The aim of this study was to find out the prevalence of this anomaly in a sample of Pakistani pop... more The aim of this study was to find out the prevalence of this anomaly in a sample of Pakistani population. Mandibular premolar (MnP) is a tooth that frequently shows variation in its morphology such as size and shape. One of these anomalies is the tooth shape deviation (TSD) in which there is increased mesiodistal and reduced faciolingual width. Orthodontic records of 500 patients were examined to find out the presence of this anomaly. The male and female patients in permanent dentition stage were included in the study with exception to those having lower premolars missing or restored. The mesiodistal and faciolingual widths of lower premolars were measured on the plaster casts between the points of maximum widths, using needle pointed dividers, and the mesiodistal / faciolingual crown index was obtained for each tooth. The teeth with values >100 were labeled as MnP-TSD. Out of 500 patients observed in total, 17 were found to have MnP-TSD giving an overall prevalence of 3.4%. The ...
Introduction: Elastic ligatures are commonly used in fixed orthodontic treatment. They are used t... more Introduction: Elastic ligatures are commonly used in fixed orthodontic treatment. They are used to hold arch wires to the brackets. Manufacturers fabricate elastic ligatures in a number of different colors. While colored elastic ligatures tend to be more attractive, acceptance of the use of such ligatures varies a great deal with age and gender. Although it is suggested that an orthodontist should stock at least ten different colors of elastic ligatures at all times, little is actually known about the patients’ color preferences for elastic ligatures. The aim of this study was to evaluate the color preference of patients receiving elastic ligatures in fixed orthodontic treatment. Material and Methods: One hundred patients undergoing fixed orthodontic treatment at Armed Forces Institute of Dentistry were selected for this study. A self-administered questionnaire was used to assess the patients’ preference regarding elastic ligatures. Questions regarding choice of colored vs transpare...
Canadian Conference on Electrical and Computer Engineering, 2005.
Hardware Software Co-synthesis involves determining the hardware and software architectures for a... more Hardware Software Co-synthesis involves determining the hardware and software architectures for an application. This process involves selection of processing elements, mapping application parts to those processing elements followed by scheduling. Various heuristic based co-...
Journal of Back and Musculoskeletal Rehabilitation
BACKGROUND: The Muscle Energy Technique (MET) is one of the treatments of choice for the manageme... more BACKGROUND: The Muscle Energy Technique (MET) is one of the treatments of choice for the management of chronic mechanical low back pain (MLBP); however, there is a paucity of evidence to justify its effectiveness. OBJECTIVES: The objectives of this review are to explore, analyze and summarize the available evidence related to the effectiveness of MET in the management of chronic MLBP. METHOD: The scoping review methodology was adopted based on a recommendation from the work of Arksey and O’Malley, to systematically appraise literature and map the existing evidence on the effectiveness of MET in the management of chronic MLBP. A systematic search was performed comprising of an electronic search of online databases using key search terms and subsided by a hand search to identify the existing literature on the topic which was summarized and discussed. RESULT: Initially 25,195 hits were identified which were screened to examine their eligibility based on predetermined inclusion criteria...
Transportation Research Record: Journal of the Transportation Research Board
The choice of vehicle type is one of the important logistics decisions made by firms. The complex... more The choice of vehicle type is one of the important logistics decisions made by firms. The complex nature of the choice process is because of the involvement of multiple agents. This study employs a random forest machine learning algorithm to represent these complex interactions with limited information about shipment transportation. The data are from Commercial Travel Surveys with information about outbound shipment transportation. This study models the choice among four road transport vehicle types: pickup/cube van, single-unit truck, tractor trailer, and passenger car. The characteristics of firms and shipments are used as explanatory variables. SHAP-based variable importance is calculated to interpret the importance of each variable, and shows that employment and weight are the most important variables in determining the choice of vehicle type. The random forest model is also compared with the multinomial and mixed logit models. The model prediction results on the validation data...
Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL has resulted ... more Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL has resulted in greatly reducing the execution time of data-parallel applications by taking advantage of the massive available parallelism. However, when a small data size application is executed on GPU there is a wastage of GPU resources as the application cannot fully utilize GPU compute-cores. There is no mechanism to share a GPU between two kernels due to the lack of operating system support on GPU. In this paper, we propose the provision of a GPU sharing mechanism between two kernels that will lead to increasing GPU occupancy, and as a result, reduce execution time of a job pool. However, if a pair of the kernel is competing for the same set of resources (i.e., both applications are compute-intensive or memory-intensive), kernel fusion may also result in a significant increase in execution time of fused kernels. Therefore, it is pertinent to select an optimal pair of kernels for fusion that will result in significant speedup over their serial execution. This research presents FusionCL, a machine learning-based GPU sharing mechanism between a pair of OpenCL kernels. FusionCL identifies each pair of kernels (from the job pool), which are suitable candidates for fusion using a machine learning-based fusion suitability classifier. Thereafter, from all the candidates, it selects a pair of candidate kernels that will produce maximum speedup after fusion over their serial execution using a fusion speedup predictor. The experimental evaluation shows that the proposed kernel fusion mechanism reduces execution time by 2.83× when compared to a baseline scheduling scheme. When compared to state-of-the-art, the reduction in execution time is up to 8%.
Objective: To evaluate the efficacy and toxicity of low dose sequential docetaxel-capecitabine ch... more Objective: To evaluate the efficacy and toxicity of low dose sequential docetaxel-capecitabine chemotherapy as first line treatment of HER 2 negative metastatic breast cancer (MBC). Design: Experimental Study, Clinical Trial. Setting: Three different oncology centers, collaborating under the Cancer Research Group Pakistan. Period: From June 2006 to December 2007. Methods: Female breast cancer patients with visceral or visceral and bone metastases and a KPS > 70 were eligible. Results: 38 patients were enrolled. Median agewas 49 years (Range 32-70). With docetaxel treatment, CR was seen in 06 (16%) patients and PR in 20 (53%) with an overall response rate of 69%. Stable disease was seen in 10 (26%) and PD in 02 (05%). Four out of six complete responses were in patients with liver metastases. Thirty six patients received capecitabine. Thirty were evaluable for response. Capecitabine added one CR (3.33%) and six partial responses (20%).Two patients (6.67 %) who had a partial respons...
Effective vector representation has been proven useful for transaction classification and cluster... more Effective vector representation has been proven useful for transaction classification and clustering tasks in Cyber-Physical Systems. Traditional methods use heuristic-based approaches and different pruning strategies to discover the required patterns efficiently. With the extensive and high dimensional availability of transactional data in cyber-physical systems, traditional methods that used frequent itemsets (FIs) as features suffer from dimensionality, sparsity, and privacy issues. In this paper, we first propose a federated learning-based embedding model for the transaction classification task. The model takes transaction data as a set of frequent item-sets. Afterward, the model can learn low dimensional continuous vectors by preserving the frequent item-sets contextual relationship. We perform an in-depth experimental analysis on the number of high dimensional transactional data to verify the developed models with attention-based mechanism and federated learning. From the resu...
Objective: To determine the clinical outcome of patients admitted with acute anterior versus acut... more Objective: To determine the clinical outcome of patients admitted with acute anterior versus acute inferior wall myocardial infarction. Study Design: Comparative cross-sectional study. Place and Duration of Study: The study was conducted in emergency departments and adult cardiology wards of Armed Forces Institute of Cardiology/National Institute of Heart Diseases, from Aug 2019 to Nov 2019. Methodology: This study was conducted on 340 patients (208 patients with Anterior wall myocardial infarction and 132 patients with inferior wall MI who presented with Acute ST-Elevation MI) to emergency department of Armed Forces Institute of Cardiology/National Institute of Heart Disease during specified period. Outcome was calculated using Electrocardiogram, Two-dimensional transthoracic echocardiogram, Troponin-I, baseline investigations and coro angiography Data was entered and analyzed with SPSS-23. Results: Mean age was 59.38 ± 12.91 years in each group. In clinical symptoms chest pain was...
High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utili... more High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utility patterns from databases. Most existing algorithms of HUIM only consider the itemset utility regardless of the length. This limitation raises the utility as a result of a growing itemset size. High average-utility itemset mining (HAUIM) considers the size of the itemset, thus providing a more balanced scale to measure the average-utility for decision-making. Several algorithms were presented to efficiently mine the set of high average-utility itemsets (HAUIs) but most of them focus on handling static databases. In the past, a fast-updated (FUP)-based algorithm was developed to efficiently handle the incremental problem but it still has to re-scan the database when the itemset in the original database is small but there is a high average-utility upper-bound itemset (HAUUBI) in the newly inserted transactions. In this paper, an efficient framework called PRE-HAUIMI for transaction insert...
Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs an... more Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs and GPUs. If the application is mapped to an appropriate processing core, then these architectures provide many performance benefits to applications. Typically, programmers map sequential applications to CPU and parallel applications to GPU. The task mapping becomes challenging because of the usage of evolving and complex CPU- and GPU-based architectures. This paper presents an approach to map the OpenCL application to heterogeneous multi-core architecture by determining the application suitability and processing capability. The classification is achieved by developing a machine learning-based device suitability classifier that predicts which processor has the highest computational compatibility to run OpenCL applications. In this paper, 20 distinct features are proposed that are extracted by using the developed LLVM-based static analyzer. In order to select the best subset of features, fe...
Objective: The relevance and use of Muscle Energy Technique (MET) as a mode of treatment for Non-... more Objective: The relevance and use of Muscle Energy Technique (MET) as a mode of treatment for Non-specific low back pain (NSLBP) over the last two decades has increased among physiotherapists and other health professionals. This supports the clinical relevance and efficacy of this technique. However, there are no studies to determine the level of MET knowledge among Nigerian physiotherapists. This study was designed to determine the MET knowledge among Nigerian physiotherapists.Method: A total of one hundred and twenty physiotherapists were recruited from the database of the Nigerian Society of Physiotherapy and participated in the study. They completed a semi-structured questionnaire containing 46-items. This was divided into four sections which sourced information on sociodemographic characteristics, work-profile, treatment activities and the knowledge of MET for the management of NSLBP. Data were analyzed using descriptive statistics for mean, frequency and percentages. Inferentia...
Our database tracking of USA water usage per well indicates that traditionally shale operators ha... more Our database tracking of USA water usage per well indicates that traditionally shale operators have been using, on average 3 to 6 million gallons of water; even up to 8 million for the entire life cycle of the well based on its suitability for re-fracturing to stimulate their long and lateral horizontal wells. According to our data, sourcing, storage, transportation, treatment, and disposal of this large volume of water could account for up to 10% of overall drilling and completion costs. With increasingly stringent regulations governing the use of fresh water and growing challenges associated with storage and use of produced and flowback water in hydraulic fracturing, finding alternative sources of fracturing fluid is already a hot debate among both the scientific community and industry experts. On the other hand, waterless fracturing technology providers claim their technology can solve the concerns of water availability for shale development. This study reviews high-level technical issues and opportunities in this challenging and growing market and evaluates key economic drivers behind water management practices such as waterless fracturing technologies, based on a given shale gas play in the United States and experience gained in Canada. Water costs are analyzed under a variety of scenarios with and without the use of (fresh) water. The results are complemented by surveys from several oil and gas operators. Our economic analysis shows that fresh water usage offers the greatest economic return. In regions where water sourcing is a challenge, however, the short-term economic advantage of using non-fresh water-based fracturing outweighs the capital costs required by waterless fracturing methods. Until waterless methods are cost competitive, recycled water usage with low treatment offers a similar net present value (NPV) to that of sourcing freshwater via truck, for instance.
Hollywood enjoys the position of being the biggest movie producers when it comes to global recogn... more Hollywood enjoys the position of being the biggest movie producers when it comes to global recognition among movie-making industries. Despite being the biggest movie producer, it has been facing high revenue losses lately since most of the films that it has created have failed to capture viewer’s attention in the first few weeks of its release resulting in a box-office flop. It has been observed in a recent study that Hollywood is estimated to witness a loss of around 1 billion to almost 10 billion US dollars till 2020. Revenue risks have created immense pressure on movie producing stakeholders. They feel a constant pressure to come up with a formula to make a successful movie, however, to date; there are no fixed ingredients that can ensure the success of a movie. Researchers and movie producers constantly feel a need to have some expert systems which would predict the fate of the movie prior to its production with reasonable accuracy. Regardless of the difficult nature of the issue area, few researchers have created expert systems to forecast the financial success of movies using different approaches, but most of them are targeted pre-release forecasting or have low prediction accuracy. Such predictions are of a seminal nature as of their limited prediction scope, and non-ability to reduce revenue loss risk. Therefore, there is a constant demand from investors to have pre-production forecasting tools with high accuracy which can help them plan and make necessary alterations to save huge investments. In this study, we proposed eighteen new features to forecast box-office success, as soon as the quotient (director and cast) signs an agreement. This proposed forecasting time is the earliest prediction that has ever been reported in the movie forecasting literature. The decision support system ranks director and lead cast by utilizing their performances of the last 100 years (1915–2015). The processed output file is a table that ranks each director and cast into four categories based on cast experience, journalist critics, media reporting, user ratings, and revenue generated by associating movie. To produce more accurate results, learner-based feature selection is also performed to select the best subsets of features. This system is intended to be a dynamic tool, integrating further data for real-time adaptation. The system has the ability to incorporate different feature selection algorithm for the progressive improvement of movie success forecasting We demonstrate the effectiveness of extracting features and explain how they improve forecasting accuracy over existing models. The adaptive behaviour of the presented system is achieved by incorporating conceptually different machine learning classifiers, i.e. support vector machine, gradient boosting, extreme boosting classifier, and random forest. A voting system is used to make the prediction by averaging the output class-probabilities. To assess the adequacy of new features, a cross-validation test is directed. Our classification results are evaluated by using two performance measures, i.e. average per cent success rate, or within one class away from its actual prediction. The new features have achieved the most noteworthy accuracy of 85% with an expansion of a 46.43% (average per cent success rate) and 5.56% (within a class away) in comparison with other state-of-the-art feature sets.
