Background: The inability to test at scale has become humanity's Achille's heel in the ongoing war against COVID-19 pandemic. A scalable screening tool would be a game changer. Building on prior work cough-based diagnosis of respiratory diseases, we propose, develop and an Artificial Intelligence (AI)-powered solution for infection that is deployable via smartphone app. app, named AI4COVID-19 records sends three 3-second cough sounds AI engine running cloud, returns result within two...

Cough acoustics contain multitudes of vital information about pathomorphological alterations in the respiratory system. Reliable and accurate detection cough events by investigating underlying latent features disease diagnosis can play an indispensable role revitalizing healthcare practices. The recent application Artificial Intelligence (AI) advances ubiquitous computing for prediction has created auspicious trend myriad future possibilities medical domain. In particular, there is...

Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of most prominent being machine learning empowered health care. One notable modern medical concerns that impose an immense worldwide burden respiratory infections. Since cough is essential symptom many infections, automated system screen for diseases based on raw data would have a multitude beneficial research applications. In literature, has already been successfully used detect events in...

In modern wireless communication systems, radio propagation modeling has always been a fundamental task in system design and performance optimization. These models are used cellular networks other systems to estimate the pathloss or received signal strength (RSS) at receiver characterize environment traversed by signal. An accurate agile estimation of is imperative for achieving desired optimization objectives. The state-of-the- art empirical based on measurements specific limited their...

The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch a myriad AI-based solutions are being proposed in literature to leverage AI modeling optimizing behavior the automation goal. However, work reliably, requires deluge training data. Consequently, success limited by fundamental challenge faced research community: scarcity In this...

Abstract Background Air pollution represents non uniform trends particularly in dense urban areas which arises the necessity for monitoring at finer resolution. Since recent advancements electrochemical technology have made it feasible to deploy economical wireless sensor nodes environmental monitoring, we present a bed of cost effective referential sensors replace role traditional weather stations. The system is intended target lower income nations like Pakistan, where air and regulation...

The growing subscriber Quality of Experience demands are posing significant challenges to the mobile cellular network operators. One such challenge is autonomic detection sleeping cells in networks. Sleeping Cell (SC) a cell degradation problem, and special case Outage Detection (COD) because it does not trigger any alarm due hardware or software problems BS. To minimize effect outages, researchers have proposed autonomous outage compensation solutions. State-of-the-art SC depends on drive...

In modern wireless communication systems, radio propagation modeling to estimate pathloss has always been a fundamental task in system design and optimization. The state-of-the-art empirical models are based on measurements specific environments limited their ability capture idiosyncrasies of various environments. To cope with this problem, ray-tracing solutions used commercial planning tools, but they tend be extremely time-consuming expensive. We propose Machine Learning (ML)-based model...

Current LTE network is faced with a plethora of Configuration and Optimization Parameters (COPs), both hard soft, that are adjusted manually to manage the provide better Quality Experience (QoE). With 5G in view, number these COPs expected reach 2000 per site, making their manual tuning for finding optimal combination parameters, an impossible fleet. Alongside thousands anticipated densification emerging networks which exacerbates burden operators managing optimizing network. Hence, we...

Recently, face recognition technology has become increasingly important for safety purposes. Masks are now required in most countries and used. Public health professionals advise people to conceal their facial features outdoors reduce COVID-19 transmission by 65%. Detecting without masks on faces is crucial. This widely used as outperforms PINs, passwords, fingerprints, other verification methods. Sunglasses, scarves, caps, makeup have made identification harder recent decades. Thus, such...

Fault diagnosis is turning out to be an intense challenge due the increasing complexity of emerging cellular networks. The root-cause analysis coverage-related network anomalies traditionally carried by human experts. However, vast and cell density networks, it neither practical nor financially viable. To address this, many studies are proposing artificial intelligence (AI)-based solutions using minimization drive test (MDT) reports. Nowadays, focus existing either on diagnosing faults in a...

A beneficial product of Smart Irrigation for Agricultural Area Pakistan has been presented in this paper. stands need a participatory solution that is efficiently workable, sustainable, and profitable, to develop the way agricultural sector by improving crop productivity with minimum water loss. The goal project introduce Cloud support System Pakistan. To achieve objective Wireless Sensor Network (WSN) used determine how much apply when irrigate. system divided into four main modules, i.e....

Mobile cellular network operators spend nearly a quarter of their revenue on maintenance and management.A significant portion that budget is spent resolving faults diagnosed in the system disrupt or degrade services.Historically, operations to detect, diagnose resolve issues were carried out by human experts.However, with diversifying cell types, increased complexity growing density, this methodology becoming less viable, both technically financially.To cope problem, recent years, research...

Diminishing viability of manual fault diagnosis in the increasingly complex emerging cellular network has motivated research towards artificial intelligence (AI)-based using minimization drive test (MDT) reports. However, existing AI solutions literature remain limited to either faults a single base station only or multiple BS scenario. Moreover, lack robustness MDT reports spatial sparsity renders these unsuitable for practical deployment. To address this problem, paper we present novel...

Contrast enhanced sonothrombolysis using streptokinase loaded phase change nano-droplets.

Minimization of Drive Test (MDT) reports are a key enabler for Machine Learning (ML)-based zero-touch automation envisioned emerging cellular networks. However, due to numerous factors, the MDT spatially sparse in nature. This sparsity undermines performance ML models that built on data estimate and optimize network KPIs. In this paper, we present evaluate framework address challenge. We leverage generative models, specifically, Gener-ative Adversarial Networks (GAN) Variational Autoencoders...

In this letter, we propose a novel network health estimation technique for wireless cellular networks. The proposed scheme makes use of graph signal processing techniques to estimate over the entire coverage area with sparse availability measured data. To achieve objective, solve an optimization problem on using proximal splitting method. results show that outperforms existing methods such as kriging improved accuracy more than 60% along reduced time complexity O(n) compared O(n <sup...

Prior to standardization, new features, algorithms, and solutions have be rigorously evaluated verified using different methods. In this regard, testbeds are considered as one of the most important effective experimental platforms for performing tests, thus paving way towards real-world implementation many solutions, from basic disruptive innovative ones. Compared computer simulators, provide near-realistic can obtain practical results while posing less risk live networks. They also cheaper...

Background: Cardiovascular disease specially ischemic heart in Pakistan has become one of the major cause mortality. Patients with symptoms/signs angina non obstructive CAD may be suspected where atherosclerotic epicardial does not limit coronary blood flow, but other processes disturb myocardial supply/demand relationship Objective: To determine frequency nonobstructive artery patients admitted for elective angiography, at NICVD, Karachi, Methods: This Cross sectional study was done...

The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch a myriad AI-based solutions are being proposed in literature modeling optimizing behavior to the automation goal. However, work reliably, AI requires deluge training data. Consequently, success limited by fundamental challenge faced research community: scarcity We present an...

Cough acoustics contain multitudes of vital information about pathomorphological alterations in the respiratory system. Reliable and accurate detection cough events by investigating underlying latent features disease diagnosis can play an indispensable role revitalizing healthcare practices. The recent application Artificial Intelligence (AI) advances ubiquitous computing for prediction has created auspicious trend myriad future possibilities medical domain. In particular, there is...