APPLICATIONS OF ARTIFICIAL INTELLIGENCE PDF

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Artificial Intelligence and Its Applications. Article (PDF Available) in Mathematical Problems in Engineering () ยท April with 5, Reads. PDF | Machine learning is one of the most exciting recent technologies in Artificial Intelligence. Learning algorithms in many applications that's. Federal University of Technology Owerri A Seminar Report Presentation On Overview and Applications of Artificial Intelligence By Kosidichimma Anyanwu.


Applications Of Artificial Intelligence Pdf

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This paper gives an overview of Artificial Intelligence and its applications used in human life. This will explore the current use of Artificial. Abstract. This paper describes the development of an application of Artificial Intelligence (AI) for. Unmanned Aerial Vehicle (UAV) control. The project was done. APPLICATIONS OF ARTIFICIAL abromishico.cf - Download as PDF File . pdf), Text File .txt) or read online. APPLICATIONS OF ARTIFICIAL.

Crimes that target information technology systems typically target e-mail accounts, bank accounts, computers, servers, websites, personal data, and digital records of private and public institutions.

Cyber crimes consist of offenses such as computer intrusions, misuse of intellectual property rights, economic espionage, online extortion, international money laundering, non-delivery of goods or services and a growing list of other offenses facilitated by Internet [8, 10, 11].

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Although cyber crime has become a common phrase today, it is difficult to define it precisely. Most of the existing definitions were developed experimentally.

Fisher and Lab defined cyber crime as crime that occurs when computers or computer networks are involved as tool, locations, or targets of crime [14]. Every day the amount of digital data stored and processed on computers and other computing systems increases exponentially, with people communicating, sharing, working, shopping, and socializing using computers and Internet. Language and country barriers have disappeared and virtual world has become more populated than ever.

The concept of crime is present when dealing with people, therefore cyber space has not stayed isolated from the concepts of crime and criminals either [11]. Brenner argues that most of the cyber crime we see today simply represents the migration of real-world crime to cyberspace which becomes the tool criminals use to commit old crimes in new ways.

AI can be described in two ways: i as a science that aims to discover the essence of intelligence and develop intelligent machines; or ii as a science of finding methods for solving complex problems that cannot be solved without applying some intelligence e.

In the application of AI to cyber defense, we are more interested in the second definition. Research interest in AI include ways to make machines computers simulate intelligent human behavior such as thinking, learning, reasoning, planning, etc. The general problem of simulating intelligence has been simplified to specific sub-problems which have certain characteristics or capabilities that an intelligent system should exhibit. The following characteristics have received the most attention [17, 18, 19]: a Deduction, reasoning, problem solving embodied agents, neural networks, statistical approaches to AI ; c Planning multi-agent planning and cooperation ; d Learning machine learning ; e Natural Language Processing information retrieval text mining, machine translation ; f Motion and Manipulation navigation, localization, mapping, motion planning ; g Perception speech recognition, facial, recognition, object recognition ; h Social Intelligence empathy simulation ; i Creativity artificial intuition, artificial imagination ; and j General Intelligence Strong AI.

Classic AI approaches focus on individual human behavior, knowledge representation and inference methods. The process of finding a solution in distributed resolution problems relies on sharing knowledge about the problem and cooperation among agents. It was from these concepts that the idea of intelligent multi-agent technology emerged.

An agent is an autonomous cognitive entity which understands its environment, i. In multi-agent systems, a group of mobile autonomous agents cooperate in a coordinated and intelligent manner in order to solve a specific problem or classes of problems.

Multi-agent technology has many applications, but this study will only discuss applications to defense against cyber intrusions See Section 4. CI includes several other nature-inspired techniques such as neural networks, fuzzy logic, evolutionary computation, swarm intelligence, machine learning and artificial immune systems. These techniques provide flexible decision making mechanisms for dynamic environments such as cyber-security applications. When we say nature-inspired, it means that there is a growing interest in the field of computing technologies to mimic biological systems such as biological immune system and their remarkable abilities to learn, memorize, recognize, classify and process information.

Artificial immune systems AISs are an example of such technology [2]. AISs are computational models inspired by biological immune systems which are adaptable to changing environments and capable of continuous and dynamical learning. Immune systems are responsible for detection and dealing with intruders in living organisms. AISs are designed to mimic natural immune systems in applications for computer security in general, and intrusion detection systems IDSs in particular [20].

