Archive for the ‘solar home’ tag

Developing Nuclear Power As Alternative Energy

Many researchers believe that harnessing the power of the atom in fission reactions is the most significant alternative energy resource that we have, for the fact of the immense power that it can generate.

Nuclear power plants are very clean-burning and their efficiency is rather staggering. Nuclear power is generated at 80% efficiency, meaning that the energy produced by the fission reactions is almost equal to the energy put into producing the fission reactions in the first place. There is not a lot of waste material generated by nuclear fission although, due to the fact that there is no such thing as creating energy without also creating some measure of waste, there is some.

The concerns of people such as environmentalists with regards to using nuclear power as an alternative energy source center around this waste, which is radioactive gases which have to be contained.

The radiation from these gases lasts for an extraordinarily long time, so it can never be released once contained and stored. However, the volume of this waste gas produced by the nuclear power plants is small in comparison to how much NOx (nitrous oxide that is, air pollution) is caused by one day’s worth of rush-hour traffic in Los Angeles.

While the radiation is certainly the more deadly by far of the two waste materials, the radiation is also by far the easier of the two to contain and store. In spite of the concerns of the environmentalists, nuclear power is actually environmentally friendly alternative energy, and the risk of the contained radiation getting out is actually quite low. With a relatively low volume of waste material produced, it should not be a difficult thing at all for storage and disposal solutions for the long term to be developed as technology advances.

The splitting of an atom releases energy in the forms of both heat and light. Atomic power plants control the fission reactions so that they don’t result in the devastating explosions that are brought forth in atomic and hydrogen bombs. There is no chance of an atomic power plant exploding like a nuclear bomb, as the specialized conditions and the pure Plutonium used to unleash an atomic bomb’s vicious force simply don’t exist inside a nuclear power plant.

The risk of a meltdown is very low. Although this latter event has happened a couple of times, when one considers that there are over 430 nuclear reactors spread out across 33 nations, and that nuclear reactors have been in use since the early 1950s, these are rare occurrences, and the events of that nature which have taken place were the fault of outdated materials which should have been properly kept up.

Indeed, if nuclear energy could become a more widely accepted form of alternative energy, there would be little question of their upkeep being maintained. Currently, six states in America generate more than half of all their electrical energy needs through nuclear power, and the media are not filled with gruesome horror stories of the power plants constantly having problems.

Fuel Crisis is it Real ?

But with all the crooks in the world today I have change my opinion about this subject. You may ask why bother writing about this subject at all. One reason is we should be trying to save fuel by any means possible, like trying to limit the amount of times you drive your car which can be done by planning your trips. You can go to work with other employees or take busses. Another suggestion is to try using a fuel saver additive in your car. But let?s get back to the reasons I believe it is real.

My first reason is technology: When I was younger the energy companies promised if the American people would allow them to build Nuclear power plants in the U.S.A that after the return on their investment on building these plants was realized, energy in the future would be dirt cheap.( Sorry youngsters that we bought that lie). Looks to me like my electric bill keeps climbing ever year not get any cheaper.

Also in the early sixties a friend of mine came up with this idea for saving fuel by eliminating oil changes in automobiles. He invented an oil filter system that was accessible from under the hood of the car instead of under the engine. This allowed all the oil to run back down into the engine from the filter because of gravity. You would unscrew the top part of the filter housing and add a roll of toilet paper and put the top back on. After installing the new roll of toilet paper you would then add one quart of oil. He would do this every 20 thousand miles and his oil was always clean on his dip stick. He told me dirt brakes down the oil and if you can keep it clean it would last much longer. No companies were interested in this invention because it would cut oil consumption. No one worried about saving furl or fuel savers in those days. By the way look under the hood of the new BMW?s today and see they used part of his idea.

Also in the sixties there was a gentleman that invented a carburetor that got 100 miles to the gallon on those big heavy old clunkers. Here drove his car from Chicago to California on one take of gas. It was advertized on television and it was big news. It was short lived because a few weeks later it was reported that he had other fuel tanks on the car. I can tell you that is a lie but the American people seem to buy those kind of lies. The man at his own expense put a copy of the blue print of his carburetor in the public libraries so if anyone wanted proof for themselves they could build one. Guess no one did ? By the way the very next year after his new invention the auto companies went to fuel ejection and replaced carburetors, and if you know anything about engines and saving fuel that was not the way to go.

My second reason is where is our fuel going?

