Musical Instrument Classification Using Embedded Hidden Markov Models

In this paper, a novel method for recognition of musical instruments in a polyphonic music is presented by using an embedded hidden Markov model (EHMM). EHMM is a doubly embedded HMM structure where each state of the external HMM is an independent HMM. The classification is accomplished for two different internal HMM structures where GMMs are used as likelihood estimators for the internal HMMs. The results are compared to those achieved by an artificial neural network with two hidden layers. Appropriate classification accuracies were achieved both for solo instrument performance and instrument combinations which demonstrates that the new approach outperforms the similar classification methods by means of the dynamic of the signal.

Effect of Distributed Generators on the Optimal Operation of Distribution Networks

This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.

Cost Optimized CO2 Pipeline Transportation Grid: A Case Study from Italian Industries

This paper presents the feasibility study of CO2 sequestration from the sources to the sinks in the prospective of Italian Industries. CO2 produced at these sources captured, compressed to supercritical pressures, transported via pipelines and stored in underground geologic formations such as depleted oil and natural gas reservoirs, un-minable coal seams and deep saline aquifers. In this work, we present the optimized pipeline infrastructure for the CO2 with appropriate constraints to find lower cost system by the use of nonlinear optimization software LINGO 11.0. This study was conducted on CO2 transportation complex network of Italian Industries, to find minimum cost network for transporting the CO2 from sources to the sinks.

Internal Accounting Controls

Internal controls of accounting are an essential business function for a growth-oriented organization, and include the elements of risk assessment, information communications and even employees' roles and responsibilities. Internal controls of accounting systems are designed to protect a company from fraud, abuse and inaccurate data recording and help organizations keep track of essential financial activities. Internal controls of accounting provide a streamlined solution for organizing all accounting procedures and ensuring that the accounting cycle is completed consistently and successfully. Implementing a formal Accounting Procedures Manual for the organization allows the financial department to facilitate several processes and maintain rigorous standards. Internal controls also allow organizations to keep detailed records, manage and organize important financial transactions and set a high standard for the organization's financial management structure and protocols. A well-implemented system also reduces the risk of accounting errors and abuse. A well-implemented controls system allows a company's financial managers to regulate and streamline all functions of the accounting department. Internal controls of accounting can be set up for every area to track deposits, monitor check handling, keep track of creditor accounts, and even assess budgets and financial statements on an ongoing basis. Setting up an effective accounting system to monitor accounting reports, analyze records and protect sensitive financial information also can help a company set clear goals and make accurate projections. Creating efficient accounting processes allows an organization to set specific policies and protocols on accounting procedures, and reach its financial objectives on a regular basis. Internal accounting controls can help keep track of such areas as cash-receipt recording, payroll management, appropriate recording of grants and gifts, cash disbursements by authorized personnel, and the recording of assets. These systems also can take into account any government regulations and requirements for financial reporting.

Accelerating Integer Neural Networks On Low Cost DSPs

In this paper, low end Digital Signal Processors (DSPs) are applied to accelerate integer neural networks. The use of DSPs to accelerate neural networks has been a topic of study for some time, and has demonstrated significant performance improvements. Recently, work has been done on integer only neural networks, which greatly reduces hardware requirements, and thus allows for cheaper hardware implementation. DSPs with Arithmetic Logic Units (ALUs) that support floating or fixed point arithmetic are generally more expensive than their integer only counterparts due to increased circuit complexity. However if the need for floating or fixed point math operation can be removed, then simpler, lower cost DSPs can be used. To achieve this, an integer only neural network is created in this paper, which is then accelerated by using DSP instructions to improve performance.

The Robot Hand System that can Control Grasping Power by SEMG

SEMG (Surface Electromyogram) is one of the bio-signals and is generated from the muscle. And there are many research results that use forearm EMG to detect hand motions. In this paper, we will talk about our developed the robot hand system that can control grasping power by SEMG. In our system, we suppose that muscle power is proportional to the amplitude of SEMG. The power is estimated and the grip power of a robot hand is able to be controlled using estimated muscle power in our system. In addition, to perform a more precise control can be considered to build a closed loop feedback system as an object to a subject to pressure from the edge of hand. Our objectives of this study are the development of a method that makes perfect detection of the hand grip force possible using SEMG patterns, and applying this method to the man-machine interface.

