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- Kanwal, Ansa, et al.
(author)
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Polyethersulfone (PES) nanofiltration membrane for treatment of toxic metal contaminated water
- 2022
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In: Emerging Techniques for Treatment of Toxic Metals from Wastewater. - 9780128228807 ; , s. 319-341
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Book chapter (other academic/artistic)abstract
- Polyethersulfone is most extensively utilized material in waste treatment application via membranes technology since it offers high thermal, chemical, and mechanical properties. The world now has problems with drinking water and the present situation seems to be very complex to meet clean water requirements. The treatment of water supplies by clean-up techniques is urgently considered by increased daily demand, which leads to dangerous conditions unless this problem is controlled. Most important contributors to ecological pollution with metal ions are mining, metal shining, power generation houses, galvanization, tannery industries, metallurgical, and electroplating. There are many techniques to remove the metal ions such as adsorption, microbial fuel cells, oxidation/reductions, ion exchange etc. Among all the technologies nanofiltration membranes attract more attention to remove the toxic metal ions from water even at lower concentration. It is very simple, feasible and economically affordable technology. Several types of nanofiltration techniques are used before but most attractive is polyethersulfone (PES) nanofiltration membrane. It minimizes several issues which are present in the nanofiltration process. In this chapter we briefly discussed the modification strategies and removal efficiency of metal ions via polyethersulfone (PES) nanofiltration membrane.
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| 5. |
- Kumar, Rohan, et al.
(author)
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Transforming the transportation sector : Mitigating greenhouse gas emissions through electric vehicles (EVs) and exploring sustainable pathways
- 2024
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In: AIP Advances. - : American Institute of Physics (AIP). - 2158-3226. ; 14:3
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Journal article (peer-reviewed)abstract
- Transportation-related emissions in Pakistan have been rapidly increasing in recent years. This study aims to determine how important it is to electrify road transportation in Pakistan to reduce greenhouse gas (GHG) emissions from the transportation sector. Motivated by the need to tackle the growing environmental issues related to conventional fuel-powered automobiles, this research explores the application of electrification techniques in the context of Pakistan’s transportation system. During the 2019 fiscal year, the transportation industry in Pakistan consumed 23 × 106 tonnes of energy from the burning of fossil fuels and produced 52.9 × 106 metric tons of CO2, which made up 31% of the country’s total carbon emissions. In this research, different scenarios, such as business as usual, low carbon, strengthen low carbon, and Pakistan National Electric Vehicle Policy 2040, are evaluated for the transportation sector of the country. Using the LEAP model, this study projects the effects of electrification on Pakistan road transportation over 30 years. When estimating how electrification will affect road transportation in Pakistan over the next 30 years, several factors were taken into account, including policy frameworks, changing consumer behavior, technology advancements, and infrastructure improvements. The analysis covered the emission levels, adoption hurdles, and possible advantages of transitioning to electric vehicles (EVs). The outcomes illustrate that adopting EVs can produce substantial drops in fuel consumption and environmental emissions, providing a sustainable solution to mitigate global warming. This work is directly associated with various Sustainable Development Goals, including SDG3 (good health and well-being), SDG7 (affordable and clean energy), and SDG13 (climate action). The results of this study highlight the considerable potential for GHG reduction associated with the widespread adoption of EVs, offering crucial insights to stakeholders and policymakers.
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| 6. |
- Ulfat, Intikhab, 1966, et al.
(author)
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Estimation of solar energy potential for Islamabad, Pakistan
- 2012
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In: Energy Procedia. - : Elsevier. - 1876-6102. ; 18, s. 1496-1500
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Conference paper (peer-reviewed)abstract
- In order to design a solar energy system with optimized performance a thorough knowledge of solar radiation data for a considerably long period (20-25 years) is a pre-requisite. For developing countries like Pakistan, the need of empirical models to assess the feasibility of solar energy utilization seems inevitable due to the absence and scarcity of trustworthy solar radiation data. We present such models for the capital city of Pakistan, Islamabad to estimate global and diffuse solar radiation. It is found that with the exception of monsoon month, solar energy can be utilized very efficiently throughout the year. The models suggested could be used for most of the north-eastern areas of Pakistan, which are similar to Islamabad with respect to the climate and the availability of solar radiation but lack in the record of solar radiation data.
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| 7. |
- Abdullah, Saad, et al.
(author)
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Low-cost BLE based intravenous monitoring and control infusion system
- 2023
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In: Int. Conf. Adv. Electron., Control Commun. Syst., ICAECCS. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665463102
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Conference paper (peer-reviewed)abstract
- Administering the medications and fluids intravenously is a frequent practice in modern medical procedures, which plays a vital role in the treatment of certain acute conditions which require immediate action by drugs or fluids. This paper covers the design of a low-cost, wireless drip monitoring system for use in the hospital environment. The device is equipped with the Bluetooth low energy based battery-operated microcontroller, an infrared based drops counting system and a digital servo motor to control the drip flow rate, and it is attached to an existing intravenous stand. A LabView graphical user interface has also been developed to provide sets of input to the system to calculate the desired drip rate and the amount of pressure that digital servo motor must apply to achieve it. The system shows an average accuracy of 96% when compared with the measured and calculated values. This allows accurate computation of the level of the drip.
