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Saleh Saeed(Saleh Saeed ),Sungjun Lee(Sungjun Lee),Yongju Cho(Yongju Cho),Unsang Park(Unsang Park) 한국전자통신연구원 2022 ETRI Journal Vol.44 No.6
The learning-based multiview stereo (MVS) methods for three-dimensional (3D) reconstruction generally use 3D volumes for depth inference. The quality of the reconstructed depth maps and the corresponding point clouds is directly influenced by the spatial resolution of the 3D volume. Consequently, these methods produce point clouds with sparse local regions because of the lack of the memory required to encode a high volume of information. Here, we apply the atrous spatial pyramid pooling (ASPP) module in MVS methods to obtain dense feature maps with multiscale, long-range, contextual information using high receptive fields. For a given 3D volume with the same spatial resolution as that in the MVS methods, the dense feature maps from the ASPP module encoded with superior information can produce dense point clouds without a high memory footprint. Furthermore, we propose a 3D loss for training the MVS networks, which improves the predicted depth values by 24.44%. The ASPP module provides state-of-the-art qualitative results by constructing relatively dense point clouds, which improves the DTU MVS dataset benchmarks by 2.25% compared with those achieved in the previous MVS methods.
Saleh A. Mohamed,Abdulrahman L. Al-Malki,Jalaluddin A. Khan,Saleh A. Kabli,Saleh M. Al-Garni 한국미생물학회 2013 The journal of microbiology Vol.51 No.5
Different solid state fermentation (SSF) sources were tested such as cantaloupe and watermelon rinds, orange and banana peels, for the production of polygalacturonase (PG) and xylanase (Xyl) by Trichoderma harzianum and Trichoderma virens. The maximum production of both PG and Xyl were obtained by T. harzianum and T. virnes grown on cantaloupe and watermelon rinds, respectively. Time course, moisture content, temperature, pH, supplementation with carbon and nitrogen sources were optimized to achieve the maximum production of both PG and Xyl of T. harzianum and T. virens using cantaloupe and watermelon rinds, respectively. The maximum production of PG and Xyl of T. harzianum and T. virens was recorded at 4–5 days of incubation, 50–66%moisture, temperature 28–35°C and pH 6–7. The influence of supplementary carbon and nitrogen sources was studied. For T. harzianum, lactose enhanced PG activity from 87 to 120 units/g solid, where starch and maltose enhanced Xyl activity from 40 to 55–60 units/g solid for T. virnes. Among the nitrogen sources, ammonium sulphate, ammonium nitrate,yeast extract and urea increased PG activity from 90to 110–113 units/g solid for T. harzianum. Similarly, ammonium chloride, ammonium sulphate and yeast extract increased Xyl activity from 45 to 55–70 units/g solid for T. virens.
AL-SALEH MOHAMMAD FRAIWAN,AL-ANANBEH AHMAD MOHAMMAD The Korean Statistical Society 2005 Journal of the Korean Statistical Society Vol.34 No.2
In this paper, we consider the estimation of the correlation coefficient in the bivariate normal distribution, based on a sample obtained using a modification of the moving extreme ranked set sampling technique (MERSS) that was introduced by Al-Saleh and Al-Hadhrami (2003a). The modification involves using a concomitant random variable. Nonparametric-type methods as well as the maximum likelihood estimation are considered under different settings. The obtained estimators are compared to their counterparts that are obtained based simple random sampling (SRS). It appears that the suggested estimators are more efficient
Other approaches to bivariate ranked set sampling
Al-Saleh, Mohammad Fraiwan,Alshboul, Hadeel Mohammad The Korean Statistical Society 2018 Communications for statistical applications and me Vol.25 No.3
Ranked set sampling, as introduced by McIntyre (Australian Journal of Agriculture Research, 3, 385-390, 1952), dealt with the estimation of the mean of one population. To deal with two or more variables, different forms of bivariate and multivariate ranked set sampling were suggested. For a technique to be useful, it should be easy to implement in practice. Bivariate ranked set sampling, as introduced by Al-Saleh and Zheng (Australian & New Zealand Journal of Statistics, 44, 221-232, 2002), is not easy to implement in practice, because it requires the judgment ranking of each of the combination of the order statistics of the two characteristics. This paper investigates two modifications that make the method easier to use. The first modification is based on ranking one variable and noting the rank of the other variable for one cycle, and do the reverse for another cycle. The second approach is based on ranking of one variable and giving the second variable the same rank (Concomitant Order Statistic) for one cycle and do the reverse for the other cycle. The two procedures are investigated for an estimation of the means of some well-known distributions. It is show that the suggested approaches can be used in practice and can be more efficient than using SRS. A real data set is used to illustrate the procedure.