Exploring the Determinants for Successful Collaboration of SMEs

The goal of this research is discovering the determinants of the success or failure of external cooperation in small and medium enterprises (SMEs). For this, a survey was given to 190 SMEs that experienced external cooperation within the last 3 years. A logistic regression model was used to derive organizational or strategic characteristics that significantly influence whether external collaboration of domestic SMEs is successful or not. Results suggest that research and development (R&D) features in general characteristics (both idea creation and discovering market opportunities) that focused on and emphasized indirected-market stakeholders (such as complementary companies and affiliates) and strategies in innovative strategic characteristics raise the probability of successful external cooperation. This can be used meaningfully to build a policy or strategy for inducing successful external cooperation or to understand the innovation of SMEs.

Artificial Neural Network based Modeling of Evaporation Losses in Reservoirs

An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Economical Operation of Hydro-Thermal Power System based on Multi-path Adaptive Tabu Search

An economic operation scheduling problem of a hydro-thermal power generation system has been properly solved by the proposed multipath adaptive tabu search algorithm (MATS). Four reservoirs with their own hydro plants and another one thermal plant are integrated to be a studied system used to formulate the objective function under complicated constraints, eg water managements, power balance and thermal generator limits. MATS with four subsearch units (ATSs) and two stages of discarding mechanism (DM), has been setting and trying to solve the problem through 25 trials under function evaluation criterion. It is shown that MATS can provide superior results with respect to single ATS and other previous methods, genetic algorithms (GA) and differential evolution (DE).

Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm

Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.

Preparation of Computer Model of the Aircraft for Numerical Aeroelasticity Tests – Flutter

Article presents the geometry and structure reconstruction procedure of the aircraft model for flatter research (based on the I22-IRYDA aircraft). For reconstruction the Reverse Engineering techniques and advanced surface modeling CAD tools are used. Authors discuss all stages of data acquisition process, computation and analysis of measured data. For acquisition the three dimensional structured light scanner was used. In the further sections, details of reconstruction process are present. Geometry reconstruction procedure transform measured input data (points cloud) into the three dimensional parametric computer model (NURBS solid model) which is compatible with CAD systems. Parallel to the geometry of the aircraft, the internal structure (structural model) are extracted and modeled. In last chapter the evaluation of obtained models are discussed.

Controlling of Load Elevators by the Fuzzy Logic Method

In this study, a fuzzy-logic based control system was designed to ensure that time and energy is saved during the operation of load elevators which are used during the construction of tall buildings. In the control system that was devised, for the load elevators to work more efficiently, the energy interval where the motor worked was taken as the output variable whereas the amount of load and the building height were taken as input variables. The most appropriate working intervals depending on the characteristics of these variables were defined by the help of an expert. Fuzzy expert system software was formed using Delphi programming language. In this design, mamdani max-min inference mechanism was used and the centroid method was employed in the clarification procedure. In conclusion, it is observed that the system that was designed is feasible and this is supported by statistical analyses..

Effect of Rotating Electrode

A gold coated copper rotating electrode was used to eliminate surface oxidation effect. This study examined the effect of electrode rotation on the ozone generation process and showed that an ozonizer with an electrode rotating system might be a possible way to increase ozone-synthesis efficiency. Two new phenomena appeared during experiments with the rotating electrode. First was that ozone concentration increased to about two times higher than that of the case with no rotation. Second, input power and discharge area were found to increase with the rotation speed. Both ozone concentration and ozone production efficiency improved in the case of rotating electrode compared to the case with a non-rotating electrode. One possible reason for this was the increase in discharge length of micro-discharges during electrode rotation. The rotating electrode decreased onset voltage, while reactor capacitance increased with rotation. Use of a rotating-type electrode allowed earlier observation of the ozone zero phenomena compared with a non-rotating electrode because, during rotation, the entire electrode surface was functional, allowing nitrogen on the electrode surface to be evenly consumed. Nitrogen demand increased with increasing rotation s

CFD Simulation of SO2 Removal from Gas Mixtures using Ceramic Membranes

This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.

Salinity on Survival and Early Development of Biofuel Feedstock Crops

Salinity level may affect early development of biofuel feedstock crops. The biofuel feedstock crops canola (Brassica napus L.), sorghum [Sorghum bicolor (L.) Moench], and sunflower (Helianthus annuus L.); and the potential feedstock crop sweet corn (Zea mays L.) were planted in media in pots and treated with aqueous solutions of 0, 0.1, 0.5 and 1.0 M NaCl once at: 1) planting; 2) 7-10 days after planting or 3) first true leaf expansion. An additional treatment (4) comprised of one-half strength of the 0.1, 0.5 and 1.0 M (concentrations 0.05, 0.25, 0.5 M at each application) was applied at first true leaf expansion and four days later. Survival of most crops decreased below 90% above 0.5 M; survival of canola decreased above 0.1 M. Application timing had little effect on crop survival. For canola root fresh and dry weights improved when application was at plant emergence; for sorghum top and root fresh weights improved when the split application was used. When application was at planting root dry weight was improved over most other applications. Sunflower top fresh weight was among the highest when saline solutions were split and top dry weight was among the highest when application was at plant emergence. Sweet corn root fresh weight was improved when the split application was used or application was at planting. Sweet corn root dry weight was highest when application was at planting or plant emergence. Even at high salinity rates survival rates greater than what might be expected occurred. Plants that survived appear to be able to adjust to saline during the early stages of development.

