Artificial intelligence (AI) describes a variety of approaches in computer applications to mimic human learning. As this technology becomes increasingly prevalent, it is inevitable that it will enter the educational environment, as both an educational tool and topic of learning. STEM education, which deals with science, technology, engineering, and math, is perhaps the most appropriate educational field in which to introduce students to this new and rapidly growing technology. In recent years, educators, AI engineers, and educational researchers have published trial results of experimental curricula implementing AI technology in student and teacher education. This systematic literature review analyzed a sample of seven such publications to identify key trends in suggested best practices for the usage of AI in STEM classrooms. The sample was analyzed for keywords using MaxQDA. The results indicated three key trends among suggested best practices. The first was that AI is best taught to students when the technology itself is the topic of education. Another trend was that simulating real world applications of AI technology was most impactful in showing students the potential, limits, and ethical implications of AI. Finally, it was found that educator's familiarity with AI is an important factor in their ability to employ it in the classroom.

Traffic sign recognition is an essential feature of intelligent transportation systems and Advanced Driver Assistance Systems (ADAS), which are necessary for improving road safety and advancing the development of autonomous cars. This research investigates the incorporation of the YOLOv9 model into traffic sign recognition systems, utilizing its sophisticated functionalities such as Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) to tackle enduring difficulties in object detection. We employed a publically accessible dataset obtained from Roboflow, which consisted of 3130 images classified into five distinct categories: speed_40, speed_60, stop, green, and red. The dataset was separated into training (68%), validation (21%), and testing (12%) subsets in a methodical manner to ensure a thorough examination. Our comprehensive trials have shown that YOLOv9 obtains a mean Average Precision (mAP@0.5) of 0.959, suggesting exceptional precision and recall for the majority of traffic sign classes. However, there is still potential for improvement specifically in the red traffic sign class. An analysis was conducted on the distribution of instances among different traffic sign categories and the differences in size within the dataset. This analysis aimed to guarantee that the model would perform well in real-world circumstances. The findings validate that YOLOv9 substantially improves the precision and dependability of traffic sign identification, establishing it as a dependable option for implementation in intelligent transportation systems and ADAS. The incorporation of YOLOv9 in real-world traffic sign recognition and classification tasks demonstrates its promise in making roadways safer and more efficient.

This study investigates the user experience (UX) of first aid training using virtual reality (VR) technology. As VR continues to be adopted for educational and training purposes, it is important to understand how learners perceive and engage with this medium for developing critical skills, such as first aid. In this study, we developed a VR application called "VR First Aid" that includes training modules on three emergency scenarios: heatstroke, shock, and seizure. The application has both tutorial and hands-on training components. We conducted a UX study by administering a questionnaire to participants. The UX of learning through the VR application was then compared to using a traditional e-book format. Results indicate that participants perceived stronger internal behavior control with the e-book but reported better confirmation, engagement, enjoyment, and intention to use when training with the VR system. Gender differences were also explored, revealing that female participants expressed greater interest in learning through the VR platform compared to male participants. These findings provide insights into the strengths and limitations of VR-based first aid training compared to traditional methods. Implications for the design and deployment of VR training systems are discussed, with a focus on optimizing the learner experience and learning outcomes.

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

Access control systems are used to control the access of people to assets. In practice, assets are either tangible (e.g. goods, cash, etc.) or data. In order to handle tangible assets, a person must physically access the space in which the assets are located (e.g. a room or a building). Access control systems for this case have been known since antiquity and are based either on mechanical locks or on certificates. In the middle of the 20th century, systems based on electromagnetic phenomena appeared. In the second half of the same century, the need to control access to data also arose. And since data can also be accessed via a computer network, it was necessary to control not only the access of persons to areas with data storage, but also to control the electronic communication of persons with these storage facilities. The different types of the above systems have developed separately and more or less independently. This paper provides an overview of the current status of different types of systems, showing that these systems are converging technologically based on the use of electronics, computing and computer communication. Furthermore, the terminology and architecture of these systems is expanded in the article to allow a unified description of these systems. The article also describes the most common types of access control system configurations.

In the current Internet system, there are many problems using anonymity of the network communication such as personal information leaks and crimes using the Internet system. This is why TCP/IP protocol used in Internet system does not have the user identification information on the communication data, and it is difficult to supervise the user performing the above acts immediately. As a study for solving the above problem, there is the study of Policy Based Network Management (PBNM). This is the scheme for managing a whole Local Area Network (LAN) through communication control for every user. In this PBNM, two types of schemes exist. As one scheme, we have studied theoretically about the Destination Addressing Control System (DACS) Scheme with affinity with existing internet. By applying this DACS Scheme to Internet system management, we will realize the policy-based Internet system management. In this paper, basic system design for PBNM scheme for multi-domain management utilizing data science and AI is showed with experiment in feasibility.