Also back in the sixties they built the Alaskan oil line in the event that we needed more oil then we could produce for the American People. Where is all that oil going that is flowing from those pipes? I can tell you it is not going to the American people or oil would not be that expensive. The oil is shipped somewhere else, most likely to Japan, and we have to import our oil so we have to pay higher prices for it. Also why do we have all our own oil wells capped? Why won?t they let us drill off our own costs when they plan on letting China drill off Florida coast? Another big question is why can?t we burn coal? I live here in Virginia and there is a train that goes past our house 24 times a day with over 100 cars of coal on it. It is being shipped somewhere over seas where some other country can save fuel oil by using our natural resources but we here in America we cannot burn our own coal. Oh by the way they bought another one hundred shinny new cars and have filled them up with coal and now are running two trains every hour.

We also have over 12 million illegal immigrants in this country using million of gallons of our fuel every single day. A good way to save fuel is by sending these people back to their own country. I think this is one good fuel saver idea, because they are here not to become Americans but to rob and pillage and take over our country and turn it into theirs. If you think this statement is not true, then take a look at Miami and some other states that have been taken over by them. Or just dial you phone company and they ask you to push some kind of number to hear their message in English.

The main reason I believe that contributes to our shortage is the lack of refineries in this country. We use to have over a hundred refineries in this country but have downsized to about 12. Sounds a little weird to me that if there is more of a demand for fuel today like they claim we should have more not less refineries.

If they would come out with the cars that run on hydrogen, build a few more nuclear power plants and come out with all the other inventions they have suppress over the years it would end all these problems. I am sure they will someday after they have everything you own in their back pockets but until then we can only hope. So until then become a real fuel saver by saving fuel any way you can.

Electricity With Wind Energy – Urgent Message !

If you’re tired of wasting money and you’re looking for information about making electricity with Wind Power then listen to what we have to share on the subject – it is of great financial importance to you. Most of us get our power supply from the electric company; however, there is a secret way that enables you to get free and unlimited power supply amazingly easily and yes, inexpensively.

You may raise an eyebrow at this claim, but the fact of the matter is that anybody can produce their own household’s power supply quite easily, and no longer have to depend on expensive electric companies. Picture this – no initial deposit required, and no monthly invoices, simply free and environmentally-friendly power to provide all the electricity you need.

Just before you search the internet for more information about making electricity with Wind Power; you have to realize, for your own financial well-being, that you can make use of a system which is already enjoyed by literally thousands of people in the united states and around the world that gives you the power to seriously decrease your power bill if not eliminate it once and for all! So we’ve piqued your curiosity and you’re wondering how this can be possible; it’s just a question of tapping into abundant energy sources – the transformation of energy that is found everywhere into electricity, in your own backyard, and in just a couple of days – all by yourself. And that’s not all. here’s the best part – everyone is capable of this, even if, like most people, you’re not a trained professional and even if, as with most people, you’re no thomas edison.

But as you go on learning about making electricity with Wind Power, listen to some more great information – using this new technology, not only you help to preserve our planet, but using this special new technology, the electric company will even buy electricity from you! Think about it – using your air-conditioning system without fretting about money, and actually making extra money by using green technology. Is this unbelievable? Do yourself a favor and just see how easy it all is; I am certain you will be very glad you took this first step.

Automated Voice Quality Testing For Voip Quality Of Service Solutions

Automated sound signals quality estimation

Sevana Oy, 2009
http://www.sevana.fi
1. INTRODUCTION
Sound signal quality estimation acquires the increasing value with the distribution of mobile communications, systems of a synthetic telephony, VoIP and various portable sound recording and sound reproducing devices. The desire naturally arises to work out a way, which would provide objective estimation (i.e. independently from estimation of particular subject) and the opportunity to automate such estimation. It is of a high importance as for comparison of competitive commercial products as well as for parameters’ optimisation of proprietary products.
One of the main parameters in systems of compression, transfer and reproduction of the sound information is the quality of the restored, received or reproduced sound.
Quantitative measurement of sound quality has specific features due to the fact that the final receiver of a sound signal is always a human, and a human is also a source of the majority of sound signals. According to the well-known fact, sound signals quality is determined not only by the technical characteristics of a sound processing and transfer systems, but also by the properties of individual peculiarities of speech perception and production, which vary in time and from individual to individual.

