Anaerobic biodigestion of pigs feces in the initial, growing and finishing stages fed with diets formulated with corn or sorghum

The objective of this study was to evaluate the quality and the production of biogas and biofertilizer obtained from biodigester supplied with pig feces in the initial, growing and finishing stages, fed with diets formulated based on corn or sorghum. Twenty bench biodigesters were used with hydraulic retention time of 30 days and daily loads that contained 4 to 6% of total solids (TS) and 3.6 to 5.2% of volatile solids (VS). In the effluent of the biodigesters, mean levels of TS were observed ranging between 1.6 and 2.0% and of VS between 1.2 and 1.6%. The mean reductions of TS were 57.7 to 64.7% and of VS from 61.7 to 69.0%, and there was only difference in the finishing phase, in which the major averages reductions were produced by the biodigesters supplied with feces from animals fed with diets based on corn. In biodigesters supplied with feces from animals in the initial and growing stages fed with diets based on corn, were observed higher average productions of biogas and the greatest average potentials of biogas production. The average potentials obtained were 0.033; 0.181; 0.685; 0.788 and 1.132 m³ per kg of affluent, manure, TS added, VS added and VS reduced, respectively. No differences were found on the average content of methane in the biogas between diets and stages. The average concentrations of nutrients N, P, K, Ca, Mg, Na, Fe, Mn, Zn and Cu in the biodigester affluent and effluent, ranged between diets and stages.

Nocturnal thermal comfort in facilities for growing swines

In most of Brazilian pig farms, the environmental acclimatization systems run manually. For night and early morning periods, this practice isn't appropriate, because, in general, there are not employees available to run these manual systems. This research aimed to compare the bioclimatic profile of two differently constructed facilities to the external environment, considering the period from 6 p.m. to 6 a.m. during the spring, in order to show that night and early morning temperatures do not coincides with growing pig's thermoneutral zone. For this reason, acclimatization must be also carried out at these periods. It was analyzed the dry bulb temperature, relative air humidity, temperature-humidity index (THI) and enthalpy data of the sheds and external areas. Under the studied conditions, it was possible to conclude that the constructively appropriate shed appeared to be less influenced by the external environment, allowing better thermal control for growing pigs. Further research must be conducted to verify if automatic cooling systems is needed during night and early morning.

Influence of distance, geometry and number of control stations on quality of local geodetic networks for the purpose of georeferencing of rural properties

The implementation of local geodetic networks for georeferencing of rural properties has become a requirement after publication of the Georeferencing Technical Standard by INCRA. According to this standard, the maximum distance of baselines to GNSS L1 receivers is of 20 km. Besides the length of the baseline, the geometry and the number of geodetic control stations are other factors to be considered in the implementation of geodetic networks. Thus, this research aimed to examine the influence of baseline lengths higher than the regulated limit of 20 km, the geometry and the number of control stations on quality of local geodetic networks for georeferencing, and also to demonstrate the importance of using specific tests to evaluate the solution of ambiguities and on the quality of the adjustment. The results indicated that the increasing number of control stations has improved the quality of the network, the geometry has not influenced on the quality and the baseline length has influenced on the quality; however, lengths higher than 20 km has not interrupted the implementation, with GPS L1 receiver, of the local geodetic network for the purpose of georeferencing. Also, the use of different statistical tests, both for the evaluation of the resolution of ambiguities and for the adjustment, have enabled greater clearness in analyzing the results, which allow that unsuitable observations may be eliminated.

Application of artificial neural networks as an alternative to volumetric water balance in drip irrigation management in watermelon crop

Precision irrigation seeks to establish strategies which achieve an efficient ratio between the volume of water used (reduction in input) and the productivity obtained (increase in production). There are several studies in the literature on strategies for achieving this efficiency, such as those dealing with the method of volumetric water balance (VWB). However, it is also of great practical and economic interest to set up versatile implementations of irrigation strategies that: (i) maintain the performance obtained with other implementations, (ii) rely on few computational resources, (iii) adapt well to field conditions, and (iv) allow easy modification of the irrigation strategy. In this study, such characteristics are achieved when using an Artificial Neural Network (ANN) to determine the period of irrigation for a watermelon crop in the Irrigation Perimeter of the Lower Acaraú, in the state of Ceará, Brazil. The Volumetric Water Balance was taken as the standard for comparing the management carried out with the proposed implementation of ANN. The statistical analysis demonstrates the effectiveness of the proposed management, which is able to replace VWB as a strategy in automation.

