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Search Results: 1 - 10 of 401554 matches for " Alaa M. Khamis "
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Market-Based Approach to Mobile Surveillance Systems
Ahmed M. Elmogy,Alaa M. Khamis,Fakhri O. Karray
Journal of Robotics , 2012, DOI: 10.1155/2012/841291
Abstract: The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is, therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given area of interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This paper proposes a market-based approach that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target tracking are studied using the proposed approach as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively. 1. Introduction One of the most active research topics is how to automate surveillance tasks based on mobile and fixed sensors platforms [1]. Many benefits can be anticipated from the use of multisensor systems in surveillance applications [2, 3], such as decreasing task completion time and increasing mission reliability. Generally, monitoring of public and private sites is the main application of multisensor surveillance systems. The primary objectives of the surveillance systems are to provide the information that makes the system able to understand and predict the actions and the interactions of the observed objects in order to carry out different tasks. Examples of these tasks would include target search, identification, and tracking. Advanced surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given area of interest (AOI) [4]. Mobile surveillance systems incorporate self-organized networks of mobile sensing nodes of different modalities, data and information fusion nodes, acting nodes, and control nodes. These self-organized nodes can collaboratively and continuously sense within the volume of interest, as well as physically manipulate and interact with it. The main goal of the surveillance system is to adjust the sensing conditions for improved visibility, and thereby improve performance [5]. In such setting, surveillance is a complex problem posing many challenging problems. This paper
Minefield Mapping Using Cooperative Multirobot Systems
Alaa Khamis,Asser ElGindy
Journal of Robotics , 2012, DOI: 10.1155/2012/698046
Adaptive Group Formation in Multirobot Systems
Ahmed Wagdy,Alaa Khamis
Advances in Artificial Intelligence , 2013, DOI: 10.1155/2013/692658
Abstract: Multirobot systems (MRSs) are capable of solving task complexity, increasing performance in terms of maximizing spatial/temporal/radio coverage or minimizing mission completion time. They are also more reliable than single-robot systems as robustness is increased through redundancy. Many applications such as rescue, reconnaissance, and surveillance and communication relaying require the MRS to be able to self-organize the team members in a decentralized way. Group formation is one of the benchmark problems in MRS to study self-organization in these systems. This paper presents a hybrid approach to group formation problem in multi-robot systems. This approach combines the efficiency of the cellular automata as finite state machine, the interconnectivity of the virtual grid and its bonding technique, and last but not least the decentralization of the adaptive dynamic leadership. 1. Introduction Any group of robots in a multirobot system (MRS) moving and coordinating together will always require the ability to quickly change group formation to adapt to the environment. All the robots within this system cooperate with each other to achieve the common goal of having the best group formation with decentralized communication between the robots in that system. This means that each robot has to consider the environmental changes, positions of other robots, and the global goal. The multi-robot systems consist of either homogenous or heterogeneous robots. Homogenous robot system consists of a number of robots with the same properties, capabilities, configuration, and shape. On the other hand, heterogeneous robot system consists of robots that have different capabilities, properties, configuration, and shapes which makes task of implementing an algorithm to control their group formation without a centralized controller/coordinator difficult. Search and destroy, search and rescue, surround and conquer, and many military applications require multi-robot systems that are able to form a group and to adapt robustly. In order to solve the group formation problem in MRS, it is required to (i)model the relationship between robots in the same system, (ii)avoid clashes between robots, obstacles and goal,(iii)build all desired formations,(iv)coordinate the motion of each robot, (v)maintain formation while in motion,(vi)develop an approach that ensures adaptability of the formation.This paper presents a hybrid approach to group formation problem in multi-robot systems. This approach combines the efficiency of the cellular automata as finite state machine, the interconnectivity
Minefield Mapping Using Cooperative Multirobot Systems
Alaa Khamis,Asser ElGindy
Journal of Robotics , 2012, DOI: 10.1155/2012/698046
Abstract: This paper presents a team-theoretic approach to cooperative multirobot systems. The individual actions of the robots are controlled by the Belief-Desire-Intention model to endow the robots with the know-how needed to execute these actions deliberately. The cooperative behaviors between the heterogeneous robots are governed by the Team-Log theory to endow all the robots in the team with the know-how-to-cooperate and determine the team members’ commitments to each other despite their different types, properties, and goals. The proposed approach is tested for validity with the real life problem of minefield mapping. Different minefield sweeping strategies are studied to control the mobility of the mobile sweepers within the minefield in order to maximize the area coverage and improve picture compilation capability of the multirobot system. 