The software delivery model known as Software as a service (SaaS) has evolved from cutting-edge innovation to an essential technology for many companies. However, due to the extensive range of cloud services that companies offer as part of their SaaS offerings, it is indispensable to thoroughly comprehend the dangers associated with using these services. This article describes those dangers and recommendations for the most effective methods of control that are open to managers. This study's objective is to investigate the factors of Technological Complexity, Security and Risk, and Technical Support within an organization to determine how these factors can influence an organization's end-use intention regarding cloud technology. The availability of technical support, the complexity of use, and the organization's training have been highlighted as the most crucial factors of this aim. The findings suggest that complexity negatively influences intention to use, although training and assistance are vital, with a similar weight. Shared or collective knowledge is essential in the adoption of cloud computing technologies.

Asthma is a chronic illness that causes improper respiratory organ function and breathing problems. Three hundred fifty million people worldwide have bronchial asthma, or one in 12 adults. Self-monitoring is the first step in managing chronic illness. This lets doctors and people monitor and address health conditions in real-time. Telemonitoring is a phrase used in IT to remotely monitor the health of patients who are not in hospitals or medical centers. Wearable medical sensors, such as IoT-based remote asthma and blood pressure sensors, capture real-time information from remotely located patients. The medical information is then transmitted through the Internet for medical diagnosis and therapy. Classical Spirometry measures how effectively a patient's lungs function and requires supervision. We want to support impacted patients; thus, we built a monitoring system. With sensors including heartbeat, dust, temperature, and humidity, the device will collect health-related data and upload it to the cloud, helping doctors diagnose patients. This study uses private cloud computing to track and monitor real-time medical information in approved areas. In addition, the private cloud-based environment called a bounded telemonitoring system is meant to capture real-time medical details of patients in the medical centers inside and outside medical wards. In addition, a new wireless sensor network scenario is intended to monitor patients' health information 24/7. This research secures medical information access and guides future medical system development.

A better and more streamlined user experience is the result of the research demonstrating how cloud analytics tools and software are particularly effective for processing vast data sets, producing insights in easily digestible formats on demand, and improving the user interface. Cloud computing is a large-scale information technology solution that can customize and deliver a new kind of environment based on information technology to everyday users, in particular to IT and computing systems users. Cloud computing was developed by Amazon Web Services (AWS) and Microsoft Azure. The use of cloud computing comes with a multitude of features and aspects, including internet backup. It comes with just-in-time delivery of standardized storage process, management, and infrastructure, as a measurable service, on a 'Pay-as-you-go' type, and is therefore widely accessible in various organizations and institutions. Cloud computing and its load balancing are essential features that must be taken care of to maintain a healthy Information Management system. In a condensed form, this paper discusses a significant number of topics that are connected to the given subject.

The consequences of this new technology for international trade have recently garnered much attention, thanks to the growing interest in AI's effects on the economy and society. Given the current reevaluation of the advantages of globalization by the world's leading nations, the focus continues to be on the policies governing international commerce. Understanding and forecasting future trade patterns is a high priority for decision-making within and between countries. This is because trade significantly impacts employment, production, pricing, and wages. Even though conventional economic models are intended to be accurate forecasters, we investigate the prospect that Artificial Intelligence (AI) techniques can produce more accurate predictions and associations. In addition, we describe contextual AI algorithms that can be used to analyze trade patterns disrupted by unusual occurrences such as trade wars and pandemics. The fuel for the algorithms that can forecast, recommend, and categorize policies can only be provided by open-government data; therefore, having access to these data is vital. The information gathered for this study describes the economic elements usually linked with international trade transactions. Association Rules are used for grouping commodity pairs. Finally, models and their results are presented and then appraised in terms of the quality of their predictions and associations, with example policy implications provided. This paper explores the interlinkages between AI technologies and international trade and outlines key trade policy considerations for policymakers looking to harness AI technologies' full potential. Specifically, the paper focuses on China's efforts to develop its artificial intelligence (AI) industry.

In the last decade, cloud computing has changed dramatically. More providers and administration contributions have entered the market, and cloud infrastructure, once limited to single-provider data centers, is expanding. This article discusses the shifting cloud foundation and the benefits of decentralizing computing from data centers. These patterns necessitate novel cloud computing architectures. These models may affect linking people and devices, data-intensive computing, the service space, and self-learning frameworks. Finally, we compiled a list of issues to consider while assessing modern cloud frameworks. Architectural and urban design projects breach scale and predictability constraints and seek enhanced competency, maintainability, energy performance, and cost-efficiency. Simulation and large-scale information processing drive this cycle. Advances in calculations and computer power help address the complex elements of a coordinated whole-structure framework. Adaptability is a barrier to the configuration, control, and development of whole-system frameworks. This position paper proposes several solutions for semi-or fully automated projects, such as short-plan boundary space exploration, large-scope high-accuracy simulation, and integrated multidisciplinary development. These computer-intensive operations were previously only accessible to the exam network. Once empowered by cloud computing and high-performance computing, these methods can stimulate intelligent plan measures, leading to enhanced results and shorter development times.