Pengaruh Kepuasan Gaji pada Keinginan untuk Pindah dengan Konflik Pekerjaan Keluarga sebagai Pemediasi (Studi pada Perusahaan Cooepariva Café Timor-national Cooperativa Business Asociation)

Tujuan penelitian ini adalah untuk mengetahui pengaruh kepuasan gaji terhadap keinginan untuk pindah dengan konflik pekerjaan keluarga sebagai variabel pemediasi. Populasi sebanyak 472 orang yang merupakan karyawan pada Perusahaan Cooperativa Café Timor-National Cooperativa Business Asociation (CCT-NCBA) diambil sampel sebanyak 100 orang, dengan menggunakan metode pengambilan sampel Convenience Sampling. Uji instrumen dilakukan melalui uji validitas dan reliabilitas yang menggunakan teknik Croanbach,s Alpha. Uji hipotesis menggunakan analisis regresi linear berganda. Berdasarkan hasil uji instrumen disimpulkan kepuasan gaji berpengaruh negatif terhadap keinginan untuk pindah. Konflik pekerjaan keluarga berpengaruh positif terhadap keinginan untuk pindah. Mediasi konflik pekerjaan keluarga berpengaruh positif terhadap kepuasan gaji dengan keinginan untuk pindah terbukti melalui pengujian analisis jalur yaitu pengaruh langsung kepuasan gaji dengan keinginan untuk pindah dengan perolehan nilai 0.178, kepuasan gaji terhadap konflik pekerjaan keluarga = 0.341 dan konflik pekerjaan keluarga terhadap keinginan untuk pindah dengan nilai 0.527 dan pengaruh tidak langsungnya = 0.180. Dalam upayanya menurunkan Turnover Intention implikasi yang dapat dilakukan Cooperativa Café Timor-National Business Asociation adalah meningkatkan nilai gaji yang diberikan kepada karyawannya, memberikan tunjangan yang dapat meringankan beban kebutuhan karyawan, meningkatkan hubungan antara sesama karyawan dan pimpinan, memberikan kesempatan kepada karyawan untuk meningkatkan kemampuaannya melalui pendidikan formal, meningkatkan loyalitas karyawan terhadap Perusahaan dengan memberikan setiap kebutuhan dan keinginan karyawan dan meningkatkan kesadaran kepada karyawan bahwa karyawan memiliki peran yang sangat penting dalam memajukan Perusahaan

EC2 model applied to the prediction of mechanical properties of soil cement based on test results at early ages

O modelo analítico proposto pelo Eurocódigo 2 (EC2) para a previsão das propriedades mecânicas do betão ao longo do tempo tem mostrado resultados bastante satisfatórios quando adaptado a formulações laboratoriais de Jet Grouting (JG) e de Cutter Soil Mixing (CSM). No entanto, apresenta com principal limitação o facto de estar dependente da realização de ensaios experimentais aos 28 dias de cura para a quantificação das respetivas propriedades, o que limita a sua aplicabilidade em fases mais avançadas do projeto, nomeadamente para fins de controlo de qualidade. No presente artigo o modelo analítico proposto pelo EC2 para a previsão da resistência e rigidez do betão é adaptado a formulações laboratoriais de JG e CSM. Em particular, a abordagem do EC2 é adaptada no sentido de considerar resultados laboratoriais a idades jovens, nomeadamente aos 3, 7 e 14 dias de cura, em substituição dos convencionais 28 dias. Os resultados obtidos mostram que o desempenho do modelo do EC2 aumenta proporcionalmente à idade dos resultados experimentais considerados. Contudo, observou-se também apenas uma ligeira diferença entre o desempenho do modelo do EC2 considerando resultados experimentais aos 14 e aos 28 dias, o que permite fazer um balanceamento entre a precisão do modelo e o tempo/custos totais do projeto.The Eurocode 2 (EC2) approach for strength and stiffness prediction of concrete has been successful adapted to soil-cement laboratory formulations for Jet Grouting (JG) and Cutter Soil Mixing (CSM) technologies. However, its dependence of 28 days test result represents an important limitation. Accordingly, in the present work EC2 approach is modified in order to use laboratory reference data at early ages (e.g. 3, 7 or 14 days) and the achieved results are compared with the conventional 28 days time of cure. As expected, the achieved results show a decrease in EC2 approach performance when reference data at early ages are used. However, it is also observed just a slightly difference in EC2 approach performance when test data at 14 days or 28 days are used. This observation allows us to balance the model prediction accuracy and time consuming in the final project and construction work costs

