Viewer`s Affective Feedback for Video Summarization

( Majdi Dammak ),( Ali Wali ),( Adel M Alimi ) 한국정보처리학회 2015 Journal of information processing systems Vol.11 No.1

For different reasons, many viewers like to watch a summary of films without having to waste their time. Traditionally, video film was analyzed manually to provide a summary of it, but this costs an important amount of work time. Therefore, it has become urgent to propose a tool for the automatic video summarization job. The automatic video summarization aims at extracting all of the important moments in which viewers might be interested. All summarization criteria can differ from one video to another. This paper presents how the emotional dimensions issued from real viewers can be used as an important input for computing which part is the most interesting in the total time of a film. Our results, which are based on lab experiments that were carried out, are significant and promising.

Digital Image Watermarking Based On Joint (DCT-DWT) and Arnold Transform

Majdi Farag Mohammed El Bireki,M. F. L. Abdullah,li Abdrhman M. Ukasha,Ali A. Elrowayati 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.5

The researcher has adopted a digital watermarking technique which operates in the frequency domain: a hybrid watermarking scheme based joint discrete wavelet transform – discrete cosine transform – (DWT-DCT). Its main objective is to test whether this technique can withstand attacks (its robustness) and invisibility (its imperceptibility), achieved by taking DCT of the DWT coefficients of the LL mid-frequency sub-bands from its band. To ensure security, the secret code (watermark) is scrambled using the Arnold transformation which is embedded in the original host image; only gray-scale digital images are used. The results of this research reveal that the secret code (watermark) is strong enough against threats (noise). Comparative results are measured using signal-to-noise ratio criterions, mean square error and normalized cross correlation. Simulated experimentation is done in Matlab.

Viewer's Affective Feedback for Video Summarization

Dammak, Majdi,Wali, Ali,Alimi, Adel M. Korea Information Processing Society 2015 Journal of information processing systems Vol.11 No.1

For different reasons, many viewers like to watch a summary of films without having to waste their time. Traditionally, video film was analyzed manually to provide a summary of it, but this costs an important amount of work time. Therefore, it has become urgent to propose a tool for the automatic video summarization job. The automatic video summarization aims at extracting all of the important moments in which viewers might be interested. All summarization criteria can differ from one video to another. This paper presents how the emotional dimensions issued from real viewers can be used as an important input for computing which part is the most interesting in the total time of a film. Our results, which are based on lab experiments that were carried out, are significant and promising.

A first-principles study of B3O3 monolayer as potential anode materials for calcium-ion batteries

Kadhim Mustafa M.,Majdi Ali,Hachim Safa K.,Abdullaha Sallalh. Ahmed,Taban Taleeb Zedan,Rheima Ahmed Mahdi 한국화학공학회 2023 Korean Journal of Chemical Engineering Vol.40 No.7

Anodic materials with fast kinetics and high capacity are prerequisites for improvement of calcium-ion batteries (CIBs). According to first-principles computations, unique calcium capacity was discovered for B3O3 monolayer. Based on findings, Ca atoms can be adsorbed on B3O3 surface, and the most stable location is the top of the pore center of B3O3 monolayer. Binding energy of B3O3 monolayer is relatively high for Ca atoms. In addition, Ca atoms have been shown to more simple diffuse on B3O3 surface, and lowest diffusion barrier was 65 meV. A more significant finding is that B3O3 monolayer-based nanostructures possess a relatively large capacity of 616.05 mAh/g (as Ca.51BO). These results are expected to support illumination mechanism of Ca storage in boron oxide materials with low-dimensional structures and pave the way for design of CIBs. Therefore, we can utilize the B3O3 anode-based CIBs as alternatives to normal Ca-ion batteries.

Thymol production in hairy root culture of Sahendian savory (Satureja sahendica Bornm)

Bahmani Helia,Maroufi Asad,Majdi Mohammad,Fakheri Barat Ali 한국식물생명공학회 2021 Plant biotechnology reports Vol.15 No.2

Sahendian savory (Satureja sahendica Bornm) is a medicinal plant species which produces valuable secondary metabolites including thymol, p-cymene and γ-terpinene. In this study, optimization of hairy roots culture in S. sahendica using Agrobac�terium rhizogenes was efciently established. High frequency of genetic transformation was obtained using node and inter�node explants and three bacterial strains (ATCC 15834, A4, and LBA 9402). However, leaf explants showed no susceptibility to induce hairy roots with the A. rhizogenes strains. The node explants and LBA 9402 strain were the best combination for root induction. Infection time of 20 min caused greater transformation occurrence compared to 10 and 30 min, respectively. Node explants infected with LBA 9402 were found to produce more transformants upon co-cultivation for 2 days. The maxi�mum induction of hairy roots was obtained from bacterial infection at a density of OD600=0.8. Polymerase chain reaction by gene-specifc primers from rol B gene confrmed the positive transformation events. S. sahendica efciently provided and produced a large number of hairy roots which could be used for the production of secondary metabolites or other molecular and biotechnological applications. Production of thymol an important secondary metabolite of S. sahendica from hairy root cultures was confrmed by TLC and GC analysis. Elicitor-treated hairy root cultures with methyl jasmonate and ammonium nitrate produced more amount of thymol compared to untreated roots. These results demonstrate that secondary metabolite production such as thymol in hairy root culture of Sahendian savory could be used to increase low secondary metabolite production in this valuable medicinal plant.

