Harold Martin

Real-Time Implementation of Multiagent-Based Game Theory Reverse Auction Model for Microgrid Market Operation

This paper presents a real-time implementation of a multiagent-based game theory reverse auction model for microgrid market operations featuring conventional and renewable distributed energy resources (DER). Studies were conducted on a grid connected microgrid consisting of a synchronous generator, two inverter-based generation units, and a combined load. The multiagent-based platform was applied to monitor, control, and perform the reverse auction process of DERs. A competitive game-theory reverse auction model was investigated to schedule the DER unit commitment with an hour-ahead market approach for the 24 h of the day. The proposed methodology was realistically implemented and operated at the Florida International University smart grid test system. The investigation shows that the proposed algorithm and the industrial hardware-based infrastructure can be implemented in the existing electric utility grid as new assets of the system are added.

An intelligent multi agent framework for active distribution networks based on IEC 61850 and FIPA standards

The development of a resilient and intelligent smart grid concept with decentralized control capability requires extensive deployment of interoperable frameworks. This paper presents a global multi agent framework using IEC 61850 and the foundation for intelligent physical agents (FIPA) standards. The developed framework was implemented on a laboratory based smart grid test bed at Florida International University. The open connectivity unified architecture (OPC UA) interface was adopted to share common information between two platforms. The hardware/software based Smart Grid Test Bed involves actual IEC 61850 intelligent electronic devices (IED) and a complete hardware based laboratory setup. In order to present the capabilities of the developed framework, an autonomous distributed energy resource (DER) ancillary service use case was realistically demonstrated as a sample study.

A novel approach of prosthetic arm control using computer vision, biosignals, and motion capture

Modern day prosthetics are traditionally controlled using EMG readings, which allow the user to control a limited number of degrees of freedom at one time. This creates a serious disadvantage compared to a biological arm because it constrains the fluid motion and dynamic functionality of the device. We present a novel architecture for controlling a transhumeral prosthetic device through the combination of several techniques, namely computer vision algorithms operating on “eye gaze” data, traditional prosthetic control methods, and the operators motion capture data. This sensor fusion allows the prosthetic device to locate itself in a 3D environment as well as the locations of objects of interest. Moreover, this architecture enables a more seamless motion and intuitive control of the prosthetic device. In this paper, we demonstrate the feasibility of this architecture and its implementation with a prototype.

Computerized neuropsychological assessment in mild cognitive impairment based on natural language processing-oriented feature extraction

Typically, neuropsychological testing helps medical experts situate a given patient in continuum of the Alzheimers disease (AD) spectrum, especially in the continuum between cognitively normal controls (CN) and the prodromal stage of mild cognitive impairment (MCI). As a well-known early symptom, some linguistic complexity changes of language have been associated with the progression of AD. Currently, the investigations of linguistic manifestations of MCI do mostly rely on manual analysis, yet linguistic complexity-based neuropsychological assessment cannot be effectively attained by using manual approaches. Taking advantage of the existing natural language processing (NLP) techniques to extract key features in linguistic complexity changes associated with the progression of MCI, this study develops an NLP-oriented computerized neuropsychological assessment to automatically analyze the distinguishing characteristics of data in the MCI group versus those in cognitively normal control (CN) group. By using the transcripts of news conferences from President Ronald Reagan, who was diagnosed with Alzheimers disease in 1994, and President Dwight D. Eisenhower (DE), and President George H. W. Bush (GB), who have no known diagnosis of AD, this study found the significantly different patterns of the linguistic complexity changes between CN and MCI subjects, which can be applied into the diagnosis of MCI.

PREDICTING COGNITIVE TEST SCORES IN ALZHEIMER’S PATIENTS USING MULTIMODAL LONGITUDINAL DATA

Alzheimer’s disease (ADAD).Methods:The search was performed on the Medline and Embase and Cochrane libraries on November 28, 2015. Critical outcomes were sensitivity and specificity and accuracy of FDG-PET in distinguishing asymptomatic ADAD from healthy controls, as assessed versus gold standard (Presenilin-1, Presenilin-2, Amyloid Precursor Protein mutation status). Minimum sample size was set a priori at 5 subjects with the target condition. Data were extracted and assessed with regard to publication bias, heterogeneity, index test (FDG-PET) imprecision, risk of bias, indirectness, and applicability. We provide assessment of the quality of evidence, of the target effect, and of strength of recommendation. Results:Out of the 13 papers obtained, only 2 papers reported the critical outcomes. These included 13 asymptomatic ADAD due to Presenilin-1 mutation and 30 non-carriers. Data provided a high level of evidence that the posterior cingulate cortex hypometabolism assessed semi-quantitatively could discriminate ADAD from controls with high sensitivity and specificity, although with large confidence intervals (Table). Strong concerns regarded the applicability of the index test, as semiquantitative methods of image analysis are increasingly but not yet routinely adopted in the clinical context, and a possible risks of bias in patients selection. Significant hypometabolism in the precuneus could be detected in mutation carriers 10 years before expected symptom onset and at the age of onset, but inconsistently across studies. Conclusions: The available data denote high quality of evidence for high diagnostic utility of semiquantitatively assessed FDG-PET in detecting early metabolic change in presymptomatic ADAD, carriers of mutation in PSEN1. However, the very low number of studies and subjects, the large confidence intervals of results, and the need of replication support only a weak recommendation for the use of FDG-PET to detect early neurodegeneration in asymptomatic subjects with familial forms of AD, and further research is warranted on this topic.

Real-time implementation of multiagent-based game theory reverse auction model for microgrid market operation

This paper presents a real-time implementation of multi-agent based game theory reverse auction model for microgrid market operation featuring conventional and renewable distributed energy resources (DER). Studies were conducted for a grid connected microgrid consisting of a synchronous generator, two inverter-based generation units and a combined load. The Multi-agent based platform was applied to monitoring, controlling and per-forming the reverse auction process of the DER. A competitive game-theory reverse auction model was investigated to schedule the DER unit commitment with hour-ahead market approach for the twenty-four hours of the day. The proposed methodology was realistically implemented and operated at Florida International University, Smart Grid Test system. The investigation shows that the proposed algorithm and the industrial based hardware structure can be implemented in existing electric utility grid as new assets of the system are added.

Uniform vs Full Height Maps Using a Time of Flight Device for Dewarping Book Spread Images in the Design of an Automated Book Reader

This study focuses on effects of uniform and full height map correction methods for dewarping book spread images in an automated book reader design for individuals with visual impairment and blindness. The design concept could also be applied to address the challenging process of book digitization. The method is dependent on the geometry of the book reader setup for acquiring the 3-D maps that yield a high reading accuracy. The experiments were performed on a testing dataset consisting of 142 pages with their corresponding depth maps that were extracted. The accuracy of the book spread images was quantified and measured by introducing the corrected images to an Optical Character Recognition engine. Initially, the book spreads were tested by placing them with a standard alignment which yielded an average accuracy of 95.55% and 96.11% with the uniform maps and the full height maps, respectively. Rotations of the book spreads are introduced in a separate test to see if the two proposed methods are tolerant to unsuspected misaligned placements of the book. These tests yield an average accuracy of 90.63% for the corrections with a uniform map and 94.75% with the full height maps.