When vocabulary teaching is taken into account in EFL classes in Turkish state primary schools, teachers generally prefer to use classical techniques. The purpose of this study is to find out the effect of a relatively new vocabulary teaching technique; teaching vocabulary through collocations. Pre-test/Post-test Control Group Design was employed in this study.Fifty-nine (59) seventh (7th) grade students from two classrooms in a lower-middle class, suburban state primary school in Konya, Turkey participated in this study. The experimental group was taught new words using collocation technique; the control group was taught new words using classical techniques such as synonym, antonym, definition and mother tongue translation as it was in the previous reading classes before the study. The statistical analysis revealed that teaching vocabulary through collocations results in a better learning of the words than presenting them using classical techniques and enhances retention of new vocabulary items. Teaching vocabulary through collocations can be an effective factor in helping students remember and use the new words easily in primary school EFL classes. Therefore, teachers of English could be encouraged to attach more importance to vocabulary teaching rather than the acquisition of grammar and the use of current vocabulary teaching strategies in their classes.

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In this work, breast cancer treatment methods are determined using data mining. For this purpose, software is developed to help to oncology doctor for the suggestion of application of the treatment methods about breast cancer patients. 462 breast cancer patient data, obtained from Ankara Oncology Hospital, are used to determine treatment methods for new patients. This dataset is processed with Weka data mining tool. Classification algorithms are applied one by one for this dataset and results are compared to find proper treatment method. Developed software program called as "Treatment Assistant" uses different algorithms (IB1, Multilayer Perception and Decision Table) to find out which one is giving better result for each attribute to predict and by using Java Net beans interface. Treatment methods are determined for the post surgical operation of breast cancer patients using this developed software tool. At modeling step of data mining process, different Weka algorithms are used for output attributes. For hormonotherapy output IB1, for tamoxifen and radiotherapy outputs Multilayer Perceptron and for the chemotherapy output decision table algorithm shows best accuracy performance compare to each other. In conclusion, this work shows that data mining approach can be a useful tool for medical applications particularly at the treatment decision step. Data mining helps to the doctor to decide in a short time.

One goal of the Toyota production system is a level usage of parts in assembly. To this end Toyota developed a 'goal chasing' algorithm for sequencing vehicles in its assembly plants. Since the goal chasing method I was computationally too burdensome for most real-world applications, Toyota developed a faster version called the' goal chasing method 2.' While this modified version performs well in automotive assembly for which it was designed, it cannot sequence products with non-zero/one part requirements. For example printed circuit boards have non-zero/one product-part usage matrices. These and other electronic products can have any number of a particular chip, resistor, capacitor, or other electronic component. Hence the product-part usage matrix for these electronic products is not zero/one, and the goal chasing method 2 cannot be used. We present another modification of the goal chasing algorithm that is faster than Toyota's goal chasing method 2, and can sequence products with non-zero/one product-part usage matrices.