The economic role of human capital, particularly education has long been documented by economists... more The economic role of human capital, particularly education has long been documented by economists and policy makers [Becker (1964)]. According to some observers view, educational system is an effective vehicle for producing the skills required to maintain growth in the economy.1 The versatile impact of education on every aspect of human existence makes it a vital area for policy framework especially for developing countries. Developing countries where majority of world’s population resides need to maximise productivity and capabilities of the advanced human capital. The benefits of education range from human to economic, social and cultural. At human level, education contributes in attractive self esteem and confidence leading towards empowerment. In Pakistan, there is significant rise in the average level of education, but over time, more and more workers incapable to use their educational background on the job. Two decades ago, it was judgment that supply of labour meeting the dem...
Abu Dhabi International Petroleum Exhibition & Conference
Conventional Coiled tubing well intervention has been carried out in oil and gas wells for more t... more Conventional Coiled tubing well intervention has been carried out in oil and gas wells for more than 30 years with not real-time data acquisition. With the advent of Coiled Tubing Telemetry (CTT) e-line/fiber optics/mono conductors in coiled tubing industry, a wide variety of opportunities has become available - downhole video camera (DVC) being one of them, to go beyond the conventional parameters and optimize the well intervention operation. DVC is used in the oil and gas industry with high success rate reported by several operating companies and service companies around the world. Video cameras have mostly been deployed using e-line; however, Coiled tubing camera runs provide the ability to clean the wellbore (by pumping fresh water or solvent) for capturing clearer, crisper videos and images. As the oil and gas industry is moving towards improving operating efficiency, minimizing the coiled tubing runs based on actual downhole data is of utmost importance. Therefore, having the ...
Abstract Among all PV devices, DSSCs are believed to be one of the most promising devices, owing ... more Abstract Among all PV devices, DSSCs are believed to be one of the most promising devices, owing to their low cost, facile methods of fabrication and eco-friendly nature. Several components such are titanium dioxide/metal oxide-based photoanode, platinum/composite material based counter electrode and sensitizing dye along with the electrolyte are the basic components which effects the performance of DSSCs. Counter electrode collects the electron from an external circuit and helps in the regeneration of dye by oxidation-reduction of electrolyte, which significantly effects the overall performance of PV devices. Several materials such as carbonaceous materials, conducting polymers, oxides, and sulfides have been investigated as the low cost and highly stable material for the potential replacement for an expensive Pt-based counter electrode in DSSCs. In this Review, an attempt has been made to present recent achievements to replace Platinum (Pt) counter electrode with other inexpensive and earth abundant materials for DSSCs. This article systematically reviews the counter electrodes in DSSCs and provides review focused on Pt-TCO free counter electrodes. The main problems and challenges such as synthesis and fabrication of various CE, commercialization of DSSCs are addressed in detail with a conclusion and proposition section.
Energy is considered to be the life line of an economy, the most vital instrument of socioeconomi... more Energy is considered to be the life line of an economy, the most vital instrument of socioeconomic development and has been recognised as one of the most important strategic commodities [Sahir and Qureshi (2007)]. Energy is not only essential for the economy but its supply is uncertain [Zaleski (2001)]. Energy is a strategic source that influenced the outcomes of wars, fueled and strangled economic development and polluted as well as clean up the environment. In the era of globalisation, a rapidly increasing demand for energy and dependency of countries on energy indicate that energy will be one of the biggest problems in the world in the next century. This requires for alternative and renewable sources of energy. Traditional growth theories focus much on the labour and capital as major factor of production and ignore the importance of energy in the growth process [Stern and Cleveland (2004)]. The neo-classical production theories stresses that economic growth increases with the inc...
