检索结果-南通市图书馆

东方电机 1991年第3期19卷 103-116,88页

作者： kha.,G〈m 张光蓉

ON FOETUSES WITH CEPhaLIC mALFORmATIONS, DELIVERED IN THE PEIPING UNION mEDICAL COLLEGE HOSPITAL FROm JULY 1ST 1922—JAN. 1ST 1934

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese medical Journal 1935年第7期49卷 624-635+726-731页

作者： kha.TI LIm m.D. Department of Obstetrics and Gynecology Peiping Union Medical College

monstrosities though not common occur frequently enough, and so ignorance of the subject is unwise. There are numerous theories of etiology; but they still remain as theories. Besides the main malformation there are usually other minor associated malformations. Like many other instances in obstetrical work, monstrosities are apt to occur in groups. Hydramnios is a frequent but not a constant associated factor with a monstrosity, and has to be differentiated from a multiple pregnancy. The fate of the child is negligible as shown by the high fetal mortality. Early prenatal diagnosis becomes very important as it not only means relieving the mother from wasting time, energy, and bearing unnecessary suffering, in order to carry an unfruitful pregnancy to term; but it also saves submitting the mother to the danger of dystocia with all its complications. Therefore, whenever the clinical symptoms and signs are suggestive of an abnormal pregnancy, such as hydramnios towards the second half of gestation, inability to palpate the fetal head, indistinct fetal heart, and excessive fetal movements, an X-ray should be taken. Any gestation beyond 4 months should allow of a satisfactory result and should it prove to be a monster, labour should be induced at once, perhaps best of all by puncture of the, membranes. That prevention is better than cure is just as true here as elsewhere.

关键词：

Performance Evaluation ofmulti-Agent Reinforcement Learning Algorithms

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Intelligent Automation & Soft Computing 2024年第2期39卷 337-352页

作者： Abdulghani m.Abdulghani mokhles m.Abdulghani Wilbur L.Walters kha.id H.Abed Department of Electrical&Computer Engineering and Computer Science Jackson State UniversityJacksonMS 39217USA

multi-Agent Reinforcement Learning(mARL)has proven to be successful in cooperative *** is used to investigate how autonomous agents with the same interests can connect and act in one *** cooperation scenarios are explored in recreational cooperative augmented reality environments,as well as realworld scenarios in *** this paper,we explore the realm of mARL and its potential applications in cooperative *** focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory withminimal *** accomplish this,we utilize the StarCraftmulti-Agent Challenge(SmAC)environment and train four mARL algorithms:Q-learning with mixtures of Experts(QmIX),Value-DecompositionNetwork(VDN),multi-agent Proximal PolicyOptimizer(mAPPO),andmulti-Agent Actor Attention Critic(mAA2C).These algorithms allow multiple agents to cooperate in a specific scenario to achieve the targeted *** results show that the QmIX algorithm outperforms the other three algorithms in the attacking scenario,while the VDN algorithm achieves the best results in the defending ***,the VDNalgorithmreaches the highest value of battle wonmean and the lowest value of dead *** research demonstrates the potential formARL algorithms to be used in real-world applications,such as controllingmultiple robots to provide helpful services or coordinating teams of agents to accomplish tasks that would be impossible for a human to *** SmAC environment provides a unique opportunity to test and evaluate mARL algorithms in a challenging and dynamic environment,and our results show that these algorithms can be used to achieve victory with minimal damage.

关键词： Reinforcement learning RL multi-agent mARL SmAC VDN QmIX mAPPO

Quality of life of COVID-19 recovered patients:a 1-year follow-up study from Bangladesh

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Infectious Diseases of Poverty 2023年第4期12卷 101-102页

作者： mohammad Delwer Hossain hawlader md Utba Rashid md Abdullah Saeed kha. mowshomi mannan Liza Sharmin Akter mohammad Ali Hossain Tajrin Rahman Sabrina Yesmin Barsha Alberi Afifa Shifat mosharop Hossian Tahmina Zerin mishu Soumik kha.Sagar Ridwana maher manna Nawshin Ahmed Sree Shib Shankar Devnath Debu Irin Chowdhury Samanta Sabed mashrur Ahmed Sabrina Afroz Borsha Faraz Al Zafar Sabiha Hyder Abdullah Enam habiba Babul Naima Nur miah md.Akiful haque Shopnil Roy K.m.Tanvir hassan mohammad Lutfor Rahman mohammad hayatun Nabi Koustuv Dalal Department of Public Health North South University Dhaka Bangladesh International Centre for Diarrhoeal Disease Research Bangladesh Dhaka Bangladesh National Institute of Preventive and Social medicine Dhaka Bangladesh Ibn Sina medical College Hospital Dhaka Bangladesh Public Health Promotion and Development Society (PPDS) Dhaka Bangladesh Covid Vaccine Coordination Cell Directorate General of Health Services (DGHS) Dhaka Bangladesh Institute of Statistical Research and Training (ISRT) University of Dhaka Dhaka Bangladesh School of Health Sciences Division of Public Health Science Mid Sweden University Sundsvall Sweden

