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Bluetooth Text Messages Integrity Security (BTMIS) Based on Blockchain
Raed Rasheed,
Raed Bulbul,
Mohammad Mikki
Issue:
Volume 6, Issue 2, December 2022
Pages:
54-60
Received:
19 January 2022
Accepted:
30 June 2022
Published:
13 July 2022
DOI:
10.11648/j.ajece.20220602.11
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Abstract: Bluetooth is one of the wireless technologies that users connect with one another through at a higher rate than with any other method when they are in close proximity to one another. This type of communication channel is susceptible to a variety of attacks, including Man-In-The-Middle (MITM) attacks and others of their ilk. On the other hand, live chatting has swiftly emerged as the most well-liked mode of text-based communication all over the world. As a consequence of this reality, one of the most significant challenges presented by wireless networks is preserving the authenticity of the data. It is not feasible to determine with absolute certainty whether or not malicious applications are capable of modifying older text that is preserved in a mobile database. This article presents a solution to the challenge of assuring the authenticity of Bluetooth text messages that is based on a distributed ledger technology (blockchain). The problem-solving strategy can be partitioned into two distinct parts. The first possibility involves sending and receiving text messages in real time using the Bluetooth channel of communication. The second type of distributed ledger is a hashing messages distributed ledger, which is based on blockchain technology and saves a hash of each and every message that is stored in the device database. This form of distributed ledger is a sort of distributed ledger for hashing messages.
Abstract: Bluetooth is one of the wireless technologies that users connect with one another through at a higher rate than with any other method when they are in close proximity to one another. This type of communication channel is susceptible to a variety of attacks, including Man-In-The-Middle (MITM) attacks and others of their ilk. On the other hand, live ...
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A Novel Grid Corrosion Detection and Two-Dimensional Imaging Approach for a Grounding Substation
Mingyang Li,
Shaorong Cao,
Wei Niu,
Mingdong Zhang,
Weidong Xie
Issue:
Volume 6, Issue 2, December 2022
Pages:
61-67
Received:
29 June 2022
Accepted:
12 July 2022
Published:
28 July 2022
DOI:
10.11648/j.ajece.20220602.12
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Abstract: The grounding grid is one of the most important components of the power grid. However, the grounding grid is buried in the ground all year round, corrosion occurs commonly, which not only deteriorates the operation of the power system, but also could result in severe economic loss. The deterioration could be caused by the following reasons: the corrosion of metal conductors in the soil as time goes, the inevitable negligence or omission during construction (such as false welding, missing welding), and the electrodynamic effect of the ground current on the voltage equalizing conductor, etc. Since a well-performed grounding is essential for the security, cost-efficiency, and stability of the substation, the detection of grounding grid corrosion is necessary. In this paper, a new method for detecting the corrosion of the grounding grid is proposed. Specifically, this novel algorithm integrates the advantages of particle swarm optimization and least-squares method-particle swarm optimization. Also, it uses the least-squares algorithm for local tuning. We simulate three different corrosion situations – multiple branches, ring-shaped branches, and straight-lined branches. These simulation results show that our approach provides a very efficient and useful solution. More importantly, a real-world case study is implemented. The results of case study are consistent with the simulation results. Hence, this paper validates the effectiveness of the proposed algorithm on both simulation and experimental level.
Abstract: The grounding grid is one of the most important components of the power grid. However, the grounding grid is buried in the ground all year round, corrosion occurs commonly, which not only deteriorates the operation of the power system, but also could result in severe economic loss. The deterioration could be caused by the following reasons: the cor...
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Compressive Sensing and Reconstruction’s Algorithm on Radar Mimo
Randrianandrasana Marie Emile,
Randriamitantsoa Paul Auguste
Issue:
Volume 6, Issue 2, December 2022
Pages:
68-80
Received:
5 July 2022
Accepted:
10 August 2022
Published:
31 August 2022
DOI:
10.11648/j.ajece.20220602.13
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Abstract: Two advanced technic appears concerning the digital processing: the detection system RADAR and a compression technic named the Compressive Sensing (CS). This modern acquisition technic combined with reconstruction, offers multiple advantages. This research explains a new technic of acquisition with compression: the Analog to Information Converter (AIC). The standard method uses Analog to Digital converters (ADC). This method named AIC can defeat even the Nyquist Shannon criteria, by using advanced transformation. This article shows the application of compressed sensing MIMO RADAR. Based on the propriety of the signal, we study criteria of mathematics’ compressibility, to the choice of the methods, the two algorithm of reconstruction that we use named Matching Pursuit (MP) and Orthogonal Matching Pursuit (OMP). So, we could have compressive sensing with Non-Uniform Sampling that we named CS-NUS on this article. Our contribution consists of using detection of the multiple targets combined with the CS. For multiple targets, we use the Principal Component Analysis (PCA) to send the signal and recover it. The Signal to Noise Ratio (SNR) and Compressive Ratio (CR) permit to conclude that Orthogonal Matching Pursuit offers a best performance than Matching Pursuit. The Matching Pursuit algorithm cited previously gives a good time reconstruction processing but not offers a good quality of reconstruction.
