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In BCI (Brain Computer Interface) domain it is challenging task to correctly classify emotions electroencephalogram (EEG) which will enable many opportunities in health care. For achieving this task, it is important to select good features and train model well. We have experimented on EEG (electroencephalogram) signals which are emotions-based data set to determine choice of patient. For this purpose, different papers have been studied and emotions data set has been selected from KAGGLE. To achieve this task RNN (Recurrent Neural Network) has been applied. We have achieved accuracy of 98.5 % which outperformed previous accuracy of 97.79% [10]. We have applied features selection through Mutual Information Regression, data training (Recurrent Neural Network) and improved accuracy. [ABSTRACT FROM AUTHOR]

Emotions play a major role in the lifestyle of every human being living in this world. As the emotions keep changing from time to time, it also affects the external environment. Recently, many research works are focused towards emotion recognition using the brain signals. Brain Computer Interface is a rapidly growing technology as it involves in providing a communication from brain to computer. To acquire the brain several ways are used by the researchers but the most preferable method is Electroencephalogram (EEG). EEG is widely used as it has many advantages than other techniques. For better understanding of the area, we present a survey of research works during the year 2016 to 2020 in.this paper and thereby we provide an overview of the available research works in emotion recognition in the field of Brain Computer Interface (BCI). This paper primarily focuses on the testing method and the type of algorithm used for classification of emotions. An analysis has been executed based on the performance metrics like accuracy, number of emotions classified choice of method and several other factors contributing for emotion recognition. [ABSTRACT FROM AUTHOR]

Motor Imagery- Brain Computer Interface (MI-BCI) is known to be a recent blooming technique since it acts as non- muscular channel that helps for disabled people for communication. A exact and trustable MI-BCI system needs the extraction of enlightening and accurate features because it is a communication link among the wired brain and an external device. A brain computer interface, or BCI, plays a crucial role in human beings, particularly disabled persons. BCI is one in which various brain functions are analyzed or controlled with the help of computers (controllers). Along with-it EEG signals could be utilized to study the brain activity and also to diagnosis of diseases like neurological disorder, Parkinson's disease. EEG signals can be processed and the features can be extracted for the dimensionality reduction with the help of various techniques which includes PCA, Fast Fourier Transformation, Wavelet Transformation. These extracted features can be classified using classifiers such as SVM, K – Nearest neighbors, Neural network and few other methods. Now a days, the role of deep learning (DL) technique has had aowing impact on Motor imaginary-EEG-based Brain Computer Interface and data set has a vital role in all applications. Here in this paper, we have reviewed the recent papers that applied Physio net dataset to analyze and evaluate electroencephalogram (EEG) signals for various applications which contains 64 EEG channels and 109 subjects executing diverse tasks. [ABSTRACT FROM AUTHOR]

After we did our research work in creating a model that suggested the possible yoga a person could do by taking in consideration of their physical parameters like BPM, sleep etc. and with any physical problem they had so that we could recommend yoga that doesn't aggravate the problem if not alleviate the issue and help them with their stress. After we analyzed the data collected from our users, we saw that even if the same set yoga was done by two individuals the improvements were varying depending upon how accurate they are performing the pose. Therefore, in this paper we created a Machine Learning model that tells a user if it is performing the pose correctly and then studied their Brain waves using NeuroSky Mind Wave with a pre and post yoga session. By providing the users if they are performing the yoga correctly, we saw improvement in their brain waves and their mental wellbeing in a few days of performing yoga. [ABSTRACT FROM AUTHOR]

The goal to converting brain activity into instructions for control and communication, predicting human mental intent has arisen as a prominent focus of research in Brain-Computer Interface research. These research entail gathering electroencephalographic data from participants in order to build classifiers that can decode users' mental states. However, training classifiers in BCI systems is difficult due to many source among the inter-subject or intra-subject variability in brain signals. This model training typically follows a common technique in terms of machine learning: i) feature extraction, needs effort and may also need domain expertise, ii) train a classifier using the retrieved features. Not only are very accurate classifiers now achievable thanks to deep learning algorithms, additionally incorporate the feature extraction stage into the process of creating classifiers. However deep learning models have the benefit of incorporating domain-dependent feature extraction during classifier construction, architectural selection procedure for BCIs is often dependent on domain knowledge. In this paper, we look at whether it's possible to build reliable classifier for deciphering P300 event-related potentials utilising a systematic deep learning model selection. The findings of Gated Recurrent Unit (GRU), long short-term memory cells (LSTMs) and convolutional neural networks (CNN) and of varied complexity are presented. Our empirical findings demonstrate which is the best model for categorization of P300 waveforms. [ABSTRACT FROM AUTHOR]

