Optimal processing chain for waste power plant

This study is done to examine waste power plant’s optimal processing chain and it is important to consider from several points of view on why one option is better than the other. This is to insure that the right decision is made. Incineration of waste has devel-oped to be one decent option for waste disposal. There are several legislation matters and technical options to consider when starting up a waste power plant. From the tech-niques pretreatment, burner and flue gas cleaning are the biggest ones to consider. The treatment of incineration residues is important since it can be very harmful for the envi-ronment. The actual energy production from waste is not highly efficient and there are several harmful compounds emitted. Recycling of waste before incineration is not very typical and there are not many recycling options for materials that cannot be easily re-cycled to same product. Life cycle assessment is a good option for studying the envi-ronmental effect of the system. It has four phases that are part of the iterative study process. In this study the case environment is a waste power plant. The modeling of the plant is done with GaBi 6 software and the scope is from gate-to-grave. There are three different scenarios, from which the first and second are compared to each other to reach conclusions. Zero scenario is part of the study to demonstrate situation without the power plant. The power plant in this study is recycling some materials in scenario one and in scenario two even more materials and utilize the bottom ash more ways than one. The model has the substitutive processes for the materials when they are not recycled in the plant. The global warming potential results show that scenario one is the best option. The variable costs that have been considered tell the same result. The conclusion is that the waste power plant should not recycle more and utilize bottom ash in a number of ways. The area is not ready for that kind of utilization and production from recycled materials.

Identification of main contamination points by hygiene indicator microorganisms in beef processing plants

The microbiological quality of beef and meat products is strongly influenced by the conditions of hygiene prevailing during their production and handling. Without proper hygienic control, the environment in slaughterhouses and butcher shops can act as an important source of microbiological contamination. To identify the main points of microbiological contamination in the beef processing chain, 443 samples of equipment, installations and products were collected from 11 establishments (1 slaughterhouse and 10 butcher shops) located in the state of Paraná, Brazil. The microbiological quality of all the samples was evaluated using Petri dishes to obtain counts of mesophilic aerobes (AC), total coliforms, Escherichia coli (EC), yeasts and molds (YM). The main contamination points identified in butcher shops, in decreasing order, were stainless steel boxes, beef tenderizers, grinders, knives, mixers, sausage stuffers, plastic boxes, floors and drains. In the slaughterhouse, these points were sausage stuffers, platforms, floors and drains. The most severely contaminated products were fresh sausages and ground beef. This information about the main points of microbiological contamination in the beef processing chain is expected to aid professionals responsible for hygiene in similar establishments to set up proper hygienic procedures to prevent or reduce microbiological contamination of beef and meat products.

Offline Handwritten Malayalam Character Recognition Based on Chain Code Histogram

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification

Opalescence in Australian-grown pecan kernels: Occurrence and causes

Opalescence is an unattractive browning of the interior of the pecan kernel compared to the white interior of normal kernels. The discoloration is due to the presence of free oil, resulting from decompartmentalization in the endosperm of opalescent,pecans. Using a subjective scoring system, approximately 70% of Australian-grown pecan kernels tested were found to exhibit opalescence to some degree. Evaluation of kernels for opalescence during the harvesting-processing chain showed that opalescence first becomes evident in kernels after mechanical cracking. Opalescent kernels were found to have lower levels of calcium and higher amounts of oil compared to nonoptalescent kernels. Differential scanning calorimetry showed that kernels do not freeze at -18 degreesC.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Vähempiarvoisen kalan käsittelyketjut ja hiilijalanjälki

