• Earthquakes and Structures
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• v.17 no.1
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• pp.75-89
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• 2019

The paper presents experimental and numerical studies carried out on low-rise RC frames, typically found in developing countries. Shake table tests were conducted on 1:3 reduced scaled two-story RC frames that included a code conforming SMRF model and another non-compliant model. The later was similar to the code conforming model, except, it was prepared in concrete having strength 33% lower than the design specified, which is commonly found in the region. The models were tested on shake table, through multiple excitations, using acceleration time history of 1994 Northridge earthquake, which was linearly scaled for multi-levels excitations in order to study the structures' damage mechanism and measure the structural response. A representative numerical model was prepared in finite element based program SeismoStruct, simulating the observed local damage mechanisms (bar-slip and joint shear hinging), for seismic analysis of RC frames having weaker beam-column joints. A suite of spectrum compatible acceleration records was obtained from PEER for incremental dynamic analysis of considered RC frames. The seismic performance of considered RC frames was quantified in terms of seismic response parameters (seismic response modification, overstrength and displacement amplification factors), for critical comparison.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.1
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• pp.43-48
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• 2016

The objective of this study is to investigate the effect of HR practices such as (Recruitment, empowerment, working condition and compensation) on Job satisfaction in the prospects of Hotel Industry of Pakistan. The sample size for this study was 100 employees who were selected through convenience sampling techniques. This study was restricted to 10 Hotels of Peshawar. Hypotheses of the study were tested through correlation and regression analysis to inspect the employee's satisfaction. The findings investigates that there is significant relationship between HR practices and job satisfaction. Moreover Recruitment and selection, empowerment and working condition have positive effect on job satisfaction, while compensation has negative effect on job satisfaction, which indicates that most of employees are not satisfied from payment of employer. Empirical findings concluded that best HR practices have significant and positive effect on employees job satisfaction. Therefore, it is suggested for HR manager to understand and implement the HR practices correctly to take good work from their employees.

• Microbiology and Biotechnology Letters
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• v.50 no.2
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• pp.245-254
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• 2022

Cellulases are a group of biocatalyst enzymes that are capable of degrading cellulosic biomass present in the natural environment and produced by a large number of microorganisms, including bacteria and fungi, etc. In the current study, we isolated, screened and characterized cellulase-producing bacteria from soil. Three cellulose-degrading species were isolated based on clear zone using Congo red stain on carboxymethyl cellulose (CMC) agar plates. These bacterial isolates, named as HB2, HS5 and HS9, were subsequently characterized by morphological and biochemical tests as well as 16S rRNA gene sequencing. Based on 16S rRNA analysis, the bacterial isolates were identified as Bacillus cerus, Bacillus subtilis and Bacillus stratosphericus. Moreover, for maximum cellulase production, different growth parameters were optimized. Maximum optical density for growth was also noted at pH 7.0 for 48 h for all three isolates. Optical density was high for all three isolates using meat extract as a nitrogen source for 48 h. The pH profile of all three strains was quite similar but the maximum enzyme activity was observed at pH 7.0. Maximum cellulase production by all three bacterial isolates was noted when using lactose as a carbon rather than nitrogen and peptone. Further studies are needed for identification of new isolates in this region having maximum cellulolytic activity. Our findings indicate that this enzyme has various potential industrial applications.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3541-3546
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• 2014

TEL-AML1 fusion oncogene (t 12; 21) is the most common chromosomal abnormality in childhood acute lymphoblastic leukemia (ALL). This translocation is associated with a good prognosis and rarely shows chemotherapeutic resistance to 3-drug based remission induction phase of treatment as well as overall treatment. Thus, the higher the frequency of this fusion oncogene, the easier to manage childhood ALL in a given region with less intensive chemotherapy. Although global frequency of TEL-AML1 has been reported to be 20-30%, a very low frequency has been found in some geographical regions, including one study from Lahore, Punjab, Pakistan and others from India. The objective of present study was to investigate if this low frequency of TEL-AML1 in pediatric ALL is only in Lahore region or similar situation exists at other representative oncology centers of Pakistan. A total of 167 pediatric ALL patients were recruited from major pediatric oncology centers situated in Lahore, Faisalabad, Peshawar and Islamabad. Patients were tested for TEL-AML1 using nested reverse transcription polymerase chain reaction (RT-PCR). Only 17 out of 167 (10.2%) patients were found to be TEL-AML1 positive. TEL-AML1+ALL patients had favorable prognosis, most of them (82.4%, 14/17) showing early remission and good overall survival. Thus, our findings indicate an overall low frequency of TEL-AML1 in Pakistan pediatric ALL patients, in accordance with lower representation of this prognostically important genetic abnormality in other less developed countries, specifically in south Asia, thus associating it with poor living standards in these ethnic groups. It also indicates ethnic and geographical differences in the distribution of this prognostically important genetic abnormality among childhood ALL patients, which may have a significant bearing on ALL management strategies in different parts of the world.

• Structural Engineering and Mechanics
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• v.64 no.2
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• pp.213-223
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• 2017

Bridges are lifeline and integral components of transportation system that are susceptible to seismic actions, their vulnerability assessment is essential for seismic risk assessment and mitigation. The vulnerability assessment of bridges common in Pakistan is very important as it is seismically very active region and the available code for the seismic design of bridges is obsolete. This research presents seismic vulnerability assessment of three real case simply supported multi-span reinforced concrete bridges commonly found in northern Pakistan, having one, two and three bents with circular piers. The vulnerability assessment is carried through the non-linear dynamic time history analyses for the derivation of fragility curves. Finite element based numerical models of the bridges were developed in MIDAS CIVIL (2015) and analyzed through with non-linear dynamic and incremental dynamic analyses, using a suite of bridge-specific natural spectrum compatible ground motion records. Seismic responses of shear key, bearing pad, expansion joint and pier components of each bridges were recorded during analysis and retrieved for performance based analysis. Fragility curves were developed for the bearing pads, shear key, expansion joint and pier of the bridges that first reach ultimate limit state. Dynamic analysis and the derived fragility curves show that ultimate limit state of bearing pads, shear keys and expansion joints of the bridges exceed first, followed by the piers ultimate limit state for all the three bridges. Mean collapse capacities computed for all the components indicated that bearing pads, expansion joints, and shear keys exceed the ultimate limit state at lowest seismic intensities.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.319-331
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• 2022

The capability to examine an X-ray image is so far a challenging task. In this work, we suggest a practical and novel algorithm based on image fusion to inspect the issues such as background noise, blurriness, or sharpness, which curbs the quality of dual-energy X-ray images. The current technology exercised for the examination of bags and baggage is "X-ray"; however, the results of the incumbent technology used show blurred and low contrast level images. This paper aims to improve the quality of X-ray images for a clearer vision of illegitimate or volatile substances. A dataset of 40 images was taken for the experiment, but for clarity, the results of only 13 images have been shown. The results were evaluated using MSE and PSNR metrics, where the average PSNR value of the proposed system compared to single X-ray images was increased by 19.3%, and the MSE value decreased by 17.3%. The results show that the proposed framework will help discern threats and the entire scanning process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.