The paper proposes an easier mechanism of computer control for physically challenged people with spinal cord injury having restrained neck movements. They do not have appropriate input devices for performing essential activities in a computer. So, there is a great demand for electronic assistive devices. Our proposed method tracks the movement of the cursor using the head movements by analyzing well efficient datasets. Initially facial landmarks are located, specifically the eyes, nose and mouth. A convex hull is represented over their facial landmarks. Then image processing is done using the open CV. The cursor can be moved to the required coordinates using facial recognition and the mouse click can be achieved by blinking of the eyes. Also, it does not respond for the reflex actions produced by the neck. This acts as an assistive system to the user, so as he/she can operate the computer independently and access anything they want. It has ease in controlling and shows a user-friendly behavior. [ABSTRACT FROM AUTHOR]

Communication through Technology and Technology via Communication is an interdisciplinary study. Language and Communication Technologies (LCT) has become a synonym to human language technology. This scientific learning can infiltrate language communication into technical stream, the way we are using in our day to day communication by using computers and smart phones. This led to the evolution of the technical language which became an interdisciplinary field embracing the fields of computer sciences and cognitive sciences. The assumption is that concept of language in communication technologies research has been a recurring process, with current research redeploying on language data as evidence of human enabled computer interface and interaction effects. This paper further discusses the importance of language variables and non verbal communication elements in the study of communication through technology. The article also analyses how technology and language are used besides to inform the pedagogue of technologies as well as how communication mediated multimedia has changed the face of language. [ABSTRACT FROM AUTHOR]

The increasing number of air pollution in various big cities in Indonesia currently increases concern. The facts show that air pollutants such as Particulate Matter and 5 elements such as HC, CO, CO2, O2 and NOx exceeded the ambient air quality standard threshold. In countries that have strict vehicle exhaust emission standards, those 5 elements must be measured, but Indonesia only measured 4 elements of the exhaust gas, without NOx. Most of the existing smoke detector tools are very inefficient to be used because of their large shape. Therefore, an exhaust emission detector test instrument was made on vehicles, in order to determine the level of emission threshold value. This study used a circuit consisting of a microcontroller block, input/output block, programmer block and Sensor block. In the microcontroller block, there are three important parts, including the oscillator circuit, the reset circuit, and the voltage circuit. In this paper, the tool was designed to read the value of exhaust emissions on the vehicle and make a comparison with that in Poltrada Bali workshop emission test equipment. Results showed that this design tool detected in real time and could show the air quality from the detection results. The measurement of exhaust emissions can be done in a short time and obtain definite results. The gas sensor can be calibrated by providing the desired value through a serial programming interface to the computer. [ABSTRACT FROM AUTHOR]

Kaira (http://verif.cs.vsb.cz/kaira/) is a high-level development environment for MPI applications. It allows to prototype, observe, debug, and analyze MPI (Message Passing Interface) applications. Kaira supported only point-to-point communication up to the last version. The current version provides an interface for MPI collective communication; communication that involves a group of processes and allows a very efficient implementation of common operations like scatter, gather, and broadcast. To achieve an efficient implementation, these operations have low-level semantics from a user perspective. This paper discusses problems that need to be solved to implement this communication into an abstract environment and describes syntax and semantics of collective transitions that introduces collective communication into Kaira. [ABSTRACT FROM AUTHOR]

