1,720,956 research outputs found
Industrial Kitchen Manufacturer Service Management
No full textAs in all production sectors, it is important to meet customer demands in a timely and accurate manner in the kitchen industry. This study is one of the rare studies that encourage the use of ERP system-based kitchen products, especially SAP, according to customer demands. In our study, a system that re-evaluates the customer communication approach for a company engaged in industrial production, covering the process from the sale of the product to the end user and the technical service process after the product sale, was discussed. Thanks to this system, the company will be able to deliver and sell the spare parts it owns or produces to service managers. At the same time, they will be able to report all commercial transactions in the system, create financial records and store them digitally in their own records. Our system works integrated with Google maps in order to reach the customer in a timely and cost-effective manner during spare parts supply processes. The system we will design; It includes call center application, spare parts application. The system generally consists of two parts: Front End and Back End. In our study, accuracy criteria were used to evaluate the performance of the system. Thanks to this system, product delivery times are shortened and customer satisfaction increases. Making some changes to the system we recommend will help many organizations in other sectors to improve their ERP systems and effectively prevent the problems encountered
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Detection of sperm cells by single-stage and two-stage deep object detectors
No full textToday, infertility is a common health concern that affects approximately 15%-20% of the world population. The evaluation of male patients with infertility includes diverse examination and laboratory tests in comparison to female patients. In the evaluation of male infertility, sperm specimens are examined in terms of morphom-etry, concentration, and motility. Detection of sperm is the critical step to determine the concentration and motility parameters. In this study, a fusion approach of deep learning-based object detection techniques is utilized in the sperm detection problem for obtaining more accurate and consistent concentration and motility characteristics of sperm specimens. First, 12 sperm specimen videos acquired from different infertile patients were recorded. Then, regions in the video frames were labeled as sperm and non-sperm by the experts. Two different scenarios have been tested over the labeled dataset. Differently arranged train and test data ratios were also utilized for each scenario. In the first scenario, deep learning-based object detection algorithms were individually performed for the sperm detection of patient-oriented videos in terms of different train/test split ratios. Videos with the lowest mAP (mean Average Precision) values resulted in the first scenario were selected for the second scenario as target videos. The rest of the videos were used for model training without any patient-oriented manner. In the second scenario, the detection performance for more challenging videos is aimed to increase by using different videos instead of using the small part of the same video in the model training. Additionally, a fusion idea of the utilized deep learning-based techniques was proposed and performed over these low mAP resulted videos to increase the detection performance. The results are compared regarding the general mAP, class-wise APs, and training time. In the first scenario, YOLOv5 achieved the best results, while the proposed fusion approach achieved the best mAP scores in the second scenario.Yildiz Technical University Scientific Research Projects Coordinatorship [FKD-2021-4554]This study was supported by Yildiz Technical University Scientific Research Projects Coordinatorship. Grant No: FKD-2021-4554. The funding institution have no direct role in the study design, data collection, analysis, and interpretation or manuscript preparation. Additionally, for the detailed definition of infertility, the authors thank Prof. Dr. Hakki Uzun (Recep Tayyip Erdogan University Faculty of Medicine, Department of Urology)
Creating a Data Generator and Implementing Algorithms in Process Analysis
Get PDFProcess mining is a new field of work that aims to meet the need of the business world to improve efficiency and productivity. This field focuses on analysing, discovering, managing, and improving business processes. Process mining uses event logs as a resource and works on this resource. Hence, the system is developed by analysing the event logs, including each step in the process model. Our study is made up of two significant stages: a data generator for processes and algorithms applied for discovering the created processes. In the first stage, the aim was to develop a simulator with the ability to generate data that could help process modelling and development. Within the framework of this study, a system was created that could work with various process models and extract meaningful information from these models. More productive and efficient processes can be developed as a result of his system. The simulator consists of three modules. The first module is the part where users create a process model. In this module, the user can create his own business process model in the system's interface or select from other registered models. In the second module, team-based data are simulated through these process models. These generated data are used in the third module, called analysis, and meaningful information is extracted. In conclusion, the process can be improved considering the information about time, resource, and cost in the generated data. At the second stage, processes were discovered using alpha, heuristic, and genetic algorithms, which are process mining discovery algorithms and synthetic and real event logs. The discovered processes were demonstrated with Petri nets, and the algorithms' performances were compared using the fitness function, accuracy rates, and running times. In our study, the heuristic algorithm is more successful because it improves the noise in the data and incomplete processes, which are the disadvantages of the alpha algorithm. However, the genetic algorithm yielded more successful results than the alpha and heuristic algorithms due to its genetic operators
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