Capacity-based cost modeling for light rail and bus rapid transit systems

Choosing between Light Rail Transit (LRT) and Bus Rapid Transit (BRT) systems is often controversial and not an easy task for transportation planners who are contemplating the upgrade of their public transportation services. These two transit systems provide comparable services for medium-sized cities from the suburban neighborhood to the Central Business District (CBD) and utilize similar right-of-way (ROW) categories. The research is aimed at developing a method to assist transportation planners and decision makers in determining the most feasible system between LRT and BRT. ^ Cost estimation is a major factor when evaluating a transit system. Typically, LRT is more expensive to build and implement than BRT, but has significantly lower Operating and Maintenance (OM) costs than BRT. This dissertation examines the factors impacting capacity and costs, and develops cost models, which are a capacity-based cost estimate for the LRT and BRT systems. Various ROW categories and alignment configurations of the systems are also considered in the developed cost models. Kikuchi's fleet size model (1985) and cost allocation method are used to develop the cost models to estimate the capacity and costs. ^ The comparison between LRT and BRT are complicated due to many possible transportation planning and operation scenarios. In the end, a user-friendly computer interface integrated with the established capacity-based cost models, the LRT and BRT Cost Estimator (LBCostor), was developed by using Microsoft Visual Basic language to facilitate the process and will guide the users throughout the comparison operations. The cost models and the LBCostor can be used to analyze transit volumes, alignments, ROW configurations, number of stops and stations, headway, size of vehicle, and traffic signal timing at the intersections. The planners can make the necessary changes and adjustments depending on their operating practices. ^

Sviluppo e test di un sistema BCI SSVEP-based

Una Brain Computer Interface (BCI) è un dispositivo che permette la misura e l’utilizzo di segnali cerebrali al fine di comandare software e/o periferiche di vario tipo, da semplici videogiochi a complesse protesi robotizzate. Tra i segnali attualmente più utilizzati vi sono i Potenziali Evocati Visivi Steady State (SSVEP), variazioni ritmiche di potenziale elettrico registrabili sulla corteccia visiva primaria con un elettroencefalogramma (EEG) non invasivo; essi sono evocabili attraverso una stimolazione luminosa periodica, e sono caratterizzati da una frequenza di oscillazione pari a quella di stimolazione. Avendo un rapporto segnale rumore (SNR) particolarmente favorevole ed una caratteristica facilmente studiabile, gli SSVEP sono alla base delle più veloci ed immediate BCI attualmente disponibili. All’utente vengono proposte una serie di scelte ciascuna associata ad una stimolazione visiva a diversa frequenza, fra le quali la selezionata si ripresenterà nelle caratteristiche del suo tracciato EEG estratto in tempo reale. L’obiettivo della tesi svolta è stato realizzare un sistema integrato, sviluppato in LabView che implementasse il paradigma BCI SSVEP-based appena descritto, consentendo di: 1. Configurare la generazione di due stimoli luminosi attraverso l’utilizzo di LED esterni; 2. Sincronizzare l’acquisizione del segnale EEG con tale stimolazione; 3. Estrarre features (attributi caratteristici di ciascuna classe) dal suddetto segnale ed utilizzarle per addestrare un classificatore SVM; 4. Utilizzare il classificatore per realizzare un’interfaccia BCI realtime con feedback per l’utente. Il sistema è stato progettato con alcune delle tecniche più avanzate per l’elaborazione spaziale e temporale del segnale ed il suo funzionamento è stato testato su 4 soggetti sani e comparato alle più moderne BCI SSVEP-based confrontabili rinvenute in letteratura.

Using electroencephalography signals to control acoustical processing

Current hearing-assistive technology performs poorly in noisy multi-talker conditions. The goal of this thesis was to establish the feasibility of using EEG to guide acoustic processing in such conditions. To attain this goal, this research developed a model via the constructive research method, relying on literature review. Several approaches have revealed improvements in the performance of hearing-assistive devices under multi-talker conditions, namely beamforming spatial filtering, model-based sparse coding shrinkage, and onset enhancement of the speech signal. Prior research has shown that electroencephalography (EEG) signals contain information that concerns whether the person is actively listening, what the listener is listening to, and where the attended sound source is. This thesis constructed a model for using EEG information to control beamforming, model-based sparse coding shrinkage, and onset enhancement of the speech signal. The purpose of this model is to propose a framework for using EEG signals to control sound processing to select a single talker in a noisy environment containing multiple talkers speaking simultaneously. On a theoretical level, the model showed that EEG can control acoustical processing. An analysis of the model identified a requirement for real-time processing and that the model inherits the computationally intensive properties of acoustical processing, although the model itself is low complexity placing a relatively small load on computational resources. A research priority is to develop a prototype that controls hearing-assistive devices with EEG. This thesis concludes highlighting challenges for future research.