2.REVIEW OF QUALITY ESTIMATION METHODS
Subjective and objective methods to measure speech quality are distinguished. Subjective methods are those, which include the hearing of a person as a component of a measuring complex. Objective methods, on the contrary, exclude participation of person’s hearing from the process of measurements.
The most widespread subjective method of speech quality estimation is MOS (Mean Opinion Score), five-point scale estimation.
This kind of estimation is determined by processing estimations given by groups of auditors to the sequences of sound signals, reproduced by various audio systems. Each auditor estimates each signal, and then the results are averaged.
To organize and implement subjective estimation is sufficiently difficult, long lasting and expensive activity, therefore investigations have been conducted in order to find objective methods, allowing receiving fast and automated estimations which would well correspond to subjective examinations.
There are various automatic estimation methods; some of them are given below [1]:
AI (Articulation Index). The idea is that the whole frequency range of speech signal is divided into 20 bands and the signal/noise ratio is determined within the band. The band broad is defined in such a way, that every band contributes equally in speech perception. The signal/noise ratio is calculated within every band. Articulation index is supposed to be equal the weighted total of the band values.
The disadvantage of the articulation index is that it does not take into account the properties of hearing and speech production, although it directs towards speech signal.
SII (Speech Intelligibility Index) is the evolution of AI method. The American Standard ANSI S3.5-1997 includes the speech intelligibility index. It provides 4 measuring procedures on different band groups: 21 critical bands, 18 one third-octave bands, 17 equal by their contribution critical bands and 6 octave bands. The signal/noise ratio is calculated within every band and the total SII coefficient, ranged from 0 to 1 is computed.
The speech intelligibility index, however, takes into account only the properties of hearing, not speech production.
STI (Speech Transmission Index). We may approximately consider speech signal as broadband signal modulated by low-frequency signal. Articulation speed determines modulation frequency. When modulation depth decreases, speech signal becomes similar to noise and its intelligibility decreases. Accordingly, intelligibility decrease can be estimated according to modulation depth decrease as well.
Whole speech range is divided into 7octave bands. An octave noise signal is the input. The test signal intensity distribution agrees with the distribution of speech signal intensities. The modulating signal frequencies vary from 0.5 to 12.5 Hz with one-third-octave interval (14 frequencies in all).
The STI measuring method is stated in the International standard IEC 268-16.
RATSI/STIPA (Rapid Speech Transmission Index). The STI method needs a lot of measuring procedures and calculations. A simplified method was developed, which provides for measuring only in 2 bands with 5 modulation frequencies and reduces the number of measuring procedures and calculations. For good intelligibility RASTI values must be not less than 0.6.
Both speech transmission index (STI) as well as rapid speech transmission index (RASTI) imitate speech production process by means of noise model, but to take into account the properties of speech production and hearing in such way is far from optimum.
C50 (factor of clearness) determines sound clearness and clarity. It is computed as near echo/far echo ratio. The method is based on the fact, that echo reduces signal intelligibility. The near echo/far echo ratios in several frequency bands are calculated. They consider near echo (less than 33 ms) as useful signal and far echo (more than 33 ms) as disturbing signal.
The factor of clearness takes into account only one kind of the possible distortions and it is worth to apply it only as one of the speech quality estimations approaches.

ITU P.862 PESQ (Perceptual Evaluation of Speech Quality). PESQ is an objective measurement method that predicts the results of subjective listening tests on telephony systems. PESQ uses a sensory model to compare the original, unprocessed signal with the degraded signal from the network or network element. The resulting quality score is similar to the subjective “Mean Opinion Score” (MOS) measured using panel tests according to ITU-T P.800. The PESQ scores are calibrated using a large database of subjective tests. The method takes into account coding distortions, errors, packet loss, delay and variable delay, and filtering in analogue network components.
Being one of the most popular tools PESQ has a number of disadvantages such as demanding test signals to be speech-like because many systems are optimized for speech and respond in an unrepresentative way to non-speech signals (e.g. tones, noise, ITU-T P.50). PESQ test signal is to be set by tester and thus vendor estimations may vary from end customer estimations. The approach performs signal level equalization what theoretically is not that good because when speaking different sound volumes may have different spectrums. PESQ cannot catch significant quality loss, which occurs when the voice is equalized such that there is far less low frequency and high frequency energy when compared to the original voice file.
The need to develop new methods and to improve existing ones is caused by desire to bring together objective and subjective estimation of quality and to explicitly use in such systems our knowledge about hearing and speech production.
To use arbitrary or particularized signal as a source signal depends on the estimation purpose (speech intelligibility evaluation, sound reproduction quality, quality estimation of speech transmitted through intercommunication channels, etc.) and allows increasing estimation objectivity.

3. GENERAL SCHEME OF THE SYSTEM

The figure 1 represents general scheme of the quality estimation system for sound signals.

