Indonesian Journal of Electrical Engineering and Computer Science
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Processing queries on encrypted document-based database
Get PDFBig data is a set of technologies and strategies for storing and analyzing large volumes of data in order to learn from it and make predictions. Since non-relational databases such as document-based have been applied in various contexts, the privacy protection must be taken into account by strengthening security to prevent the exposure of user data. In this paper, we focus mainly on secret sharing scheme that supports secure query with data interoperability to design a practical model for document-based databases, especially MongoDB. This approach, being based on secure query processing by defining elementary and suitable operators, allows us to perform operational computations and aggregations on encrypted data in the non-relational document database MongoDB. The obtained results, in the present work, could find places in various fields where data privacy and security are primordial such as healthcare, cloud computing, financial services, artificial intelligence and machine learning, in which user data remains secure and confidential during processing
Deep learning-based cryptanalysis in recovering the secret key and plaintext on lightweight cryptography
Get PDFThe development of machine learning (ML) technologies provide a new development direction for cryptanalysis. Several ML research in the field of cryptanalysis was carried out to identify the cryptographic algorithm used, find out the secret key, and even recover the secret message The first objective of this study is to see how much influence optimization and activation function have on the multi-layer perceptron (MLP) model in performing cryptanalysis. The second research objective, which is to compare the performance of cryptanalysis in recovering keys and the plaintext. Several experiments have been carried out, the observed parameters found that the use of the rectified linear unit (ReLU) activation function and the ADAM optimizer improves the performance of deep learning (DL)-based cryptanalysis as evidenced by a significantly smaller error rate. DL-based cryptanalysis works more effectively in recovering keys than recovering plaintext. DL-based cryptanalysis managed to recover the keys with an average loss of 0.007, an average of 49 epochs, and an average time of 0.178 minutes
Ba3GdNa(PO4)3F:Eu2+ phosphor with blue-red emission colors on white-LED properties
Get PDFThe blue/red-emission phosphor Ba3GdNa(PO4)3F:Eu2+ (BGN(PO)F-Eu) is used in this work for diodes emit white illumination (wLED). The phosphor is prepared using the solid-phase reaction. The suitable concentrations of Eu2+ ion dopant is about 0.7% and 0.9%. The BGN(PO)F-Eu phosphor can provide wLED light with the spectral wavelength in the region of blue (480 nm) and orange-red colors (595-620 nm). With the resulted emissions the phosphor can be appropriate for plant growing because they compatible with absorption spectra of plants’ carotenoids and chlorophylls for stimulating the photosynthesis. The phosphor influences on the wLED lighting properties depending on the doping dosages. It is possible to enhance the luminous intensity of the wLED with higher BGN(PO)F-Eu phosphor amount. Meanwhile, the color properties does not get significant improvements. Thus, the BGN(PO)F-Eu phosphor could be used with other luminescent materials to stimulate the hue rendering performance
Study on neuromorphic computation and its applications
Get PDFNeuromorphic computing offers a promising alternative to traditional von Neumann architectures, especially for applications that require efficient processing in edge environments. The challenge lies in optimizing spiking neural networks (SNNs) for these environments to achieve high computational efficiency, particularly in event-driven applications. This paper investigates the integration of advanced simulation tools, such as Simeuro and SuperNeuro, to enhance SNN performance on edge devices. Through comprehensive studies of various SNN models, a novel SNN design with optimized hardware components is proposed, focusing on energy and communication efficiency. The results demonstrate significant improvements in computational efficiency and performance, validating the potential of neuromorphic architectures for executing event-driven scientific applications. The findings suggest that neuromorphic computing can transform the way edge devices handle event-driven tasks, offering a pathway for future innovations in diverse application domains
Core methodological classes of text extraction and localization-a snapshot of approaches
Get PDFThe motivation to work on text extraction and localization is quite a substantial that potentially influences a larger area of application right from business intelligence to advanced data analytics. At present, there are massive archives of literatures addressing varying ranges of problems associated with text extraction and localization with an effective realization of respective contribution as well as on-going issues. However, problem statement is that all these massive implementation studies are further required to converge down in order to realize the core classes of methodologies involved in text extraction. Hence, this manuscript uses desk research methodology to address this issue by presenting a compact insight of core methodological classes where all the recent implementation work are converged down to understand its strength and weakness. The research outcome contributes towards facilitating information of current research trend and identified research gap. The proposed review study assists in undertaking decision of suitable approach of text extraction, localization, detection, recognition, and classification
A new modified B4 inverter using SRF controller with SVPWM technique for grid-connected PV system