In our society more people are suffering from paralytic diseases that cause them several disabilities like they are unable to talk, move and tell their day to day needs, they could, in any case, utilize their eyes and here and there tilt their body and head. The project has been working by the rule of BCI – Brain Computer Interface. This project controls the wheelchair to move to their desired places and other implemented applications with the help of the eyeblink to drive wheelchair by themselves. The wheelchair starts moving when program has been running, then eyeblink chooses the direction. The Brain computer interface-(BCI) has another correspondence channel with the human cerebrum, an advanced PC. The aggressive objective of a BCI is at long last the rebuilding of developments, correspondence, and ecological control for disabled individuals. An electroencephalogram (EEG) based cerebrum PC point of interaction was associated with a Virtual Reality framework to control a savvy home application. It offers an option in contrast to regular correspondence and control. The feigned work avoids body's normal productive ways, named as neuromuscular result sides. Different Brain depicts different results of brain visuals. This result gives wavelengths given with numerous amplitude and frequency. This brain connection will be done with the help of numerous neurons. Every connection with neuron will make just one minute electric delivery. These works manage the signs from the mind. Different moods will be few consequences of numerous results for brain connections. This result gives wavelengths depicted with different types of frequency and amplitude. This transmission was created with the help of cerebrum sensor which is isolated as bundles. Parcel details are communicated in a medium called remote-blue tooth. The wave which will be estimated gives the wave details. This changes it to the sign using the MATLAB-GUI platform. Then directions would be shipped off house segment to make the fan and bulb work. Our work is done by man mind presumption and the muscle squinting helps with the ON and OFF. [ABSTRACT FROM AUTHOR]

Embedding a new programming language into an existing one is a widely used technique, because it fastens the development process and gives a part of a language infrastructure for free (e.g. lexical, syntactical analyzers). In this paper we are presenting a new advantage of this development approach regarding to adding testing support for these new languages. Tool support for testing is a crucial point for a newly designed programming language. It could be done in the hard way by creating a testing tool from scratch, or we could try to reuse existing testing tools by extending them with an interface to our new language. The second approach requires less work, and also it fits very well for the embedded approach. The problem is that the creation of such interfaces is not straightforward at all, because the existing testing tools were mostly not designed to be extendable and to be able to deal with new languages. This paper presents an extendable and modular model of a testing framework, in which the most basic design decision was to keep the - previously mentioned - interface creation simple and straightforward. Other important aspects of our model are the test data generation, the oracle problem and the customizability of the whole testing phase. [ABSTRACT FROM AUTHOR]

CLIR techniques searches unrestricted texts and typically extract term and relationships from bilingual electronic dictionaries or bilingual text collections and use them to translate query and/or document representations into a compatible set of representations with a common feature set. In this paper, we focus on dictionary-based approach by using a bilingual data dictionary with a combination to statistics-based methods to avoid the problem of ambiguity also the development of human computer interface aspects of NLP (Natural Language processing) is the approach of this paper. The intelligent web search with regional language like Bengali is depending upon two major aspect that is CLIA (Cross language information access) and NLP. In our previous work with IIT, KGP we already developed content based CLIA where content based searching in trained on Bengali Corpora with the help of Bengali data dictionary. Here we want to introduce intelligent search because to recognize the sense of meaning of a sentence and it has a better real life approach towards human computer interactions. [ABSTRACT FROM AUTHOR]

Locked-in syndrome (LIS) has to be aware of, even though it is rare in the world. However, this disease has been reported to have ten years survival rates as high as 80 %. The physical appearance of the syndrome is a total paralysis but with preservation of consciousness. Consciousness indicates that the patient's brain is still able to work quite well. Brain Computer Interfaces (BCI) is a technology that allow users to directly have control on computers or external devices by focusing on which action the users want to do through their brainwaves, which are recorded by the means of electroencephalograph. In this paper, we combine a feature of SDK community edition from a commercial BCI device called Emotiv EPOC+, which is the most credible and cost-effective mobile EEG headset on the market, with UNITY3D, the world’s leading content-creation engine, to build a beautiful and engaging content in Visual Request System to enable communication between patients with LIS and the people around them. In Visual Request System, there are 2 categories of requests, which are internal request system and external request system. Both requests depend on where the request came from. We tested the system and EPOC Control Panel on 10 volunteers to get the success rate data, and we make questionnaire for comparing user-friendly interface between a Visual Request System and Cognitiv Suite in the EPOC Control Panel software from Emotiv and we also ask them about the comfort when using Emotiv EPOC+. Then, we record every calibration data of Cognitiv suite EPOC Control Panel in Xavier TestBench 3.1.18, after that we analyze what happen in calibration data using Power Spectral Density with time window in 10 seconds duration. The results of our research conclude that the Visual Request System built on UNITY3D and Emotiv EPOC+ can be used as a communication system to help LIS patients by making some improvements and the Visual Request System is more user-friendly than EPOC Control Panel to show communication message. Power Spectral Density with time window in 10 second duration analysis indicates that the signal received by the Emotiv only based on an 8 seconds calibration is intersected to one another signal. Therefore, increasing the number of mental states that must be detected by the system will make the system more difficult to distinguish each mental state signal. [ABSTRACT FROM AUTHOR]