1. Introduction Developing a robust and cooperative team of robots capable of solving complex tasks is an interesting area of research that attracts many researchers nowadays. Achieving robust and productive cooperation between various system components is inspired by different domains such as biology, artificial life, psychology, and cognitive science in order to build artificially cooperative intelligent systems. Cooperation is defined in [1] as a purposive positive interference of agents to further the achievement of a common goal or goals compatible with their own. To achieve this effective cooperation in multirobot systems (MRS), the robots must have know-how for solving simple problems in an autonomous way and a know-how-to-cooperate by which agents can share common interests and interact with each other to solve complex problems cooperatively. In recent years, scientific community has seen a great number of research works dedicated to cooperative multirobot systems and their applications in different areas such as search and rescue [2, 3], distributed surveillance [4], communication relaying [5], agriculture [6], sorting [7], emergency services [8], and landmine detection [9]. Minefield reconnaissance and mapping is one of the most promising applications of cooperative multirobot systems. In the context of humanitarian demining, cooperative multirobot systems can be beneficial for deminers, civilians, and government. The design of an accurate sensor may reduce the amount of time needed to determine whether a landmine exists, but does not increase the safety of the deminer. Since the safety issues during the eradication process are of great concern, the use and integration of cheap and simple mobile sweepers in
Handling Data Uncertainty and Inconsistency Using Multisensor Data Fusion
Waleed A. Abdulhafiz,Alaa Khamis
Advances in Artificial Intelligence , 2013, DOI: 10.1155/2013/241260
Abstract: Data provided by sensors is always subjected to some level of uncertainty and inconsistency. Multisensor data fusion algorithms reduce the uncertainty by combining data from several sources. However, if these several sources provide inconsistent data, catastrophic fusion may occur where the performance of multisensor data fusion is significantly lower than the performance of each of the individual sensor. This paper presents an approach to multisensor data fusion in order to decrease data uncertainty with ability to identify and handle inconsistency. The proposed approach relies on combining a modified Bayesian fusion algorithm with Kalman filtering. Three different approaches, namely, prefiltering, postfiltering and pre-postfiltering are described based on how filtering is applied to the sensor data, to the fused data or both. A case study to find the position of a mobile robot by estimating its x and y coordinates using four sensors is presented. The simulations show that combining fusion with filtering helps in handling the problem of uncertainty and inconsistency of the data. 1. Introduction Multisensor data fusion is a multidisciplinary research area borrowing ideas from many diverse fields such as signal processing, information theory, statistical estimation and inference, and artificial intelligence. This is indeed reflected in the variety of the techniques reported in the literature [1]. Several definitions for data fusion exist in the literature. Klein [2] defines it by stating that data can be provided either by a single source or by multiple sources. Data fusion is defined by Joint Directors of Laboratories (JDL) [3] as a “multilevel, multifaceted process handling the automatic detection, association, correlation, estimation, and combination of data and information from several sources.” Both definitions are general and can be applied in different fields including remote sensing. In [4], the authors present a review and discussion of many data fusion definitions. Based on the identified strengths and weaknesses of previous work, a principled definition of data fusion is proposed as the study of efficient methods for automatically or semiautomatically transforming data from different sources and different points in time into a representation that provides effective support for human or automated decision making. Data fusion is applied in many areas of autonomous systems. Autonomous systems must be able to perceive the physical world and physically interact with it through computer-controlled mechanical devices. A critical problem of autonomous
A Comparative Study between Optimization and Market-Based Approaches to Multi-Robot Task Allocation
Mohamed Badreldin,Ahmed Hussein,Alaa Khamis
Advances in Artificial Intelligence , 2013, DOI: 10.1155/2013/256524
Abstract: This paper presents a comparative study between optimization-based and market-based approaches used for solving the Multirobot task allocation (MRTA) problem that arises in the context of multirobot systems (MRS). The two proposed approaches are used to find the optimal allocation of a number of heterogeneous robots to a number of heterogeneous tasks. The two approaches were extensively tested over a number of test scenarios in order to test their capability of handling complex heavily constrained MRS applications that include extended number of tasks and robots. Finally, a comparative study is implemented between the two approaches and the results show that the optimization-based approach outperforms the market-based approach in terms of optimal allocation and computational time. 1. Introduction In the last few years, the field of research in mobile robotics has encountered a significant shift as the researchers in this field have recently started focusing on MRS rather than single-robot systems. This increased interest in the community of mobile robotics research towards MRS comes from the significant advantages and higher potential provided by MRS than single-robot systems. The advantages of a robot team are many; some examples of these advantages include, but are not limited to, resolving task complexity, increased system reliability, increased system performance, and finally easier and simpler design [1]. One of the main areas of research in this field is the task allocation problem in MRS, where the mapping of robots to tasks is done in order to increase the overall performance of the system. The task allocation problem is a major issue in MRS as it focuses on the proper utilization of the available resource. In MRS, the available resources are the robots which are used to solve a problem or to perform a certain task. Thus, in order to increase the performance of the system, one must efficiently utilizes the available robots in order to solve the required tasks. Since the decision of which robot will do which task has a significant effect on the performance of the system, the allocation of the tasks to the proper robots strongly affects the performance of the system [2]. The task allocation problem is proved to be one of the toughest problems especially when it comes to complex heterogeneous robot teams that are required to solve and execute complex problems and tasks. The heterogeneity of the robots simply indicates that the robot team consists of robots that have different features such as different capabilities and skills, different