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.

Plant leaf classification is an imperative task when their use in real world is considered either for medicinal purposes or in agricultural sector. Accurate identification of plants is, therefore, quite important, since there are numerous poisonous plants which if by mistake consumed or used by humans can prove fatal to their lives. Furthermore, in agriculture, detection of certain kinds of weeds can prove to be quite significant for saving crops against such unwanted plants. In general, Artificial Neural Networks (ANN) are a suitable candidate for classification of images when small datasets are available. However, these suffer from local minima problems which can be effectively resolved using some global optimization techniques. Considering this issue, the present research paper presents an automated plant leaf classification system using optimized soft computing models in which ANNs are optimized using Grasshopper Optimization algorithm (GOA). In addition, the proposed model outperformed the state-of-the-art techniques when compared with simple ANN and particle swarm optimization based ANN. Results show that proposed GOA-ANN based plant leaf classification system is a promising technique for small image datasets.

The DNA (Deoxyribonucleic Acid) database size increases tremendously transmuting from millions to billions in a year. Ergo for storing, probing the DNA database requires efficient lossless compression and encryption algorithm for secure communication. The DNA short pattern repetitions are of paramount characteristics in biological sequences. This algorithm is predicated on probing exact reiterate, substring substitute by corresponding ASCII code and engender a Library file, as a result get cumulating of the data stream. In this technique the data is secured utilizing ASCII value and engendering Library file which acts as a signature. The security of information is the most challenging question with veneration to the communication perspective. The selective encryption method is used for security purpose, this technique is applied on compressed data or in the library file or in both files. The fractional part of a message is encrypted in the selective encryption method keeping the remaining part unchanged, this is very paramount with reference to selective encryption system. The Huffman's algorithm is applied in the output of the first phase reiterate technique, including transmuting the Huffman's tree level position and node position for encryption. The mass demand is the minimum storage requirement and computation cost. Time and space complexity of Repeat algorithm are O(N²) and O(N). Time and space complexity of Huffman algorithm are O(n log n) and O(n log n). The artificial data of equipollent length is additionally tested by this algorithm. This modified Huffman technique reduces the compression rate & ratio. The experimental result shows that only 58% to 100% encryption on actual file is done when above 99% modification is in actual file can be observed and compression rate is 1.97bits/base.

The decision to integrate mobile cloud computing (MCC) in higher education without first defining suitable usage scenarios is a global issue as the usage of such services becomes extensive. Consequently, this study investigates the security determinants of the educational use of mobile cloud computing among universities students. This study proposes and develops a theoretical model by adopting and modifying the Protection Motivation Theory (PMT). The studys findings show that a significant amount of variance in MCC adoption was explained by the proposed model. MCC adoption intention was shown to be highly influenced by threat appraisal and coping appraisal factors. Perceived severity alone explains 37.8% of students "Intention" to adopt MCC applications, which indicates the student's perception of the degree of harm that would happen can hinder them from using MCC. It encompasses concerns about data security, privacy breaches, and academic integrity issues. Response cost, perceived vulnerability and response efficacy also have significant influence on students "intention" by 18.8%, 17.7%, and 6.7%, respectively.

Component-based software development (CBD) is a methodology that has been embraced by the software industry to accelerate development, save costs and timelines, minimize testing requirements, and boost quality and output. Compared to the conventional software development approach, this led to the system's development being completed more quickly. By choosing components, identifying systems, and evaluating those systems, CBSE contributes significantly to the software development process. The objective of CBSE is to codify and standardize all disciplines that support CBD-related operations. Analysis of the comparison between component-based and scripting technologies reveals that, in terms of qualitative performance, component-based technologies scale more effectively. Further study and application of CBSE are directly related to the CBD approach's success. This paper explores the introductory concepts and comparative analysis related to component-based software engineering which have been around for a while, but proper adaption of CBSE are still lacking issues are also focused.

With the great development of technology in all fields these days, including the financial field, people have gone into cryptocurrency trading, without prior knowledge or experience, which made them prey and coveted by hackers through phishing attacks. Therefore, we will study cases where people can be a victim of phishing because cryptocurrency occurs without an intermediary, such as banks and monetary institutions. It is a form of peer-to-peer transaction, physical wallets, and fake investing. This study aims to know the concept of a phishing attack on cryptocurrencies, and to measure the extent of peoples awareness of the security risks on these currencies. Previous literature will be reviewed, and a questionnaire will be published on traders who use cryptocurrency trading platforms, and then we collect data and analyze the answers provided, so that we can suggest educational solutions to these phishing problems.