This paper presents some proposals of architecture and interfaces among the different types of processing units of MIRAX on-board computing subsystem. MIRAX satellite payload is composed of dedicated computers, two Hard X-Ray cameras and one Soft X-Ray camera (WFC flight spare unit from BeppoSAX satellite). The architectures for the On-Board Computing Subsystem will take into account hardware or software solution of the event preprocessing for CdZnTe detectors. Hardware and software interfaces approaches will be shown and also requirements of on-board memory storage and telemetry will be addressed. © 2006 American Institute of Physics [ABSTRACT FROM AUTHOR]

Nowadays Multi-core CPUs have become a trend in personal computers, smart phones and tablet market. Due to high performance of these architectures developers like Google Play Store and Apple App Store have been able to adopt more attractive interfaces and powerful applications. Complexity and size of these applications is getting bigger and multitasking is always used in nowadays computing. But these huge development in software and hardware needs to have good user feedback. To improve the user experience needed to push into the limits of multi-core systems. In this paper will be described how to improve the real time performance by reducing the user wait time, power consumption, memory usage of multi-core systems that use different run queue for different core scheduling technique over private cloud. Traditional way it is not take in the consideration in order to equal the balancing cores but to minimize the cost in time, memory and power consumption of task migrations. This will be possible by creating a importance level of performing task migrations to balance core usage and designing a algorithm to share the tasks into different core queues to create a balanced core usage. This new technique will improve the real time characteristics such as waiting time, cache efficiency and power consumption. [ABSTRACT FROM AUTHOR]

Conventional Supervisory control and data Acquisition (SCADA) systems use PC, notebook, thin client, and PDA as a Client. Nowadays the Process Industries are following multi shift system that's why multi- client of different category have to work at a single human Machine Interface (HMI). They may hack the HMI Display and change setting of the other client. This paper introduces a Hacker tracking security (HTS) System for HMI. This is developed by using the conventional and Biometric authentication. HTS system is developed by using Numeric passwords, Smart card, biometric, blood flow and Finger temperature. This work is also able to identify the hackers. [ABSTRACT FROM AUTHOR]

Typically a system consists of hardware as the controller and software which is installed in the personal computer (PC). In the effective nuclear detection, the hardware involves the detection setup and the electronics used, with the software consisting of analysis tools and graphical display on PC. A data acquisition interface is necessary to enable the communication between the controller hardware and PC. Nowadays, Universal Serial Bus (USB) has become a standard connection method for computer peripherals and has replaced many varieties of serial and parallel ports. However the implementation of USB is complex. This paper describes the implementation of data acquisition interface between a field-programmable gate array (FPGA) board and a PC by exploiting the USB link of the FPGA board. The USB link is based on an FTDI chip which allows direct access of input and output to the Joint Test Action Group (JTAG) signals from a USB host and a complex programmable logic device (CPLD) with a 24 MHz clock input to the USB link. The implementation and results of using the USB link of FPGA board as the data interfacing are discussed. [ABSTRACT FROM AUTHOR]

A Brain-Computer Interface (BCI) is a hardware/software based system that translates the Electroencephalogram (EEG) signals produced by the brain activity to control computers and other external devices. In this paper, we will present a non-invasive BCI system that reads the EEG signals from a trained brain activity using a neuro-signal acquisition headset and translates it into computer readable form; to control the motion of a robot. The robot performs the actions that are instructed to it in real time. We have used the cognitive states like Push, Pull to control the motion of the robot. The sensitivity and specificity of the system is above 90 percent. Subjective results show a mixed trend of the difficulty level of the training activities. The quantitative EEG data analysis complements the subjective results. This technology may become very useful for the rehabilitation of disabled and elderly people. [ABSTRACT FROM AUTHOR]

