Constructing a Multilingual E-Learning Ontology through Web Crawling and Scraping

The emergence of digital technologies has transformed the landscape of education, driving the exploration of innovative methods to improve the efficiency and effectiveness of university e- learning. This study focuses on leveraging network management principles in combination with web crawling trends to propose a novel approach: a web crawling and scraping-driven method for constructing a multilingual ontology tailored specifically for university e-learning. The primary goal of this research is to create a comprehensive and continuously updated knowledge repository by systematically gathering and extracting information from a wide range of online sources. By incorporating multilingual capabilities into the proposed ontology, the aim is to transcend language barriers and establish a globally accessible and inclusive e-learning environment. This approach recognizes the intricate relationship between technology and education, highlighting the potential of automated data retrieval and ontology construction in reshaping the future of university e-learning. This research contributes significantly to the rapidly growing field of educational technology by introducing a forward-thinking paradigm. It empowers both educators and learners with a versatile and personalized learning experience that transcends cultural and linguistic boundaries. As the digital era continues to evolve, this approach serves as a beacon of innovation, exemplifying the transformative power of integrating cutting-edge technology with pedagogical efforts. In essence, this study presents a groundbreaking approach to enhance university e- learning by harnessing the capabilities of web crawling, scraping, and multilingual ontology construction. It emphasizes the importance of adapting to the ever-evolving digital landscape to provide an inclusive and accessible education experience for learners worldwide. Ultimately, this research represents a significant step forward in the ongoing effort to revolutionize education through the integration of advanced technology and pedagogical innovation

Machine learning Algorithm of Intrusion Detection System

Web of thing (WoT) is a gifted answer for interface and access each gadget through the web. Consistently the gadget includes increments with huge variety fit as a fiddle, size, use and intricacy. In this paper Since WoT drives the world and changes individuals' lives with its wide scope of administrations and applications. In any case, WoT offers various types of assistance through applications, it faces serious security issues and powerless against assaults, for example, sinkhole assault, overhang dropping, forswearing of administration assaults. So on, the Interruption recognition framework is utilized to recognize such assaults when the organization's security is penetrated. Given a scale extension of Web of Things for a practical asset the executives in brilliant urban communities, a legitimate plan of an interruption recognition framework IDS is basic to protect the future organization framework from interlopers. With the development of associated things, the most broadly utilized brought together cloud-based IDS regularly suers from high inertness and organization overhead, subsequently coming about in lethargy to assaults and moderate recognition of pernicious clients

A State of Art for Smart Gateways Issues and Modification

The Internet of Things (IoT) is a collection of objects such as sensors, actuators, and processors, which interconnected within a specific network to perform a task collaboratively. The IoT is one of the prevalent technologies, which has developed dramatically in recent years. Its reputation derives from its relevance and role in employing things in the best way, starting with smartphones that opened new horizons in control technologies and later developing new ideas regarding cloud-computing services. A smart gateway plays an essential role in the IoT applications that responsible for enabling communication between the network layer and the ubiquitous sensors network layer. IoT gateways are methods that operate with influential data centers as a point of communication between lower-end users. IoT gateways connect the heterogeneous devices in use and carry out many tasks to accomplish the computing mission. This work searches how IoT gateway's function and how they interact. In particular, it lists interface issues related to IoT gateways. In this paper, we research IoT and Smart Gateways and address Smart Gateways problems and computing techniques to promote IoT programs' stable transition to the Smart Gateway

State of Art Survey for IoT Effects on Smart City Technology: Challenges, Opportunities, and Solutions

Automation frees workers from excessive human involvement to promote ease of use while still reducing their input of labor. There are about 2 billion people on Earth who live in cities, which means about half of the human population lives in an urban environment. This number is rising which places great problems for a greater number of people, increased traffic, increased noise, increased energy consumption, increased water use, and land pollution, and waste. Thus, the issue of security, coupled with sustainability, is expected to be addressed in cities that use their brain. One of the most often used methodologies for creating a smart city is the Internet of Things (IoT). IoT connectivity is understood to be the very heart of the city of what makes a smart city. such as sensor networks, wearables, mobile apps, and smart grids that have been developed to harness the city's most innovative connectivity technology to provide services and better control its citizens The focus of this research is to clarify and showcase ways in which IoT technology can be used in infrastructure projects for enhancing both productivity and responsiveness

Comprehensive Survey for Cloud Computing Based Nature-Inspired Algorithms Optimization Scheduling