The elementary stage is of great importance in establishing and supporting students during the beginning of their school life. Therefore, the current study aims to explore the Saudi teachers' perspectives about online learning and its effectiveness on some students' skills. The sample consisted of 250 male and female elementary teachers from different Saudi regions, and they responded to an online questionnaire consisting of both open and closed items to investigate their perspectives on online learning and face-to-face learning. The results showed a great perception and awareness among male and female teachers about the advantages and disadvantages of online learning. In addition, the results show that elementary teachers prefer face-to-face learning because it is the most stable and avoids many of the disadvantages mentioned for online learning. From this point of view, the study emphasizes the importance of integrating the two types of learning and directing teachers' professional development practices towards enhancing and developing their digital skills.

VANETs have become one of the most attractive research areas in the world of wireless networks in recent years. Indeed, vehicular networks have become capable of optimizing road traffic, which significantly reduces the number of accidents through notifications exchanged between nearby vehicles. The routing function based on the opportunistic algorithm is a critical part of the vehicle's communication system and will therefore be an ideal target for attacks that could aim to prevent alert messages from reaching their destination, and thus endanger human lives. The black hole attack is a major threat to the security of VANETs. The main idea of this paper focuses on the analysis of this type of attack in VANETs using Discrete-Time Markov Chains (DTMC). and deduce at the end the effect of the number of malicious nodes on the delivery rate in the network.

Agile project management is an ongoing method to project completion that actually took place all across length of the project's life cycle. Because loop allows you to adapt as you go rather than maintaining a linear route, iterative methods are mainly applied in software development to ensure velocity and agility. Many pitfalls abound in agile software development adaptations that organizations fail to sidestep. New competitive challenges, fluctuating market dynamics, technological disruption, and the ever-changing demands of empowered customers confront organizations around the world. Organizations are all under tremendous pressure to adapt to change and deliver good products and services to customers more swiftly. Research measured at the challenges that could be encountered and offered advice for how agile development might flourish as it becomes a component of a company's family. Our paper gives a comprehensive review of the most significant obstacles that companies encounter while adopting agile techniques. Adaptability. The agile approach encompasses a variety of techniques, which each have different usage in various sectors. Because certain other standards existing today clash with agile methodology, the adaptation of any of the agile techniques in work environments posed a problem. In this paper, we will cover some of the challenges that firms face in adopting the agile software development life cycle.

This paper is an extended paper showing the role of Decision Support Systems (DSS) in other fields of Marketing Management (M.Mgnt). DSS facilitates in decision making many M.Mgnt concepts and Customer Relationship Management (CRM) is one of them and it depends on the firm's tasks for developing and retaining customers while achieving their satisfaction and enhancing the sense of belongingness for their products and services. Profit maximization, the process of customer value, and building strategic values for the firm are the three empirical benefits of CRM that are achieved through analytical, operational, and direction (AOD) capabilities respectively. This research focuses on the application of DSS models of what-if analysis (WIA) for CRM at (AOD) and also shows the dependence on the Information Success model (ISM). Hypothetical data are analyzed for (AOD) by three types of (WIA) to attain CRM and profit maximization and this analytical method can be used by any customer-oriented firm as a general model.

Social media sites like as twitter, Facebook and flicker widely used by people, not only as a source of distributing information but also as for communication purpose, with the advancement of technology today. Now a day's one of the most frequently used communication methods are social networks. In various research studies, their use in different fields and the effects of social media on student's behaviors, chat sites and blogs caused by Facebook has been analyzed. In order to obtain the basic data, a general scanning model that is public opinion and views of parents and comments that are openly available across social media sites, used to perceive attitude of graduate students, instead of traditional methods like questionnaires and survey's conduction. A dataset of nearly 20000 reviews of parents was collected from different social media networks about their children's, while in another dataset in which 362 graduate school teachers who observe the students to use social media during classes, labs and in campus during free times, their comments about those students were chosen. As per this study, through different positive and negative factors the detailed analysis has been performed to show effect of social media on student's behavior.

Nowadays high security is an important issue for most of the secure places and recent advances increase the needs of high-security systems. Therefore, needs to high security for controlling and permitting the allowable people to enter the high secure places, increases and extends the use of conventional recognition methods. Therefore, a novel identification method using retinal images is proposed in this paper. For this purpose, new mathematical functions are applied on corners and bifurcations. To evaluate the proposed method we use 40 retinal images from the DRIVE database, 20 normal retinal image from STARE database and 140 normal retinal images from local collected database and the accuracy rate is 99.34 percent.

