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In this work, the hardware and software used in developing a bivalve gape measurement system is explored. This system employs the Hall-effect phenomenon to accurately measure and report the gape of a bivalve. The system uses a Hall Effect sensor (Symmetry Electronics’ H2425) and a small magnet in which both are glued to the exterior of the shells of a bivalve. Consequently, the Hall Effect sensor reports the distance of the magnet, hence the gape opening, to a microcontroller that records and transmits the data to a ground station. This system has been designed to operate in the field as well as in a laboratory environment. In a laboratory setting, this system uses Wi-Fi or Bluetooth to transmit its data. In the field however, due to the lack of availability of power, two setups have been established. The first setup does not transmit data, instead, it saves the data in an SD card within the system’s enclosure. This setup is fully submersible. The battery, microcontroller and SD card reader are all submerged alongside the bivalve. This experiment shows that the system can work for as long as 29 days with a single battery charge. Therefore, each month the battery of this system will have to be replaced if data collection is to continue. The second field system is one that wields cellular network to communicate its data. This is a viable solution since most reefs exist close enough to the shore where cellular signal is available. Additionally, the system includes a solar collector panel for charging the battery during the day and constantly keeping the system transmitting at night. The laboratory system as well as the underwater field system are both fully operational and have been producing gape data for several months. The cellular system is currently being tested and data from all systems will be made available under the MBRACE project data repository.

This study describes a Multi-Agent Hardware In the Loop Simulator (HILS) for Unmanned Aerial Vehicles’ (UAV) autopilots. This HILS system allows multiple autopilots to fly multiple virtual airframes in the same virtual environment allowing these agents to interact as a swarm. This system makes the exploration and evaluation of Multi Agent Systems (MAS) possible at minimal cost.

African-American and Hispanic males are significantly underrepresented in STEM. While youth start narrowing their career choices in middle school, National Maker programs rarely specifically target minority males. Four Historically Black Colleges/Universities (HBCUs), in partnership with The Verizon Foundation, have established Maker communities in underserved urban and rural communities. The Minority Male Maker Program allows middle school students and their teachers to develop science, technology, engineering, and mathematics (STEM) skills while expressing their creativity. The long term goals of this project are to increase participant interest in STEM careers and college attendance. In the short term, we anticipate increased technology proficiency, STEM engagement and academic achievement. Additional outcomes include increased teacher and mentor understanding of STEM instruction delivery and mentorship. Panelists will discuss disparities facing men of color and a new National program designed to provide early exposure to STEM. Recommendations for developing programs targeting minority male students will be discussed.

In this research a HILS system in which a small autopilot can experience flight stimuli, such as pitch, roll, yaw, and GPS is investigated. These stimuli are controlled by a flight simulator hosting an airframe model that the autopilot in question fly s. Such a system allows the autopilot to fly the virtual model of the flight simulator while experiencing all flight stimuli as if it is in real flight.

Application Specific Integrated Circuits (ASICs) are most commonly designed on high end computer platforms, such as the SUN workstation. This paper describes a cost-effective method of designing ASICs on PCS. With the rapidly increasing power of the PC, and the ease of communication through the Internet, today it is possible to run some of popular VLSI CAD packages at a much lower cost. Today, at the University of Southern Mississippi the software package MAGIC has been used for that purpose on PC based stations. This paper starts with an overview of ASIC design on PC platforms and its impact on industry and academia. The software and hardware requirements and the techniques needed to acquire VLSI capabilities on a PC are examined. This is followed by a comparison of the available VLSI software in the market and its suitability for the class environment.

Searching for information in books or other printed forms could well be a thing of the past, as most information is readily available in electronic format in the Internet. Using a computer console, an Internet connection and the proper software a vast sea of information may be accessed with ease. The main requirements are but a computer and an Internet link. Teaching Internet access allows educators and students to remain on the cutting edge of technology. Using the Internet as a reference resource in teaching classes has the immediate advantage of allowing quick access to vast resources, also the Internet may be used as a communication tool. In both cases, as a resource or a communications tool, the Internet is superior to the conventional educational tools. However, using the Internet has some disadvantages, such as the limited control over plagiarism and the difficulty in verifying the reliability of information resources. When comparing the advantages and drawbacks of the Internet as an educational tool it is clear that its advantages by far outweigh its drawbacks.

Learning is a key element in the strive for machine intelligence. Unsupervised learning is even more important for robots or autonomous systems that operate in remote environment away from human interactions, such as the case in the fully automated factory floor. To achieve unsupervised learning, a variety of models and techniques have been employed by investigators. In this paper some of the models, especially in the area of Neural Networks are compared and contrasted. Special consideration will be given self organizing maps (Kohonen Networks) [1,6]. A comparison of the Kohonen Networks and their biological counterparts is given. The introduction of these systems to increase the intelligence, and hence the autonomy of systems, is considered.

