A personalized healthcare recommendation system uses artificial intelligence (AI) and machine learning (ML) to provide tailored health suggestions based on an individual’s medical history, symptoms, genetic data, real-time conditions. It collects data from sources such as wearable devices, electronic records (EHRs), mobile applications, analyzing patterns predict potential risks offer preventive measures. With the integration of big Internet Things (IoT), these systems enhance diagnosis...

Autonomous driving is one of the newly emerging feats in artificial intelligence (AI). The challenge developing autonomous cars to design controllers that can steer a vehicle right direction with enough speed. A good controller activates set multiple actuators simultaneously. output function sensory inputs. Nowadays, are mostly developed by connecting car simulator machine learning (ML) algorithm. provides pragmatic environment for simulated cars. ML algorithm, on other hand, does job an...

The development of its people is one the principal objectives an economy. To ambit that greater capabilities and opportunities will improve productivity people, human also expected to have a positive influence on economic growth. primary objective this paper empirically examine whether significantly affects We use panel data consisting 25 developed developing countries from year 2000 2014. has been collected Human Development Report (UNDP) World Indicators (World Bank). Ordinary least...

Contemporary models of Unmanned Aerial Vehicles (UAVs) are largely developed using simulators. In a typical scheme, flight simulator is dovetailed with machine learning (ML) algorithm. A good provides realistic environment for simulated aircraft. It also the ability to invoke and fly various The ML algorithm, in turn, allows find an appropriate set control inputs that can be useful flying aircraft autonomously. Creating UAVs this way has certain obvious benefits. process development...

Recommender system (RS) has become a very important factor in many eCommerce sites. In our daily life, we rely on the recommendation from other persons either by word of mouth, letters, movie, item and book reviews printed newspapers, etc. The typical Systems are software tools techniques that provide support to people identifying interesting products services online store. It also provides for certain users who search recommendations. most open challenge Collaborative filtering recommender...

Undertaking engineering research can be compounding for beginning graduate students and thwarting even seasoned researchers. With a wealth of academic literature myriad software development open-source computing tools available online, the life researcher should have become much easier. However, overwhelming body knowledge, that is increasing rapidly by day, quite frequently often confuses about things done. It normal to find who are clueless how they conduct their research. Similarly, part...

The advent of cloud-based super-computing platforms has given rise to a Data Science (DS) boom. Many types technological problems that were once considered prohibitively expensive tackle are now candidates for exploration. Machine Learning (ML) tools valued only in academic environments quickly being embraced by industrial giants and tiny startups alike. Coupled with modern-day computing power, ML can be looked at as hammers deal even the most stubborn nails. have become so ubiquitous...

The computational complexity of Evolutionary Algorithms (EAs) is a well-known concern. This paper concerned with the resource consumption GELAB, novel Grammatical Evolution (GE) system implemented in Matlab. GE an evolutionary technique for program search that manipulates large populations computer programs over multiple generations. In this paper, we present our reflections on some recently conducted experiments GELAB. GELAB leverages power Matlab to perform hybrid optimization its...

This paper presents our reflections about recent, intense involvement with the simulation of unmanned aerial vehicles (UAVs). Our idea was to integrate a flight simulator machine learning (ML) algorithm. As in any research project, we came across many challenging issues. We would like highlight those issues and their workarounds. hope is that this will make it easier for wider community address challenges involved UAV simulation.

There is an increasing interest in upgrading the E-Model, a parametric tool for speech quality estimation, to wideband and super-wideband contexts. The main motivation behind this has been quantify gain lent by various new codecs communication situations. have numerous such contributions, all of them more or less successful. This paper reports on extension E-Model mixed narrowband/wideband (NB/WB) context. More specifically, we take novel approach toward deriving effective equipment...

<p>As algorithms get better at their accuracy and computational efficiency, they invoke curiosity among the affected scientific communities to check if can benefit from newer versions or not. Computer vision is one such domain that has observed rapid growth in terms of algorithmic advancements. The advent deep learning was itself a catalyst for agile innovation. Coupled with improvements object detection, speed innovation become tremendous. And so there are many engineering disciplines...

Every now and then, we witness significant improvements in the performance of Deep Learning models. A typical cycle improvement involves enhanced accuracy followed by reduced computing time. As algorithms get better at their job, it is worthwhile to try evaluate on problems that are affected them. Computationally intense problems, such as object detection for Computer Aided Laparoscopy (CAL), can benefit from technologies. Recently a new set variants You Look Only Once (YOLO) models based...

Convolutional Neural Networks (CNNs) have been successfully adopted by state-of-the-art feature point detection and description networks for the past number of years. The focus these systems has predominately on accuracy system, rather than its efficiency or ability to be implemented in real-time embedded robotic devices. This paper demonstrates how techniques, developed other CNN use cases, can integrated into interest compress their network size reduce computational complexity; this...

<title>Abstract</title> The aim of this project is to develop a Testbed for designing and training Multi-agent Reinforcement Learning (RL) algorithms cooperative self-organizing Unmanned Aerial Vehicles (UAVs). main purpose the development scalable distributed testbed based on RL enable UAVs make decisions using real-time data perform tasks autonomously. In project, novel developed that allows integration different with flight simulator. This supports learn fly coordinate together in...

Diversity is a much sought after aspect of any evolutionary system. More diversity means cornucopia diverse behaviors and traits among the individuals population. Lack diversity, on other hand, leads to stagnant population whose are more or less similar each other. Subsequently, they fail produce variety offspring. Grammatical Evolution (GE), being an Evolutionary Algorithm (EA), also aspirant diversity. It allows GE system maintain dynamic over multiple generations.In this paper, we present...