This paper presents a work in developing a mathematical model for the optimization of transports. The decisions to be made are routing decisions, truck assignment and the determination of the pickup order for a set of loads and available trucks. The model presented takes these aspects into account simultaneously. The MILP model is implemented in the Microsoft Excel environment, utilizing the LP-solve freeware as the optimization engine and Visual Basic for Applications as the modeling interface. [ABSTRACT FROM AUTHOR]

A new format for the unified data exchange between ionosonde data producers and users of ionogram-derived characteristics is introduced, dubbed SAOXML 5 to reflect its heritage in the previous Standard Archiving Output (SAO) format version 4 and a general-purpose computer language XML commonly used for data exchange. The SAOXML 5 specification shall serve as the reference for development of input and output interfaces for the software projects that read and write ionogram-derived data. The paper discusses motivation for introducing new format and outlines basic principles of its design and use. [ABSTRACT FROM AUTHOR]

A mobile version of the software package Dynamic Dislocation of Crystallographic Slip (MDDCS) designed for modeling the expansion dynamics of dislocation loops and formation of a crystallographic slip zone in FCC-metals is examined. The paper describes the possibilities for using MDDCS, the application interface, and the database scheme. The software has a simple and intuitive interface and does not require special training. The user can set the initial parameters of the experiment, carry out computational experiments, export parameters and results of the experiment into separate text files, and display the experiment results on the device screen. [ABSTRACT FROM AUTHOR]

The permutation generation method is based on starter sets generation under exchange operation and exploited it for listing down all n! Permutations. However permutation generation is time consuming process, the implementation of sequential algorithm to parallel computation is the option for reducing the computation time. The sequential algorithm is implemented to a parallel algorithm by integrating with Message Passing Interface (MPI) libraries by parallelizing the starter sets generation task. The speedup and efficiency is the indicator tool for analyzing performance of this parallel algorithm. The results show reduction time computation of parallel algorithm among processors. [ABSTRACT FROM AUTHOR]

Network thieves may spoof IP packets by changing headers of the IP packets to mislead people to understand that the devices are beginning from a trusted source.Hence, various defence mechanisms have been developed to detect and prevent IP spoofing attacks.However, most of them were implemented in the host or router phases using many shared resources on the networks while the attack was in progress. Most of the frauds occurred in the online with distributed denial of service (DDoS) attackers. By implementing the technique of IP spoofing the method of attackers to avoid exposure as well as place a heavy burden for target community to control attack packets. This papersuggested an Enhanced Inter-Domain Packet Filter (E-IDPF) design can be reduce IP Spoofing on a network. The proposed model does not require global routing data. The proposed model uses Design Science Research Methodology (DSRM). DSRM is suitable for developing artefacts consisting of algorithms or human/computer interfaces. There are five steps in DSRM, issue awareness, suggestion, development, evaluation and conclusion, which must followed at some point in designing, enforcing and testing. The enhanced proposed model also supports for the Packet filtering techniques and it is implemented on network border routers. The conditions are set where E-IDPF ignores phishing packets and allows pushing applications with legitimate source addresses. The comprehensive simulation studies confirm even with partial network distribution the proposed model can restrict phishing attackers' functionality. Also, they can help manipulate the method of attacking the packets in accordance with small scale of candidate networks. [ABSTRACT FROM AUTHOR]

In recent years through advances in computing methods and hardware it has become easier to solve machine learning and signal processing problems than previous decades. This generated extensive interest in EEG-based Brain Computer Interfaces (EEG-BCI) that could possibly be applied to various assistive technologies that can gain from the hand-free and individual thought translation aspect of this field. Having saud that, most of the research has been at the proof-of-concept stage, rather than at a more practical one. Consequently, there have been few advances in technologies that allow individuals with severely impaired motor systems (humans with Multiple Schlerosis, Amyotrophic Lateral Schlerosis, etc.) to navigate spatially in a simulated 2D or 3D environment. With newer technologies and growing trends of automation and application of artificial intelligence we face newer challenges to bring those newer technologies to the ever-growing diverse population. However, no one has recently investigated the general trends in various aspects of interface design BCI for web applications. In this study, we examined advances in EEG-BCI research over the last decade with the aim of investigating the latest trends in EEG-based web interface design application. In this article, we investigated the number of published BCI publications for each like control mechanism. [ABSTRACT FROM AUTHOR]