Biomarkers in Nile Tilapia Oreochromis niloticus niloticus (Linnaeus, 1758) to Assess the Impacts of River Nile Pollution: Bioaccumulation, Biochemical and Tissues Biomarkers  [PDF]
Alaa G. M. Osman
Journal of Environmental Protection (JEP) , 2012, DOI: 10.4236/jep.2012.328112
Abstract: The use of biomarkers has become an important tool for modern environmental assessment as they can help to predict pollutants involved in the monitoring program. Here I present data on bioaccumulation, biochemical and tissues biomarkers in Nile tilapia as early warning indicators of river Nile pollution. Nile tilapia sampled from downstream sites accumulated higher levels of all the detected heavy metals than those collected from upstream sites. Heavy metal residues in the tissues of Nile tilapia exhibited different patterns of accumulation and distribution among the selected tissues. Remarkable alterations in the activities of glucose-6-phosphate dehydrogenase (G6PDH) and lactate dehydrogenase (LDH) in the tissues of Nile tilapia were detected. These alterations were followed, in the present study, by the occurrence of histological lesions in liver and gill tissues of fish collected from the same sites. Alterations in bioaccumulation patterns, in enzyme activities and in histology go in parallel with the elevation in the levels of water chemical parameters detected in the downstream sites as a result of pollution stress in these areas. These results provide evidence that bioaccumulation, biochemical and tissues biomarkers can be sensitive indicators of exposure to mixed pollutants in surface waters.
Evolutionary Approach to Forex Expert Advisor Generation  [PDF]
Alaa Eldin M. Ibrahim
Intelligent Information Management (IIM) , 2014, DOI: 10.4236/iim.2014.63014

We have developed a genetic algorithm approach for automatically generating expert advisors, computer programs that trade automatically in the financial markets. Our system, known as GenFx or Genetic Forex, evaluates evolutionarily generated expert advisors strategies using predetermined fitness functions to automatically prioritize parents for breeding. GenFx simulates several key factors in natural selection. It employs a multiple generation breeding population, a notion of gender, and the concept of aging to maintain diversity while providing many breeding opportunities to highly successful offspring. The approach is also especially efficient running in a multiple processor, multiple selection-strategy mode using multiple settings. We found out that a multi-processor gender-based running of the system outperformed all single runs of the system. This system is inspired by GenShade, a previous system that we have developed for evolutionary generating procedural textures. The methods described in this paper are not limited to the Forex market or financial problems only but are applicable to many other fields.

Genotoxicity Tests and Their Contributions in Aquatic Environmental Research  [PDF]
Alaa G. M. Osman
Journal of Environmental Protection (JEP) , 2014, DOI: 10.4236/jep.2014.514132

As many chemicals with genotoxic potential are emitted to surface water, genotoxicity tests are gaining importance which led to the development of several techniques to detect directly DNA damage. The relevance of detecting the genotoxic risks associated with water pollution was firstly perceived in the late 1970s. Since that time several tests have been developed for evaluating DNA alterations in aquatic animals. These tests rely on the premise that any changes to DNA may have long-lasting and profound consequences. Sister chromatid test, chromosome aberrations, comet assay, and micronucleus test are currently the most widely employed methods to detect DNA lesions in ecotoxicology. Chromosomal aberration and sister chromatid exchanges are time consuming, resource intensive and require proliferating cell population. Hence, Comet assay and Micronucleus test as cost effective and more sensitive test systems have now been introduced for assessing the genotoxicity of chemicals. This review presents a synthesis of the state of the art in the methodologies of comet assay and micronucleus test and their contributions in aquatic environmental research. The text explores the latest knowledge and thinking on these very important approaches for the assessment of environmental health, management, and conservation. The primary concern of the present review is the measurement of genotoxic potential in aquatic organisms under field and laboratory conditions, where effects of chemicals at different levels of biological organization can be examined.

Capacity Utilisation and Unemployment in Selected West Africa Countries  [PDF]
Alaa M. Soliman
Theoretical Economics Letters (TEL) , 2017, DOI: 10.4236/tel.2017.76117
Abstract: The purpose of this research paper is to examine the proposition that capacity utilisation is an important factor in the determination of unemployment and wages. Underlying this proposition is the notion that capacity utilisation helps to determine the future path of the economy and is a significant factor in the response of the economy to different supply and demand shocks. We derived capacity utilisation and unemployment relationships, which were estimated and tested using data covering from 1997 to 2016 for three West Africa countries. The results suggest that long-term unemployment and capacity utilisation have a significant impact on unemployment. The policy implications of our findings are that in view of the strong effect of capacity utilisation on unemployment, programmes that enhance efficiency in production and investment enhancing policies may allow unemployed to regain access to the labour market.
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