Speech Act Knowledge : A Case of Iranian EFL Learners
Acknowledgments We acknowledge Golestan University that supported this study under grant number 992124. We are also grateful to the participants who took part in our study.Peer reviewedPublisher PD
Development of new materials based on polymeric reinforced and self-reinforced biocomposites from natural resources
Programa Oficial de Doutoramento en Física Aplicada. 5021V01[Abstract]
The present thesis has focused on the development and study of biodegradable polymeric biocomposites obtained from natural resources for food packaging industry. Two types of biopolymer matrix i.e. poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and potato starch and two types of filler i.e. cellulose nanocrystals (CNC) and PHBV microparticles were used. Fillers were introduced into the matrices with different methods including solvent cast film, melt mixing and extrusion. In this regard, two approaches of reinforcing and self-reinforcing were followed. As a result, three different compositions were developed namely PHBV/CNC and starch/PHBV microparticles in the reinforcing approach and PHBV/PHBV microparticles in the self-reinforcing approach.
The main aim was to produce biocomposites with modified thermal, mechanical and morphological properties and also with higher crystallinity and barrier properties. Results showed that in all cases, the filler acted as nucleating agent inside the matrix. Consequently, biocomposites with improved properties were obtained which made these ecological materials to be good candidates for packaging applications.[Resumen]
La presente tesis se ha centrado en el desarrollo y estudio de biocompuestos poliméricos biodegradables obtenidos a partir de recursos naturales para la industria de envase y embalaje de alimentos. Se usaron dos tipos de matrices de biopolímero, poli (3-hidroxibutirato-co-3-hidroxivalerato) (PHBV) y almidón de patata y dos tipos de relleno, nanocristales de celulosa (CNC) y micropartículas de PHBV. Los rellenos se introdujeron en las matrices con diferentes métodos, incluyendo el cast film, mezcla en estado fundido y extrusión. En este sentido, se aplicaron dos enfoques de refuerzo y auto-refuerzo. Se desarrollaron tres composiciones diferentes: PHBV/CNC y almidón/micropartículas de PHBV en el enfoque de refuerzo y PHBV/micropartículas de PHBV en el enfoque de auto-refuerzo.
El objetivo principal fue producir biocompuestos con propiedades térmicas, mecánicas y morfológicas modificadas y también con mayor cristalinidad y propiedades barrera. En todos los casos, el relleno actuó como agente nucleante dentro de la matriz. En consecuencia, se obtuvieron biocompuestos con propiedades mejoradas que hacen a estos materiales ecológicos ser buenos candidatos para aplicaciones de envase y embalaje.[Resumo]
A presente tese centrouse no desenvolvemento e estudo de biocomposites poliméricos biodegradables obtidos de recursos naturais para a industria do envase e embalaxe de alimentos. Foron utilizados dous tipos de matrices de biopolímeros, poli (3-hidroxibutirato-co-3-hidroxivalerato) (PHBV) e almidón de pataca e dous tipos de recheo, nanocristais de celulosa (CNC) e micropartículas de PHBV. Os recheos foron introducidos nas matrices con diferentes métodos, incluido cast film, mestura en fundido e extrusión. A este respeto, aplicáronse dous enfoques de reforzo e auto-reforzo. Desenvolvéronse tres composicións diferentes: PHBV/CNC e almidón/micropartículas de PHBV no enfoque de reforzo e PHBV/micropartículas de PHBV no enfoque de auto-reforzo.
O obxectivo principal foi producir biocomposites con propiedades térmicas, mecánicas e morfolóxicas modificadas e tamén con maior cristalinidade e propiedades barreira. En todos os casos, o recheo actuou como axente nucleante dentro da matriz. Consecuentemente, obtivéronse biocomposites con propiedades melloradas que fan que estes materiais ecolóxicos sexan bos candidatos para aplicacións de envase e embalaxe
system dynamics modeling of the food-water-energy nexus in urban areas, focusing on community gardens
The urgent need to address sustainability challenges in food, water, and energy (FWE) has led to the FWE Nexus framework. Ensuring food security and sustainable urban agriculture are critical elements of sustainable development. Community gardens (CG) have gained prominence as they enhance food production, foster social cohesion, and mitigate environmental impacts. This study investigates CGs’ land usage using a system dynamics modeling approach based on data from a case study at Concordia University’s Loyola Campus Garden. Simulations were done using the Vensim Software. The objective is to analyze land usage in response to various CG scenarios: (1) harvesting ratio on dedicated CG land, (2) production efficiency by involving experienced farmers, and (3) cost considerations.
The findings reveal insights into CGs’ potential for sustainable development. More CG land leads to increased local food production, impacting food security positively. Improving CG efficiency enhances their role in addressing food-related challenges. However, financial considerations must be balanced for long-term viability and scalability.
The study aligns with the United Nations Sustainable Development Goals (SDGs). Evidence supports CGs’ contributions to SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production). Policymakers, planners, and community organizers can leverage insights to promote sustainable urban agriculture and achieve development objectives.
Furthermore, this study highlights CGs’ importance in the FWE Nexus framework and their potential for sustainable development. Understanding land usage dynamics allows informed decisions to enhance food security, foster communities’ well-being, and promote responsible consumption in urban areas
The Effect of Interactionist vs. Interventionist Models of Dynamic Assessment on L2 Learners’ Pragmatic Comprehension Accuracy and Speed
Various models of Dynamic Assessment (DA) have been used in L2 pragmatic instruction and have proved their significant contributions to pragmatic production; however, there is a paucity of research regarding their implementation for pragmatic comprehension. Therefore, this study sought to investigate the effects of interactionist and interventionist models of DA on the accuracy and speed of pragmatic comprehension among a convenience sample of 60 advanced EFL learners who were randomly assigned into two DA groups and a control group. A listening pragmatic comprehension test developed and validated by Garcia (2004) was used both as a pretest and as a posttest. During the 14-session treatment, the interactionist DA group received metapragmatic instruction about 28 conversations, and learners interacted with each other and the teacher. Assistance and scaffolding were continuously provided by the teacher as the more knowledgeable other (MKO) within the learners’ Zone of Proximal Development (ZPD). The interventionist DA class received its treatment based on DA procedures as presented by Lantolf and Poehner (2010). However, the Non-DA group only received metapragmatic instruction about the conversations from the instructor without any DA-based intervention or interaction. Data analysis using one-way ANCOVA revealed that study groups differed in their pragmatic comprehension accuracy and speed: DA groups significantly outperformed the control group. The interventionist DA group did significantly better than the interactionist DA group for pragmatic accuracy but nor for pragmatic comprehension speed. The pedagogical implication of the study is that teachers can utilize interventionist and interactionist DA to foster learners’ pragmatic comprehension accuracy
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