This paper summarizes the workings of a hand held numerical prototype device that incorporates resistive sensor arrays for breath analysis diagnostics. The sensor array detects and measures three distinct biomarkers in exhaled human breath. The device has an advance peripheral interface controller with internal ADCs and LCD driver. The LCD used is a 16×2 display that shows the readings for all the three sensors. The device may be used as a simple health monitoring system. [ABSTRACT FROM AUTHOR]

Electroencephalogram is one the common method to acquire EEG data for any purposes like Brain Computer Interfaces. Many people are suffering from disabilities like locked in syndrome or Amyotrophic Lateral Sclerosis and which impair normal communication. Here provide a control scheme method for brain computer interfaces using vowel speech imaginary. Three healthy subjects were selected and EEG were recorded during the performance of three tasks, imaginary speech of the English vowels /a/, /u/ and no action state as control. To enhance the classification performance, wavelet transform were used and Linear Discriminant Analysis (LDA), Support Vector Machine (SVM) and k-Nearest Neighbor (KNN) were used as classifier. Features namely mean, standard deviation, band power, entropy and skewness are extracted from each EEG data. The performance of classifier was evaluated by measuring sensitivity, specificity and accuracy. The overall accuracies ranged from (72-80) %. Results indicate significant potential for the use of vowel speech imagery as a speech prosthesis controller. [ABSTRACT FROM AUTHOR]

Stroke diminishes someone’s quality of life since post-stroke symptoms can make some limbs do not function normally -in most cases, feet-thus the stroke patients’ mobility will be limited. However, the brain wave of stroke patients was observed as normal, thus in this study, the normal brainwaves were utilized to rehabilitate post-stroke patient and were expected to help their mobility through wheelchairs with brain waves control so that post-stroke patients can improve their quality of life. Brain Computer Interfaces (BCI) is a technology that allows taking action on a computer based on brain waves. Brain waves are recorded by electroencephalography so they can be processed by a computer. There have been many studies using BCI including analyzing brain waves in humans, many things that can be utilized using BCI make a lot of researchers use them to make smart wheelchairs that use brain control. and developments continue to be made to create the most optimal system. In this project we use one of the topics that is still being developed, that is Motor Imagery, where we record and analyze the brain waves while imagining motor activities such as moving hands, walking, running and so on. This record will serve as data reference to trigger the process on the computer to move the actuator. The purpose of this project is to control the wheelchair based on motor movements obtained by BCI using the Neurosky Mindwave Mobile 2 headset. This headset has one electrode where the signals from one electrode are analyzed by concentration and meditation values from the case of imagery motors, which in this project are more portable than using conventional EEG data acquisition devices that are not portable and use many channels. This headset is able to record data wirelessly via Bluetooth to a PC (Personal Computer), so the obtained signal can be processed and classified into five movement classes using the Matlab GUI, where the classes are default/motionless, move forward, move backward, turn right and turn left. The method used for the wheelchair was replacement of the default joystick in the electric wheelchair with an self-made controller module which was based on brain waves signals obtained from the headset will be processed and classified by Matlab GUI and then forwarded to Arduino Uno to control the motor in the wheelchair. The average success rates of the five classes from five trials were: the first class with a success rate of 82.22 %, the second class with a success rate of 70 %, the third class with a success rate of 73.33 %, the fourth class with a success rate of 46.67 % and the fifth class with a success rate of 17.78 %. The results of this study indicate that Neurosky Mindwave mobile 2 headset can be a possible choice for this project. [ABSTRACT FROM AUTHOR]

The Atomic and Molecular Data Unit at the IAEA works with a network of national data centres to encourage and coordinate production and dissemination of fundamental data for atomic, molecular and plasma-material interaction (A+M/PMI) processes that are relevant to the realization of fusion energy. The Unit maintains numerical and bibliographical databases and has started a Wiki-style knowledge base. The Unit also contributes to A+M database interface standards and provides a search engine that offers a common interface to multiple numerical A+M/PMI databases. Coordinated Research Projects (CRPs) bring together fusion energy researchers and atomic, molecular and surface physicists for joint work towards the development of new data and new methods. The databases and current CRPs on A+M/PMI processes are briefly described here. [ABSTRACT FROM AUTHOR]

