48 research outputs found
Analytical view of Pakistan-United States Relations: Past and Present
Relations between Pakistan and United States are like the swing of pendulum Pakistan from the very first day is playing catalyst role for the interests of the United States in the region But the relations between two countries remained difficult and widen the trust deficit with the span of time Despite aids from the US Pakistan also suffered irreparable loss for her pleasure and to get financial support from unequal ally History reveals that United States always used Pakistan for self-purposes The aim of this paper is to analyze the Pak- US relations in the current scenario Methodology This is a descriptive study which consists of secondary source of data collection based on reports books periodic journals web-based article
PLC Based Load Sharing of Transformers
The transformer is very expensive and bulky power system equipment. It runs and feed the load for 24 hours a day. Sometimes the load on the transformer unexpectedly rises above its rated capacity in that situation the load on the transformer increases and it will be overloaded and current will increase and cause overheating which in results damage the insulation of transformer. That insulation failure resulting in interruption of power supply. The common problems which transformer face is overloading voltage fluctuations and heating effect. It takes lot of time to fix the transformer so that a device need to be introduced a device which would help in automatically sharing of these over voltages. We will try to build an automated transformer sharing system in this project where the transformer current is confined to auxiliary transformer and automatically enters system.
There are three transformers working as sources in this project, initially when the main switched ON the load that time load will be shared through the first transformer but when the load on first transformer suddenly increase above its reference value then immediately second transformer connected parallel with first transformer automatically through PLC by busing relay circuit
Ship Detection And Tracking In Inland Waterways Using Improved Yolov3 And Deep Sort
Ship detection and tracking is an important task in video surveillance in inland waterways. However, ships in inland navigation are faced with accidents such as collisions. For collision avoidance, we should strengthen the monitoring of navigation and the robustness of the entire system. Hence, this paper presents ship detection and tracking of ships using the improved You Only Look Once version 3 (YOLOv3) detection algorithm and Deep Simple Online and Real-time Tracking (Deep SORT) tracking algorithm. Three improvements are made to the YOLOv3 target detection algorithm. Firstly, the Kmeans clustering algorithm is used to optimize the initial value of the anchor frame to make it more suitable for ship application scenarios. Secondly, the output classifier is modified to a single SoftMax classifier to suit our ship dataset which has three ship categories and mutual exclusion. Finally, Soft Non-Maximum Suppression (Soft-NMS) is introduced to solve the deficiencies of the Non-Maximum Suppression (NMS) algorithm when screening candidate frames. Results showed the mean Average Precision (mAP) and Frame Per Second (FPS) of the improved algorithm are increased by about 5% and 2, respectively, compared with the existing YOLOv3 detecting Algorithm. Then the improved YOLOv3 is applied in Deep Sort and the performance result of Deep Sort showed that, it has greater performance in complex scenes, and is robust to interference such as occlusion and camera movement, compared to state of art algorithms such as KCF, MIL, MOSSE, TLD, and Median Flow. With this improvement, it will help in the safety of inland navigation and protection from collisions and accidents
Anomalous correlation-induced dynamical phase transitions
The nonanalyticity of the Loschmidt echo is termed as the dynamical quantum
phase transitions. It extends the notion of quantum criticality to a
nonequilibrium scenario, corresponding to the singular behaviour of the
Loschmidt echo at critical times in quantum quenched systems. Here, we
establish a new paradigm of dynamical phase transitions driven by a sudden
change in the internal spatial correlations of the disorder potential in a
low-dimensional disordered system. The Loschmidt echo characterizes the quantum
quench dynamics and shows a distinctly different behaviour for different
correlation exponents in the time scale. Our results indicate the existence of
anomalous dynamical phase transitions triggered by the spatial correlations of
the random potential. The physical origin of the anomalous transitions is the
overlap between two distinctly different extended states. Furthermore, the
quench dynamics show a clear signature of the delocalization phase transition
in the correlated Anderson model.Comment: 8 pages, 8 figure
Clinical outcomes of sirolimus with eluting stent implantation in coronary artery disease
OBJECTIVE: To evaluate the immediate post procedure, thirty-days, and six-months clinical outcomes of sirolimus-eluting stents (SES) implantation in patients with single and multivessel coronary artery disease (CAD).