Mohammad Fraiwan AL-Saleh,Ahmad Mohammad Al-Ananbeh 한국통계학회 2005 Journal of the Korean Statistical Society Vol.34 No.2
In this paper, we consider the estimation of the correlation coefficient in the bivariate normal distribution, based on a sample obtained using a modi- fication of the moving extreme ranked set sampling technique (MERSS) that was introduced by Al-Saleh and Al-Hadhrami (2003a). The modification involves using a concomitant random variable. Nonparametric-type methods as well as the maximum likelihood estimation are considered under different settings. The obtained estimators are compared to their counterparts that are obtained based simple random sampling (SRS). It appears that the suggested estimators are more efficient
Saleh A. Aldahash,Shaaban A. Salman,Abdelrasoul M. Gadelmoula 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.12
Recently, the adaptive network-based fuzzy inference system (ANFIS) has been used extensively in modeling of manufacturing processes to save both optimization time and manufacturing costs. ANFIS is a powerful iterative tool for optimizing non-linear and multivariable manufacturing operations. In the present study, ANFIS is used to predict the optimum manufacturing parameters in selective laser sintering (SLS) of cement-filled polyamide 12 (PA12) composite. For this purpose, a set of cement-filled PA12 test specimens is manufactured by SLS technique with 8 different values of laser power (4.5 - 8 Watt) and 8 different weight fractions of white cement (5 % - 40 %). Mechanical characterization of cementfilled PA12 is carried out to evaluate the ultimate tensile strength (UTS), compressive strength, and flexural properties. The experimental data are then divided into two groups; one group for training the ANFIS model and the other group for checking the validity of the identified model. The built ANFIS model was validated experimentally and comparison with experimental results revealed mean relative errors of 2.92 %, 3.84 %, 4.75 %, and 3.31 % in the predictions of UTS, compressive strength, flexural modulus, and flexural yield strength, respectively.
Saleh S. Baakeem,Jamel Orfi,Abdelbasset Bessadok-Jemai 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.4
Riyadh is a desert region characterized by large daily and seasonal ambient temperature variations. Air cooling using mechanical vapor compression requires high energy rates resulting in negative environmental impacts. The use of non-conventional cooling methods such as evaporative cooling is attractive and needs further investigations particularly in such critical weather conditions. This paper deals with the analysis of the performance of a direct evaporative cooling in hot and arid weather conditions. Theoretical models using heat and mass transfer, exergy and cost analysis are first developed and presented. Such models have been systematically validated using available experimental and theoretical results from previous studies. The second part of the work concerns the analysis of the performance of a direct evaporative cooler under a metropolitan central Arabian Peninsula (Riyadh, KSA) weather conditions using average hourly temperature and relative humidity of the month of July. The optimum operating parameters of the cooler have been then selected. The analysis shows that the effect of the cooler effectiveness on the exergy efficiency is not significant. The suitable value of the effectiveness of the evaporative cooler working under summer weather of the studied location is found to be between 0.7-0.8. Such a value achieves comfortable conditions at low cost.
Saleh, Matasem,Jhanjhi, NZ,Abdullah, Azween,Saher, Raazia International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.8
The Internet of Things (IoT) is a technology that offers lucrative services in various industries to facilitate human communities. Important information on people and their surroundings has been gathered to ensure the availability of these services. This data is vulnerable to cybersecurity since it is sent over the internet and kept in third-party databases. Implementation of data encryption is an integral approach for IoT device designers to protect IoT data. For a variety of reasons, IoT device designers have been unable to discover appropriate encryption to use. The static support provided by research and concerned organizations to assist designers in picking appropriate encryption costs a significant amount of time and effort. IoTES is a web app that uses machine language to address a lack of support from researchers and organizations, as ML has been shown to improve data-driven human decision-making. IoTES still has some weaknesses, which are highlighted in this research. To improve the support, these shortcomings must be addressed. This study proposes the "IoTES with Security" model by adding support for the security level provided by the encryption algorithm to the traditional IoTES model. We evaluated our technique for encryption algorithms with available security levels and compared the accuracy of our model with traditional IoTES. Our model improves IoTES by helping users make security-oriented decisions while choosing the appropriate algorithm for their IoT data.
UPHILL ZAGREB INDICES OF SOME GRAPH OPERATIONS FOR CERTAIN GRAPHS
SALEH, ANWAR,BAZHEAR, SARA,MUTHANA, NAJAT The Korean Society for Computational and Applied M 2022 Journal of applied mathematics & informatics Vol.40 No.5-6
The topological indices are numerical parameters which determined the biological, physical and chemical properties based on the structure of the chemical compounds. One of the recently topological indices is the uphill Zagreb indices. In this paper, the formulae of some uphill Zagreb indices for a few graph operations of some graphs have been derived. Furthermore, the precise formulae of those indices for the honeycomb network have been found along with their graphical profiles.