A modified double rhombus antenna is designed to detect cell phones for post disaster search and rescue operations. The antenna consists of two rhombus shape dipoles with different size fed by microstrip line with a truncated ground plane which acts as reflector to produce end fire radiation. It was found that the directivity of the antenna depends mainly on the length and width of the dielectric substrate. Different configurations have been studied to obtain high directivity.

In automatic robot program synthesis the number of variables that should be taken into consideration become prohibitively numerous. Due to the ambiguity and sheer size of items to be considered conventional computation methods cannot satisfactorily solve the problem. A Neural Network model that acquires data from a Solid Modeling data base, combines the completeness of information provided by solid modeling with the uncertainty encountered in the grouping process to perform geometrical classification of objects. The capabilities of Neural Networks to learn non-geometrical patterns in the grasping process, are yet to be achieved. Much progress needs to be made in both the neural model complexity and the computing machinery power before real intelligent program synthesis can be achieved.

A CMOS digital microcircuit, utilizing sub-micron technology, was designed for the purpose of providing integrated control circuitry to an array of high-voltage micro-electromechanical systems (MEMS) switch based phase shifter devices. The grid of MEMS phase shifters is part of a phased array antenna system. The phase of each element of the array is controlled via the CMOS microcircuit. This paper presents the design, physical layout, and the measured test results for CMOS digital control circuit that has been fabricated using the MOSIS Integrated Circuit Fabrication Service. The circuit converts serial data to parallel outputs to reduce number of control lines and lower the cost of wiring the phased array. In addition, discrete digital control circuitry for loading phase shifts into each MEMS device is presented.

The purpose of this research is to develop natural movement algorithms that are more computationally efficient than those presently being used. This paper provides a new mathematical algorithm for solving the inverse kinematic problems needed to simulate the limb movements of a 3-D virtual human figure. This is accomplished by first decoupling the system of equations, then performing singular value decomposition (SVD) on the resulting matrix of constants coefficients.

Field Programmable Gate Arrays are generic devices that contain a vast number of basic digital components. The interconnections between these components are defined by the user. By specifying these interconnections different digital circuits may be realized. FPGAS are reprogrammable devices, making the change from one digital circuit to another as simple as downloading a new interconnection file. Furthermore the definition of the interconnection file may be carried out at high level machine languages, making the design and debugging of complex digital circuits rather simple. This publication discusses the use of FPGA as an alternate solution to ASICs. A review of the FPGA technology and its impact on the use of ASICs is carried out. This is followed by a projection of the impact of FPGA on digital technology. Finally methods on introducing FPGA technology to in the classroom and its impact on the quality of future engineers in considered. A case study of the FPGA impact on the Computer Engineering Technology Department of the University of Southern Mississippi will be considered.

This paper starts with an overview of a classical PID controller design. An account of how Neural Networks may be incorporated to provide control is such a setup. The example used in this paper is the problem of controlling a High Frequency Acoustics Platform (HFAP) in-flight. The HFAP is towed by a ship and flown in the water behind the ship to acquire acoustic data reflected from the sea floor. The stability of such a platform is of prime importance to the accuracy of data collected. Using fight data from previous runs of the platform, a Neural Network is trained. The trained network is then used to predict the behavior of the platform. These predictions may then be directly translated to control signals minimizing the platform's spatial deviations. In this paper results form the trained Neural Network on predicting the behavior of the platform are displayed. Network prediction results illustrating the ability of the network to operate with partial input are displayed. Displaying these results in contrast with conventional controller results given the same input parameters emphasizes the importance of such a feature. Finally the use of different network architectures and the cost of using these network, in terms of computing power is investigated.

This paper addresses the impact of neural networks on autonomous systems. Some neural network models are used to illustrate the effectiveness and suitability of these networks for space exploration. Fault tolerance and self learning capabilities of neural networks are used to illustrate such suitability. The advantages and disadvantages of the utilization of neural networks in autonomous systems are discussed and contrasted with the conventional systems currently in use.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

In this paper we show that learning schemes can be utilized to generate robot grasping points. These learning schemes can be based on the geometrical similarity of objects and the functional similarity of tasks. This approach will drastically increase the speed of the search process and enrich the system's knowledge base. A Neural Network model that acquires data from a sold modeling data base is suggested. This model combines the completeness of information provided by solid modeling with the uncertainty encountered in the grouping process to perform geometrical classification of objects.