Visibility of resources and assets in the shipyard through industrial internet of things

Industrial Internet of Things is becoming one of the fundamental technologies with the potential to be widely used in shipyards as in other industries to increase information visibility. This article aims to analyze how to develop an industrial IoT-enabled system that provides visibility and tracking of assets at SEDEF Shipyard, which is in the digital transformation process. The research made use of data from previous studies and by using content analysis, the findings were discussed. Industrial IoT enables the collection and analysis of data for more informed decisions. Based on the findings, sensor data in the shipyard are transmitted to the cloud via connected networks. These data are analysed and combined with other information and presented to the stakeholders. Industrial IoT enables this data flow and monitors processes remotely and gives the ability to quickly change plans as needed. Keywords: Shipyard, Industrial Internet of Things, Cyber-Physical System, Visibility, Assets tracking;

An analysis on industrial internet of things in digital transformation of shipyard industry in Turkey

Shipyards often face unique challenges, as the construction of ships takes months or even years to complete. As in any sector, Industry 4.0 (I4.0) also affects the shipbuilding sector. With this digital transformation, it aims to meet the challenges of shipbuilding more personalized ships with shorter delivery times, greater flexibility, and higher quality. Therefore, this study aims to review IIoT technologies that will perform the digital transformation in the shipyard. In this study, an analysis of the digital transformation for the shipyard industry of Turkey in general was made and more specifically focused on how to implement IIoT for Sedef Shipbuilding Inc., which is one of the leading shipbuilding companies in Turkey. This study contributes to digital transformation technologies that can be applied in shipyards by providing analysis of existing reference frames for IIoT technologies in shipyard digital transformation. Keywords: ; IoT Ecosystem; IIoT Architecture;Industry 4.0; Industrial Internet of Things; Shipbuilding 4.0; Shipyard 4.0

Learning programming languages by using e-learning technology

Nowadays gaining new skills is a necessity and as such, avenues for gaining new skills need to be easily accessed and available. LMS which stands for Learning Management System gives you the ability to create, discover, and track courses anywhere with any device. In the past, strong softwares for handling complex databases have cooperated with digital platforms to manage and handle the curriculum of the courses and they provided evaluation tools. This paper aims to describe the Learning Management System and how it can benefit the educational process, basing on a case study of C Programming Online Course at the Near East University . The research used resources from previous studies and collected data using a case study. The findings are presented in the research. Based on the findings, it is evident that the benefits LMS has on learning programming is significant. Keywords: Cloud Storage; LMS; Online Compiler, Software Programming;

Prediction of renewable energy consumption for future world by using artificial neural networks

Artificial intelligence has proven itself in many areas in combating complex and challenging problems. In this study, the estimation of the use of artificial neural networks in long term renewable energy consumption was undertaken. The study proposes an artificial intelligence predicting energy consumption and energy needs of houses and buildings in the future by using feedback artificial neural networks. In this study, "Google Project Sunroof-Solar Panel Power Consumption Offset Estimate" data set is used. With the database, artificial intelligence has been obtained by using artificial neural networks with feedback. The training of the artificial intelligence obtained was completed with 7999 samples with 25 different categories. This database, which Google collects, is obtained at high costs, so it is not possible for everyone to access such and its bases. Our artificial intelligence with feedback artificial neural network obtained a high percentage for training success. Validation success was high and test success was high too. Keywords: Artificial Neural Networks; Energy Consumption; Energy; Renewable Energy

Smart learning technology for computer programming driven by research related to COVID-19

The restrictions imposed by COVID-19 have significantly affected the reorganization of educational processes, including the process of computer programming learning in higher education. The work experiences in teaching programming languages in higher education have served as an idea for the development of smart learning technology, as a complement to the pre-existing ecosystem for digital learning, in particular C++ programming, in higher education. This paper aims to present the realization of smart learning technology, describes its use and provides information about the level of acceptance of higher education students. The opinions and experiences of the students who used the technology, during the summer semester of 2020, were obtained through an anonymous questionnaire, prepared by the author of the paper. The results were obtained during implementation of the curriculum in advanced C++ programming in the Faculty of ICТ. The results show the potential for wider application of this Smart Learning technology, especially in technical areas. Keywords: C++; covid19; programming; smart learning, technology