BackgroundThe COVID-19 pandemic posed a danger to global public health because of the unprecedented physical,mental,social,and environmental impact affecting quality of life(QoL).The study aimed to find the changes in QoL among COVID-19 recovered individuals and explore the determinants of change more than 1 year after recovery in low-resource ***-19 patients from all eight divisions of Bangladesh who were confirmed positive by reverse transcription-polymerase chain reaction from June 2020 to November 2020 and who subsequently recovered were followed up twice,once immediately after recovery and again 1 year after the first *** follow-up study was conducted from November 2021 to January 2022 among 2438 individuals using the World Health Organization Quality of Life Brief Version(WHOQOL-BREF).After excluding 48 deaths,95 were rejected to participate,618 were inaccessible,and there were 45 cases of incomplete *** statistics,paired-sample analyses,generalized estimating equation(GEE)analysis,and multivariable logistic regression analyses were performed to test the mean difference in participants’QoL scores between the two *** participants(n=1710,70.1%)were male,and one-fourth(24.4%)were older than *** average physical domain score decreased significantly from baseline to follow-up,and the average scores in psychological,social,and environmental domains increased significantly at follow-up(Phat older age groups(Pmale(Phaving hospital admission during COVID-19 illness(Phaving three or more chronic diseases(Pmale sex[adjusted odd ratio(aOR)=1.3,95%confidence interval(CI)1.0–1.6]were associated with reduced social domain scores on multivariable logistic regression *** or semi-urban peo

关键词： Quality of life Health-related quality of life Reverse transcription-polymerase chain reaction COVID-19 Bangladesh

AI Safety Approach for minimizing Collisions in Autonomous Navigation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal on Artificial Intelligence 2023年第1期5卷 1-14页

作者： Abdulghani m.Abdulghani mokhles m.Abdulghani Wilbur L.Walters kha.id H.Abed Department of Electrical&Computer Engineering and Computer Science Jackson State UniversityJackson39217USA

Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize *** systems are developed under the term Artificial Intelligence(AI)*** safety is essential to provide reliable service to consumers in various fields such asmilitary,education,healthcare,and *** paper presents the design of an AI safety algorithmfor safe autonomous navigation using Reinforcement Learning(RL).machine Learning Agents Toolkit(mL-Agents)was used to train the agentwith a proximal policy optimizer algorithmwith an intrinsic curiositymodule(PPO+ICm).This training aims to improve AI safety and minimize or prevent any mistakes that can cause dangerous collisions by the intelligent *** experiments have been executed to validate the results of our *** designed algorithmwas tested in a virtual environment with four differentmodels.A comparison was presented in four cases to identify the best-performing model for improvingAI *** designed algorithmenabled the intelligent agent to perform the required task safely using RL.A goal collision ratio of 64%was achieved,and the collision incidents were minimized from 134 to 52 in the virtual environment within 30min.

关键词： Artificial intelligence AI safety autonomous robots unmanned systems Unity simulations reinforcement learning RL machine learning mL-Agents human-machine teaming

multiple Data Augmentation Strategy for Enhancing the Performance of YOLOv7 Object Detection Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal on Artificial Intelligence 2023年第1期5卷 15-30页

作者： Abdulghani m.Abdulghani mokhles m.Abdulghani Wilbur L.Walters kha.id H.Abed Department of Electrical&Computer Engineering and Computer Science Jackson State UniversityJackson39217USA

The object detection technique depends on various methods for duplicating the dataset without adding more *** augmentation is a popularmethod that assists deep neural networks in achieving better generalization performance and can be seen as a type of implicit *** is recommended in the casewhere the amount of high-quality data is limited,and gaining new examples is costly and *** this paper,we trained YOLOv7 with a dataset that is part of the Open Images dataset that has 8,600 images with four classes(Car,Bus,motorcycle,and Person).We used five different data augmentations techniques for duplicates and improvement of our *** performance of the object detection algorithm was compared when using the proposed augmented dataset with a combination of two and three types of data augmentation with the result of the original *** evaluation result for the augmented data gives a promising result for every object,and every kind of data augmentation gives a different *** mAP@.5 of all classes was 76%,and F1-score was 74%.The proposed method increased the mAP@.5 value by+13%and F1-score by+10%for all objects.

关键词： Artificial intelligence object detection YOLOv7 data augmentation data brightness data darkness data blur data noise convolutional neural network

Implementation of Strangely Behaving Intelligent Agents to Determine Human Intervention During Reinforcement Learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal on Artificial Intelligence 2022年第4期4卷 261-277页

作者： Christopher C.Rosser Wilbur L.Walters Abdulghani m.Abdulghani mokhles m.Abdulghani kha.id H.Abed Department of Electrical&Computer Engineering and Computer Science Jackson State University(JSU)Jackson39217MSUSA

Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their ***,simulations of different learning environments in previous research show that after millions of timesteps of successful training,an intrinsically motivated agent may learn to act in ways unintended by the *** potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real *** investigated this topic by using Unity’s machineLearningAgent Toolkit(mL-Agents)implementation of the Proximal Policy Optimization(PPO)algorithm with the Intrinsic Curiosity module(ICm)to train autonomous exploring agents in three learning *** demonstrate that ICm,although designed to assist agent navigation in environments with sparse reward generation,increasing gradually as a tool for purposely training misbehaving agent in significantly less than 1 million *** present the following achievements:1)experiments designed to cause agents to act undesirably,2)a metric for gauging how well an agent achieves its goal without collisions,and 3)validation of PPO best ***,we used optimized methods to improve the agent’s performance and reduce collisions within the same *** achievements help further our understanding of the significance of monitoring training statistics during reinforcement learning for determining how humans can intervene to improve agent safety and performance.

关键词： Artificial intelligence AI safety reinforcement learning human-inthe-loop intrinsic motivation unity simulations human-machine teaming