Inclusion or Exclusion? Trade union strategies and Labor migration

Inclusion or Exclusion? Trade Union Strategies and Labor Migration This research identified and analyzed immigration-related strategies of the Finnish Construction Trade Union (FCTU) and the Service Union United (SUU); e.g. how the unions react to labor immigration, whether unions seek to include migrants in the unions, and what is migrants’ position in the unions. The two unions were chosen as the focus of the research because the workforce in the sectors they represent is migrant-dense. The study also analyzed the experiences that migrants who work in these sectors have with trade unions. The Estonian labor market situation –including the role of Estonian trade unions– was also examined as it has a considerable impact on the operating environment of the FCTU. The results of the study indicate that immigration is a contradictory issue for both unions. On the one hand, they strive to include migrants as trade union members and to defend migrants’ labor rights. On the other hand, they, together with their umbrella organization the Central Organisation of Finnish Trade Unions (SAK), seek to prevent labor immigration from outside the EU and EEA countries. They actively defend current labor immigration restrictions by drawing atten- tion to high unemployment figures and to the breaches of working conditions migrants encounter. In contrast, the employer organizations promote a more liberal state policy on labor immigration because they see it as a boost for business. Both the unions and the employer organizations ground their arguments on national interest. However, the position of the trade union movement is not uniform: unions belonging to the Confederation of Unions for Professionals and Managerial Staff in Finland (Akava) embrace more liberal labor immigration stances than the SAK. A key trade union strategy is to try to guarantee that migrants’ working condi- tions do not differ from those of the natives. The FCTU and the SUU inform migrants about Finnish collective agreements and trade union membership in the most common migrant languages. This is important for the unions because it is not in their interest that migrants’ working conditions are undercut. The interviewed migrants said that natives had more negotiating power with employers, which is often negatively portrayed in migrants’ working conditions. Migrants perceive that trade unions have an important role in protecting their working conditions. However, they stressed that migrants’ knowledge of unions is often very limited. The number of migrants in both two unions studied here is increasing. Espe- cially in the SUU, a considerable proportion of the new members are migrants. The FCTU is in a more challenging situation than the SUU because migrant construc- tion workers often work only for short periods in Finland and are consequently not interested in becoming union members. The unions’ strategies partly differ: the FCTU was the first Finnish trade union to establish a trade union branch/lo- cal for migrant members. The goal is to facilitate migrants’ inclusion in the union and to highlight the specific problems they face. The SUU, for its part, insists that such a special strategy would exclude migrants within the union organization. Despite the unions’ strategies, migrants are still underrepresented as union members and officials, which some of the interviewed migrants saw as a problem. Immigrants’ perception of trade unions was pragmatic: they had joined unions when membership yielded concrete benefits. In spite of the unions’ strategies, migrants –and temporary migrants– encoun- ter specific problems in terms of working conditions. Both unions demand more state intervention to protect migrants’ labor rights because overseeing working conditions consumes union resources. However, without the unions’ intervention, these problems would be more common than is currently the case. For instance, some of the interviewed migrants had received trade union assistance in claim- ing unpaid wages. The study demonstrated with the help of building on Walter Korpi’s power resources theory, that immigration is a power resource issue for the unions: suc- cessful immigration-related strategies strengthen unions –and vice versa. The research also showed how the unions’ operating environments constrain and enable their immigration-related strategies. This study has illuminated a previously ignored dimension: the immigrant- inclusive strategies of the Finnish trade unions. The research material consists of 78 qualitative interviews, observation in trade union events, and trade unions’ and employer organizations’ public state- ments.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.

Controlling full penetration in MAG welding by the application of infrared thermography and neural network

In this study, an infrared thermography based sensor was studied with regard to usability and the accuracy of sensor data as a weld penetration signal in gas metal arc welding. The object of the study was to evaluate a specific sensor type which measures thermography from solidified weld surface. The purpose of the study was to provide expert data for developing a sensor system in adaptive metal active gas (MAG) welding. Welding experiments with considered process variables and recorded thermal profiles were saved to a database for further analysis. To perform the analysis within a reasonable amount of experiments, the process parameter variables were gradually altered by at least 10 %. Later, the effects of process variables on weld penetration and thermography itself were considered. SFS-EN ISO 5817 standard (2014) was applied for classifying the quality of the experiments. As a final step, a neural network was taught based on the experiments. The experiments show that the studied thermography sensor and the neural network can be used for controlling full penetration though they have minor limitations, which are presented in results and discussion. The results are consistent with previous studies and experiments found in the literature.

Mémoire sur les ville et tour de Crest

Ancien possesseur : Argenson, Antoine-René de Voyer (1722-1787 ; marquis de Paulmy d')

Dragon (Jean). Album des amis de Jean Dragon, professeur à l'académie de Die et pasteur de Crest.

Il contient des inscriptions et des signatures recueillies entre les années 1599 et 1615 à Genève et dans le Dauphiné. On y remarque celles qui émanent des personnages suivants : " Is. Casaubonus (fol. 17), Theodorus Beza (fol. 112), Joannes Vulso Columberius (fol. 142), Joannes Leslaeus a Crychy Scotus (fol. 144), Jacobus Goulartius Genevensis (fol. 175), Johannes Goulartius Genevensis (fol. 175 v°). " Petit volume de 181 feuillets, hauts de 153 millimètres et larges de 98. On a fait servir à la composition de cet album : 1° 96 feuillets appartenant à douze cahiers signés A-M, ornés d'encadrements variés et sur les rectos desquels avaient été imprimés les médaillons de personnages célèbres, et des devises en grec, en latin, en allemand, en français, en italien et en espagnol ; 2° 85 feuillets à encadrements variés.