Abstract—This paper demonstrates a comparative study of
Arabic Multi-Document Summarization System (AMD-SS).
These methods are compared and analyzed, aiming to detect
which method generates a genuine summary and achieves the
best results in comparison with the human summarization
techniques. The comparative study shows that there is a lack in
the area of Arabic Automatic Text Summarization systems.
Therefore, we proposed an Arabic Text Summarization model
that built in linear algorithms based on parallel computing
techniques. The proposed model is built in order to generate an
Arabic Document Summary (ADS) that is fully coherent,
grammatical and meaningful Arabic sentences, closing to a
human summarization. Recent researches have not provided
perfect Arabic summary.

2017 8th International Conference on Information Technology (ICIT)

Cognitive agents for business and industrial environments are one of the most dominant ideas in multi-agent scheme today. We propose a general, flexible, and powerful architecture to build software agents that embed artificial cognitive factors. The propose agent possesses sensible knowledge and reactive abilities, and interacts with the external complex business environment, including other agents. We examine if artificial cognitive states can improve the performance of agents in some business and industrial conditions. Our agent model generates responsive actions in reaction to certain stimuli. Cognitive Agent Model (CAM) is proposed for this purpose. Sales and Production Planning (SPP) (as business and manufacturing application) is chosen to demonstrate the use of our agent.  Netlogo is used as an agent programming language. It is the agent-oriented language used to simulate and implement our proposed models.

Keywords: Agent, Agent Modeling, Cognitive Factors, Believable, Behavior, Decision Making, Intelligent, Multi-Agent System.

Accepted in

Journal of Theoretical and Applied Information Technology-Scopus Indexed

The evolving necessity of the Internet increases the demand on the bandwidth. Therefore, this demand opens the doors for the hackers’ community to develop new methods and techniques to gain control over networking systems. Hence, the intrusion detection systems (IDS) are insufficient to prevent/detect unauthorized access the network. Network Intrusion Detection System (NIDS) is one example that still suffers from performance degradation due the increase of the link speed in today’s networks. In This paper we proposed a novel algorithm to detect the intruders, who’s trying to gain access to the network using the packets header parameters such as; source/destination address, source/destination port, and protocol without the need to inspect each packet content looking for signatures/patterns. However, the “Packet Header Matching” algorithm enhances the overall speed of the matching process between the incoming packet headers against the rule set. We ran the proposed algorithm to proof the proposed concept in coping with the traffic arrival speeds and the various bandwidth demands. The achieved results were of significant enhancement of the overall performance in terms of detection speed.

https://arxiv.org/abs/1108.1417

This chapter proposes modeling of artificial emotions through agents based on the symbolic approach. Two models were built for agent-based systems; one was supported with artificial emotions and the other one without. Both were used in solving a benchmark problem: orphanage care. The goal was to have a clean and healthy environment for an orphanage house.  An application symbolic approach utilizes symbolic emotional rule-based systems (i.e. rule base that generates emotions) with continuous interactions with the environment and an  internal “thinking” machinery that comes as a result of a series of inferences, evaluations, evolution processes, adaptations, learning and emotions. The two systems were simulated and results were compared. The study showed that systems with proper model of emotions could perform better than systems without emotions. The study sheds the light on how artificial emotions can be modeled in simple rule-based agent systems, and if emotions as they exist in real intelligence can be helpful for artificial intelligence..

Environmental Management, Sustainable Development and Human Health,

Chapter 20. Modeling of Artificial Emotions and its Application Towards a Healthy Environment, http://www.crcnetbase.com/doi/abs/10.1201/9780203881255.ch20

There is an increasing awareness among modern business, engineers, managers, and planners to design and
operate their systems even to minimize cost, or to maximum profit (maximum efficiency/business benefits).
Accordingly, significant work has been done on business (specially, on manufacturing system) operations for
total demand and on the optimal allocation of resources available. Linear Assignment Problems (LAP) is one of
the most important optimization problem solving methods (in Operation Research) support this problem. This
paper proposes a new modifications on the Best Candidates Method (BCM) and compares the proposed method
with other Linear Programming (LP) methods in solving Linear Assignment Problems (LAP). In general, there
are many development approaches for LAP to reach the optimal solution through minimize or maximize the
objective function. Each problem solving technique (method) has its own time complexity, and solution
optimality. Some methods can be used successfully when dealing with small scale problems, while they
considered as an inefficient method when solving large scale problems. Performance of different LAP problem
solving methods is presented because of their wide used in different area of optimization problems. We
introduce our new modifications on BCM in solving LAP problems which has significant improvements in the
number of combinations and searching strategy.