Análise de sinais cerebrais utilizando árvores de decisão

Este trabalho propõe um estudo de sinais cerebrais aplicados em sistemas BCI (Brain-Computer Interface - Interfaces Cérebro Computador), através do uso de Árvores de Decisão e da análise dessas árvores com base nas Neurociências. Para realizar o tratamento dos dados são necessárias 5 fases: aquisição de dados, pré-processamento, extração de características, classificação e validação. Neste trabalho, todas as fases são contempladas. Contudo, enfatiza-se as fases de classificação e de validação. Na classificação utiliza-se a técnica de Inteligência Artificial denominada Árvores de Decisão. Essa técnica é reconhecida na literatura como uma das formas mais simples e bem sucedidas de algoritmos de aprendizagem. Já a fase de validação é realizada nos estudos baseados na Neurociência, que é um conjunto das disciplinas que estudam o sistema nervoso, sua estrutura, seu desenvolvimento, funcionamento, evolução, relação com o comportamento e a mente, e também suas alterações. Os resultados obtidos neste trabalho são promissores, mesmo sendo iniciais, visto que podem melhor explicar, com a utilização de uma forma automática, alguns processos cerebrais.

Adquisición y análisis de señales cerebrales utilizando el dispositivo MindWave

La actividad cerebral puede ser monitoreada mediante la electroencefalografía y utilizada como un indicador bioeléctrico. Este articulo muestra como un dispositivo de bajo costo y fácil acceso puede utilizarse para el desarrollo de aplicaciones basadas en interfaces cerebro-computador (BCI). Los resultados obtenidos muestran que el dispositivo MindWave puede efectivamente utilizarse para la adquisición de señales relacionadas a la actividad cerebral en diversas actividades cerebrales bajo la influencia de diversos estímulos. Se propone además el uso de la transformada Wavelet para el acondicionamiento de las señales EEG con el objetivo de utilizar algoritmos de inteligencia artificial y técnicas de reconocimiento de patrones para distinguir respuestas cerebrales.

Sviluppo di un sistema per gestire e partizionare segnali neurali

La Brain Computer Interface, con l’acronimo BCI, è un mezzo per la comunicazione tra cervello e macchina. La comunicazione si basa sulla emanazione di segnali elettrici del cervello che vengono rilevati da un dispositivo, il quale invia i segnali digitalizzati ad un elaboratore. I segnali elettrici, chiamati EEG, permettono al cervello di regolare la comunicazione tra le diverse cellule neurali. La BCI intercetta questi segnali e, previa elaborazione, permette di ottenere diversi diagrammi, detti metriche, per poter misurare, sotto svariati aspetti, il funzionamento del cervello. Le ricerche scientifiche sulle EEG hanno rilevato una correlazione tra i segnali elettrici nel cervello di un soggetto con il suo livello di performance e stato emotivo. È quindi possibile comprendere, tramite una serie di parametri, come la mente dei soggetti reagisce a stimoli esterni di svariata tipologia durante lo svolgimento di un’attività. L’elaboratore, che riceve il segnale dalla BCI, è il componente che si occupa di trasformare i segnali elettrici, generati dal cervello e digitalizzati, in risultati facilmente interpretabili dall’utente. Elaborare i segnali EEG in tempo reale porta a dover utilizzare algoritmi creati appositamente per questo scopo e specifici perle metriche preposte. Lo scopo di questa tesi è quello di presentare un progetto sullo sviluppo della fase di smistamento dei dati ricevuti dall’elaboratore. Nel contempo si fornirà una conoscenza scientifica minima per comprendere le scelte fatte. Tale progetto è stato reso possibile dalla collaborazione con l’azienda Vibre, che si dedica allo sviluppo di un sistema comprendente BCI ed elaboratore.

Analisi e utilizzo di tecniche di stimolazione epidurale per il ripristino dell’attività locomotoria in soggetti con lesioni spinali

La lesione del midollo spinale (LM) è una complessa condizione fisica che racchiude in sé sfide di carattere biomedico nonché etico-giuridico. La complessità della LM nonché la diversificazione delle esperienze dei singoli soggetti affetti da LM rendono questo un topic di grande interesse per la ricerca biomedicale, in relazione a nuovi metodi di cura e di riabilitazione dei soggetti. In particolare, la sinergia tra i saperi medico, informatici e ingegneristici ha permesso di sviluppare nuove tecnologie di comunicazione e di controllo neurologico e motorio che, capaci di sopperire a deficit cerebrali e/o motori causati da LM, consentono ai pazienti di avere una qualità di vita sensibilmente migliore, anche in termini di autonomia. Tra queste nuove tecnologie assistive primeggiano per efficacia e frequenza di utilizzo le Brain Computer Interfaces (BCI), strumenti ingegneristici che, attraverso la misurazione e l’analisi di segnali provenienti dall’attività cerebrale, traducono il segnale registrato in specifici comandi, rappresentando per l’utente con LM un canale di comunicazione con l’ambiente esterno, alternativo alle normali vie neurali. In questo elaborato l’analisi di due sperimentazioni, una su scimmia l’altra su uomo, entrambi affetti da LM, con differenti sistemi di monitoraggio dell’attività neurale, ha permesso di evidenziare un limite della ricerca sul topic: nonostante i promettenti risultati ottenuti su primati non umani, il carattere invasivo del sistema BCI–EES rende difficile traslare la sperimentazione su uomo. La sperimentazione su LM pone delle sfide anche dal punto di vista etico: sebbene siano auspicati lo sviluppo e l’applicazione di metodi alternativi alla sperimentazione animale, l’impiego di primati non umani appare ancora una scelta obbligata nel campo della ricerca di soluzioni terapeutiche finalizzate al ripristino della funzione locomotoria, per via della stretta affinità in termini di conformazione fisica, genetica e anatomica.

