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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.
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.
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, Tanveer,Biswas, Indraneel,Lim, Han-Seok,Rahman, Mustafizur Korean Society for Precision Engineering 2008 International Journal of Precision Engineering and Vol.9 No.3
Electrolytic in-process dressing (ELID) grinding is a new technique for achieving a nanoscale surface finish on hard and brittle materials such as optical glass and ceramics. This process applies an electrochemical dressing on the metal-bonded diamond wheels to ensure constant protrusion of sharp cutting grits throughout the grinding cycle. In conventional ELID grinding, a constant source of pulsed DC power is supplied to the ELID cell, but a feedback mechanism is necessary to control the dressing power and obtain better performance. In this study, we propose a new closed-loop wheel dressing technique for grinding wheel truing that addresses the efficient correction of eccentric wheel rotation and the nonuniformity in the grinding wheel profile. The technique relies on an iterative control algorithm for the ELID power supply. An inductive sensor is used to measure the wheel profile based on the gap between the sensor head and wheel edge, and this is used as the feedback signal to control the pulse width of the power supply. We discuss the detailed mathematical design of the control algorithm and provide simulation results that were confirmed experimentally.
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.
Dentists' Perception of the Role they Play in Early Detection of Oral Cancer
Saleh, Amyza,Kong, Yink Heay,Vengu, Nedunchelian,Badrudeen, Haja,Zain, Rosnah Binti,Cheong, Sok Ching Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.1
Background: Dentists are typically the first professionals who are approached to treat ailments within the oral cavity. Therefore they should be well-equipped in detecting suspicious lesions during routine clinical practice. This study determined the levels of knowledge on early signs and risk factors associated with oral cancer and identified which factors influenced dentist participation in prevention and early detection of oral cancer. Materials and Methods: A survey on dentists' knowledge and their practices in prevention and early detection of oral cancer was conducted using a 26-item self-administered questionnaire. Results and Conclusions: A response rate of 41.7% was achieved. The level of knowledge on early signs and risk habits associated with oral cancer was high and the majority reported to have conducted opportunistic screening and advised patients on risk habit cessation. Factors that influenced the dentist in practising prevention and early detection of oral cancer were continuous education on oral cancer, age, nature of practice and recent graduation. Notably, dentists were receptive to further training in the area of oral cancer detection and cessation of risk habits. Taken together, the study demonstrated that the dental clinic is a good avenue to conduct programs on opportunistic screening, and continuous education in these areas is necessary to adequately equip dentists in running these programs. Further, this study also highlighted knowledge deficits and practice shortcomings which will help in planning and developing programs that further encourage better participation of dentists in prevention and early detection of oral cancer.