A Computational Model of Minimal Consciousness Functions

Interest in Human Consciousness has been revived in the late 20th century from different scientific disciplines. Consciousness studies involve both its understanding and its application. In this paper, a computational model of the minimum consciousness functions necessary in my point of view for Artificial Intelligence applications is presented with the aim of improving the way computations will be made in the future. In section I, human consciousness is briefly described according to the scope of this paper. In section II, a minimum set of consciousness functions is defined - based on the literature reviewed - to be modelled, and then a computational model of these functions is presented in section III. In section IV, an analysis of the model is carried out to describe its functioning in detail.

Analysis of Hollow Rollers Implementation in Flexible Manufacturing of Large Bearings

In this paper is study the possibility of successfully implementing of hollow roller concept in order to minimize inertial mass of the large bearings, with major results in diminution of the material consumption, increasing of power efficiency (in wind power station area), increasing of the durability and life duration of the large bearings systems, noise reduction in working, resistance to vibrations, an important diminution of losses by abrasion and reduction of the working temperature. In this purpose was developed an original solution through which are reduced mass, inertial forces and moments of large bearings by using of hollow rollers. The research was made by using the method of finite element analysis applied on software type Solidworks - Nastran. Also, is study the possibility of rapidly changing the manufacturing system of solid and hollow cylindrical rollers.

Increasing the Efficacy of Educators Teaching Online

In order to provide and maintain effective pedagogy for the burgeoning virtual reality community, it is vital to have trained faculty in the institutions of higher education who will teach these courses and be able to make full use of their academic knowledge and expertise. As the number of online courses continues to grow, there is a need for these institutions to establish mentoring programs that will support the novice online instructor. The environment in which this takes place and the factors that ensure its success are critical to the adoption of the new instructional delivery format taught by both seasoned educators and adjunct instructors. Effective one-on-one mentoring promotes a professional, compassionate and collegial faculty who will provide a consistent and rigorous academic program for students online.

Periodic Control of a Reverse Osmosis Water Desalination Unit

Enhancement of the performance of a reverse osmosis (RO) unit through periodic control is studied. The periodic control manipulates the feed pressure and flow rate of the RO unit. To ensure the periodic behavior of the inputs, the manipulated variables (MV) are transformed into the form of sinusoidal functions. In this case, the amplitude and period of the sinusoidal functions become the surrogate MV and are thus regulated via nonlinear model predictive control algorithm. The simulation results indicated that the control system can generate cyclic inputs necessary to enhance the closedloop performance in the sense of increasing the permeate production and lowering the salt concentration. The proposed control system can attain its objective with arbitrary set point for the controlled outputs. Successful results were also obtained in the presence of modeling errors.

HIV Modelling - Parallel Implementation Strategies

We report on the development of a model to understand why the range of experience with respect to HIV infection is so diverse, especially with respect to the latency period. To investigate this, an agent-based approach is used to extract highlevel behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A network of independent matrices mimics the chain of lymph nodes. Dealing with massively multi-agent systems requires major computational effort. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach and, using the MPI library, are here implemented, tested and optimized. Our current focus is on the various implementations of the data transfer across the network. Three communications strategies are proposed and tested, showing that the most efficient approach is communication based on the natural lymph-network connectivity.

Steady-State Performance of a New Model for UPFC Applied to Multi-Machines System with Nonlinear Load

In this paper, a new developed construction model of the UPFC is proposed. The construction of this model consists of one shunt compensation block and two series compensation blocks. In this case, the UPFC with the new construction model will be investigated when it is installed in multi-machine systems with nonlinear load model. In addition, the steady–state performance of the new model operating as impedance compensation will be presented and compared with that obtained from the system without compensation.

An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition

Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.

