Enhancing performance of reinforcement learning models in the presence of noisy rewards

Reinforcement learning models learn the optimal policy by interacting with the environment and observing the states and rewards. If the rewards that the model observes are noisy then learning an optimal policy becomes a difficult task. We present an approach that can enhance the performance of reinforcement learning models in the presence of noisy rewards. Along with the standard reinforcement learning model, we propose to use a noise filter which estimates the true reward that the model should receive. The noise filter is designed using a non-linear approximator. Through various experiments we demonstrate that this approach improves the performance of the model in the presence of noisy rewardsOperations Research and Industrial Engineerin

Status of electric vehicles charging methods

Compared with vehicles powered by fuel, electric vehicles are more efficient in energy saving, emission reduction, and environmental protection. As a result, it is becoming most important with more applications in the transportation sector. As Electric vehicles usage is growing from day to day Electric vehicles (EVs) will become a reality in the future. The time taking the method of charging an EV becomes a major problem to accept the electronic revolution of the automobile industry. In this paper, we have discussed the various charging methods for an Electric vehicle, which also gives us a view of electric vehicle use in today’s world. It gives a brief overview of the present and methods recommended for EV charging

Notes on distribution of Acronema hookeri (Apiaceae) and Impatiens falcifera (Balsaminaceae) in Arunachal Pradesh, India

In the present communication, the distribution of two species, Acronema hookeri (C.B.Clarke) H.Wolff and Impatiens falcifera Hook.f. has been discussed. The latter is recorded here as a new distributional record, whereas the former is reported as the first authentic record from Arunachal Pradesh. Short descriptions, notes, and field photographs are provided to identify the species easily

A Retrospective Assessment of CRP Levels in Children with Acute Bronchiolitis: An Observational Study

Aim: The aim of the present study was to assess the frequency of elevated CRP in children with acute bronchiolitis. Material & methods: A retrospective assessment of children with acute bronchiolitis admitted to Department of Pediatrics, GS Medical College, Pilkhuwa, Uttar Pradesh. Demographic, clinical, laboratory and radiological data, and outcomes were collected. Patients with high CRP were compared with those with normal levels for the duration of 12 months. Total 200 patients were included in the study. Results: Of 200 patients, 120 (60%) were males. Median presentation age was 3.9 (interquartile range (IQR), 1.27-12.33) months. The most common clinical presentation was cough (160 (80%) patients) followed by fever (152 (76%) patients). Median CRP level was 10.5 (IQR, 2.8-35.1) mg/L. CRP was high in 150 (75%) patients. Respiratory syncytial virus (RSV) was detected in 70 patients. 170/200 patients had positive chest X-ray. Antibiotics were used in 140/20 patients. The significant variables were tested for multicollinearity (VIF > 8) between each other and were put into a logistic regression model. Accordingly, fever (P = 0.018) and hemoglobin level (P = 0.003) were found to be the independent predictor for high CRP levels. Conclusion: This study showed that most patients with acute bronchiolitis had high rate of elevated CRP values that did not correlate with the rate of bacterial coinfection. Children with high CRP levels were older at presentation, presented with more fever and cough, and had a lower hemoglobin level despite that those factors were previously reported to be associated with the disease severity and bacterial coinfection

Load balancing for Software Defined Network using Machine learning

Software-Defined Networking is one of the most revolutionary and prominent technology in the field of networking. It solves the problem that our traditional network faces. Still it can face a problem of bottleneck and can be overloaded. To overcome this issue, various researcher has it given various works but they are based on two or three-parameter to perform load balancing and also they are static or dynamic. We have proposed an intelligent technique that forwards the packet i.e. TCP/UDP packet traffic based on several parameters (based on 12 parameters discussed in the latter part of this section). Based on these parameters, we have applied the trained machine using KMeans [1] and DBSCAN [2] clustering algorithm and also determine the optimal number of clusters. We have tested it on the huge number of packet that are 5000, 10000, 20000, 50000, 100000, 10000000.We have also compared there results of the KMeans and DBSCAN algorithm and also discussed researchers vie

Over current protection of distribution system with impact of solar and wind generation using DIgSIlent power factory

The utilization of renewable resources has been growing very fast worldwide recently to manage the increasing energy gap, but it also raises some challenges like protection issues, transient stability issues and security issues in the power system operation. Mainly, wind and solar photovoltaic renewable power generation sources are account for bulky renewable energy share. The transients in power systems including renewables are reduced and have recently attracted wide attention. The impact of renewables generation on power system transients should be effectively analyzed and evaluated to improve power system reliability, stability, operation and security. DIgSILENT Power Factory software is more powerful and useful for providing phasor of fundamental power frequency components better than other existing software’s; therefore, DIgSILENT Power Factory is proposed for modeling and analysis of the system.&nbsp

Attachment styles and depression among nursing officers of tertiary care centre in India

Background: The concept of attachment plays a relevant role in mental health. Attachment style refers to how a person perceives and experiences interpersonal relationships. There are various attachment styles or patterns through which an individual attaches or form relationships with others. Attachment has a persistent and long-term impact on depression. The main aim of the study is to assess the attachment styles and depression among nursing officers of tertiary care centre in India. Methods: Descriptive research design was used. The study was conducted at all India institute of medical sciences (AIIMS), Jodhpur among 250 nursing officers selected by convenient sampling technique. Self-structured attachment style questionnaire was used to assess the attachment style and structured questionnaire centre for epidemiologic studies depression scale was used to assess the depression among nursing officers. Data analysis was done by using statistical package for social sciences-version 25 (SPSS-25). Frequency, percentage, mean, standard deviation, chi square test, Fisher exact test and Pearson correlation were used. Results: Result revealed that out of 250, majority 213 (85.2%) nursing officers had secure attachment style. Majority 183 (73.2%) nursing officers were normal, showed no depression. Moderate negative correlation was there between secure attachment style and depression scores. Strong positive correlation was found between anxious attachment style and depression scores. There was moderate positive correlation between avoidant, fearful attachments and depression scores respectively. Conclusions: The study indicates that majority of nursing officers were having secure attachment style and were normal, showed no depression. The study established a relationship between attachment style and depression

Conciseness: An Overlooked Language Task

We report on novel investigations into training models that make sentences concise. We define the task and show that it is different from related tasks such as summarization and simplification. For evaluation, we release two test sets, consisting of 2000 sentences each, that were annotated by two and five human annotators, respectively. We demonstrate that conciseness is a difficult task for which zero-shot setups with large neural language models often do not perform well. Given the limitations of these approaches, we propose a synthetic data generation method based on round-trip translations. Using this data to either train Transformers from scratch or fine-tune T5 models yields our strongest baselines that can be further improved by fine-tuning on an artificial conciseness dataset that we derived from multi-annotator machine translation test sets.Comment: EMNLP 2022 Workshop on Text Simplification, Accessibility, and Readability (TSAR

Breech presentation and neonatal fracture shaft femur – A rare case presentation

The breech extraction of the fetus through the vagina has a greater risk of hip fracture compared with the extraction by abdominalroute. A 2980 g male infant was delivered at 39 weeks by elective cesarean section for breech presentation. The newborn sustaineda fracture of the right femur. A simple immobilization of the limb in extension led to a complete healing of the fracture withoutsequelae. This case highlights that fact that cesarean delivery reduces the risk of causing a traumatic injury of the newborn comparedto vaginal delivery; especially, with breech presentation but does not eliminate this possible accidental complication