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| 9. |
- Kanwal, K., et al.
(author)
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Current Diagnostic Techniques for Pneumonia : A Scoping Review
- 2024
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In: Sensors. - : Multidisciplinary Digital Publishing Institute (MDPI). - 1424-8220. ; 24:13
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Journal article (peer-reviewed)abstract
- Community-acquired pneumonia is one of the most lethal infectious diseases, especially for infants and the elderly. Given the variety of causative agents, the accurate early detection of pneumonia is an active research area. To the best of our knowledge, scoping reviews on diagnostic techniques for pneumonia are lacking. In this scoping review, three major electronic databases were searched and the resulting research was screened. We categorized these diagnostic techniques into four classes (i.e., lab-based methods, imaging-based techniques, acoustic-based techniques, and physiological-measurement-based techniques) and summarized their recent applications. Major research has been skewed towards imaging-based techniques, especially after COVID-19. Currently, chest X-rays and blood tests are the most common tools in the clinical setting to establish a diagnosis; however, there is a need to look for safe, non-invasive, and more rapid techniques for diagnosis. Recently, some non-invasive techniques based on wearable sensors achieved reasonable diagnostic accuracy that could open a new chapter for future applications. Consequently, further research and technology development are still needed for pneumonia diagnosis using non-invasive physiological parameters to attain a better point of care for pneumonia patients.
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| 10. |
- Sehar, Urooba, et al.
(author)
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A hybrid dependency-based approach for Urdu sentiment analysis
- 2023
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In: Scientific Reports. - London : Springer Nature. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- In the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse backgrounds, races, cultures, and age groups, spanning a wide range of topics. Businesses can leverage this data to extract valuable insights, improve their services, and effectively reach a broader audience based on users’ expressed opinions on social media platforms. To harness the potential of this extensive and unstructured data, a deep understanding of Natural Language Processing (NLP) is crucial. Existing approaches for sentiment analysis (SA) often rely on word co-occurrence frequencies, which prove inefficient in practical scenarios. Identifying this research gap, this paper presents a framework for concept-level sentiment analysis, aiming to enhance the accuracy of sentiment analysis (SA). A comprehensive Urdu language dataset was constructed by collecting data from YouTube, consisting of various talks and reviews on topics such as movies, politics, and commercial products. The dataset was further enriched by incorporating language rules and Deep Neural Networks (DNN) to optimize polarity detection. For sentiment analysis, the proposed framework employs predefined rules to trigger sentiment flow from words to concepts, leveraging the dependency relations among different words in a sentence based on Urdu language grammatical rules. In cases where predefined patterns are not triggered, the framework seamlessly switches to its sub-symbolic counterpart, passing the data to the DNN for sentence classification. Experimental results demonstrate that the proposed framework surpasses state-of-the-art approaches, including LSTM, CNN, SVM, LR, and MLP, achieving an improvement of 6–7% on Urdu dataset. In conclusion, this research paper introduces a novel framework for concept-level sentiment analysis of Urdu language data sourced from social media platforms. By combining language rules and DNN, the proposed framework demonstrates superior performance compared to existing methodologies, showcasing its effectiveness in accurately analyzing sentiment in Urdu text data.
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| 11. |
- UL Muram, Faiz, et al.
(author)
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Facilitating the Compliance of Process Models with Critical System Engineering Standards using Natural Language Processing
- 2021
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In: International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE - Proceedings. - : Science and Technology Publications, Lda. - 9789897585081 ; , s. 306-313
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Conference paper (peer-reviewed)abstract
- Compliance of process models with relevant standards is mandatory for certifying the critical systems. However, it is often carried out in a manual manner, which is complex and labour-intensive. Previous studies have not considered the automated processing of standard documents for achieving and demonstrating the process compliance. This paper leverages natural language processing for extracting the normative process models embedded in the standard documents. The mapping rules are established for structuring the standard requirements and content elements of process models, such as tasks, roles and work products. They are organized into a process structure by considering the phases, activities and milestones. During the planning phase, the standard requirements, process models and compliance mappings are generated in EPF Composer; it supports the major parts of the OMG's Software & Systems Process Engineering Metamodel (SPEM) 2.0. The reverse compliance of extended or pre-existing process models can be carried out during the execution phase; specifically, the compliance gaps are detected, possible measures for their resolution are provided and missing elements are added after the process engineer approval. The applicability of the proposed methodology is demonstrated for the ECSS-E-ST-40C compliant space system engineering process.
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