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    Analysis of sports injuries related with shooting
    (Edizioni Minerva Medica, 2016) Kabak, Banu; Karanfilci, Muharrem; Ersoz, Taner; Kabak, Mehmet
    BACKGROUND: Athletes typically maintain rigorous training and work programs to be able to participate in competitions. An injury that occurs during the competition that causes withdrawal from the competition and a possible departure from sports, can render results athletes' and their support staff's efforts as meaningless. The early detection of injuries in the competition and developing preventive training programs can help ensure that participating in competitions and the associated preparatory efforts are not wasted. In this study, the sports injuries discussed occurred during training and competition events of the Turkish Shooting Sportive group. Body parts of injuries are determined and exercise programs focused on the affected body parts are developed. METHODS: A total of 729 athletes (285 female, 444 male) who participated in Turkish Shooting Sports Championship during the 2010-2011 competition period participated in the study. Athletes were given a questionnaire that was developed prior to the event, and the questionnaire was filled in during interviews conducted one-on-one. Data was collected from the questionnaire and SPSS v.16.0 was used to analyze the results. The study was completed in six months. RESULTS: The results showed that the most of the injuries that occurred during training were strain and muscle tears whereas most of the injuries occurred during the actual competition were strain, muscle tears, tendinitis, and sprain. The results also indicated that during training, the most frequently-occurring injuries were in shoulder, calf-thigh, hand and wrist; whereas during the competition, it was manifested in the shoulder, foot and ankle. CONCLUSIONS: Muscle strengthening, stretching and proprioception exercises for these body parts should be included as part of the athletic training program.
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    Defective products management in a furniture production company: A data mining approach
    (Wiley, 2022) Ersoz, Taner; Guven, Ilker; Ersoz, Filiz
    Quality is one of the main focuses of the manufacturing companies. Therefore, this issue takes attention of many researchers from both academic and professional environment. In industries like furniture where company types are most likely workshop or small-medium enterprise and production method is traditional, effective methods to prevent faulty production must be considered. Traditional or statistical methods are good to track defective products and keep the within desired levels, however not as good to prevent them from occurring. These methods come with an acceptance to some level of defective production. In this study, it is aimed to evaluate the in the furniture production sector and to reveal the source of the defective production and the factors that cause the defect in terms of which department. In addition, finding the most appropriate methods to accurately analyze the data coming from the company is another research topic of this study. In the research, artificial neural networks and decision tree models were established and inferences were made from the data sets. The model established in the application revealed the causes of the problems experienced in the production process of the company, thus root cause of defective products can be found and prevented. By using data mining techniques, this study developed an effective approach to improve the quality of the production process and to predict and prevent errors before they occur. According to results of the study classification and regression tree algorithm outperformed other methods by yielding 90.12% correct prediction rate. 87.5% of the defects caused by cover and seat cushion problems account for defects in the textile department.
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    ESTIMATION OF CORRUGATED BOARD BOX PRICE CHANGES IN THE FOOD INDUSTRY
    (Rtu Press, 2018) Ersoz, Taner; Alanlar, Ezgi
    It is important to predict the value of variables like prices of financial assets and values of indexes. Various model are developed continuously for this aim. In this study, the rates of price changes that could occur in corrugated cardboard boxes were estimated by linear regression analysis. The aim of the study is to estimate the rate of change in the corrugated board box industry which has recently been experiencing price changes and to contribute to the company's evaluations on the subject.
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    Predictive analytics in human resources using machine learning and data mining
    (2023) Ersoz, Taner; Ersoz, Filiz; Bedir, Emre
    Human resource management information systems (HRIS) are rapidly evolving as a result of today's technologies and global technological developments. With the digitalization of businesses, it is widely used in predictive applications in human resources (HR) and HRIS. HR and HRIS, better managing human resources data and making more accurate and reliable decisions are of critical importance for businesses. In this field, data mining and machine learning approaches are used to reveal meaningful relationships and trends between data in management decisions through predictive analysis. Both approaches are very important in the field of HR and are very effective for businesses to transform data sets into useful information. It helps businesses understand trends that can lead to more accurate and reliable business decisions by using analytical capabilities. Within the scope of this study, research was conducted on the use of the HRIS system with white-collar employees of a company in the automotive sector in Bursa. The cost, time saving and strategic impact of the human resources information system on the company and information technology infrastructure, its differences and relationships according to the department worked, age, gender and education level were investigated through statistics and data mining. Knime and SPSS Statistics programs, which are machine learning tools, were used in the research. HRIS results were evaluated and suggestions were made for future planning.
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    Process Improvement in Furniture Manufacturing: A Case Study
    (Ieee, 2018) Ersoz, Filiz; Ersoz, Taner; Peker, Hamza
    Today, with the increasing competition, enterprises are working to increase the product quality in order to meet the demands of the customers and increase the market share. The Six Sigma philosophy that emerged in the 1970s is a study to reduce the costs of poor quality in the production and service process. In this study, Six Sigma philosophy was applied in order to reduce the cycle time of the diamond sofa product produced by a furniture enterprise. Firstly, the production line was examined in detail by SIPOC analysis method and the cycle times of the processes were collected by chronometry method. Then, statistical methods such as project identification document, Pareto diagram, Fishbone diagram were used. The control of the change in cycle time in the production of diamond sofa was calculated by ARENA 9.0 simulation program.
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    Statistical analysis of water discharging from rocks of different origin: a case study from Turkey
    (Springer, 2016) Keskin, Tulay Ekemen; Kacaroglu, Fikret; Ersoz, Taner; Dugenci, Muharrem
    The present study was conducted in Sivas, Karabuk and Bartin regions of Turkey, which have rocks of different origins, agricultural and mining activities. Correlation, principal components, hierarchical cluster and multidimensional scaling analyses were applied to determine the processes controlling the chemical composition of groundwater. The results show that dissolution-weathering process, agricultural activities, oxidation processes of sulfide minerals, mining activities, coal levels, alteration of volcanics and progressive silicate hydrolysis effects the physicochemical properties of groundwater in the study areas. Principal components and multidimensional scaling analyses provided excellent visual representations of the grouping of the waters. The significant variables in the first factor are SO4, Mn, Fe, Al, and pH. The factor represents the groundwater reached by these elements via the dissolution and oxidation processes of sulfide minerals (especially pyrite). Ca, EC, and HCO3 are generally grouped under the second factor representing the dissolution of carbonate rocks. The third factor represented by Na, CO3, and pH is mostly related to alteration of volcanics, progressive silicate hydrolysis and dissolution, and probably ion exchange between Ca and Na. The fourth factor of NO3 and Cl is strongly influenced by agricultural activity. The measurement, analyses and evaluation results showed that the groundwater contamination is caused by (1) NO3 in waters discharging from clastic rocks in areas where intensive agricultural activities are conducted; (2) Al, Fe, Mn, and SO4 ions in water emerging from volcanics containing Pb-Zn-Cu ore deposits; and (3) Al, Fe, and Mn in water issuing from coal levels and altered volcanics. Some of these waters are used by adjacent towns for drinking, domestic, and irrigation purposes.