Review of cloud computing in science, technology, and real life

This paper presents an overview of the general idea and history of cloud computing in theory. The objective of this review is to draw attention to preceding studies about cloud computing that have common characteristics with the theme of this paper. There were some points discussed in general, including the advantages of this technology, its subjects, security, and the effects of adopting cloud computing in an organization.

An evaluation of CNN and ANN in prediction weather forecasting: A review

Artificial intelligence through deep neural networks is now widely used in a variety of applications that have profoundly altered human livelihoods in a variety of ways. People's daily lives have become much more convenient. Image recognition, smart recommendations, self-driving vehicles, voice translation, and a slew of other neural network innovations have had a lot of success in their respective fields. The authors present the ANN applied in weather forecasting. The prediction technique relies solely upon learning previous input values from intervals in order to forecast future values. And also, Convolutional Neural Networks (CNNs) are a form of deep learning technique that can help classify, recognize, and predict trends in climate change and environmental data. However, due to the inherent difficulties of such results, which are often independently identified, non-stationary, and unstable CNN algorithms should be built and tested with each dataset and system separately. On the other hand, to eradicate error and provides us with data that is virtually identical to the real value we need Artificial Neural Networks (ANN) algorithms or benefit from it. The presented CNN model's forecasting efficiency was compared to some state-of-the-art ANN algorithms. The analysis shows that weather prediction applications become more efficient when using ANN algorithms because it is really easy to put into practice.

Maintenance modelling and optimization in the industry 4.0 context: Applications to the maintenance and design of industrial vehicles

This paper focused on the maintenance problems encountered by industrial vehicles within the Volvo Group. The main goal of the research on this subject was to propose to customers’ a personalized maintenance offer which adapts to their constraints while reducing the impact on the operating costs. To achieve this, a policy has been developed. This policy works on the dynamic gathering of information using both the available monitoring information and the knowledge of the multi-component system. Its objective is to guarantee to the customer the autonomy of its system over given periods of operation while minimizing the total cost of maintenance. The paper showed that the policy developed does indeed reduce the total maintenance cost compared to the previous policy used within the Volvo group. Nevertheless, this policy still has room for improvement.

Study the impact of different preparation methods on the structural and dielectric properties of nickel-zinc ferrite

In the current study, nickel-zinc ferrite nanoparticles Ni (1-x) ZnxFe2O4 (X= 0, 0.25, 0.50, 0.75, 1) have been arranged by sol-gel auto combustion and common chemical precipitation methods, The samples were described by x-ray (XRD) deflection, Fourier converts Infrared Spectroscopy (FTIR), dielectric perpetual and dielectric loss element. the XRD analysis confirms the cubic lone phase spinel configuration for all the synthesized materials. Average crystalline size is estimated of the (311) peaks of the x-ray diffractogram using Scherrer’s formulation institute in the range 38.90 to 37.71 nm for sol-gel auto burning method and from 18.61 to 23.41 nm for co-precipitation method. The Fourier transform infrared spectroscopy was studied so as to assert the construction of the spinel phase and to recognize the kind of carbon remaining in the samples. The dielectric fixed and the dielectric loss factor were measured in the range between 50 Hz – 3 MHz at room temperature were located to be reduced with a rise in regularity.

Influence of external loads to wind turbine tower

One of the most important parts of a wind turbine is a tower. There are various designs of the wind turbine towers, and they are most often made of steel pipes, lattice towers or concrete towers. In order to increase energy density to meet the growing electricity needs, larger wind turbine projects have been developed. Larger wind turbine towers can generate more electricity, but such large sizes also create higher costs in terms of development and maintenance. This research sets up a model of a wind turbine tower, where the load to the tower is calculated by its relation to the wind velocity. Analytical approach coupled with a finite element method (FEM) is used to analyse the distribution of tower stresses under these loads. The fatigue analysis of the column is performed using the load from its own weight, the weight of the housing and the distribution of the wind velocity. The effects of different loads are also compared. The results show that the main loads of the tower are the wind force acting on the area of ??rotation of the wind turbine blades and the moment caused by the uneven wind velocity. Construction is modelled using SolidWorks modelling package, where the analysis was performed using FEM in ANSYS software. As a result of the analysis, the stress distribution in the support was determined and compared with analytical calculations.

