Search results for: Huiwen You
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

Search results for: Huiwen You

4 Control of Stability for PV and Battery Hybrid System in Partial Shading

Authors: Weiying Wang, Qi Li, Huiwen Deng, Weirong Chen

Abstract:

The abrupt light change and uneven illumination will make the PV system get rid of constant output power, which will affect the efficiency of the grid connected inverter as well as the stability of the system. To solve this problem, this paper presents a strategy to control the stability of photovoltaic power system under the condition of partial shading of PV array, leading to constant power output, improving the capacity of resisting interferences. Firstly, a photovoltaic cell model considering the partial shading is established, and the backtracking search algorithm is used as the maximum power point to track algorithm under complex illumination. Then, the energy storage system based on the constant power control strategy is used to achieve constant power output. Finally, the effectiveness and correctness of the proposed control method are verified by the joint simulation of MATLAB/Simulink and RTLAB simulation platform.

Keywords: backtracking search algorithm, constant power control, hybrid system, partial shading, stability

Procedia PDF Downloads 274
3 Bodily Liberation and Spiritual Redemption of Black Women in Beloved: From the Perspective of Ecofeminism

Authors: Wang Huiwen

Abstract:

Since its release, Toni Morrison's novel Beloved has garnered significant international recognition, and its adaptation of a historical account has profoundly affected readers and scholars, evoking a visceral understanding of the suffering endured by black slaves. The ecofeminist approach has garnered more attention in recent times. The emergence of ecofeminism may be attributed to the feminist movement, which has subsequently evolved into several branches, including cultural ecofeminism, social ecofeminism, and socialist ecofeminism, each of which is developing its own specific characteristics. The many branches hold differing perspectives, yet they all converge on a key principle: the interconnectedness between the subjugation of women and the exploitation of nature can be traced back to a common underlying cognitive framework. Scholarly investigations into the novel Beloved have primarily centered on the cultural interpretations around the emancipation of African American women, with a predominant lens rooted in cultural ecofeminism. This thesis aims to analyze Morrison's feminist beliefs in the novel Beloved by integrating socialist and cultural ecofeminist perspectives, which seeks to challenge the limitations of essentialism within ecofeminism while also proposing a strategy to address exploitation and dismantle oppressive structures depicted in Beloved. This thesis examines the white patriarchal oppression system underlying the relationships between men and women, blacks and whites, and man and nature as shown in the novel. What the black women have been deprived of compared with the black men, white women and white men is a main clue of this research, while nature is a key complement of each chapter for their loss. The attainment of spiritual redemption and ultimate freedom is contingent upon the social revolution that enables bodily emancipation, both of which are indispensable for black women. The weighty historical pains, traumatic recollections, and compromised sense of self prompted African slaves to embark on a quest for personal redemption. The restoration of the bond between black men and women, as well as the relationship between black individuals and nature, is a clear and undeniable pathway towards the final freedom of black women in the novel Beloved.

Keywords: beloved, ecofeminism, black women, nature, essentialism

Procedia PDF Downloads 36
2 Evaluating the Characteristics of Paediatric Accidental Poisonings

Authors: Grace Fangmin Tan, Elaine Yiling Tay, Elizabeth Huiwen Tham, Andrea Wei Ching Yeo

Abstract:

Background: While accidental poisonings in children may seem unavoidable, knowledge of circumstances surrounding such incidents and identification of risk factors is important in the development of secondary prevention strategies. Some risk factors include age of the child, lack of adequate supervision and improper storage of substances. The aim of this study is to assess risk factors and circumstances influencing outcomes in these children. Methodology: A retrospective medical record review of all accidental poisoning cases presenting to the Children’s Emergency at National University Hospital (NUH), Singapore between January 2014 and December 2015 was conducted. Information on demographics, poisoning circumstances and clinical outcomes were collected. Results: Ninety-nine of a total of 186 poisoning cases were accidental ingestions, with a mean age of 4.7 (range 0.4 to 18.3 years). The gender distribution is rather equal with 52(52.5%) females and 47(47.5%) males. Seventy-nine (79.8%) were self-administered by the child and in 20 cases (20.2%), the substance was administered erroneously by caregivers 12/20 (60.0%) of whom were given the wrong drug dose while 8/20 (40.0%) were given the wrong substance. Self-administration was associated with presentation to the ED within 12 hours (p=0.027, OR 6.65, 95% CI 1.24-35.72). Notably, 94.9% of the cases involved substances kept within reach of the child. Sixty-nine (82.1%) had the substance kept in the original container, 3(3.6%) in food containers, 8(9.5%) in other containers and 4(4.8%) without a container. Of the 50 cases with information on labelling, 40/50(80.0%) were accurately labelled, 2/50 (4.0%) wrongly labelled, and 8/50 (16.0%) were unlabelled. Implicated substances included personal care products (11.1%), household cleaning products (3.0%), and different classes of drugs such as paracetamol (22.2%), antihistamines (17.2%) and sympathomimetics (8.1%). Children < 3 years of age were 4.8 times more likely to be poisoned by household substances than children >3 years of age (p=0.009, 95% CI 1.48-15.77). Prehospital interventions were more likely to have been done in poisoning with household substances (p=0.005, OR 6.12 95% CI 1.73-21.68). Fifty-nine (59.6%) were asymptomatic, 34 (34.3%) had a Poisoning Severity Score (PSS) grade of 1 (minor) and 6 (6.1%) grade 2 (moderate). Older children were 9.3 times more likely to be symptomatic (p<0.001, 95% CI 3.15-27.25). Thirty (32%) required admission. Conclusion: A significant proportion of accidental poisoning cases were due to medication administration errors by caregivers, which should be preventable. Risk factors for accidental poisoning included lack of adequate caregiver supervision, improper labelling and young age of the child. There is an urgent need to improve caregiver counselling during medication dispensing as well as to educate caregivers on basic child safety measures in the home to prevent future accidental poisonings.

Keywords: accidental, caregiver, paediatrics, poisoning

Procedia PDF Downloads 182
1 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 91