International Journal of Engineering Science and Technology (IJEST). ISSN : 0975-5462 Vol. 5 No.05. p1137.  May 2013, URL: http://www.ijest.info/docs/IJEST13-05-05-101.pdf.

Steganography is defined as the art of hiding secret information, which is used to guarantee information is accessible only by authorized parties who has the secret key and is inaccessible to others. The least-significant bit (LSB) approach is one of the most important scenarios in steganography. However, the most current LSB approaches should apply some changing in the image’s pixels values, which make the image suspected by intruders and hackers. This paper proposed an image Steganographic system based on the exact matching between the image’s pixel values and the secret data. As well as, a random key-dependent data (RKDD) in the proposed system is then generated without performing any modifications on the image’s pixel values. Moreover, the proposed system has been tested successfully on numerous images giving ultimate results. These significant results can be perceived in terms of fast searching time, a great number of matches, reduced the key size, achieving steganography performance criteria, invisibility, payload/ capacity and robustness.

Abstract

Artificial emotions play an important role at the control level of agent architectures: emotion may lead to reactive or deliberative behaviors, it may intensify an agent’s motivations, it can create new goals (and then sub-goals) and it can set new criteria for the selection of the methods and the plans the agent uses to satisfy its motives. Since artificial emotion is a process that operates at the control level of agent architecture, the behavior of the agent will improve if agent’s emotion process improves (El-Nasr, Ioerger, & Yen, 1998; El-Nasr & Yen, 1998). In this introductory chapter, our aim is to build agents with the mission “to bring life” several applications, such as: information, transaction, education, tutoring, business, entertainment and e-commerce. Therefore we want to develop artificial mechanisms that can play the role emotion plays in natural life. We call these mechanisms “artificial emotions” (Scheutz, 2004). As Damasio (1994) argues, emotions are necessary for problem solving because when we plan our lives, rather than examining every opinion, some possibilities are emotionally blocked off. We will try to investigate if artificial emotional control can improve performance of the agent in some circumstances. We would like to introduce the readers to our model, which is based on both symbolic and computational relations. Simulations are left for another publication. The space available is barely enough to give an overall picture about our model. The main contributions of this proposal model is to argue that emotion learning is a valid approach to improve the behavior of artificial agents, and to present a systematic view of the kinds of emotion learning that can take place, assuming emotion is a process involving assessment, emotion-signal generation, emotion-response and then emotion learning (LeDoux, 1996). To come across as emotional, an agent needs to incorporate a deeper model of personality, sensitivity, mood, feeling and emotions, and, in particular, directly connect these affective concepts. For agents to be believable, the minds of agents should not be restricted to model reasoning, intelligence and knowledge but also emotions, sensitivity, feeling, mood and personality (Nemani & Allan, 2001). We will propose EMAM (Emotional Agent Model) for this purpose. EMAM generates artificial emotion signals, evaluates and assesses events, takes into account the integration of personality, sensitivity, mood, feeling and motivational states then takes proper action or plans for actions (sequence of actions) (LeDoux, 1996; Gratch, 2000).

Published book by IGI Inc.: “Simulation and Modeling:  Current Technologies and Applications”, 2007.

http://www.igi-global.com/chapter/emotional-agen-modelig-emam/28995

Abstract

This paper proposes modeling of artificial emotions through agents based on symbolic approach. The symbolic approach utilizes symbolic emotional rule-based systems (rule base that generated emotions) with continuous interactions with environment and an internal “thinking” machinery that comes as a result of series of inferences, evaluation, evolution processes, adaptation, learning, and emotions. We build two models for agent based systems; one is supported with artificial emotions and the other one without emotions. We use both in solving a bench mark problem; “The Orphanage Care Problem”. The two systems are simulated and results are compared. Our study shows that systems with proper model of emotions can perform in many cases better than systems without emotions. We try to shed the light here on how artificial emotions can be modeled in a simple rule-based agent systems and if emotions as they exist in “real intelligence” can be helpful for “artificial intelligence”. Agent architectures are presented as a generic blueprint on which the design of agents can be based. Our focus is on the functional design, including flow of information and control. With this information provided, the generic blueprints of architectures should not be difficult to implement agents, thus putting these theoretical models into practice. We build the agents using this architecture, and many experiments and analysis are shown.

International Journal of Information and Software Technology,  An  Elsevier  Publishing Journal, Volume 49, Issue 6, June 2007.

http://www.sciencedirect.com/science/article/pii/S0950584906001030