Research Article
Existence and Numerical Investigation of Monkey-Pox Mathematical Model by Natural Adomain Decomposition Method
Issue:
Volume 9, Issue 3, September 2024
Pages:
43-60
Received:
29 March 2024
Accepted:
10 August 2024
Published:
22 August 2024
DOI:
10.11648/j.mma.20240903.11
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Abstract: In this paper, studied the mathematical model concerning the transmission of Monkey-Pox disease. A class viral disease that mostly occurs in west and central Africa, transmitted from animals into human is belonging to the Small-pox family known is Monkey-pox infections disease. According to the scientist the primary best of the proposed disease is still in doubt. The proposed model will be investigate for the purpose of both qualitative and numerical solutions. At the early stage of this study, investigate the existence of proposed model. In this connection, the authors developed the desired condition of existence and stability for consider model by using the tools of analysis. At the second phase of this research work,the author investigated the numerical solutions for the consider Monkey-pox transmission diseases model. For numerical investigation, the authors use the tool of well know semi-analytical techniques known as Natural Transform coupled with Adomain Decomposition Method. The consider techniques are powerful tools for of obtaining approximate solutions of differential equation or system of differential equations. The proposed techniques base on recursive scheme for solutions of system of differential equations. For the authenticity and accuracy of obtain solutions, the obtain solutions are visualized graphically to desired the dynamical behavior of desired results with the help of Mathematica. That show the proposed method is best tools for solution of differential equations.
Abstract: In this paper, studied the mathematical model concerning the transmission of Monkey-Pox disease. A class viral disease that mostly occurs in west and central Africa, transmitted from animals into human is belonging to the Small-pox family known is Monkey-pox infections disease. According to the scientist the primary best of the proposed disease is ...
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Research Article
An Improved Single Objective Optimization Approach for Double-Layered Multi-Head Weighing Process
Issue:
Volume 9, Issue 3, September 2024
Pages:
61-69
Received:
12 July 2024
Accepted:
14 August 2024
Published:
6 September 2024
Abstract: In recent years, the double-layered multi-head weighers whose hoppers are arranged in two levels are widely used in the accurate and reliable weighing for packing food products. The weighing processes are mathematically modeled into a single objective optimization problems. The objective of packing problem is to minimize the total weight of combined hoppers for a package under the condition that the total weight must be no less than a specified target weight. This paper proposes a novel single objective optimization approach for double-layered multi-head weighing process. More precisely, relying on a new bound on the optimal weight, this study accurately determines the number of hoppers to be combined at each packing operation, and find the best possible hopper combination using the single-objective algorithm. This method significantly speeds up the packing process as a whole. According to the present approach, the candidate number of hoppers to be combined can be taken one or two integral values. The probability that the accurate number of hoppers to be combined becomes one integral value is explicitly calculated, which is the performance factor to the previous one. In addition, results from the numerical experiments to show the effectiveness of the proposed approach are presented.
Abstract: In recent years, the double-layered multi-head weighers whose hoppers are arranged in two levels are widely used in the accurate and reliable weighing for packing food products. The weighing processes are mathematically modeled into a single objective optimization problems. The objective of packing problem is to minimize the total weight of combine...
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Research Article
Analysis of Electroencephalographic Signals Using the Root Mean Square (RMS) Fluctuation Function: Applicable Sample Test
Issue:
Volume 9, Issue 3, September 2024
Pages:
70-75
Received:
19 August 2024
Accepted:
9 September 2024
Published:
29 September 2024
Abstract: Brain signals extracted through brain-computer interface systems (BCI2000- http://www.bci2000.org) allow researchers and computer scientists to cooperate with techniques, mathematical models and statistical inferences that allow the interpretation of a variety of signals provided by people with conditions that significantly affect the ability to move or perform motor activities due to limitations in muscles, bones or nervous system. For this study, we propose a preliminary test with the root mean square (rms) fluctuation function, with EEG data, whose task was the response given to real/imaginary motor stimulus. To validate the model and all the steps up to the configuration of the rms function, we chose the information contained in the EEG of subject S003, available in the public database https://physionet.org/content/eegmmidb/1.0.0/. Considering the distribution of electrodes in the brain (lobes: frontal, parietal, temporal and occipital) and given the data availability conditions (10 - 10 system, EDF format and 160 samples per second), we analyzed 12 of the 64 channels and four stimuli, namely: opening and closing the left or right fist, imagining opening and closing the left or right fist, opening and closing both fists or both feet and imagining opening and closing both fists or both feet. We evaluated their fluctuations individually and the amplitudes of channels 32 and 37 in relation to the others (11, 22, 24, 43, 44, 49, 54, 61, 63 and 64). We observed quantitative similarities when the brain performs the same real/imaginary motor task and that the time of the amplitude changes with the increase of the scale n (time scales). In all experiments (S003_R3, S003_R4, S003_R5, S003_R6), channel 32 x 24, for n > 20 (15 seconds) was smaller than the others, showing that channel 32 (left hemisphere) has the largest fluctuation. From data processing (.EDF) to visualization of FDFA/∆log curves, we conclude that it is possible to replicate the study for more channels, as well as to investigate other types of activities in the human brain adapted to potential variations (DDP) generated by neurons via signals extracted from the EEG device.
Abstract: Brain signals extracted through brain-computer interface systems (BCI2000- http://www.bci2000.org) allow researchers and computer scientists to cooperate with techniques, mathematical models and statistical inferences that allow the interpretation of a variety of signals provided by people with conditions that significantly affect the ability to mo...
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,
Amjad Ali