A New Scheme for Improving the Quality of Service in Heterogeneous Wireless Network for Data Stream Sending

In this paper, we first consider the quality of service problems in heterogeneous wireless networks for sending the video data, which their problem of being real-time is pronounced. At last, we present a method for ensuring the end-to-end quality of service at application layer level for adaptable sending of the video data at heterogeneous wireless networks. To do this, mechanism in different layers has been used. We have used the stop mechanism, the adaptation mechanism and the graceful degrade at the application layer, the multi-level congestion feedback mechanism in the network layer and connection cutting off decision mechanism in the link layer. At the end, the presented method and the achieved improvement is simulated and presented in the NS-2 software.

Handwritten Character Recognition Using Multiscale Neural Network Training Technique

Advancement in Artificial Intelligence has lead to the developments of various “smart" devices. Character recognition device is one of such smart devices that acquire partial human intelligence with the ability to capture and recognize various characters in different languages. Firstly multiscale neural training with modifications in the input training vectors is adopted in this paper to acquire its advantage in training higher resolution character images. Secondly selective thresholding using minimum distance technique is proposed to be used to increase the level of accuracy of character recognition. A simulator program (a GUI) is designed in such a way that the characters can be located on any spot on the blank paper in which the characters are written. The results show that such methods with moderate level of training epochs can produce accuracies of at least 85% and more for handwritten upper case English characters and numerals.

The Functionality and Usage of CRM Systems

Modern information and communication technologies offer a variety of support options for the efficient handling of customer relationships. CRM systems have been developed, which are designed to support the processes in the areas of marketing, sales and service. Along with technological progress, CRM systems are constantly changing, i.e. the systems are continually enhanced by new functions. However, not all functions are suitable for every company because of different frameworks and business processes. In this context the question arises whether or not CRM systems are widely used in Austrian companies and which business processes are most frequently supported by CRM systems. This paper aims to shed light on the popularity of CRM systems in Austrian companies in general and the use of different functions to support their daily business. First of all, the paper provides a theoretical overview of the structure of modern CRM systems and proposes a categorization of currently available software functionality for collaborative, operational and analytical CRM processes, which provides the theoretical background for the empirical study. Apart from these theoretical considerations, the paper presents the empirical results of a field survey on the use of CRM systems in Austrian companies and analyzes its findings.

Methanol Concentration Sensitive SWCNT/Nafion Composites

An aqueous methanol sensor for use in direct methanol fuel cells (DMFCs) applications is demonstrated; the methanol sensor is built using dispersed single-walled carbon nanotubes (SWCNTs) with Nafion117 solution to detect the methanol concentration in water. The study is aimed at the potential use of the carbon nanotubes array as a methanol sensor for direct methanol fuel cells (DMFCs). The concentration of methanol in the fuel circulation loop of a DMFC system is an important operating parameter, because it determines the electrical performance and efficiency of the fuel cell system. The sensor is also operative even at ambient temperatures and responds quickly to changes in the concentration levels of the methanol. Such a sensor can be easily incorporated into the methanol fuel solution flow loop in the DMFC system.

Simulation and Design of Single Fed Circularly Polarized Triangular Microstrip Antenna with Wide Band Tuning Stub

Recently, several designs of single fed circularly polarized microstrip antennas have been studied. Relatively, a few designs for achieving circular polarization using triangular microstrip antenna are available. Typically existing design of single fed circularly polarized triangular microstrip antennas include the use of equilateral triangular patch with a slit or a horizontal slot on the patch or addition a narrow band stub on the edge or a vertex of triangular patch. In other word, with using a narrow band tune stub on middle of an edge of triangle causes of facility to compensate the possible fabrication error and substrate materials with easier adjusting the tuner stub length. Even though disadvantages of this method is very long of stub (approximate 1/3 length of triangle edge). In this paper, instead of narrow band stub, a wide band stub has been applied, therefore the length of stub by this method has been decreased around 1/10 edge of triangle in addition changing the aperture angle of stub, provides more facility for designing and producing circular polarization wave.