Energetic sustainability of three arabica coffee growing systems used by family farming units in Espírito Santo state

Three growing systems of Arabica coffee were evaluated under the energy perspective, in the state of Espírito Santo in Brazil. The systems are conventional cultivation (CC), cultivation with good agricultural practices (CGP) and organic farming (OF). It was made a comparison of the energy flows within these three systems to show sustainable levels of each one based on production average data of several family-farming units. Therefore, we analyzed crop yield, total energy efficiency reverse (TEER), energy efficiency of ripe coffee (EERC) and non-renewable energy efficiency (NREE). OF system had values for TEER, EERC and NREE of 3.3 4.7 and 7.9 respectively. Yet CC showed values of 1.8, 1.9 and 1.6 for TEER, EERC and NREE respectively. Furthermore, CGP presented values for TEER, EERC and NREE of 0.7, 1.3 and 1.4 respectively. The highest yield was observed in CGP, reaching an amount of 1794 kg ha-1(17,455 MJ); however, this system expends more energy than it converts. Thus, over those points, OF is the most sustainable system.

Deficit irrigation in grapevine cv. Syrah during two growing seasons in the brazilian semiarid

Irrigation plays an important role for grape’s yield as well as on its quality for winemaking. Thus, the effects of deficit irrigation strategies on yield and quality of wine grapes cv. Syrah were evaluated in Petrolina, State of Pernambuco, Brazil. Evaluations were carried out throughout the second and third growing seasons, which were from November 2010 to February 2011 (rainy season) and from May to September 2011 (dry season), respectively. Vines were drip irrigated and the experimental design was completely randomized with three treatments and four replications. The treatments were full irrigation (FI), performed according crop evapotranspiration; regulated deficit irrigation (RDI), in which irrigation was interrupted in phenological growth stage of bunch closure, but was occasionally performed according soil water monitoring of the root zone; and deficit irrigation (DI), when irrigation was interrupted from bunch closure to harvesting. Differences on leaf water content among treatments were observed in both growing seasons and RDI and DI treatment plants presented moderate water stress. The number of bunches did not differ among treatments in both growing seasons; however, bunch weight per plant, average bunch weight and soluble solid content were higher in FI treatment during the dry season. Deficit irrigation strategies promoted water saving.

Techno-Economic Feasibility of Novel On-Line Condition Monitoring Methods in Low Voltage Distribution Networks

The focus in this thesis is to study both technical and economical possibilities of novel on-line condition monitoring techniques in underground low voltage distribution cable networks. This thesis consists of literature study about fault progression mechanisms in modern low voltage cables, laboratory measurements to determine the base and restrictions of novel on-line condition monitoring methods, and economic evaluation, based on fault statistics and information gathered from Finnish distribution system operators. This thesis is closely related to master’s thesis “Channel Estimation and On-line Diagnosis of LV Distribution Cabling”, which focuses more on the actual condition monitoring methods and signal theory behind them.

Knowledge sharing in intrafirm networks in organization

The objective of this study was research the shared knowledge and the means of sharing with the help of social network analysis. The purpose of this study was to give descriptive information to case-organization about its situational network status in different units. The premise of the study is the success of organizational competences and networks, especially when it comes to the sharing of knowledge. The research was accomplished in a TEKES –projects, Developing Network-Based Services – The Role of Competences and Networks COMNET –projects case-organization. Lappeenranta School of Business and the case-organization started the project in co-operation. The baseline for the study was organizational competencies and organizational networks as success factors, especially from the knowledge sharing’s point of view. The research was based on triangulation, which included pre-interviews, network analyses accomplished by Webropol –e-mail survey and qualitative interviews. The results indicated that regular unit meetings were experienced to be the most important method of knowledge sharing along with e-mailing, intranet and weekly bulletins. The co-operation between units was also experienced to be important when evaluating knowledge sharing and communication. The intrafirm network was experienced tight. Dispersed units and partly unclear means of information sharing were the biggest obstacles for information communication. Knowledge sharing, communication with others and trainings were seen important in the case-organization.

The challenges and success factors of commercializing cleaner technologies

Cleaner technologies include products, services, technologies, processes and systems that in use create less environmental hazard than the existing alternatives. Rapidly growing cleantech sector possesses an essential competitive advantage in the future. However, no profound research has been conducted on the characteristics of cleaner technologies and their effect on the commercialization process. This thesis aims at synthesizing scattered information and creating a basis for accelerating cleaner technology commercialization in Finnish context. Two research questions are defined: 1. What are the key challenges and success factors in the commercialization of cleaner technologies based on the existing literature? 2. What kind of lessons can be learned from the Finnish success stories of cleantech commercialization? The research was conducted as a literature review and supported with three case interviews. The results suggest that literature-based challenges are mostly related to, for example, difficulty in gathering customer information, unrealistic customer expectations, lack of resources, networks and proper success indicators, legislation, and unstructured strategy planning stemming from company culture. Handling the barriers require, above all, open communication from all stakeholders, management commitment and accurate goal setting, government-driven funding and incentives, and cooperation with educational facilities. Finnish success cases emphasize especially customer attention: listening to customers and receiving feedback from them during the whole commercialization process to correct the errors early and save resources, visionary in fulfilling customer needs, ability to question company’s own business performance, not being afraid of making mistakes but learning from them, and continuously observing and evaluating the commercialization process.