Many applications in the real world include optimizing specific targets, such as cost minimization, energy conservation, climate, and maximizing production, efficiency, and sustainability. The optimization problem is strongly non-linear with multifunctional landscapes under several dynamic, non-linear constraints in some instances. It is challenging to address those issues. Also, with the increasing strength of modern computers, simplistic brute force methods are still inefficient and unwanted. Practical algorithms are also vital for these implementations whenever possible. Cloud computing has become an essential and popular emerging computing environment that supports on-demand services and provides internet-based services. Cloud computing allows a range of services and tools to be easily accessed from anywhere in the world. Since cloud computing has global access to its services, there will always be threats and challenges facing its servers and services, such as; task scheduling, security, energy efficiency, network load, and other challenges. In the research area, many algorithms have been addressed to solve these problems. This paper investigates relevant analysis and surveys on the above topics, threats, and outlooks. This paper offers an overview of nature-inspired algorithms, their applications, and valuation, emphasizing cloud computing problems. Many problems in science and engineering can be viewed as optimization problems with complex non-linear constraints. Highly nonlinear solutions typically need advanced optimization algorithms, and conventional algorithms can have difficulty addressing these issues. Because of its simplicity and usefulness, nature-inspired algorithms are currently being used. There are nevertheless some significant concerns with computing and swarming intelligence influenced by evolution

A Survey of Data Mining Activities in Distributed Systems

Distributed systems, which may be utilized to do computations, are being developed as a result of the fast growth of sharing resources. Data mining, which has a huge range of real applications, provides significant techniques for extracting meaningful and usable information from massive amounts of data. Traditional data mining methods, on the other hand, suppose that the data is gathered centrally, stored in memory, and is static. Managing massive amounts of data and processing them with limited resources is difficult. Large volumes of data, for instance, are swiftly generated and stored in many locations. This becomes increasingly costly to centralize them at a single location. Furthermore, traditional data mining methods typically have several issues and limitations, such as memory restrictions, limited processing ability, and insufficient hard drive space, among others. To overcome the following issues, distributed data mining's have emerged as a beneficial option in several applications According to several authors, this research provides a study of state-of-the-art distributed data mining methods, such as distributed common item-set mining, distributed frequent sequence mining, technical difficulties with distributed systems, distributed clustering, as well as privacy-protection distributed data mining. Furthermore, each work is evaluated and compared to the others

A State of Art Survey for Understanding Malware Detection Approaches in Android Operating System

Mobile malware is malicious software that targets mobile phones or wireless-enabled Personal digital assistants (PDA), by causing the collapse of the system and loss or leakage of confidential information. As wireless phones and PDA networks have become more and more common and have grown in complexity, it has become increasingly difficult to ensure their safety and security against electronic attacks in the form of viruses or other malware. Android is now the world's most popular OS. More and more malware assaults are taking place in Android applications. Many security detection techniques based on Android Apps are now available. Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and methods from different perspectives. Existing research suggests that machine learning is an effective and promising way to detect Android malware. Notwithstanding, there exist reviews that have surveyed different issues related to Android malware detection based on machine learning. The open environmental feature of the Android environment has given Android an extensive appeal in recent years. The growing number of mobile devices, they are incorporated in many aspects of our everyday lives. In today’s digital world most of the anti-malware tools are signature based which is ineffective to detect advanced unknown malware viz. Android OS, which is the most prevalent operating system (OS), has enjoyed immense popularity for smart phones over the past few years. Seizing this opportunity, cybercrime will occur in the form of piracy and malware. Traditional detection does not suffice to combat newly created advanced malware. So, there is a need for smart malware detection systems to reduce malicious activities risk. The present paper includes a thorough comparison that summarizes and analyses the various detection techniques

State of Art Survey for Fault Tolerance Feasibility in Distributed Systems

The use of technology has grown dramatically, and computer systems are now interconnected via various communication mediums. The use of distributed systems (DS) in our daily activities has only gotten better with data distributions. This is due to the fact that distributed systems allow nodes to arrange and share their resources across linked systems or devices, allowing humans to be integrated with geographically spread computer capacity. Due to multiple system failures at multiple failure points, distributed systems may result in a lack of service availability. to avoid multiple system failures at multiple failure points by using fault tolerance (FT) techniques in distributed systems to ensure replication, high redundancy, and high availability of distributed services. In this paper shows ease fault tolerance systems, its requirements, and explain about distributed system. Also, discuss distributed system architecture; furthermore, explain used techniques of fault tolerance, in additional that review some recent literature on fault tolerance in distributed systems and finally, discuss and compare the fault tolerance literature

Scheduling Algorithms Implementation for Real Time Operating Systems: A Review

The term "Real-Time Operating System (RTOS)" refers to systems wherein the time component is critical. For example, one or more of a computer's peripheral devices send a signal, and the computer must respond appropriately within a specified period of time. Examples include: the monitoring system in a hospital care unit, the autopilot in the aircraft, and the safety control system in the nuclear reactor. Scheduling is a method that ensures that jobs are performed at certain times. In the real-time systems, accuracy does not only rely on the outcomes of calculation, and also on the time it takes to provide the results. It must be completed within the specified time frame. The scheduling strategy is crucial in any real-time system, which is required to prevent overlapping execution in the system. The paper review classifies several previews works on many characteristics. Also, strategies utilized for scheduling in real time are examined and their features compared