Trainable character recognition interface computer (INCOM) /

"UILU-ENG 78 1737."

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Title Model for Computer Networks Optimization

The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

Construction and Evaluation of an Opto-Coupled Potentiostat with a PC/PDA Interface

The design, construction, and characterization of a portable opto-coupled potentiostat are presented. The potentiostat is battery-powered, managed by a microcontroller, which implements cyclic voltammetry (CV) using suitable sensor electrodes. Its opto-coupling permits a wide range of current measurements, varying from mA to nA. Two software interfaces were developed to perform the CV measurement: a virtual instrument for a personal computer (PC) and a C-base interface for personal digital assistant (PDA). The potentiostat has been evaluated by detection of potassium ferrocyanide in KCl medium, both with macro and microelectrodes. There was good agreement between the instrumental results and those from commercial equipment.

XSophe-Sophe-XeprView (R). A computer simulation software suite (v. 1.1.3) for the analysis of continuous wave EPR spectra

The XSophe-Sophe-XeprView((R)) computer simulation software suite enables scientists to easily determine spin Hamiltonian parameters from isotropic, randomly oriented and single crystal continuous wave electron paramagnetic resonance (CW EPR) spectra from radicals and isolated paramagnetic metal ion centers or clusters found in metalloproteins, chemical systems and materials science. XSophe provides an X-windows graphical user interface to the Sophe programme and allows: creation of multiple input files, local and remote execution of Sophe, the display of sophelog (output from Sophe) and input parameters/files. Sophe is a sophisticated computer simulation software programme employing a number of innovative technologies including; the Sydney OPera HousE (SOPHE) partition and interpolation schemes, a field segmentation algorithm, the mosaic misorientation linewidth model, parallelization and spectral optimisation. In conjunction with the SOPHE partition scheme and the field segmentation algorithm, the SOPHE interpolation scheme and the mosaic misorientation linewidth model greatly increase the speed of simulations for most spin systems. Employing brute force matrix diagonalization in the simulation of an EPR spectrum from a high spin Cr(III) complex with the spin Hamiltonian parameters g(e) = 2.00, D = 0.10 cm(-1), E/D = 0.25, A(x) = 120.0, A(y) = 120.0, A(z) = 240.0 x 10(-4) cm(-1) requires a SOPHE grid size of N = 400 (to produce a good signal to noise ratio) and takes 229.47 s. In contrast the use of either the SOPHE interpolation scheme or the mosaic misorientation linewidth model requires a SOPHE grid size of only N = 18 and takes 44.08 and 0.79 s, respectively. Results from Sophe are transferred via the Common Object Request Broker Architecture (CORBA) to XSophe and subsequently to XeprView((R)) where the simulated CW EPR spectra (1D and 2D) can be compared to the experimental spectra. Energy level diagrams, transition roadmaps and transition surfaces aid the interpretation of complicated randomly oriented CW EPR spectra and can be viewed with a web browser and an OpenInventor scene graph viewer.

Using visual spatial search interface for WWW applications

Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented. (C) 2001 Published by Elsevier Science Ltd.

A laparoscopic surgery training interface

Laparoscopy is a surgical procedure on which operations in the abdomen are performed through small incisions using several specialized instruments. The laparoscopic surgery success greatly depends on surgeon skills and training. To achieve these technical high-standards, different apprenticeship methods have been developed, many based on in vivo training, an approach that involves high costs and complex setup procedures. This paper explores Virtual Reality (VR) simulation as an alternative for novice surgeons training. Even though several simulators are available on the market claiming successful training experiences, their use is extremely limited due to the economic costs involved. In this work, we present a low-cost laparoscopy simulator able to monitor and assist the trainee’s surgical movements. The developed prototype consists of a set of inexpensive sensors, namely an accelerometer, a gyroscope, a magnetometer and a flex sensor, attached to specific laparoscopic instruments. Our approach allows repeated assisted training of an exercise, without time constraints or additional costs, since no human artificial model is needed. A case study of our simulator applied to instrument manipulation practice (hand-eye coordination) is also presented.

A mobile systems interface protocol

Recent progresses in the software development world has assisted a change in hardware from heavy mainframes and desktop machines to unimaginable small devices leading to the prophetic "third computing paradigm", Ubiquitous Computing. Still, this novel unnoticeable devices lack in various capabilities, like computing power, storage capacity and human interface. Connectivity associated to this devices is also considered an handicap which comes generally associated expensive and limited protocols like GSM and UMTS. Considering this scenario as background, this paper presents a minimal communication protocol introducing better interfaces for limited devices. Special attention has been paid to the limitations of connectivity, storage capacity and scalability of the developed software applications. Illustrating this new protocol, a case-study is presented addressing car sensors communicating with a central