Genetic algorithms are yet another example of an AI technique, i. They provide robust, adaptive, and optimal solutions even for complex computing problems. They can be used for generating rules for classification of security attacks and making specific rules for different security attacks in IDSs [21, 22]. Many methods for securing data over networks and the Internet have been developed e. IDPSs provide four vital security functions: monitoring, detecting, analyzing, and responding to unauthorized activities [23, 24].

Figure 1. A typical IDPS [24]. Neural networks that have ability to learn, process distributed information, self-organize and adapt, are applicable to solving problems that require considering conditionality, imprecision and ambiguity at the same time. When neural networks consist of a large number of artificial neurons, they can provide a functionality of massively parallel learning and decision-making with high speed, which makes them suitable for learning pattern recognition, classification, and selection of responses to attacks [5, 7].

Those characteristics include the following [25]: Real-time intrusion detection while the attack is in progress or immediately afterwards, False positive alarms must be minimized, Human supervision should be reduced to minimum, and continuous operation should be ensured, Recoverability from system crashes, either accidental or those resulting from attacks, Self-monitoring ability in order to detect attackers attempts to change the system, Compliance to the security policies of the system that is being monitored, and Adaptability to system changes and user behavior over time.

For instance, neural networks are being applied to intrusion detection and prevention, but there are also proposals for using neural networks in Denial of Service DoS detection, computer worm detection, spam detection, zombie detection, malware classification and forensic investigations [5].

Some IDSs use intelligent agent technology which is sometimes even combined with mobile agent technology.

Mobile intelligent agents can travel among collection points to uncover suspicious cyber activity [2]. Wang et al. This section will briefly present related work and some existing applications of AI techniques to cyber defense. Artificial Neural Network Applications ANN is a computational mechanism that simulates structural and functional aspects of neural networks existing in biological nervous systems.

They are ideal for situations that require prediction, classification or control in dynamic and complex computer environments [26]. Chen designed NeuroNet a neural network system which collects and processes distributed information, coordinates the activities of core network devices, looks for irregularities, makes alerts and initiates countermeasures.

Barika et al.

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Itikhar et al. Their experiments showed that their neural network approach detects DoS attacks with more accuracy and precision than other approaches [30].

Wu presented a hybrid method of rule-based processing and back-propagation neural networks for spam filtering. Their approach proved to be much more robust compared to other spam detection approaches that use keywords, because spamming behaviors frequently change [31]. Salvador et al. Experiments showed how their approach is computationally efficient, easy to deploy in real network scenarios and achieves good Zombie detection results [32].

Bitter et al. Al-Janabi and Saeed designed a neural network-based IDS that can promptly detect and classify various attacks [33]. Barman and Khataniar also studied the development of IDSs based on neural network systems.

Their experiments showed that the system they proposed has intrusion detection rates similar to other available IDSs, however, it proved to be at least Intelligent Agent Applications Intelligent agents are autonomous computer-generated forces that communicate with each other to share data and cooperate with each other in order to plan and implement appropriate responses in case of unexpected events.

Their mobility and adaptability in the environments they are deployed in, as well as their collaborative nature, makes intelligent agent technology suitable for combating cyber attacks. Rowe developed a counterplan system which can prevent particular cyber attack plans using multi-agent planning together with some novel inference methods [35].

Gou et al. The experiments showed that their system effectively thwarts worm propagation even at the high worm infection rates [36]. Phillips et al. They implemented their system in Prolog and applied it to combating DoS and distributed DoS attacks automatically and without human intervention [4]. Kotenko and Ulanov proposed a framework for adaptive and cooperative defense mechanisms against Internet attacks.

Their approach is based on intelligent multi-agent modeling and simulation, where groups of intelligent agents interact and adjust their configuration and behavior according to the network condition and severity of attacks.

They tested their approach on investigating distributed DoS attacks and defense mechanisms. This program allows the designers to focus more on the design itself and less on the design process.

The software also allows the user to focus less on the software tools. The AIDA uses rule based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective.

In , NASA 's Dryden Flight Research Center , and many other companies, created software that could enable a damaged aircraft to continue flight until a safe landing zone can be reached. The neural network used in the software proved to be effective and marked a triumph for artificial intelligence. The Integrated Vehicle Health Management system, also used by NASA, on board an aircraft must process and interpret data taken from the various sensors on the aircraft.

The system needs to be able to determine the structural integrity of the aircraft.

The system also needs to implement protocols in case of any damage taken the vehicle. Haitham Baomar and Peter Bentley are leading a team from the University College of London to develop an artificial intelligence based Intelligent Autopilot System IAS designed to teach an autopilot system to behave like a highly experienced pilot who is faced with an emergency situation such as severe weather, turbulence, or system failure.

