Analysis and Implementation of Admissible Heuristics in 8 Puzzle Problem

N-puzzle problem has been one of the basic problem since the beginning of artificial intelligence. The most popular version of n-puzzle among people is 8-puzzle problem. It consists of an area divided into 3x3 grid containing 8 numbered (to identify) tiles and one empty grid. We are given an initial state and we have to reach the goal state which is also specified. In this project, we have used various informed search methods like a*algorithm, ida* algorithm to solve the puzzle. Various heuristic involved in the informed search like number of misplaced tiles, Manhattan distance were analyzed; Manhattan distance being one of the most popular ones. Drawbacks of the heuristics are mentioned and an improvement in Manhattan distance heuristic is implemented

Study, Design and Fabrication of a 3D Printer

3D printing is called as desktop fabrication. It is a process of prototyping where by a structure is synthesized from a 3d model. The 3d model is stored in as a STL format and after that forwarded to a 3D printer. It can use a wide range of materials such as ABS, PLA, and composites as well.3D printing is a rapidly developing and cost optimized form of rapid prototyping. The 3D printer prints the CAD design layer by layer forming a real object. 3D printing process is derived from inkjet desktop printers in which multiple deposit jets and the printing material, layer by layer derived from the CAD 3D data. 3D printing significantly challenges mass production processes in the future. This type of printing is predicted to influence industries, like automotive, medical, education, equipment, consumer products industries and various businesse

Artificial Intelligence in Battle against Antimicrobial Resistance: Opportunities and Challenges

Due to the overuse and abuse of antibiotics, antimicrobial resistance (AMR) poses a serious risk to socioeconomic development and public health. A paradigm shift is required to address this dilemma, and artificial intelligence (AI) appears as a possible remedy. AI, including machine learning (ML) and deep learning (DL), has demonstrated significant promise in several medical research fields, especially in the fight against AMR. Applications of AI in AMR use cutting-edge computational methods to analyze gene expression and whole-genome sequencing data, assisting in discovering infectious disease etiology and disease subtypes. These AI-driven systems have several advantages over more conventional ones, including less need for human involvement, more accuracy, and lower costs. However, they also encounter difficulties, such as inconsistent performance across datasets, with data volume critically influencing model efficacy. The accessibility and expense of high-throughput sequencing data, particularly next-generation sequencing data, also pose challenges to the wider application of AI models for AMR investigation. Despite these difficulties, AI has significant promise in the fight against AMR, and its advantages and disadvantages must be carefully considered in order to build successful tactics for dealing with this urgent worldwide problem. We assess research papers on AMR analysis using AI on various datasets and contrast the effectiveness of various AI models. We thoroughly reviewed the DL models used up to this point in the field of AMR, and we additionally discussed the challenges that come with deploying these approaches. This paper offers a thorough overview of AI's applications in AMR analysis, highlighting both its benefits and drawbacks

Enhancing Cardiovascular Disease Prediction Based on AI and IoT Concepts

One-third of all deaths worldwide yearly are attributable to cardiovascular disease (CVD). In contrast to the 7% of the wealthy who experience premature death, 43% of the poor do. Lifestyle diseases like obesity and diabetes are to blame. The importance of early identification of heart disease was demonstrated, and premature mortality was kept to a minimum. Combining clinical and biochemical data is essential for the early diagnosis of heart illness. Numerous IoT-enabled wearable healthcare applications have been created and released in recent years. Although the ability of wearable devices to share patient health data is expanding, it remains challenging to predict and identify health problems. Security, data storage, and patient monitoring are all part of the system. Artificial intelligence (AI) therapies may one day change the face of cardiology by providing doctors with cutting-edge data analysis and therapeutic decision-making resources. As the volume and complexity of data continue to increase, AI tools like machine learning (ML) and deep learning (DL) can assist medical professionals in learning more. Suppose we want to provide medical care to the elderly and those with chronic illnesses in the comfort of their own homes. In that case, we must upgrade our communication and information technology systems. The implemented DNN model's accuracy is amazing at 95.34 % and can yield other noteworthy outcomes when used to identify CVDs. We discuss and suggest the most suitable AI-IoT models for early CVD prediction and detection to reduce computational costs and increase time efficiency