Fig.1. General scheme of the quality estimation system for sound signals

A generator of test signals allows sound signal forming according to one of the sound flow models. It can be either a particularized set of sound signals or a signal, received in output of statistical speech model. (Signal models in details are considered later.) Generator’s signal can either be saved for follow-up usage or be exposed to processing and estimation. Bank of signals stores sound data, received as a result of signals’ generator work or from some external sources.
Accordingly, an input of estimation block is a signal of generator directly or one of the bank of signals. Test signal is the input of the synchronizer or of the device under test, which can be for example, a vocoder or a communication channel. The output signal of the device under test is an input of synchronizer also.
The synchronizer matches in time an initial signal and a processed signal. The synchronized signals in chunks input in analytical module, which determines the degree of similarity for signals and issues the quality estimation as the measure of similarity between the initial and the processed signals.
Let’s consider the functioning of system modules in details.
3.1. Generator of test signals

The generator of test signals consists of a generator of noise signals and a simplified statistical speech model. Both of generators simulate the process of “speaking”, but their approaches to speech production simulating differ. The statistical model forms sound flow on the base of human speech patterns and the generator of noise signals bases on knowledge about sound perception and speech production.
3.2. Generator of noise signals
The generator of noise signals operates on speech flow model like one, which used in the STI method. The idea is that we may approximately consider speech signal as broadband signal modulated by low-frequency signal. Articulation speed determines modulation frequency, which varies from 0.63 to 13.44 Hz.

As a modulation signal the noise signal is used, resulting from white noise by means of cutting the critical bands of hearing and speech production. In the first case the signal generated allows estimation of sound signal quality in general, in the other case – particularly speech signal estimation. Critical bands in details are considered in the description of the analytical module.
3.3. Statistical speech model
Language consists of sounds. Every individual generates a unique set of sounds. However, one can distinguish standard speakers (SS), generating average kinds of sounds. Standard speakers are subdivided according to their age, gender, region, social status, education, occupation etc.
One should determine sound frequencies, probabilities of sounds following each other, intonation contours, vocabularies, physical properties of individual sounds for every standard speaker. Based on these data one can simulate natural speech flow.
One should also include in the system statistic information about the population structure and with its help generate speech flows with the features, which characterize population of some region or the whole country.
Broadly speaking, statistic model contains statistic data about the population structure, speech bases of standard speakers, speech signal processing facilities (algorithms of synthesis), means of speed sounds parameters determination, generation algorithms of sounds and standard speakers distributions.

The interface block provides interaction with outer world (or User) and also synchronizes functions of other blocks of statistic model.

The block of speaker choice generates sample of standard speakers (or sequence of indexes of standard speakers). Depending on the command a representative sample of standard speakers or a sample from one standard speaker can be generated. The sample is representative in the sense that the speech parameters distribution in it corresponds to the speech parameters distribution of the population, described in the model.

The sequence of indexes of standard speakers is saved in the block of standard speaker choice for further usage.

The block of sound choice forms the prosodic (the descriptions of sounds). Depending on the command prosodic is constituted either for a representative sound sample, or for a specified sequence of sounds, or for one specified sound.

Prosodic is saved in the prosodic buffer follow-up usage.

The block of speech flow transforms descriptions of sounds in readings of speech signal.

The block of the descriptions of standard speakers stores descriptions of standard speakers and on query returns necessary parts of descriptions, information about their number, list of speakers.
3.4. Signals synchronizer
The synchronizer matches in time domain initial and processed signals. Input of the synchronizer receives signal segments (pDATA), duration of which is equal to VAD (Voice Activity Detection) frame, and criterions of VAD activity for them are specified in the pDATA segments.
Any sound signal can be separated into active and inactive phases. The first corresponds to active sound processes, the latter – to low-level background noise. The elementary way of dividing these two phases is to divide them according to signal energy level. However such approach is not accurate enough. In our approach VAD algorithm presented in recommendation G.723 is used for this purpose (as a part of VAD vocoder).
After filtration the state criterions and signal frames enter the the synchronizer blocks, which combine active signal fragments and pauses. The modules use common data: buffer of active etalon signal (EBuffer1), buffer of active signal under test (TBuffer1), buffer of the etalon signal pause (EBuffer0), buffer of signal under test pause (TBuffer0), readiness criterion of buffers of active signal and pauses (dReady[0..1]). There is also a counter of synchronization errors (dErrorCounter).
Output of the synchronizer is a pair of buffers with active signals or a pair of buffers with pauses. Both of the blocks of synchronizer can initiate an appearance of a pair of synchronized buffers.
The synchronized buffers and the criterion of activity are the input of analytical module.
3.5. Analytical module
The analytical module compares separately the combined pairs of fragments of active and inactive phase signal that allows getting more accurate estimation.