The aim of this study was to find out the prevalence of this anomaly in a sample of Pakistani pop... more The aim of this study was to find out the prevalence of this anomaly in a sample of Pakistani population. Mandibular premolar (MnP) is a tooth that frequently shows variation in its morphology such as size and shape. One of these anomalies is the tooth shape deviation (TSD) in which there is increased mesiodistal and reduced faciolingual width. Orthodontic records of 500 patients were examined to find out the presence of this anomaly. The male and female patients in permanent dentition stage were included in the study with exception to those having lower premolars missing or restored. The mesiodistal and faciolingual widths of lower premolars were measured on the plaster casts between the points of maximum widths, using needle pointed dividers, and the mesiodistal / faciolingual crown index was obtained for each tooth. The teeth with values >100 were labeled as MnP-TSD. Out of 500 patients observed in total, 17 were found to have MnP-TSD giving an overall prevalence of 3.4%. The ...
Introduction: Elastic ligatures are commonly used in fixed orthodontic treatment. They are used t... more Introduction: Elastic ligatures are commonly used in fixed orthodontic treatment. They are used to hold arch wires to the brackets. Manufacturers fabricate elastic ligatures in a number of different colors. While colored elastic ligatures tend to be more attractive, acceptance of the use of such ligatures varies a great deal with age and gender. Although it is suggested that an orthodontist should stock at least ten different colors of elastic ligatures at all times, little is actually known about the patients’ color preferences for elastic ligatures. The aim of this study was to evaluate the color preference of patients receiving elastic ligatures in fixed orthodontic treatment. Material and Methods: One hundred patients undergoing fixed orthodontic treatment at Armed Forces Institute of Dentistry were selected for this study. A self-administered questionnaire was used to assess the patients’ preference regarding elastic ligatures. Questions regarding choice of colored vs transpare...
Canadian Conference on Electrical and Computer Engineering, 2005.
Hardware Software Co-synthesis involves determining the hardware and software architectures for a... more Hardware Software Co-synthesis involves determining the hardware and software architectures for an application. This process involves selection of processing elements, mapping application parts to those processing elements followed by scheduling. Various heuristic based co-...
Journal of Back and Musculoskeletal Rehabilitation
BACKGROUND: The Muscle Energy Technique (MET) is one of the treatments of choice for the manageme... more BACKGROUND: The Muscle Energy Technique (MET) is one of the treatments of choice for the management of chronic mechanical low back pain (MLBP); however, there is a paucity of evidence to justify its effectiveness. OBJECTIVES: The objectives of this review are to explore, analyze and summarize the available evidence related to the effectiveness of MET in the management of chronic MLBP. METHOD: The scoping review methodology was adopted based on a recommendation from the work of Arksey and O’Malley, to systematically appraise literature and map the existing evidence on the effectiveness of MET in the management of chronic MLBP. A systematic search was performed comprising of an electronic search of online databases using key search terms and subsided by a hand search to identify the existing literature on the topic which was summarized and discussed. RESULT: Initially 25,195 hits were identified which were screened to examine their eligibility based on predetermined inclusion criteria...
Transportation Research Record: Journal of the Transportation Research Board
The choice of vehicle type is one of the important logistics decisions made by firms. The complex... more The choice of vehicle type is one of the important logistics decisions made by firms. The complex nature of the choice process is because of the involvement of multiple agents. This study employs a random forest machine learning algorithm to represent these complex interactions with limited information about shipment transportation. The data are from Commercial Travel Surveys with information about outbound shipment transportation. This study models the choice among four road transport vehicle types: pickup/cube van, single-unit truck, tractor trailer, and passenger car. The characteristics of firms and shipments are used as explanatory variables. SHAP-based variable importance is calculated to interpret the importance of each variable, and shows that employment and weight are the most important variables in determining the choice of vehicle type. The random forest model is also compared with the multinomial and mixed logit models. The model prediction results on the validation data...
Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL has resulted ... more Employing general-purpose graphics processing units (GPGPU) with the help of OpenCL has resulted in greatly reducing the execution time of data-parallel applications by taking advantage of the massive available parallelism. However, when a small data size application is executed on GPU there is a wastage of GPU resources as the application cannot fully utilize GPU compute-cores. There is no mechanism to share a GPU between two kernels due to the lack of operating system support on GPU. In this paper, we propose the provision of a GPU sharing mechanism between two kernels that will lead to increasing GPU occupancy, and as a result, reduce execution time of a job pool. However, if a pair of the kernel is competing for the same set of resources (i.e., both applications are compute-intensive or memory-intensive), kernel fusion may also result in a significant increase in execution time of fused kernels. Therefore, it is pertinent to select an optimal pair of kernels for fusion that will result in significant speedup over their serial execution. This research presents FusionCL, a machine learning-based GPU sharing mechanism between a pair of OpenCL kernels. FusionCL identifies each pair of kernels (from the job pool), which are suitable candidates for fusion using a machine learning-based fusion suitability classifier. Thereafter, from all the candidates, it selects a pair of candidate kernels that will produce maximum speedup after fusion over their serial execution using a fusion speedup predictor. The experimental evaluation shows that the proposed kernel fusion mechanism reduces execution time by 2.83× when compared to a baseline scheduling scheme. When compared to state-of-the-art, the reduction in execution time is up to 8%.
Objective: To evaluate the efficacy and toxicity of low dose sequential docetaxel-capecitabine ch... more Objective: To evaluate the efficacy and toxicity of low dose sequential docetaxel-capecitabine chemotherapy as first line treatment of HER 2 negative metastatic breast cancer (MBC). Design: Experimental Study, Clinical Trial. Setting: Three different oncology centers, collaborating under the Cancer Research Group Pakistan. Period: From June 2006 to December 2007. Methods: Female breast cancer patients with visceral or visceral and bone metastases and a KPS > 70 were eligible. Results: 38 patients were enrolled. Median agewas 49 years (Range 32-70). With docetaxel treatment, CR was seen in 06 (16%) patients and PR in 20 (53%) with an overall response rate of 69%. Stable disease was seen in 10 (26%) and PD in 02 (05%). Four out of six complete responses were in patients with liver metastases. Thirty six patients received capecitabine. Thirty were evaluable for response. Capecitabine added one CR (3.33%) and six partial responses (20%).Two patients (6.67 %) who had a partial respons...
Effective vector representation has been proven useful for transaction classification and cluster... more Effective vector representation has been proven useful for transaction classification and clustering tasks in Cyber-Physical Systems. Traditional methods use heuristic-based approaches and different pruning strategies to discover the required patterns efficiently. With the extensive and high dimensional availability of transactional data in cyber-physical systems, traditional methods that used frequent itemsets (FIs) as features suffer from dimensionality, sparsity, and privacy issues. In this paper, we first propose a federated learning-based embedding model for the transaction classification task. The model takes transaction data as a set of frequent item-sets. Afterward, the model can learn low dimensional continuous vectors by preserving the frequent item-sets contextual relationship. We perform an in-depth experimental analysis on the number of high dimensional transactional data to verify the developed models with attention-based mechanism and federated learning. From the resu...
Objective: To determine the clinical outcome of patients admitted with acute anterior versus acut... more Objective: To determine the clinical outcome of patients admitted with acute anterior versus acute inferior wall myocardial infarction. Study Design: Comparative cross-sectional study. Place and Duration of Study: The study was conducted in emergency departments and adult cardiology wards of Armed Forces Institute of Cardiology/National Institute of Heart Diseases, from Aug 2019 to Nov 2019. Methodology: This study was conducted on 340 patients (208 patients with Anterior wall myocardial infarction and 132 patients with inferior wall MI who presented with Acute ST-Elevation MI) to emergency department of Armed Forces Institute of Cardiology/National Institute of Heart Disease during specified period. Outcome was calculated using Electrocardiogram, Two-dimensional transthoracic echocardiogram, Troponin-I, baseline investigations and coro angiography Data was entered and analyzed with SPSS-23. Results: Mean age was 59.38 ± 12.91 years in each group. In clinical symptoms chest pain was...
High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utili... more High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utility patterns from databases. Most existing algorithms of HUIM only consider the itemset utility regardless of the length. This limitation raises the utility as a result of a growing itemset size. High average-utility itemset mining (HAUIM) considers the size of the itemset, thus providing a more balanced scale to measure the average-utility for decision-making. Several algorithms were presented to efficiently mine the set of high average-utility itemsets (HAUIs) but most of them focus on handling static databases. In the past, a fast-updated (FUP)-based algorithm was developed to efficiently handle the incremental problem but it still has to re-scan the database when the itemset in the original database is small but there is a high average-utility upper-bound itemset (HAUUBI) in the newly inserted transactions. In this paper, an efficient framework called PRE-HAUIMI for transaction insert...
Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs an... more Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs and GPUs. If the application is mapped to an appropriate processing core, then these architectures provide many performance benefits to applications. Typically, programmers map sequential applications to CPU and parallel applications to GPU. The task mapping becomes challenging because of the usage of evolving and complex CPU- and GPU-based architectures. This paper presents an approach to map the OpenCL application to heterogeneous multi-core architecture by determining the application suitability and processing capability. The classification is achieved by developing a machine learning-based device suitability classifier that predicts which processor has the highest computational compatibility to run OpenCL applications. In this paper, 20 distinct features are proposed that are extracted by using the developed LLVM-based static analyzer. In order to select the best subset of features, fe...
Objective: The relevance and use of Muscle Energy Technique (MET) as a mode of treatment for Non-... more Objective: The relevance and use of Muscle Energy Technique (MET) as a mode of treatment for Non-specific low back pain (NSLBP) over the last two decades has increased among physiotherapists and other health professionals. This supports the clinical relevance and efficacy of this technique. However, there are no studies to determine the level of MET knowledge among Nigerian physiotherapists. This study was designed to determine the MET knowledge among Nigerian physiotherapists.Method: A total of one hundred and twenty physiotherapists were recruited from the database of the Nigerian Society of Physiotherapy and participated in the study. They completed a semi-structured questionnaire containing 46-items. This was divided into four sections which sourced information on sociodemographic characteristics, work-profile, treatment activities and the knowledge of MET for the management of NSLBP. Data were analyzed using descriptive statistics for mean, frequency and percentages. Inferentia...
Our database tracking of USA water usage per well indicates that traditionally shale operators ha... more Our database tracking of USA water usage per well indicates that traditionally shale operators have been using, on average 3 to 6 million gallons of water; even up to 8 million for the entire life cycle of the well based on its suitability for re-fracturing to stimulate their long and lateral horizontal wells. According to our data, sourcing, storage, transportation, treatment, and disposal of this large volume of water could account for up to 10% of overall drilling and completion costs. With increasingly stringent regulations governing the use of fresh water and growing challenges associated with storage and use of produced and flowback water in hydraulic fracturing, finding alternative sources of fracturing fluid is already a hot debate among both the scientific community and industry experts. On the other hand, waterless fracturing technology providers claim their technology can solve the concerns of water availability for shale development. This study reviews high-level technical issues and opportunities in this challenging and growing market and evaluates key economic drivers behind water management practices such as waterless fracturing technologies, based on a given shale gas play in the United States and experience gained in Canada. Water costs are analyzed under a variety of scenarios with and without the use of (fresh) water. The results are complemented by surveys from several oil and gas operators. Our economic analysis shows that fresh water usage offers the greatest economic return. In regions where water sourcing is a challenge, however, the short-term economic advantage of using non-fresh water-based fracturing outweighs the capital costs required by waterless fracturing methods. Until waterless methods are cost competitive, recycled water usage with low treatment offers a similar net present value (NPV) to that of sourcing freshwater via truck, for instance.
Hollywood enjoys the position of being the biggest movie producers when it comes to global recogn... more Hollywood enjoys the position of being the biggest movie producers when it comes to global recognition among movie-making industries. Despite being the biggest movie producer, it has been facing high revenue losses lately since most of the films that it has created have failed to capture viewer’s attention in the first few weeks of its release resulting in a box-office flop. It has been observed in a recent study that Hollywood is estimated to witness a loss of around 1 billion to almost 10 billion US dollars till 2020. Revenue risks have created immense pressure on movie producing stakeholders. They feel a constant pressure to come up with a formula to make a successful movie, however, to date; there are no fixed ingredients that can ensure the success of a movie. Researchers and movie producers constantly feel a need to have some expert systems which would predict the fate of the movie prior to its production with reasonable accuracy. Regardless of the difficult nature of the issue area, few researchers have created expert systems to forecast the financial success of movies using different approaches, but most of them are targeted pre-release forecasting or have low prediction accuracy. Such predictions are of a seminal nature as of their limited prediction scope, and non-ability to reduce revenue loss risk. Therefore, there is a constant demand from investors to have pre-production forecasting tools with high accuracy which can help them plan and make necessary alterations to save huge investments. In this study, we proposed eighteen new features to forecast box-office success, as soon as the quotient (director and cast) signs an agreement. This proposed forecasting time is the earliest prediction that has ever been reported in the movie forecasting literature. The decision support system ranks director and lead cast by utilizing their performances of the last 100 years (1915–2015). The processed output file is a table that ranks each director and cast into four categories based on cast experience, journalist critics, media reporting, user ratings, and revenue generated by associating movie. To produce more accurate results, learner-based feature selection is also performed to select the best subsets of features. This system is intended to be a dynamic tool, integrating further data for real-time adaptation. The system has the ability to incorporate different feature selection algorithm for the progressive improvement of movie success forecasting We demonstrate the effectiveness of extracting features and explain how they improve forecasting accuracy over existing models. The adaptive behaviour of the presented system is achieved by incorporating conceptually different machine learning classifiers, i.e. support vector machine, gradient boosting, extreme boosting classifier, and random forest. A voting system is used to make the prediction by averaging the output class-probabilities. To assess the adequacy of new features, a cross-validation test is directed. Our classification results are evaluated by using two performance measures, i.e. average per cent success rate, or within one class away from its actual prediction. The new features have achieved the most noteworthy accuracy of 85% with an expansion of a 46.43% (average per cent success rate) and 5.56% (within a class away) in comparison with other state-of-the-art feature sets.