Facial image noise classification and denoising using neural network

Image denoising is an important aspect of image processing. Noisy images are produced as a result of technical and environmental flaws. As a result, it is reasonable to consider image denoising an important topic to research, as it also aids in the resolution of other image processing issues. The challenge, however, is that the traditional techniques used are time-consuming and inflexible. This article purposed a system of classifying and denoising noised images. A CNN and UNET based model architecture is designed, implement, and evaluated. The facial image dataset is processed and then it is used to train, valid and test the models. During preprocessing, the images are resized into 48*48, normalize, and various noises are added to the image. The preprocessing for each model is a bit different. The training and validation accuracy for the CNN model is 99.87% and 99.92% respectively. The UNET model is also able to get optimal PSNR and SSIM values for different noises.

Lossy codecs for digital image signatures

Most applications in recent times make use of images one way or the other. As physical devices for capturing images improve, the quality and sizes of images also increase. This causes a significant footprint of images on storage devices. There is ongoing research to reduce the footprint of images on storage. Since storage is a finite resource, the goal is to reduce the sizes of images while maintaining enough quality pleasant to the human eye. In this paper, the design of two lossy codecs for compressing grayscale digital signature images has been presented. The algorithms used either simple thresholding or transform coding to introduce controlled losses into the image coding chain. This was to reduce, to a great extent, the average number of bits per pixel required to represent the images. The codecs were implemented in MATLAB and experiments were conducted with test images to study the performances of the algorithms.

Influences of nanoparticles on aquatic organisms: Current situation of nanoparticles effects in aquatic ecosystems

The quick improvement of nanotechnology permits a wide range of utilization of engineered nanoparticles, such as personal care products, medicals, optics, electronics, and automobiles. The nanoparticles manufactured from Ag, Au carbon-nanotube, ZnO, SiO2, TiO2, Cu, Ni, and magnetic ferrites are among the generally utilized in products. The nanoparticles are produced and utilized in large quantities and release into marine and freshwater ecosystems during production, use, discharge, treatment, and deposition. Those particles with a mean size of 1 nm - 100 nm are of potential environmental risks because of their particular qualifications and high reactivity although their great economical values. Based on the studies, the size, shape, and surface physical and chemical characteristics of the nanoparticles show the level of aggregation, solubility, structural and chemical composition, the importance of the use of nanoparticles, and their toxicity with biological systems. Nanoparticles can potentially cause adverse impacts on tissue, cellular, genetic materials, and protein- enzyme levels due to their unique physical and chemical qualifications. In this study, the effects of nanoparticles on aquatic organisms and aquatic ecosystems were evaluated.

Waste management in a university campus

In this study, we discussed how can be the management hierarchy and management process in a university campus. Erciyes University is in the middle of the Anatolia Region that has about 60.000 population. The university has faculty /institutional administrations and hospital-related buildings and research centers. It has an area of about 20 m2 for each person on the campus. The university is responsible in terms of legislative directives that are in operation. The waste directive is published by the university in 2017 that shares the responsibilities and distributes the tasks for each unit on the university campus. In Turkey, zero waste projects and zero waste legislation are also in operation by 2019. The importance of waste management strategy is important for Sustainable Development Goals (SDG) that is published by the United Nations and put in consideration of Times Higher Education (THE) which is one of the most confidential ranking systems for universities. There is also, environmental assessment system for university campuses, the Green-Metric. One of the grading subjects of the Council of Higher Education (YÖK) in Turkey is the zero waste strategy on the campus. Therefore, the operation of a zero-waste strategy gains importance.

Electricity generation potential of municipal solid wastes produced in the province of Edirne

As a result of Turkey's economic growth, industrial development has accelerated across the country and this has ultimately led to the environmental sector and waste management gaining importance. In Turkey, where there is a depletion of natural resources, the expansion of energy demand, and the orientation in environmental technologies, waste is no longer a problematic issue that needs to be eliminated; but it has become a source of raw materials whose processing and recycling can be achieved with today's technology. In the scope of sustainable development, the waste hierarchy includes the three priority targets. These are prevention of waste production, reuse, recycling, or recovery respectively. The method for non-recoverable wastes is landfilling with energy recovery if possible. In this context, this study aims to investigate the electricity generation potential of the solid wastes disposed at the Edirne Solid Waste Landfill Facility. When the amount of waste to be sent to the facility, which was assumed to have a 20-year economic life, increases by 5% in parallel with the population profile, it is seen that electricity production will go up rapidly until 2040. However, the results of the study present that the potential of methane production will fall as the stored waste age increases so that a significant decrease in electricity production should be expected from 2045 onwards. Once it is considered that the facility continues to produce electricity for a hundred years beyond 2040, the electricity generated from the facility will contribute to the electricity network and provide the avoidance of approximately 25 thousand tons of CO2 on a national basis.