A data mining approach for jet grouting uniaxial compressive strength prediction

Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a great versatility, being the best solution for several soil treatment improvement problems. However, JG lacks design rules and quality control. As the result, the main JG works are planned from empirical rules that are often too conservative. The development of rational models to simulate the effect of the different parameters involved in the JG process is of primary importance in order to satisfy the binomial safety-economy that is required in any engineering project. In this work, three data mining models, i.e. Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Functional Networks (FN), were adapted to predict the Uniaxial Compressive Strength (UCS) of JG laboratory formulations. A comparative study was held, by using a dataset used that was obtained from several studies previously accomplished in University of Minho. We show that the novel data-driven models are able to learn with high accuracy the complex relationships between the UCS of JG laboratory formulations and its contributing factors.Tecnasol-FG

Application of data mining techniques in the estimation of the uniaxial compressive strength of jet grouting columns over time

Jet grouting (JG) is a soil treatment technique which is the best solution for several soil improvement problems. However, JG lacks design rules and quality controls. As a result, the main JG works are planned from empirical rules that are too conservative. The development of rational models to simulate the effects of the different parameters involved in the JG process is of primary importance in order to satisfy the binomial safety-economy that is required in any engineering project. In this paper, we present a new approach to predict the uniaxial compressive strength (UCS) of JG materials based on data mining techniques. This model was developed and verified using data from a JG laboratory formulation that involves the measurement of UCS. The results of the proposed approach are compared with the EC2 analytical model adapted to the JG material, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the UCS of JG material and its contributing factors.Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/ 45781/2008Tecnasol-FG

Support vector machines in mechanical properties prediction of jet grouting columns

Strength and stiffness are the mechanical properties currently used in geotechnical works design, namely in jet grouting (JG) treatments. However, when working with this soil improvement technology, due to its inherent geological complexity and high number of variables involved, such design is a hard, perhaps very hard task. To help in such task, support vector machine (SVM), which is a data mining algorithm especially adequate to explore high number of complex data, can be used to learn the complex relationship between mechanical properties of JG samples extracted from real JG columns (JGS) and its contributing factors. In the present paper, the high capabilities of SVM in Uniaxial Compressive Strength (UCS) and Elastic Young Modulus estimation of JG laboratory formulations are summarized. After that, the performance reached by the same algorithm in the study of JGS are presented and discussed. It is shown, by performing a detailed sensitivity analysis, that the relation between mixture porosity and the volumetric content of cement, as well as the JG system are the key variables in UCS prediction of JGS. Furthermore, it is underlined the exponential effect of the age of the mixture in UCS estimation as well as the high iteration between these two key variables.Fundação para a Ciência e a Tecnologia (FCT

Application of a sensitivity analysis procedure to interpret uniaxial compressive strength prediction of jet grouting laboratory formulations performed by SVM model

Jet Grouting (JG) technology, one of the most efficient soft soils improvement methods, has been widely applied in important geotechnical works due to its versatility. However, there is still an important limitation to overcome related with the absence of rational approaches for its design. In the present work, three different Data Mining (DM) techniques, i.e., Artificial Neuronal Networks (ANN), Support Vector Machines (SVM) and multiple regression are trained in order to predict elastic young modulus (E0) of JG mixtures. It is shown that the complex relationships between E0 and its contribut- ing factors can be learned using DM tools, particularly by SVM and ANN algorithms. By performing a detailed sensitivity analysis, understandable knowledge is extracted from the trained models, in terms of the relative importance of the attributes, as well as its effect in E0 prediction. In addition, the mathemati- cal expression proposed by Eurocode 2 to estimate concrete stiffness, is adapted to JG material. Its low performance is assessed and compared with those achieved by DM models.The authors wish to thank to “Fundação para a Ciência e a Tecnologia” (FCT) for the finan- cial support under the strategic project PEst-OE/ ECI/UI4047/2011 and the doctoral Grant SFRH/ BD/45781/2008Tecnasol-FG

Transarterial embolisation of a large focal nodular hyperplasia, using microspheres, in a paediatric patient

Benign liver tumours are uncommon in children, haemangiomas being the most frequent. Focal nodular hyperplasia (FNH) represents about 2% of paediatric liver tumours. In children, as in adults, a conservative approach is generally recommended. However, large lesions (greater than 5 cm) are more frequent in the paediatric age group, and in these cases, as well as in growing lesions, surgical removal may be advised. Transarterial embolisation (TAE) has been a successful alternative option described in older patients, especially in cases where surgical removal is not possible. This minimally invasive procedure may also become an option in the paediatric group. The authors report the case of a boy with a large FNH treated with TAE using microspheres