Silicon-based Low-Power Reconfigurable Optical Add-Drop Multiplexer (ROADM)

We demonstrate a 1×4 coarse wavelength division-multiplexing (CWDM) planar concave grating multiplexer/demultiplexer and its application in re-configurable optical add/drop multiplexer (ROADM) system in silicon-on-insulator substrate. The wavelengths of the demonstrated concave grating multiplexer align well with the ITU-T standard. We demonstrate a prototype of ROADM comprising two such concave gratings and four wide-band thermo-optical MZI switches. Undercut technology which removes the underneath silicon substrate is adopted in optical switches in order to minimize the operation power. For all the thermal heaters, the operation voltage is smaller than 1.5 V, and the switch power is ~2.4 mW. High throughput pseudorandom binary sequence (PRBS) data transmission with up to 100 Gb/s is demonstrated, showing the high-performance ROADM functionality.

The Influence of Electrode Heating On the Force Generated On a High Voltage Capacitor with Asymmetrical Electrodes

When a high DC voltage is applied to a capacitor with strongly asymmetrical electrodes, it generates a mechanical force that affects the whole capacitor. This is caused by the motion of ions generated around the smaller of the two electrodes and their subsequent interaction with the surrounding medium. If one of the electrodes is heated, it changes the conditions around the capacitor and influences the process of ionisation, thus changing the value of the generated force. This paper describes these changes and gives reasons behind them. Further the experimental results are given as proof of the ionic mechanism of the phenomenon.

Multiple Peaks Tracking Algorithm using Particle Swarm Optimization Incorporated with Artificial Neural Network

Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Software Tools for System Identification and Control using Neural Networks in Process Engineering

Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Business Diversification Strategies in the Italian Energy Markets

The liberalization and privatization processes have forced public utility companies to face new competitive challenges, implementing strategies to gain market share and, at the same time, keep the old customers. To this end, many companies have carried out mergers, acquisitions and conglomerations in order to diversify their business. This paper focuses on companies operating in the free energy market in Italy. In the last decade, this sector has undergone profound changes that have radically changed the competitive scenario and have led companies to implement diversification strategies of the business. Our work aims to evaluate the economic and financial performances obtained by energy companies, following the beginning of the liberalization process, verifying the possible relationship with the implemented diversification strategies.

A Design of Electronically Tunable Voltagemode Universal Filter with High Input Impedance

This article presents a voltage-mode universal biquadratic filter performing simultaneous 3 standard functions: lowpass, high-pass and band-pass functions, employing differential different current conveyor (DDCC) and current controlled current conveyor (CCCII) as active element. The features of the circuit are that: the quality factor and pole frequency can be tuned independently via the input bias currents: the circuit description is very simple, consisting of 1 DDCC, 2 CCCIIs, 2 electronic resistors and 2 grounded capacitors. Without requiring component matching conditions, the proposed circuit is very appropriate to further develop into an integrated circuit. The PSPICE simulation results are depicted. The given results agree well with the theoretical anticipation.

Performance Improvement of Moving Object Recognition and Tracking Algorithm using Parallel Processing of SURF and Optical Flow

The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can-t do real-time object recognition and tracking. The proposed method uses a typical way of feature extraction SURF and moving object Optical Flow for reduce disadvantage and real-time moving object recognition and tracking, and parallel processing techniques for speed improvement. First analyse that an image from DB and acquired through the camera using SURF for compared to the same object recognition then set ROI (Region of Interest) for tracking movement of feature points using Optical Flow. Secondly, using Multi-Thread is for improved processing speed and recognition by parallel processing. Finally, performance is evaluated and verified efficiency of algorithm throughout the experiment.

Implementing Knowledge Transfer Solution through Web-based Help Desk System

Knowledge management is a process taking any steps that needed to get the most out of available knowledge resources. KM involved several steps; capturing the knowledge discovering new knowledge, sharing the knowledge and applied the knowledge in the decision making process. In applying the knowledge, it is not necessary for the individual that use the knowledge to comprehend it as long as the available knowledge is used in guiding the decision making and actions. When an expert is called and he provides stepby- step procedure on how to solve the problems to the caller, the expert is transferring the knowledge or giving direction to the caller. And the caller is 'applying' the knowledge by following the instructions given by the expert. An appropriate mechanism is needed to ensure effective knowledge transfer which in this case is by telephone or email. The problem with email and telephone is that the knowledge is not fully circulated and disseminated to all users. In this paper, with related experience of local university Help Desk, it is proposed the usage of Information Technology (IT)to effectively support the knowledge transfer in the organization. The issues covered include the existing knowledge, the related works, the methodology used in defining the knowledge management requirements as well the overview of the prototype.