Get PDFThe integration of renewable power sources into the grid presents a complex challenge, as the grid operates at AC voltage, while photovoltaic (PV) arrays generate DC power. A 3-phase inverter synchronizes with the grid’s voltage and frequency for efficient energy integration. In conventional technique, a 3-ph 6-switch (B6) inverter is used for sharing the power to the grid. In this paper reduced switch count 3-ph 4-switch (B4) inverter topology is introduced with reduced power losses. This topology has 4 insulated gate bipolar transistor (IGBT) switches and two capacitors replacing the other 2 switches positioned in one leg of the inverter, which connects to a grid connected PV system. A grid synchronization method called synchronous reference frame (SRF) based proportional integral (PI) is used to track the phase angle of the grid and subsequently inject current into the grid. A B4 inverter is operated by a novel space vector pulse width modulation (SVPWM) control technique which operates in 4 possible switching states. A comparative analysis is carried out with the PV array grid integration connected through B4 and B6 inverter topologies with SRF control. The modeling and design are carried out in a MATLAB/Simulink environment with graphs plotted according to the conditions. The comparative analysis validates the importance of SRF controllers for the grid integration of any renewable source
Enhancing mobility with customized prosthetic designs driven by genetic algorithms
Get PDFUsing genetic algorithms, this research intends to usher in a new era of prosthetic design that is redefining mobility. Through repeated evolutionary processes influenced by natural selection, the goal is to optimize prosthetic design parameters including material composition, structure, and control systems. The objective is to create prosthetic limbs that are more personalized to each user's requirements, improving their efficiency, comfort, and functioning via the application of genetic algorithms. The goal of this study is to show that the suggested strategy may improve mobility and user happiness more than standard ways by simulating and testing prosthetic devices in real-world settings. The end goal is to create conditions for a new age of prosthetic technology, where amputees' quality of life is greatly enhanced by devices that are individually designed to meet their biomechanical needs. The impact of prosthetic design and individual patient factors patient dataset derived from a random 5-sample with the following characteristics: ages 32–68, weight 65–90, height 155–180, crossover rate 0.6–0.9, mutation rate 0.05–0.2, population size 70–120, generations 30–60
SDN multi-access edge computing for mobility management
Get PDFIn recent trends, multi-access edge computing (MEC) is becoming a realistic framework for extensive social networking. The rapid proliferation of internet of things (IoT) devices has led to an unprecedented increase in data generation, placing significant strain on conventional cloud computing infrastructure. MEC also supports ultra-reliable and low latency communications (URLLC) by delivering information and computational resources more quickly to mobile users. As a result, the need for low-latency and reliable communication has become paramount. This paper proposes an MEC architecture that integrates software defined networking (SDN) and virtualization techniques, where MEC enables the orchestration and organization of mobile edge hosts (MEH). Furthermore, the proposed MEC-SDN design minimizes latency while ensuring consistent ultra-low latency communications. The result analysis clearly demonstrates that the proposed MEC-SDN model achieves latency of 6-14 ms, bandwidth of 5.2 Mbits/sec, and SDN-BWMS of 5.4 Mbits/sec, outperforming the existing SDN-Mobile Core Network model. Mobile edge systems are enabled in this research to provide mobility support for users
ClearNet: auto-encoder based denoising model for endoscopy images
Get PDFGastrointestinal (GI) endoscopy images play a crucial role in the detection and diagnosis of diseases within the digestive tract. However, the development of effective computer vision models for automated analysis and denoising of endoscopy images faces challenges arising from the diverse nature of abnormalities and the presence of image artefacts. In this work, the utilization of an encoder-decoder network for denoising GI endoscopy images using the HyperKvasir dataset has been analyzed. This approach involves training a custom encoder-decoder model on this extensive multiclass endoscopy image dataset and assessing its performance across 23 prevalent classes of digestive tract issues. Here experiments showcase the model’s ability to learn robust visual representations from endoscopic data, enabling accurate disease prediction. The achieved promising results highlight the potential of encoder-decoder architectures as a foundational framework for computer-aided endoscopy analysis with a specific focus on denoising applications. Our model manages to increase the peak signal-tonoise ratio (PSNR) of original-noisy pair from 19.118954 to 69.892631 for original-reconstructed pair showcasing almost perfect reconstruction
Cryptographically secure digital certificates on a distributed ledger
Get PDFVerification of a qualification, achievement, quality, or aspect of a person’s background is one of the biggest problems nowadays as we have seen many platforms where students can get fake credentials. Every organization must select professional and academically qualified employees to give quality service. As a result, corporations rely on academic certifications to confirm and measure their prospective employees’ academic qualifications. On the other hand, these employers lack a standardized process for confirming the legitimacy of academic certificates or degrees. Because the present procedures for verifying educational certifications are time-consuming, exhausting, and costly, just a few employers verify certificates for prospective employees. This research examines the issues that are related to the smart verification of someone’s credentials. To make the process of verifying digital credentials quicker, simpler, and more cost-effective, we suggest decentralized architecture. We present the prototype, design, and implementation of the proposed framework