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.

Asiakastarpeiden kartoitus kuljetusten häiriöiden analysoinnin ja hallinnan kehittämiseksi

Tämä diplomityö on tehty osana Logproof-tutkimushanketta, joka keskittyy häiriöttömyyden hallintaan logistisissa monitoimijaverkostoissa. Työn tavoitteena on selvittää logistiikkaintensiivisten yritysten tarpeita kuljetusten häiriöiden analysoinnin ja hallinnan kehittämiseksi ja siten ennakoivan riskienhallinnan edistämiseksi. Asiakastarvetietoa on kerätty hyödyntäen puolistrukturoituja haastatteluja ja tietoa on analysoitu käyttäen hyväksi sisällönanalyysiä sekä tulkintataulukkoa. Kiinnostus kuljetusten häiriöitä ja niiden analysointia kohtaan on kasvamassa ja yrityksissä tiedostetaan hallintajärjestelmien ja analysoinnin tarve tulevaisuudessa. Kirjallisuuskatsauksen ja asiakastarpeiden kartoituksen avulla työssä on selvitetty yritysten nykytilaa kuljetusten häiriöiden hallinnan ja analysoinnin osalta ja tarkasteltu mahdollisia tulevaisuuden kehityssuuntia analysoimalla asiakkaiden näkyviä ja piileviä tarpeita. Työssä on edellisten lisäksi tarkasteltu, kuinka havaitut asiakastarpeet ovat sovitettavissa yhteen case-yrityksen, Oy Lars Krogius Ab:n, ARS (Analytic Rou-ting Solution) -palvelun ominaispiirteiden kanssa. Työ tarjoaa tarvetietoa palvelun tulevaisuuden kehitykselle.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Reusable formal architectures for networked systems

Today's networked systems are becoming increasingly complex and diverse. The current simulation and runtime verification techniques do not provide support for developing such systems efficiently; moreover, the reliability of the simulated/verified systems is not thoroughly ensured. To address these challenges, the use of formal techniques to reason about network system development is growing, while at the same time, the mathematical background necessary for using formal techniques is a barrier for network designers to efficiently employ them. Thus, these techniques are not vastly used for developing networked systems. The objective of this thesis is to propose formal approaches for the development of reliable networked systems, by taking efficiency into account. With respect to reliability, we propose the architectural development of correct-by-construction networked system models. With respect to efficiency, we propose reusable network architectures as well as network development. At the core of our development methodology, we employ the abstraction and refinement techniques for the development and analysis of networked systems. We evaluate our proposal by employing the proposed architectures to a pervasive class of dynamic networks, i.e., wireless sensor network architectures as well as to a pervasive class of static networks, i.e., network-on-chip architectures. The ultimate goal of our research is to put forward the idea of building libraries of pre-proved rules for the efficient modelling, development, and analysis of networked systems. We take into account both qualitative and quantitative analysis of networks via varied formal tool support, using a theorem prover the Rodin platform and a statistical model checker the SMC-Uppaal.

Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

A cyber security architecture for military networks using a cognitive network approach

Cyber security is one of the main topics that are discussed around the world today. The threat is real, and it is unlikely to diminish. People, business, governments, and even armed forces are networked in a way or another. Thus, the cyber threat is also facing military networking. On the other hand, the concept of Network Centric Warfare sets high requirements for military tactical data communications and security. A challenging networking environment and cyber threats force us to consider new approaches to build security on the military communication systems. The purpose of this thesis is to develop a cyber security architecture for military networks, and to evaluate the designed architecture. The architecture is described as a technical functionality. As a new approach, the thesis introduces Cognitive Networks (CN) which are a theoretical concept to build more intelligent, dynamic and even secure communication networks. The cognitive networks are capable of observe the networking environment, make decisions for optimal performance and adapt its system parameter according to the decisions. As a result, the thesis presents a five-layer cyber security architecture that consists of security elements controlled by a cognitive process. The proposed architecture includes the infrastructure, services and application layers that are managed and controlled by the cognitive and management layers. The architecture defines the tasks of the security elements at a functional level without introducing any new protocols or algorithms. For evaluating two separated method were used. The first method is based on the SABSA framework that uses a layered approach to analyze overall security of an organization. The second method was a scenario based method in which a risk severity level is calculated. The evaluation results show that the proposed architecture fulfills the security requirements at least at a high level. However, the evaluation of the proposed architecture proved to be very challenging. Thus, the evaluation results must be considered very critically. The thesis proves the cognitive networks are a promising approach, and they provide lots of benefits when designing a cyber security architecture for the tactical military networks. However, many implementation problems exist, and several details must be considered and studied during the future work.