IoT is collection of different "things" which are associated with open web. As all the things are connected to the Internet, it offers convenience to end users for accessing the resources from "Any Where, Any Time" throughout the globe. At the same time, open nature of IoT provides a fertile ground to an intruder for launching different security related threats. If we can no apply proper security safeguards to the IoT System, then it will be not useful to society. Authentication, Encryption, Trust Management and Secure Routing are different domains to offer security in IoT system. Among them, Authentication is very much important security service as it validates device identity before granting access to system services/ resources. Existing IoT Authentication algorithms are fail to verify device identity in unambiguous way. They are vulnerable to different security threats such as Key Stolen threat, MITM threat and Location Spoofing threat. So, it is a demand of time to design an efficient and secure Multi-factor IoT algorithm which can offer better security and validate device identity in unambiguous way.

This article identifies the problems and substantiates the directions for the development of distance learning technologies in the training of personnel. An example of using digital media to create a remote access laboratory is given. The article is devoted to the definition of the main aspects of the organization of distance education. Rapid digitization, economic, political and social changes taking place in Ukraine necessitate the reform of the education system. First of all, it concerns meeting the educational needs of citizens throughout their lives, providing access to educational and professional training for all who have the necessary abilities and adequate training. The most effective solution to the above-mentioned problems is facilitated by distance learning. The article analyzes the essence and methods of distance learning organization, reveals the features of the use of electronic platforms for the organization of this form of education in different countries of the world. The positive characteristics of distance learning are identified, namely: extraterritoriality; savings on transport costs; the interest of modern youth in the use of information tools in everyday life; increase in the number of students; simplicity and accessibility of training; convenient consultation system; democratic relations between the student and the teacher; convenience for organizations in training their employees without interrupting their regular work; low level of payment for distance education compared to traditional education; individual learning pace; new teacher status. Among the negative features of online education, the author refers to the following problems: authentication of users during knowledge verification, calculation of the teacher's methodological load and copyright of educational materials; the high labor intensity of developing high-quality educational content and the high cost of distance learning equipment; the need to provide users with a personal computer and access to the Internet; the need to find and use effective motivation mechanisms for education seekers.

The research involved children and parents of primary school-aged children with cognitive development disorder, as well as scientific and pedagogical workers who organized the psychological and pedagogical principles for organizing distance learning. The purpose of the research lies in establishing how effectively children, parents and their teachers cope with online distance learning during the pandemic, as well as investigating the extent to which such educational technology affects the emotional and behavioural state of the child. The research methodology is based on complexity. In the course of the research, the method of pedagogical experiment was used; observation and questionnaire methods were also introduced; the descriptive method, analysis and synthesis were used to review the theoretical material. The hypothesis lies in the fact that distance online education increases academic difficulties, changes the behavioural and emotional picture of a child with cognitive development disorder; consequently, the behaviour and emotional background will be limited by certain parameters, and this requires the active involvement of parents and teachers in the distance work process. The results of the research have revealed that distance education causes a number of restrictions for children with cognitive development disorder, namely: concentration of attention has decreased, anxiety has increased, and sleep has worsened. Behavioural changes predicted increased restlessness and aggression. Parents and teachers have had methodological, academic and everyday difficulties; all participants in the educational process have been more limited in the conditions of online distance learning. difficulties and improving the behaviour and emotional states of all participants in the educational process.

IOT has carried out important function in converting the traditional fitness care corporation. With developing call for in population, traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings. The worldwide is handling devastating developing antique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens. There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized, right blanketed care to prevent and manipulate excessive coronial situations. Many tech orientated packages related to Health Monitoring have been delivered these days as taking advantage of net boom everywhere on globe, manner to improvements in cellular and in IOT generation. Such as optimized indoor networks insurance, community shape, and fairly-low device fee performances, advanced tool reliability, low device energy consumption, and hundreds higher unusual common usual performance in network safety and privacy. Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem. However, many challenges in this new paradigm shift notwithstanding the fact that exist, that need to be addressed. So the out most purpose of this research paper is 3 essential departments: First, evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring; Second, present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets; Third, communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead. Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.

As the Restaurant industry is growing rapidly. The demand for an effortless POS (Point Of Sale) system which can make management easy is increasing. So, the purpose of this study is to digitalise the growing industry of restaurants and its consumers by utilizing cross-platform development. Crossplatform development frameworks provide great opportunities to solve the issues of handling ubiquitous devices with minimum efforts to reduce the cost and increase the stability, accessibility of the end consumers. By availing those opportunities, an Integrated POS system with cross platform is proposed. This integrated cross-platform POS system is originally designed for a single restaurant managed by its own private cloud server. This research solves the 2 major problems. One of them is the accessibility of the system on modern devices without even writing platform-specific code with the help of cross-platform development. This included web, mobile, desktops & tablets at the same time with the same codebase. Second one is handling data consistency with ubiquitous devices with the help of cloud infrastructure to make data safe and consistent more than ever. In the Development of this system Dart will be used as the primary programming language for cross-platform development. On the Cloud server system apache will be used as the web server and PHP as server side language. System will be using MySQL as the database server.