The condition of Baltic Sea has weakened considerably because of eutrophication which has caused massive increase of devalued fish. The condition of Baltic Sea can be helped by fishing these fish. This study handles three different ways to approach those fish utilizations and counts carbon footprint for those three chains. Environmental point of views are also examined. There are three different fish processing chains. Every processing chain begins with fishing the fish in Baltic Sea. After that the fishes are prepared by crushing and some formic acid is added to ensure preservation. In the first processing chain the fishes are processed as biodiesel. The waste from the biodiesel process is taken to the anaerobic digestion and the forming methane is used as energy. In the second chain the fishes are taken straight to the anaerobic digestion after preparing. In the third chain, the fish will be first prepared and then taken to fur farms as forage. The carbon footprint has been calculated for 1000 kg fish. The carbon footprint in the first chain is 164-178 kg CO2e, in the second chain 313 – 333 kg CO2e and in the third chain 363 kg CO2e. In the processing chains the bioenergy is produced from the biodiesel, anaerobic digestion and from the glycerol, which is by-product of the biodiesel. The energy produced from the biodiesel is so-called emission neutral, which is not taken into account when calculating emissions. The energy is used to compensate the emissions caused by fossil fuels. The PAS 2050 was used to calculate the carbon footprint. Only carbon dioxide and methane were used when calculating the carbon footprint.

Suunnittelulla ja ruo´on hyötykäytöllä tehokkuutta rantojen hoitoon : Tuloksia ja kokemuksia VELHO-hankkeesta

Varsinais-Suomen ELY-keskuksen toteuttamassa VELHO-hankkeessa kehitettiin kustannustehokkaita ratkaisuja ranta-alueiden umpeenkasvun aiheuttamiin ongelmiin luomalla uusi konsepti ranta-alueiden monikäyttösuunnitteluun, edistämällä järviruo’on hyötykäyttöä ja valmistelemalla esityksiä uuteen maaseudun kehittämisohjelmaan. Tässä julkaisussa esitellään työn tulokset ja johtopäätökset. Hankkeessa laadittiin kolme ranta-alueiden monikäyttösuunnitelmaa: Mynälahden Sarsalanaukko ja Musta-aukko, Oukkulanlahti – Naantalinaukko ja Eurajoen - Luvian rannikko. Suunnitelmissa sovitettiin yhteen ranta-alueiden eri käyttömuotoja ja pyrittiin löytämään optimaalinen verkosto hyötykäyttöön leikattavien ruovikoiden, avoimena pidettävien merenrantaniittyjen ja säilytettävien ruovikoiden välille. Kustannustehokkuuteen pyrittiin kohdentamalla hoitotoimet laajoihin kokonaisuuksiin sekä järviruo’on hyötykäytöllä. Suunnitelmat laadittiin laajassa osallistavassa prosessissa. Hankkeessa laadituissa ranta-alueiden monikäyttösuunnitelmissa esitettiin erilaisia maankäyttötavoitteita ja hoitosuosituksia yli 2000 hehtaarille. Ruovikoiden ja rantaniittyjen lisäksi suunnittelun kohteena olivat myös rantojen läheiset peltoalueet, reunavyöhykkeet ja muut perinnebiotoopit. Hoitotoimilla tavoitellaan alueiden luonnon monimuotoisuuden ja vesien tilan paranemista, maiseman avartumista ja virkistyskäytön helpottumista. Ruovikoiden erilaisia leikkuumenetelmiä (talvileikkuut, vesileikkuut, maaleikkuut) testattiin 90 hehtaarin alalla. Rantaniittyjen kunnostuksessa testattiin maaleikkuun lisäksi ruovikon niittomurskausta. Ruokomassan hyötykäyttökokeissa testattiin kahden eri ruokolaadun eli tuoreen kesäruo’on ja kuivan talviruo’on esikäsittelyä ja hyötykäyttöä energiantuotannossa (poltto, biokaasutus) ja maataloudessa (maanparannusaine, viherlannoite, kuivike, katemateriaali). Maaseudun kehittämisohjelmaan tehtiin esityksiä tukimuotojen kehittämiseksi: rantaniittyjen kunnostuksen lisääminen ja hoidon laadun parantaminen, ruovikoiden vesileikkuut ravinteiden poistajina sekä ruokomassojen käyttö maan orgaanisen aineen lisääjänä. Hankkeen kokemusten mukaan yksi kustannustehokkaimmista hoito- ja käyttöketjuista on ruovikon leikkuu loppukesällä ja siitä kertyvän massan käyttö ranta-alueiden läheisillä pelloilla viherlannoitteena ja maanparannusaineena. Yhden hehtaarin ruovikon kesäleikkuulla poistetaan keskimäärin 80 kg typpeä ja 7 kg fosforia. Vesiensuojelullisten hyötyjen lisäksi leikkuulla parannetaan umpeenkasvusta kärsivien lajien elinoloja, lisätään rantojen vetovoimaisuutta ja edistetään luonnonhoitoyrittäjyyden edellytyksiä. Peltokäytössä käsittelyketju on lyhyt eikä se vaadi pitkiä kuljetusmatkoja. Ruokomassa kierrättää ravinteita takaisin pelloille ja parantaa maan rakennetta. Järviruo’on hyötykäytöllä ei pystytä kattamaan koko leikkuu- ja käyttöketjun kustannuksia. Leikkuusta ja hyötykäytöstä saatavien monien eri aineellisten ja aineettomien ekosysteemipalveluhyötyjen vuoksi toimintaan on tarpeen suunnata yhteiskunnan tukea ja luoda käytännön toteutusta edistäviä tukimuotoja. Kustannustehokkuutta voidaan edelleen parantaa laitteita ja menetelmiä kehittämällä.