Two introductory lectures on high energy QCD and heavy ion collisions

These introductory lectures present a broad overview of the physics of high parton densities in QCD and its application to our understanding of the early time dynamics in heavy ion collisions.Comment: Lectures by R. V. at the QGP Winter School, Jaipur, India, Feb. 1st-3rd, 200

IoT Ecosystems Enable Smart Communication Solutions: A Case Study

The Internet of Things (IoT) is a platform for innovation, allowing people to invest in and use IoT to improve life, business, and society. It will be applicable to all or any industry sectors, verticals, people, machines, and everything. This creates difficult requirements in terms of higher system capacity, extremely low latency, such as for the tactile Internet, extremely high throughput values, a wide range of services, such as IoT and M2M, and a more uninterrupted experience. As a symbiotic confluence of up to date and existing technologies, the IOT architecture will use Hetnet RAN, Cloud enhanced RAN, and SW defined data centres to combine novel and legacy technologies. As a result, IOT will combine next-generation largearea extensible service experiences anytime and anywhere, with ultra-dense installations, nearzero latency, and GB experiences–when and where it matters. Collaboration on research, standardisation, and spectrum sharing with the IT/Internet world, industry verticals, policymakers, and academia is a significant success element. Trillions of dollars in smart ecosystems prospects covering secure connections, digital service enablement, applications and repair provisioning, and a wide range of internet of things and consumer applications are available to communications service providers and enterprises

Internet of Things brings Revolution in eHealth: Achievements and Challenges

The medical field has benefited greatly from the technological revolution around our world, as well as the introduction of artificial intelligence (AI) and the Internet of Things (IoT). IoT aims to make life easier and more convenient by bridging the various gaps in connecting various devices that people employ. A wide range of applications and technologies, including wearable device development, advanced care services, personalized care packages, and remote patient monitoring, benefit healthcare professionals and patients. These technologies gave rise to new terms such as the Internet of Medical Things (IoMT), the Internet of Health Things (IoHT), e-Health, and telemedicine. With the advent of technology and the availability of various connected devices, smart healthcare, which has grown in popularity in recent years, has been positively redefined. Through the selection of literature reviews, we systematically investigate how the adoption (and integration) of IoT technologies in healthcare is changing the way traditional services and products are delivered. This paper outlines (i) selected IoT technologies and paradigms related to health care, as well as, (ii) various implementation scenarios for IoT-based models. It also discusses (iii) the various advantages of these applications and finally, (iv) a summary of lessons learned and recommendations for future applications

Deep Learning-based Gated Recurrent Unit Approach to Stock Market Forecasting: An Analysis of Intel\u27s Stock Data

The stock price index prediction is a very challenging task that\u27s because the market has a very complicated nonlinear movement system. This fluctuation is influenced by many different factors. Multiple examples demonstrate the suitability of Machine Learning (ML) models like Neural Network algorithms (NN) and Long Short-Term Memory (LSTM) for such time series predictions, as well as how frequently they produce satisfactory outcomes. However, relatively few studies have employed robust feature engineering sequence models to forecast future prices. In this paper, we propose a cutting-edge stock price prediction model based on a Deep Learning (DL) technique. We chose the stock data for Intel, the firm with one of the quickest growths in the past ten years. The experimental results demonstrate that, for predicting this particular stock time series, our suggested model outperforms the current Gated Recurrent Unit (GRU) model. Our prediction approach reduces inaccuracy by taking into account the random nature of data on a big scale

An Overview of the Genus Nardostachys

Nardostachys jatamansi, a medicinally important herb of Nepalese origin, has been used for centuries in the Ayurvedic and Unani systems of medicine. In combination with Marsilea minuta it is being used as an antistress and anticonvulsant drug and also finds use in the treatment of epilepsy. Recently, it has been reported that N. jatamansi, which plays an important role in protecting from cerebral ischemia and liver damage, is also used for the treatment of osteoporosis and hypercalcemia. The other member of the genus Nardostachys, N. chinensis, possesses antifungal and antimalarial properties. It is also used in the treatment of skin dysfunction. A short summary of the chemical constituents of the two species along with their physical and biological properties is reported