Abstract: Two advanced technic appears concerning the digital processing: the detection system RADAR and a compression technic named the Compressive Sensing (CS). This modern acquisition technic combined with reconstruction, offers multiple advantages. This research explains a new technic of acquisition with compression: the Analog to Information Converter (...
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Reliability Assessment and Optimal Placement of Switches in Electric Power Distribution System by Using PSO
Issue:
Volume 6, Issue 2, December 2022
Pages:
81-90
Received:
3 June 2021
Accepted:
30 October 2021
Published:
18 October 2022
DOI:
10.11648/j.ajece.20220602.14
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Abstract: Reliable electric power supply is a pillar perquisite for technological, social, political and economic development of any nation. Modernization and developing in every aspect without reliable electric power supply is un predictable. Here in our country Ethiopian has a serious power interruption problem because of unwanted very high outage frequency and longtime system restoration. Due to this, utilities must strive and ensure that the customer’s reliability requirements are met and the regulators requirements satisfied at the lowest possible cost. In this paper the reliability assessment is done on both 15kV Ankober electric power system to assess the performance of the existing system and also predictive reliability improvement for the future system considering distribution system reconfiguration (optimal coordination of switches) and by de. For predictive reliability and power quality improvement binary particle swarm optimization has been applied which delivers optimal number and optimal placement of switches on the selected The placement of switches in strategic places reduces the outage time in case of interruption, and improves the reliability of the network. There are many measures to assess the reliability of distribution network. The most common measures are expected outage cost (ECOST), system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), in this paper the focus of reliability measure is the impact of energy not supplied and its cost. To solve the problem of number of sectionalizes switches allocation a binary particle swarm optimization (BPSO) method has been selected. To illustrate the performance a proposed algorithm, an actual 15kV Ankober feeder of Debre Berhan distribution system was selected as the test system. As the result the optimal number and placement of sectionalizes switches changed from S8, S18, S22, and S26 to [S13, S19, S21, S26, S31, S33, S35, S39, S42] and the existing energy not supplied (EENS) can be improved 391.705 kW to 306.4322 kW.
Abstract: Reliable electric power supply is a pillar perquisite for technological, social, political and economic development of any nation. Modernization and developing in every aspect without reliable electric power supply is un predictable. Here in our country Ethiopian has a serious power interruption problem because of unwanted very high outage frequenc...
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Research on Working Characteristics Prediction of Passenger Vehicle Shock Absorber Based on Deep Learning
Jinyun Chang,
Xuewu Zhu,
Chao Han,
Xingming Zhao,
Jiaxing Sun,
Feng Hu
Issue:
Volume 6, Issue 2, December 2022
Pages:
91-98
Received:
25 November 2022
Accepted:
16 December 2022
Published:
29 December 2022
DOI:
10.11648/j.ajece.20220602.15
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Abstract: The shock absorber is an important component of the automobile suspension system, which mainly plays the role of attenuating vibration during the driving of the car. The shock absorber is subjected to complex alternating loads during the recovery and compression process, and its dynamic damping characteristics show strong nonlinearity. The dynamic performance of the shock absorber has an important impact on the vehicle ride comfort and handling stability, so it is of great significance to carry out the prediction research on the working characteristics of the shock absorber. This paper introduces the structure and working principle of an automobile hydraulic shock absorber, and analyzes the reasons for the high nonlinearity of the working characteristics of the shock absorber. A prediction method and implementation framework of shock absorber working characteristics based on long short memory neural network (LSTM) algorithm are proposed, and abundant sample data are obtained through passenger vehicle durability test and shock absorber bench test. The effectiveness of feature selection is verified by data preprocessing and distribution law statistics. Finally, the LSTM intelligent algorithm is used to train, verify and test the sample data, and a prediction model of the working characteristics of the shock absorber is established. By comparing with the actual working characteristics data of the shock absorber, the accuracy and applicability of the prediction model are verified.
Abstract: The shock absorber is an important component of the automobile suspension system, which mainly plays the role of attenuating vibration during the driving of the car. The shock absorber is subjected to complex alternating loads during the recovery and compression process, and its dynamic damping characteristics show strong nonlinearity. The dynamic ...
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