Individual disturbance and neighborhood mutation search enhanced whale optimization: performance design for engineering problems

Qiao Shimeng,Yu Helong,Heidari Ali Asghar,El-Saleh Ayman A,Cai Zhennao,Xu Xingmei,Mafarja Majdi,Chen Huiling 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5

The whale optimizer is a popular metaheuristic algorithm, which has the problems of weak global exploration, easy falling into local optimum, and low optimization accuracy when searching for the optimal solution. To solve these problems, this paper proposes an enhanced whale optimization algorithm (WOA) based on the worst individual disturbance (WD) and neighborhood mutation search (NM), named WDNMWOA, which employed WD to enhance the ability to jump out of local optimum and global exploration, adopted NM to enhance the possibility of individuals approaching the optimal solution. The superiority of WDNMWOA is demonstrated by representative IEEE CEC2014, CEC2017, CEC2019, and CEC2020 benchmark functions and four engineering examples. The experimental results show that thes WDNMWOA has better convergence accuracy and strong optimization ability than the original WOA.

A horizontal and vertical crossover cuckoo search: optimizing performance for the engineering problems

Su Hang,Zhao Dong,Yu Fanhua,Heidari Ali Asghar,Xu Zhangze,Alotaibi Fahd S,Mafarja Majdi,Chen Huiling 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.1

As science and technology advance, more engineering-type problems emerge. Technology development has likewise led to an increase in the complexity of optimization problems, and the need for new optimization techniques has increased. The swarm intelligence optimization algorithm is popular among researchers as a flexible, gradient-independent optimization method. The cuckoo search (CS) algorithm in the population intelligence algorithm has been widely used in various fields as a classical optimization algorithm. However, the current CS algorithm can no longer satisfy the performance requirements of the algorithm for current optimization problems. Therefore, in this paper, an improved CS algorithm based on a crossover optimizer (CC) and decentralized foraging (F) strategy is proposed to improve the search ability and the ability to jump out of the local optimum of the CS algorithm (CCFCS). Then, in order to verify the performance of the algorithm, this paper demonstrates the performance of CCFCS from six perspectives: core parameter setting, balance analysis of search and exploitation, the impact of introduced strategies, the impact of population dimension, and comparison with classical algorithms and similar improved algorithms. Finally, the optimization effect of CCFCS on real engineering problems is tested by five classic cases of engineering optimization. According to the experimental results, CCFCS has faster convergence and higher solution quality in the algorithm performance test and maintains the same excellent performance in engineering applications.

Ensembles of neural network with stochastic optimization algorithms in predicting concrete tensile strength

Juan Hu,Fenghui Dong,Yiqi Qiu,Lei Xi,Ali Majdi,H. Elhosiny Ali 국제구조공학회 2022 Steel and Composite Structures, An International J Vol.45 No.2

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDAMLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

Effects of mining activities on Nano-soil management using artificial intelligence models of ANN and ELM

Liu, Qi,Peng, Kang,Zeng, Jie,Marzouki, Riadh,Majdi, Ali,Jan, Amin,Salameh, Anas A.,Assilzadeh, Hamid Techno-Press 2022 Advances in nano research Vol.12 No.6

Mining of ore minerals (sfalerite, cinnabar, and chalcopyrite) from the old mine has led in significant environmental effects as contamination of soils and plants and acidification of water. Also, nanoparticles (NP) have obtained global importance because of their widespread usage in daily life, unique properties, and rapid development in the field of nanotechnology. Regarding their usage in various fields, it is suggested that soil is the final environmental sink for NPs. Nanoparticles with excessive reactivity and deliverability may be carried out as amendments to enhance soil quality, mitigate soil contaminations, make certain secure land-software of the traditional change substances and enhance soil erosion control. Meanwhile, there's no record on the usage of Nano superior substances for mine soil reclamation. In this study, five soil specimens have been tested at 4 sites inside the region of mine (<100 m) to study zeolites, and iron sulfide nanoparticles. Also, through using Artificial Neural Network (ANN) and Extreme Learning Machine (ELM), this study has tried to appropriately estimate the mechanical properties of soil under the effect of these Nano particles. Considering the RMSE and R2 values, Zeolite Nano materials could enhance the mine soil fine through increasing the clay-silt fractions, increasing the water holding capacity, removing toxins and improving nutrient levels. Also, adding iron sulfide minerals to the soils would possibly exacerbate the soil acidity problems at a mining site.