Modelling ecological values in heterogeneous and dynamic landscapes with geospatial data

Our surrounding landscape is in a constantly dynamic state, but recently the rate of changes and their effects on the environment have considerably increased. In terms of the impact on nature, this development has not been entirely positive, but has rather caused a decline in valuable species, habitats, and general biodiversity. Regardless of recognizing the problem and its high importance, plans and actions of how to stop the detrimental development are largely lacking. This partly originates from a lack of genuine will, but is also due to difficulties in detecting many valuable landscape components and their consequent neglect. To support knowledge extraction, various digital environmental data sources may be of substantial help, but only if all the relevant background factors are known and the data is processed in a suitable way. This dissertation concentrates on detecting ecologically valuable landscape components by using geospatial data sources, and applies this knowledge to support spatial planning and management activities. In other words, the focus is on observing regionally valuable species, habitats, and biotopes with GIS and remote sensing data, using suitable methods for their analysis. Primary emphasis is given to the hemiboreal vegetation zone and the drastic decline in its semi-natural grasslands, which were created by a long trajectory of traditional grazing and management activities. However, the applied perspective is largely methodological, and allows for the application of the obtained results in various contexts. Models based on statistical dependencies and correlations of multiple variables, which are able to extract desired properties from a large mass of initial data, are emphasized in the dissertation. In addition, the papers included combine several data sets from different sources and dates together, with the aim of detecting a wider range of environmental characteristics, as well as pointing out their temporal dynamics. The results of the dissertation emphasise the multidimensionality and dynamics of landscapes, which need to be understood in order to be able to recognise their ecologically valuable components. This not only requires knowledge about the emergence of these components and an understanding of the used data, but also the need to focus the observations on minute details that are able to indicate the existence of fragmented and partly overlapping landscape targets. In addition, this pinpoints the fact that most of the existing classifications are too generalised as such to provide all the required details, but they can be utilized at various steps along a longer processing chain. The dissertation also emphases the importance of landscape history as an important factor, which both creates and preserves ecological values, and which sets an essential standpoint for understanding the present landscape characteristics. The obtained results are significant both in terms of preserving semi-natural grasslands, as well as general methodological development, giving support to science-based framework in order to evaluate ecological values and guide spatial planning.

Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment

A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography-derived values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5m grids (grid-processed). LiDAR profiles were then compared to leaf biomass field profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests.