The Intelligent Autopilot System combines the principles of Apprenticeship Learning and Behavioural Cloning whereby the autopilot observes the low-level actions required to maneuver the airplane and high-level strategy used to apply those actions.

AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. See AI effect. AI can be used to potentially determine the developer of anonymous binaries. AI can be used to create other AI.

APPLICATIONS OF ARTIFICIAL INTELLIGENCE.pdf

In June , a research team from the visual computing group of the Technical University of Munich and from Stanford University developed Face2Face, [13] a program which animates the face of a target person, transposing the facial expressions of an exterior source.

The technology has been demonstrated animating the lips of people including Barack Obama and Vladimir Putin. Since then, other methods have been demonstrated based on deep neural network , from which the name " deepfake " was taken. Hollywood film studios had already used the technique in animated films, [ which?

The main difference is that today anyone can use a deep fake software and rig videos. In September , the U. Senator Mark Warner proposed to penalize social media companies that allow sharing of deepfake documents on their platform. Vincent Nozick, a researcher from the Institut Gaspard Monge , found a way to detect rigged documents by analyzing the movements of the eyelid.

Department of Defense has given 68 million dollars to work on deepfake detection. The future of AI in the classroom is looking bright. AI tutors also eliminate the intimidating idea of tutor labs or human tutors which can cause anxiety and stress for some students.

Ambient informatics is the idea that information is everywhere in the environment and that technologies automatically adjust to your personal preferences. While there are many benefits to the use of AI in the classroom, there are also several dangers that need to be taken into account before implementing them.

Another advancement includes the presentation of performance data and enrichment methods on an individual basis. Within curriculum, AI could help determine if there are underlying biases in texts and instructions. For teachers, AI could soon have the power to relay data regarding efficacy of varying learning interventions from a, potentially, global database.

As a whole AI has the power to influence education by taking district, state, national, and global data into consideration as it seeks to better individualize learning for all. Although AI can provide many assets to a classroom, many experts still agree that they will not be able to replace teachers altogether.

Many teachers fear the idea of AI replacing them in the classroom, especially with the idea of personal AI assistants for each student. The reality is, AI can create a more dystopian environment with revenge effects. This means that technology is inhibiting society from moving forward and causing negative, unintended effects on society.

Also, the need for AI technologies to work simultaneously may lead to system failures which could ruin an entire school day if we are relying on AI assistants to create lessons for students every day.

Best books on Artificial Intelligence for beginners with PDF download

It is inevitable that AI technologies will be taking over the classroom in the years to come, thus it is essential that the kinks of these new innovations are worked out before teachers decide whether or not to implement them into their daily schedules.

Algorithmic trading involves the use of complex AI systems to make trading decisions at speeds several orders of magnitudes greater than any human is capable of, often making millions of trades in a day without any human intervention. Such trading is called High-frequency Trading , and it represents one of the fastest growing sectors in financial trading. Many banks, funds, and proprietary trading firms now have entire portfolios which are managed purely by AI systems.

Automated trading systems are typically used by large institutional investors, but recent years have also seen an influx of smaller, proprietary firms trading with their own AI systems. Several large financial institutions have invested in AI engines to assist with their investment practices.

Its wide range of functionalities includes the use of natural language processing to read text such as news, broker reports, and social media feeds.

It then gauges the sentiment on the companies mentioned and assigns a score. Its machine learning systems mine through hoards of data on the web and assess correlations between world events and their impact on asset prices.

Several products are emerging that utilize AI to assist people with their personal finances. For example, Digit is an app powered by artificial intelligence that automatically helps consumers optimize their spending and savings based on their own personal habits and goals. The app can analyze factors such as monthly income, current balance, and spending habits, then make its own decisions and transfer money to the savings account.

AI, an upcoming startup in San Francisco, builds agents that analyze data that a consumer would leave behind, from Smartphone check-ins to tweets, to inform the consumer about their spending behavior.

Robo-advisors are becoming more widely used in the investment management industry. Robo-advisors provide financial advice and portfolio management with minimal human intervention. This class of financial advisers work based on algorithms built to automatically develop a financial portfolio according to the investment goals and risk tolerance of the clients. It can adjust to real-time changes in the market and accordingly calibrate the portfolio.

Their technology will be licensed to banks for them to leverage for their underwriting processes as well. This platform utilizes machine learning to analyze tens of thousands traditional and nontraditional variables from download transactions to how a customer fills out a form used in the credit industry to score borrowers.

The platform is particularly useful to assign credit scores to those with limited credit histories, such as millennials. The s is really when AI started to become prominent in the finance world. This is when Expert Systems became more of a commercial product in the financial field.