METHODS: A case series of all consecutive patients undergoing percutaneous coronary interventions (PCI) with SES implantation at Shifa International Hospital, Islamabad, were evaluated at early post-procedure, 30-days and six-months clinical follow-up for the incidence of major adverse cardiac event (MACE). This included death, nonfatal myocardial infarction (MI) and repeat revascularization.
RESULTS: Out of 206 consecutive patients, 324 had SES implanted. Cumulative MACE rate was 2.93% and 6% at 30-days and six-months follow-ups respectively. Five patients developed ST-segment elevation MI (STEMI). One patient developed non-STEMI. Emergency Coronary Artery Bypass Grafting (CABG) was done in two patients. Repeat (PCI) was carried in three (1.46%) patients for acute in-stent thrombosis. Diabetes Mellitus and multivessel stenting were found to be the independent predictors for acute in-stent thrombosis (P-value \u3c 0.02 and 0.05 respectively).
CONCLUSION: SES implantation in coronary artery disease can be safe and effective MACE at one and six months follow-ups
General practitioner\u27s knowledge regarding the diagnosis and drug therapy for acute myocardial infarction
OBJECTIVE: To assess the general practitioners (GP) knowledge regarding the diagnosis and initial drug therapy for acute myocardial infarction (AMI).
METHODS: A questionnaire-based survey was conducted in randomly selected GPs of Karachi. Doctors working in community as GPs who were registered medical practitioners having a Bachelor of Medicine & Bachelor of Surgery degree were included in the study. Doctors working at tertiary care facilities or having a post graduate degree or post graduate training in a specialty other than family medicine were excluded from the study.
RESULTS: A total of 186 GPs participated in our study. GPs who studied research journals were 2.33 times more likely to investigate serum cardiac troponins levels for the diagnosis of AMI compared to those who did not study research journals (P = 0.02). Twenty six percent of the GPs said that they would refer a patient with suspected AMI without treatment, while 76% said that they would consider some treatment prior to referral. Fifty eight percent of the GPs identified ST segment elevation myocardial infarction (STEMI) of \u3c 12 hours duration as an indication of thrombolysis while 28% identified posterior wall AMI as a thrombolytic indication.
CONCLUSION: GPs, although adequately aware of the presenting features of AMI, were lacking in knowledge regarding the means for confirmation of diagnosis, initial drug therapy and were less likely to carry management steps in their practice
Breast cancer risk prediction using machine learning: a systematic review
BackgroundBreast cancer is the leading cause of cancer-related fatalities among women worldwide. Conventional screening and risk prediction models primarily rely on demographic and patient clinical history to devise policies and estimate likelihood. However, recent advancements in artificial intelligence (AI) techniques, particularly deep learning (DL), have shown promise in the development of personalized risk models. These models leverage individual patient information obtained from medical imaging and associated reports. In this systematic review, we thoroughly investigated the existing literature on the application of DL to digital mammography, radiomics, genomics, and clinical information for breast cancer risk assessment. We critically analyzed these studies and discussed their findings, highlighting the promising prospects of DL techniques for breast cancer risk prediction. Additionally, we explored ongoing research initiatives and potential future applications of AI-driven approaches to further improve breast cancer risk prediction, thereby facilitating more effective screening and personalized risk management strategies.Objective and methodsThis study presents a comprehensive overview of imaging and non-imaging features used in breast cancer risk prediction using traditional and AI models. The features reviewed in this study included imaging, radiomics, genomics, and clinical features. Furthermore, this survey systematically presented DL methods developed for breast cancer risk prediction, aiming to be useful for both beginners and advanced-level researchers.ResultsA total of 600 articles were identified, 20 of which met the set criteria and were selected. Parallel benchmarking of DL models, along with natural language processing (NLP) applied to imaging and non-imaging features, could allow clinicians and researchers to gain greater awareness as they consider the clinical deployment or development of new models. This review provides a comprehensive guide for understanding the current status of breast cancer risk assessment using AI.ConclusionThis study offers investigators a different perspective on the use of AI for breast cancer risk prediction, incorporating numerous imaging and non-imaging features