• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.252-258
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• 2022

Globalization, development of the information society, intensification of migration processes, and internationalization of education in recent years have significantly affected the international labour market and increased competition between professionals in various fields. Academic, research and teaching staff are currently facing rapid changes and growing demand for quality educational services. Under such conditions, educational institutions around the world pay particular attention to improving the quality of the educational process in order for their graduates to be able to compete in the international labour market. The study of the experience of teachers' professional training in advanced countries opens new opportunities for improving the system of pedagogical training in Ukraine in order to adapt it to the requirements of the European educational space. The progressive achievements of countries demonstrating a high level of teachers' professional training in accordance with international standards, having rich historical educational traditions are of considerable scientific interest; consequently, this contributes to their leadership in science and education at the regional and global levels. The purpose of the present academic paper lies in analysing the latest trends in exploring teaching experience in the European countries and performance review of passing by students and teachers of the program on studying of pedagogical practice and experience of teaching in the countries of Europe. Methodology. Analytical and empirical (questionnaire) methods were used in the research process. Results. According to the obtained results of the research, the advantages, the most common areas of educational programs and the wishes of the participants regarding the practical implementation of the experience were identified.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.367-373
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• 2022

Femtocells have recently been recognized for their potential to boost network capacity, improve end-user QoS and throughput, and do so at a cheap cost and with ease of implementation. The use of femtocells in indoor environments, such as residential buildings with neighboring homes, is becoming more popular. Femtocells are subject to interference from other femtocells, and the unwanted effects of interference are amplified when femtocells are deployed in close proximity to one another. As a consequence, the network's overall performance is degraded to a significant degree. One of the strategies that is thought to be effective in reducing the impact of interference is altering the transmission power of the femtocells. In this paper, a dynamic downlink transmission power of femtocells is suggested. In accordance with the observed cost function unit, each femtocell automatically changes its transmission power. If a femtocell causes too much interference for its neighbors, its transmission power level will be limited by that interference's rate. A simulation experiment is conducted to validate the effectiveness of the suggested system when compared with other schemes. When compared to previous schemes, which are addressed in this study, the numerical results show that the proposed strategy could provide more capacity while also ideally mitigating the influence of interference among co-channel deployed femtocells.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.216-222
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• 2021

Advances in technology have given educators a tool to empower them to assist with developing the best possible human resources. Teachers at universities prefer to use more modern technological advances to help them educate their students. This opens up a necessity to research the capabilities of cloud-based learning services so that educational solutions can be found among the available options. Based on that, this essay looks at models and levels of deployment for the e-learning cloud architecture in the education system. A project involving educators explores whether gement Systems (LMS) can function well in a collaborative remote learning environment. The study was performed on how Blackboard was being used by a public institution and included research on cloud computing. This test examined how Blackboard Learn performs as a teaching tool and featured 60 participants. It is evident from the completed research that computers are beneficial to student education, especially in improving how schools administer lessons. Convenient tools for processing educational content are included as well as effective organizational strategies for educational processes and better ways to monitor and manage knowledge. In addition, this project's conclusions help highlight the advantages of rolling out cloud-based e-learning in higher educational institutions, which are responsible for creating the integrated educational product. The study showed that a shift to cloud computing can bring progress to educational material and substantial improvement to student academic outcomes, which is related to the increased use of better learning tools and methods.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.570-578
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• 2021

Recently, in the field of engineering and scientific and technical calculations, problems of mathematical modeling, real-time problems, there has been a tendency towards rejection of sequential solutions for single-processor computers. Almost all modern application packages created in the above areas are focused on a parallel or distributed computing environment. This is primarily due to the ever-increasing requirements for the reliability of the results obtained and the accuracy of calculations, and hence the multiply increasing volumes of processed data [2,17,41]. In addition, new methods and algorithms for solving problems appear, the implementation of which on single-processor systems would be simply impossible due to increased requirements for the performance of the computing system. The ubiquity of various types of parallel systems also plays a positive role in this process. Simultaneously with the growing demand for parallel programs and the proliferation of multiprocessor, multicore and cluster technologies, the development of parallel programs is becoming more and more urgent, since program users want to make the most of the capabilities of their modern computing equipment[14,39]. The high complexity of the development of parallel programs, which often does not allow the efficient use of the capabilities of high-performance computers, is a generally accepted fact[23,31].