Lokal utveckling och företagssamverkan i träbranschen : Dokumentation och preliminär analys av ett 30-tal fall

Networks and cooperatives have become very common in the woodworking industry during the1990’s. As part of a research project on small enterprise development in the woodworking industry within the Target 6 area (in Sweden) of the European Community, this study follows the development of a dozen cooperative projects during the period 1997-2000. In order to broaden the knowledge base of the study, in 1998 we carried out a survey of cooperative ventures in the woodworking industry in the rest of the country, and collected information about their history, present situation and future strategy. Together with our own material we achieved a body of material consisting of some 30 cases which were subjected to exploratory analysis. We identified the following categories of projects and cooperative ventures; ”Local development projects”, ”Development networks”, ”Producer networks” and ”Development supporting networks”. Most of the producer networks were horizontally integrated but some of them were vertically integrated, along the processing chain from the forest to the customer. Nearly all the local development projects and the networks had been initiated within the last four years. It is, therefore, too early to make any conclusions about their success. Our main finding, so far, is that local development and the establishment of networks requires ”driving forces” in the form of committed individuals, time, money and project organisation. Most of the projects and networks were supported by public funds.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Utilização de bacteriófagos ambientais no controle de biofilmes de Salmonella spp. em superfícies utilizadas na indústria de processamento e comercialização de frango de corte e derivados

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

TDOA for Narrow-band Signal with Low Sampling Rate and Imperfect Synchronization

Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

SMARTnet: First Experience of Setting Up a Telescope System to Survey the Geostationary Ring

Space debris in geostationary orbits may be detected with optical telescopes when the objects are illuminated by the Sun. The advantage compared to Radar can be found in the illumination: radar illuminates the objects and thus the detection sensitivity depletest proportional to the fourth power of the d istance. The German Space Operation Center, GSOC, together with the Astronomical Institute of the University of Bern, AIUB, are setting up a telescope system called SMARTnet to demonstrate the capability of performing geostationary surveillance. Such a telescope system will consist of two telescopes on one mount: a smaller telescope with an aperture of 20cm will serve for fast survey while the larger one, a telescope with an aperture of 50cm, will be used for follow-up observations. The telescopes will be operated by GSOC from Oberpfaffenhofen by the internal monitoring and control system called SMARTnetMAC. The observation plan will be generated by MARTnetPlanning seven days in advance by applying an optimized planning scheduler, taking into account fault time like cloudy nights, priority of objects etc. From each picture taken, stars will be identified and everything not being a star is treated as a possible object. If the same object can be identified on multiple pictures within a short time span, the trace is called a tracklet. In the next step, several tracklets will be correlated to identify individual objects, ephemeris data for these objects are generated and catalogued . This will allow for services like collision avoidance to ensure safe operations for GSOC’s satellites. The complete data processing chain is handled by BACARDI, the backbone catalogue of relational debris information and is presented as a poster.

The ManTIS Field Spectro-Goniometer Movie - Presentation of the Instrument and Measurement Scheme

This article presents and technically describes a new field spectro-goniometer system for the ground-based characterization of the surface reflectance anisotropy under natural illumination conditions developed at the Alfred Wegener Institute (AWI). The spectro-goniometer consists of a Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS), and a hyperspectral sensor system. The presented measurement strategy shows that the AWI ManTIS field spectro-goniometer can deliver high quality hemispherical conical reflectance factor (HCRF) measurements with a pointing accuracy of ±6 cm within the constant observation center. The sampling of a ManTIS hemisphere (up to 30° viewing zenith, 360° viewing azimuth) needs approx. 18 min. The developed data processing chain in combination with the software used for the semi-automatic control provides a reliable method to reduce temporal effects during the measurements. The presented visualization and analysis approaches of the HCRF data of an Arctic low growing vegetation showcase prove the high quality of spectro-goniometer measurements. The patented low-cost and lightweight ManTIS instrument platform can be customized for various research needs and is available for purchase.