The Use of Information for Inventory Decision in the Healthcare Industry

In this study, we explore the use of information for inventory decision in the healthcare organization (HO). We consider the scenario when the HO can make use of the information collected from some correlated products to enhance its inventory planning. Motivated by our real world observations that HOs adopt RFID and bar-coding system for information collection purpose, we examine the effectiveness of these systems for inventory planning with Bayesian information updating. We derive the optimal ordering decision and study the issue of Pareto improvement in the supply chain. Our analysis demonstrates that RFID system will outperform the bar-coding system when the RFID system installation cost and the tag cost reduce to a level that is comparable with that of the barcoding system. We also show how an appropriately set wholesale pricing contract can achieve Pareto improvement in the HO supply chain.

Decision Trees for Predicting Risk of Mortality using Routinely Collected Data

It is well known that Logistic Regression is the gold standard method for predicting clinical outcome, especially predicting risk of mortality. In this paper, the Decision Tree method has been proposed to solve specific problems that commonly use Logistic Regression as a solution. The Biochemistry and Haematology Outcome Model (BHOM) dataset obtained from Portsmouth NHS Hospital from 1 January to 31 December 2001 was divided into four subsets. One subset of training data was used to generate a model, and the model obtained was then applied to three testing datasets. The performance of each model from both methods was then compared using calibration (the χ2 test or chi-test) and discrimination (area under ROC curve or c-index). The experiment presented that both methods have reasonable results in the case of the c-index. However, in some cases the calibration value (χ2) obtained quite a high result. After conducting experiments and investigating the advantages and disadvantages of each method, we can conclude that Decision Trees can be seen as a worthy alternative to Logistic Regression in the area of Data Mining.

A Robust STATCOM Controller for a Multi-Machine Power System Using Particle Swarm Optimization and Loop-Shaping

Design of a fixed parameter robust STATCOM controller for a multi-machine power system through an H-? based loop-shaping procedure is presented. The trial and error part of the graphical loop-shaping procedure has been eliminated by embedding a particle swarm optimization (PSO) technique in the design loop. Robust controllers were designed considering the detailed dynamics of the multi-machine system and results were compared with reduced order models. The robust strategy employing loop-shaping and PSO algorithms was observed to provide very good damping profile for a wide range of operation and for various disturbance conditions. 

A Study of the Cyclic Variations of the Enzyme and the Electrolyte Activity in Uterine and Oviducal Secretions during an Estrous Cycle of the Ewe

Uterine and oviducal fluids are necessary for capacitation of the spermatozoa and early embryonic development. The aim of the present study was to determine the effects of estrous cycle phases (follicular and luteal) on some biological parameters (enzymes, electrolytes and total proteins) in uterine and oviducal secretions of ewes. Oviducal and uterine fluids were collected, diluted and centrifuged. According to our results, concentrations of GPT, G6PDH, total proteins, K and Na were significantly (P

Micropolar Fluids Effects on the Dynamic Characteristics of Four-lobe Journal Bearing

Dynamic characteristics of a four-lobe journal bearing of micropolar fluids are presented. Lubricating oil containing additives and contaminants is modelled as micropolar fluid. The modified Reynolds equation is obtained using the micropolar lubrication theory and solving it by using finite difference technique. The dynamic characteristics in terms of stiffness, damping coefficients, the critical mass and whirl ratio are determined for various values of size of material characteristic length and the coupling number. The results show compared with Newtonian fluids, that micropolar fluid exhibits better stability.