Closed frequent itemsets mining based on It-Tree

In the last decade, the amount of collected data, in various computer science applications, has grown considerably. These large volumes of data need to be analysed in order to extract useful hidden knowledge. This work focuses on association rule extraction. This technique is one of the most popular in data mining. Nevertheless, the number of extracted association rules is often very high, and many of them are redundant. In this paper, we propose an algorithm, for mining closed itemsets, with the construction of an it-tree. This algorithm is compared with the DCI (direct counting & intersect) algorithm based on min support and computing time. CHARM is not memery-efficient. It needs to store all closed itemsets in the memory. The lower min-sup is, the more frequent closed itemsets there are so that the amounts of memory used by CHARM are increasing.

Making sure of students attendance and the system of mark management by using mobile applications

Marking attendance in the class meeting session and recording the marks of the students are the prime tasks of the subject handlers, but current methods are time consuming and hectic. To avoid these problems, this paper aims to present a mobile application for student attendance and mark management system. This application is mainly designed for the faculties and other staff members of the organization who maintain attendance and marks regularly. Using this system, the subject handlers, staff or the authorities can verify the number of students present or absent in the class meeting sessions. This application allows the users to mark attendance through mobile devices and to keep in touch with students. It also gives a prior intimation to students as soon as their attendance goes below the specified percentage through an alert message. Keywords: attendance; mobile applications; manual; student management, student attendance

Extraction of urban buildings using color image processing and morphological operations.

In many geospatial applications, automated detection of buildings has become a key concern in recent years. Determination of building locations provides great benefits for numerous geospatial applications such as urban planning, disaster management, infrastructure planning, environmental monitoring. The study aims to present a practical technique for extracting the buildings from high-resolution satellite images using color image segmentation and binary morphological image processing. The proposed method is implemented on satellite images of 4 different selected study areas of the city of Batikent, Ankara. According to experiments conducted on the study areas, overall accuracy, sensitivity, and F1 values were computed to be on average, respectively. After applying morphological operations, the same metrics are calculated . The results show that the determination of urban buildings can be done more successfully with the suitable combination of morphological operations using rectangular structuring element. Keywords: Building Extraction; Colour Image Processing;Colour space conversion; Image Morphology; Remote Sensing

The significance of typography in data visualization

With the development of technology and the dominance of the digital world, typography has become a critical issue. Information design systems are considered as one of the significant areas of graphic design and big data provides essential information on data visualization. This research aims to analyse the effects of typographic elements on visualizing data in terms of visual communication, by discussing the value that typography gives to design space. The research discusses randomly selected 10 infographic design samples published in the last six months on google. From the results, 5 designs with typographic concern were more favourable and visually more striking and preferable than the other 5 designs in terms of design disciplines. As in all areas of graphic design, it is argued that the power of typography is an indisputable concept in data visualization, which is seen as a sub-branch of information design. Keywords: data visualization; design; typography, significance, technology

A new strategy for curriculum learning using model distillation

In recent years, deep neural networks have been successful in both industry and academia, especially for computer vision tasks. Humans and animals learn much better when gradually presented in a meaningful order showing more concepts and complex samples rather than randomly presenting the information. The use of such training strategies in the context of artificial neural networks is called curriculum learning. In this study, a strategy was developed for curriculum learning. Using the CIFAR-10 and CIFAR-100 training sets, the last few layers of the pre-trained on ImageNet Xception model were trained to keep the training set knowledge in the model’s weight. Finally, a much smaller model was trained with the sample sorting methods presented using these difficulty levels. The findings obtained in this study show that the accuracy value generated when trained by the method we provided with the accuracy value trained with randomly mixed data was more than 1% for each epoch. Keywords: Curriculum learning, model distillation, deep learning, academia, neural networks.