A Brain Computer Interface (BCI) system processes and translates neuronal signals, that mainly comes from EEG instruments, into commands for controlling electronic devices. This system can allow people with motor disabilities to control external devices through the real-time modulation of their brain waves. In this context an EEG-based BCI system that allows creative luminous artistic representations is here presented. The system that has been designed and realized in our laboratory interfaces the BCI2000 platform performing real-time analysis of EEG signals with a couple of moving luminescent twin robots. Experiments are also presented. [ABSTRACT FROM AUTHOR]

The World Wide Web rapidly guides the world into a newly amazing electronic world, where everyone can publish anything in electronic form and extract almost all the information. Extraction of information from semi structured or unstructured documents, such as web pages, is a useful yet complex task. Data extraction, which is important for many applications, extracts the records from the HTML files automatically. Ontologies can achieve a high degree of accuracy in data extraction. We analyze method for data extraction OBDE (Ontology-Based Data Extraction), which automatically extracts the query result records from the web with the help of agents. OBDE first constructs an ontology for a domain according to information matching between the query interfaces and query result pages from different web sites within the same domain. Then, the constructed domain ontology is used during data extraction to identify the query result section in a query result page and to align and label the data values in the extracted records. The ontology-assisted data extraction method is fully automatic and overcomes many of the deficiencies of current automatic data extraction methods. [ABSTRACT FROM AUTHOR]

Mobile computing environments are characterized by heterogeneity-systems consisting of different device types, operating systems, network interfaces, and communication protocols. Such heterogeneity calls for middleware that can adapt to different execution contexts, hide heterogeneity from applications, and transparently and dynamically switch between network and sensor technologies. Additionally, middleware for context-aware systems must keep a context model (a model of their environment), taking into account several aspects of the environment. The more complex and heterogeneous an execution environment is, the more complicated its underlying context model. Moreover, because systems can evolve, context management must also support model evolution without restarting, reconfiguring, or redeploying applications and services. We describe a context management middleware that can efficiently handle context despite the execution environment's heterogeneity and evolution. It uses context meta-information to improve a context-aware system's overall performance. [ABSTRACT FROM AUTHOR]

The Freescale automatic fault detection and classification (FDC) system has logged data from over 3.5 million implants in the past two years. The Freescale FDC system is a low cost system which collects summary implant statistics at the conclusion of each implant run. The data is collected by either downloading implant data log files from the implant tool workstation, or by exporting summary implant statistics through the tool’s automation interface. Compared to the traditional FDC systems which gather trace data from sensors on the tool as the implant proceeds, the Freescale FDC system cannot prevent scrap when a fault initially occurs, since the data is collected after the implant concludes. However, the system can prevent catastrophic scrap events due to faults which are not detected for days or weeks, leading to the loss of hundreds or thousands of wafers. At the Freescale ATMC facility, the practical applications of the FD system fall into two categories: PM trigger rules which monitor tool signals such as ion gauges and charge control signals, and scrap prevention rules which are designed to detect specific failure modes that have been correlated to yield loss and scrap. PM trigger rules are designed to detect shifts in tool signals which indicate normal aging of tool systems. For example, charging parameters gradually shift as flood gun assemblies age, and when charge control rules start to fail a flood gun PM is performed. Scrap prevention rules are deployed to detect events such as particle bursts and excessive beam noise, events which have been correlated to yield loss. The FDC system does have tool log-down capability, and scrap prevention rules often use this capability to automatically log the tool into a maintenance state while simultaneously paging the sustaining technician for data review and disposition of the affected product. © 2006 American Institute of Physics [ABSTRACT FROM AUTHOR]

In this work is presented the development of a mechatronics device to simulate the interaction of the surgeon with the surgical instrument (resectoscope) used during a Transurethral Resection of the Prostate (TURP). Our mechatronics interface is part of a computer assisted system for training in TURP, which is based on a 3D graphics model of the prostate which can be deformed and resected interactively by the user. The mechatronics interface, is the device that the urology residents will manipulate to simulate the movements performed during surgery. Our current prototype has five degrees of freedom, which are enough to have a realistic simulation of the surgery movements. Two of these degrees of freedom are linear, to determinate the linear displacement of the resecting loop and the other three are rotational to determinate three directions and amounts of rotation. © 2006 American Institute of Physics [ABSTRACT FROM AUTHOR]