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.354-362
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• 2021

The device to device (D2D) communication is an important and emerging area for future cellular networks. It is concerned about all aspect of secure data transmission between end devices along with originality of the data. In this paradigm, the major concerns are about how keys are delivered between the devices when the devices require the cryptographic keys. Another major concern is how effectively the receiver device verifies the data sent by the sender device which means that the receiver checks the originality of the data. In order to fulfill these requirements, the proposed system able to derive a cryptographic key using a single secret key and these derived keys are securely transmitted to the intended receiver with procedure called mutual authentication. Initially, derived keys are computed by applying robust procedure so that any adversary feel difficulties for cracking the keys. The experimental results shows that both sender and receiver can identify themselves and receiver device will decrypt the data only after verifying the originality of the data. Only the devices which are mutually authenticated each other can interchange the data so that entry of the intruder node at any stage is not possible.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.77-84
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• 2023

The utilization of GPUs on general-purpose computers is currently on the rise due to the increase in its programmability and performance requirements. The utility of tools like NVIDIA's CUDA have been designed to allow programmers to code algorithms by using C-like language for the execution process on the graphics processing units GPU. Unfortunately, many of the performance and correctness bugs will happen on parallel programs. The CUDA tool support for the parallel programs has not yet been actualized. The use of a dynamic analyzer to find performance and correctness bugs in CUDA programs facilitates the execution of sophisticated processes, especially in modern computing requirements. Any race conditions bug it will impact of program correctness and the share memory bank conflicts to improve the overall performance. The technique instruments the programs in a way that promotes accessibility of the memory locations accessed by different threads well as to check for any bugs in the code of a program. The instrumented source code will be used initiated directly in the device emulation code of CUDA to send report for the user about all errors. The current degree of automation helps programmers solve subtle bugs in highly complex programs or programs that cannot be analyzed manually.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.1-8
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• 2023

The artificial intelligence of robot is the weakness of digital intelligence of a person who able to train, self-realize and to develop competences, creative, professional and behavioral skills. A new methodology proposed for managing robots inside the mines using an electronic system designed for driving robots to injured people in seas, mines or wells who can not be reached by human force. This paper also explains the concept of managing and remote-controlling the process of searching and helping the injured. The user controls the robot through an application that receives all the reports that the robot sends from the injured person. The robot's tasks are to take a sample of the blood of the injured person, examine it, and measure the percentage of oxygen underground and send it to the user who directs the robot to pump a specific percentage of oxygen to the injured person. The user can also communicate with the person The patient and determine his condition through the camera connected to the robot equipped with headphones to communicate with the injured and the user can direct the camera of the robot and take x-rays from the injured.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.67-78
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• 2024

Software-Defined Networking (SDN) is a new emerging networking paradigm that has adopted a logically centralized architecture to increase overall network performance agility and programmability. Combining network virtualization with SDN will guarantees for combined advantages of improved flexibility and network performance. Combining SDN with hypervisors divides the network physical resources into several logical transparent and isolated virtual SDN network (vSDN), where each has its virtual controller. However, SDN hypervisors bring several advantages as well as several challenges to its network operators as for the virtual appliances, their efficient placement, assurance of network performance is mandatory, and their dynamic instantiation with their migration. In this article, we provide a brief and concise review of network virtualization along with its implementation in the SDN network. SDN hypervisors types are discussed, and taxonomy is provided to demonstrate the importance of hypervisors in SDN. A comparison of SDN hypervisors is performed to elaborate on the vital hypervisor software along with their features, and different challenges are discussed faced by the SDN network. A framework is proposed to add combined functionalities of hypervisors to create a more effective and efficient virtual system. The purpose of the framework is to increase network performance through proper configuration of resources, software, control plane isolation functions with defined rules and policies.