The economic role of human capital, particularly education has long been documented by economists... more The economic role of human capital, particularly education has long been documented by economists and policy makers [Becker (1964)]. According to some observers view, educational system is an effective vehicle for producing the skills required to maintain growth in the economy.1 The versatile impact of education on every aspect of human existence makes it a vital area for policy framework especially for developing countries. Developing countries where majority of world’s population resides need to maximise productivity and capabilities of the advanced human capital. The benefits of education range from human to economic, social and cultural. At human level, education contributes in attractive self esteem and confidence leading towards empowerment. In Pakistan, there is significant rise in the average level of education, but over time, more and more workers incapable to use their educational background on the job. Two decades ago, it was judgment that supply of labour meeting the dem...
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Conventional Coiled tubing well intervention has been carried out in oil and gas wells for more t... more Conventional Coiled tubing well intervention has been carried out in oil and gas wells for more than 30 years with not real-time data acquisition. With the advent of Coiled Tubing Telemetry (CTT) e-line/fiber optics/mono conductors in coiled tubing industry, a wide variety of opportunities has become available - downhole video camera (DVC) being one of them, to go beyond the conventional parameters and optimize the well intervention operation. DVC is used in the oil and gas industry with high success rate reported by several operating companies and service companies around the world. Video cameras have mostly been deployed using e-line; however, Coiled tubing camera runs provide the ability to clean the wellbore (by pumping fresh water or solvent) for capturing clearer, crisper videos and images. As the oil and gas industry is moving towards improving operating efficiency, minimizing the coiled tubing runs based on actual downhole data is of utmost importance. Therefore, having the ...
Abstract Among all PV devices, DSSCs are believed to be one of the most promising devices, owing ... more Abstract Among all PV devices, DSSCs are believed to be one of the most promising devices, owing to their low cost, facile methods of fabrication and eco-friendly nature. Several components such are titanium dioxide/metal oxide-based photoanode, platinum/composite material based counter electrode and sensitizing dye along with the electrolyte are the basic components which effects the performance of DSSCs. Counter electrode collects the electron from an external circuit and helps in the regeneration of dye by oxidation-reduction of electrolyte, which significantly effects the overall performance of PV devices. Several materials such as carbonaceous materials, conducting polymers, oxides, and sulfides have been investigated as the low cost and highly stable material for the potential replacement for an expensive Pt-based counter electrode in DSSCs. In this Review, an attempt has been made to present recent achievements to replace Platinum (Pt) counter electrode with other inexpensive and earth abundant materials for DSSCs. This article systematically reviews the counter electrodes in DSSCs and provides review focused on Pt-TCO free counter electrodes. The main problems and challenges such as synthesis and fabrication of various CE, commercialization of DSSCs are addressed in detail with a conclusion and proposition section.
Energy is considered to be the life line of an economy, the most vital instrument of socioeconomi... more Energy is considered to be the life line of an economy, the most vital instrument of socioeconomic development and has been recognised as one of the most important strategic commodities [Sahir and Qureshi (2007)]. Energy is not only essential for the economy but its supply is uncertain [Zaleski (2001)]. Energy is a strategic source that influenced the outcomes of wars, fueled and strangled economic development and polluted as well as clean up the environment. In the era of globalisation, a rapidly increasing demand for energy and dependency of countries on energy indicate that energy will be one of the biggest problems in the world in the next century. This requires for alternative and renewable sources of energy. Traditional growth theories focus much on the labour and capital as major factor of production and ignore the importance of energy in the growth process [Stern and Cleveland (2004)]. The neo-classical production theories stresses that economic growth increases with the inc...
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Papers by USMAN MAQBOOL AHMED