The integral spectrum is determined for each fragment using discrete cosine transformation (DCT). Spectrum integration is calculated according to the proprietary formula.
In the spectrum calculation the interpenetration of windows comes to N/2 samples, the known Hamming or Blackmann-Harris window function is applied to every window.
Levels of spectrum energy on bands are determined for all sets of bands. Groups of critical bands [2-6], determined by different authors resulting from different models of sound perception and speech production are already known.

Band boundaries (initial and terminal indexes) as well as band energy values are determined according to a set of proprietary formulas.

The initial quality estimation value is taken as 100%. Further it decreases proportionally to distinction of energies on bands. Quality estimation values are determined on every set of bands. The overall quality estimation on all bands is calculated according to proprietary formulas.

To determine sound (D) and word (W) intelligibility the Pokrovskij’s formulas may be used:
To go from the quality loss coefficient to the sound intelligibility value, a correspondent table is used.

To determine value in intermediate points, interpolation (for example, Lagrange interpolation polynomial) is used.

Quality estimations can be translated similarly into MOS estimation values.

4. IMPLEMENTATION & CONCLUSIONS
Algorithms described are implemented for voice quality estimation and comparison of external initial signals and signals under test.
As the external arbitrary signals recorded with the sampling frequency of 8 kHz and the capacity of samples equal to 16 bits can be used. Supposed, the signal under test is received from an initial signal as a result of some transformations (for example, compression/restoration, transmission through communication channels, filtration). In additional as an initial external signal a record of the phonetically representative text read aloud by several speaker of different age of both gender.
As internal initial signals (i.e. signals, which the user of the program has no access to) the signals generated according to the noise model (the description of the generator is given below) and the signals, generated on the basic of the statistic model.
The internal signals are put in the system of sound data comparison/restoration, implemented for example as a DLL with the specified interface. The signal processed by means of methods contained in DLL is considered as the signal under test and is exposed to the quality estimation procedure described earlier.

Presented method of sound signal quality estimation has a number of advantages over known methods of quality measurements, namely:
? it is universal since it allows judging the quality of signals from various source and processed in different ways;
? one can optimize quality estimation signal depending on the purposes:
o in speed (for example, it is possible to receive rough estimation quickly);
o in signal type (using different bands for speech signals and sound signals in general);
? resulting estimations correlate well with that of S;
? quality estimations received for speech signals can be translated into values of various kinds of intelligibility.

Test results representing quality estimations of several standard voice codecs, received on various test signals using the method suggested and the implementation described have a very strong correspondence with known MOS values for these codecs [6].

5. TRENDS OF DEVELOPMENT

According to the structure of the suggested quality estimation system of sound signals the system can develop in following trends:
? the test signal model improvement. Here the noise model can be supplied with a set of multiband modulated noise signals; the set of data and algorithms of the statistic speech model can be enriched, the number of preprepared test signals (such as records of PhRT) can be enlarged;
? the development of more upgraded algorithms of synchronization, based, for example, on coincidence of maximums in signal energy spectrums;
? the acoustic model modernization with taking into account masking effects and the fact that pure tones and band noise cause the hearing in some way differently;
? the signal comparison scheme modernization. Current distance measure is not accurate enough for strongly different signals. For higher universality of the system it is desired to use the correlation analysis methods for comparison;
? to solve a number of practical problems the systems requires the possibility to work with multichannel (Stereo-, Quadro-, etc.) and to receive immediate quality estimations;
? absolutely correct translation of the objective estimations into MOS estimation values requires further experimental researches.
REFERENCES
1. Aldoshina I., “Bases of psychoacoustics”, The sound producer, 2002, 5, 8
2. Sekunov N., “Processing of a sound on PC”, bhv, Saint-Petersburg, 2001
3. Sapozhkov M.A., “Speech signal in cybernetics and communications”, Svyazizdat, Moscow, 1963
4. Pokrovskiy N.B., “Calculation and measurement of speech legibility”, Svyazizdat, Moscow, 1962
5. Sorokin V.N., “Speech synthesis”, Nauka, Moscow, 1992
6. http://www.sevana.fi/audio_speech_codecs_quality_analysis.php

Sevana Oy (Ltd) is a privately owned software company founded in 2003 in Finland with offices in Russia and Estonia.The company creates software in computer and telecommunications technologies. In 2008 it created a new technology for automated voice and audio quality analysis.In Q1 2009 it announced a new algorithm based engine for associations for market basket analysis.

Sevana Oy http://www.sevana.fi

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