It was first commercially shipped in Robots have become common in many industries and are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. In the automotive industry , a sector with particularly high degree of automation, Japan had the highest density of industrial robots in the world: Artificial neural networks are used as clinical decision support systems for medical diagnosis , such as in Concept Processing technology in EMR software.

Other tasks in medicine that can potentially be performed by artificial intelligence and are beginning to be developed include:. There are over 90 AI startups in the health industry working in these fields.

Another application of AI is in the human resources and recruiting space. There are three ways AI is being used by human resources and recruiting professionals: Typically, resume screening involves a recruiter or other HR professional scanning through a database of resumes. Now startups like Pomato are creating machine learning algorithms to automate resume screening processes.

KE Solutions, founded in , has developed recommendation systems to rank jobs for candidates, and rank resumes for employers. It helps recruiters to overcome technical barriers.

From to , consumer goods company Unilever used artificial intelligence to screen all entry-level employees. Unilever partnered with Pymetrics and HireVue to enable its AI-based screening and increased their applicants from 15, to 30, in a single year.

Unilever also decreased time to hire from 4 months to four weeks and saved over 50, hours of recruiter time. The job market has seen a notable change due to artificial intelligence implementation. It has simplified the process for both recruiters and job seekers i. According to Raj Mukherjee from Indeed. AI-powered engine streamlines the complexity of job hunting by operating information on job skills, salaries, and user tendencies, matching people to the most relevant positions.

Machine intelligence calculates what wages would be appropriate for a particular job, pulls and highlights resume information for recruiters using natural language processing, which extracts relevant words and phrases from text using specialized software.

Another application is an AI resume builder which requires 5 minutes to compile a CV as opposed to spending hours doing the same job. In the AI age chatbots assist website visitors and solve daily workflows. Moreover, the research proves automation will displace between and million employees.

Some AI applications are geared towards the analysis of audiovisual media content such as movies, TV programs, advertisement videos or user-generated content. The solutions often involve computer vision , which is a major application area of AI. Typical use case scenarios include the analysis of images using object recognition or face recognition techniques, or the analysis of video for recognizing relevant scenes, objects or faces. The system also needs to implement protocols in case of any damage taken the vehicle.

Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. See AI effect. AI can be used to potentially determine the developer of anonymous binaries. The technology has been demonstrated animating the lips of people including Barack Obama and Vladimir Putin. Since then, other methods have been demonstrated based on deep neural network , from which the name " deepfake " was taken.

Hollywood film studios had already used the technique in animated films,[ which? The main difference is that today anyone can use a deep fake software and rig videos. Senator Mark Warner proposed to penalize social media companies that allow sharing of deepfake documents on their platform. Department of Defense has given 68 million dollars to work on deepfake detection. AI tutors also eliminate the intimidating idea of tutor labs or human tutors which can cause anxiety and stress for some students.

Ambient informatics is the idea that information is everywhere in the environment and that technologies automatically adjust to your personal preferences. While there are many benefits to the use of AI in the classroom, there are also several dangers that need to be taken into account before implementing them.

Another advancement includes the presentation of performance data and enrichment methods on an individual basis. Within curriculum, AI could help determine if there are underlying biases in texts and instructions. For teachers, AI could soon have the power to relay data regarding efficacy of varying learning interventions from a, potentially, global database. As a whole AI has the power to influence education by taking district, state, national, and global data into consideration as it seeks to better individualize learning for all.

Although AI can provide many assets to a classroom, many experts still agree that they will not be able to replace teachers altogether. Many teachers fear the idea of AI replacing them in the classroom, especially with the idea of personal AI assistants for each student. The reality is, AI can create a more dystopian environment with revenge effects.

This means that technology is inhibiting society from moving forward and causing negative, unintended effects on society. Also, the need for AI technologies to work simultaneously may lead to system failures which could ruin an entire school day if we are relying on AI assistants to create lessons for students every day.Resilience to noise and incomplete data.

A mere year later an improved type of domestic robot was released in the form of Aibo , a robotic dog with intelligent features and autonomy. Most researchers hope that their work will eventually be incorporated into a machine with general intelligence known as strong AI , combining all the skills above and exceeding human abilities at most or all of them. Major companies are investing in AI to handle difficult customer in the future.

They tested it in an online network environment and the results showed that the proposed IDPS offers high detection rate for the main attack types Probe and DoS within a few seconds, and also automatically protects the computer network from the attacks. Al-Janabi and Saeed designed a neural network-based IDS that can promptly detect and classify various attacks [33].