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Image-Based Automatic Energy Meter Reading Using Deep Learning

Computers, Materials & Continua 2023年第1期74卷 203-216页

作者： muhammad Imran Hafeez Anwar muhammad Tufail abdullah Khan Murad Khan Dzati Athiar Ramli Institute of Computer Sciences and Information Technology Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAttock CampusAttock CityPakistan Kuwait College of Science and Technology Kuwait CityKuwait School of Electrical&Electronic Engineering USM Engineering CampusUniversiti Sains MalaysiaPenang14300Malaysia

We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time ***,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by *** this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and *** image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image *** training and evaluation,the image dataset is annotated to produce the ground truth of all the ***,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the *** proves to be robust against the mentioned image variations compared with the traditional handcrafted *** proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.

关键词： Convolutional neural network object localization machine learning

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Active Learning Strategies for Textual Dataset-Automatic Labelling

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Computers, Materials & Continua 2023年第8期76卷 1409-1422页

作者： Sher muhammad Daudpota Saif Hassan Yazeed Alkhurayyif abdullah Saleh Alqahtani muhammad Haris Aziz Department of Computer Science Sukkur IBA UniversitySukkur65200Pakistan Al Quwayiyah College of Sciences and Humanities Shaqra UniversityShaqra15526Saudi Arabia Self-Development Skills Department Common First Year DeanshipKing Saud UniversityRiyadh12373Saudi Arabia STC’s Artificial Intelligence Chair Department of Information SystemsCollege of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia College of Engineering&Technology University of SargodhaSargodha40100Pakistan

The Internet revolution has resulted in abundant data from various sources,including social media,traditional media,*** the availability of data is no longer an issue,data labelling for exploiting it in supervised machine learning is still an expensive process and involves tedious human *** overall purpose of this study is to propose a strategy to automatically label the unlabeled textual data with the support of active learning in combination with deep *** specifically,this study assesses the performance of different active learning strategies in automatic labelling of the textual dataset at sentence and document *** achieve this objective,different experiments have been performed on the publicly available *** first set of experiments,we randomly choose a subset of instances from training dataset and train a deep neural network to assess performance on test *** the second set of experiments,we replace the random selection with different active learning strategies to choose a subset of the training dataset to train the same model and reassess its performance on test *** experimental results suggest that different active learning strategies yield performance improvement of 7% on document level datasets and 3%on sentence level datasets for auto labelling.

关键词： Active learning automatic labelling textual datasets

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A looming twindemic of COVID-19 and dengue on post-flood scenario in the developing countries

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Asian Pacific Journal of Tropical Medicine 2022年第9期15卷 383-384页

作者： abdullah Sher Ali muhammad Salman Muddasir Khan Department of Health and Biological Sciences Abasyn University Peshawar Khyber Pakhtunkhwa(KPK)Pakistan Department of Food Engineering School of Animal Science and Food EngineeringUniversity of Sao PauloCEP13635-900PirassunungaSPBrazil Department of Veterinary Microbiology Faculty of Veterinary SciencesChulalongkorn UniversityBangkokThailand Centre of Biotechnology and Microbiology University of PeshawarKPKPakistan

Pakistan has recently faced a disastrous and lethal flooding across the country,affecting 33 million people and 1400 healthcare facilities,putting further strain on the nation's fragile healthcare *** country faces widespread infectious diseases including dengue and COVID-19[1].To date,SARS-CoV-2 has caused about 6.53 million deaths and spread globally,infecting about 612 million *** the developing world,infection rate is particularly high in Pakistan,causing 30606 deaths so far[2].As of September 2022,healthcare authorities claimed a continued rise in dengue cases due to heavy flood in the *** date,a total of 14173 dengue cases have been reported,and the highest number of cases was documented in Sindh province(5203),followed by Khyber Pakhtunkhwa(4538),Punjab(3101),and Islamabad with 1331[3].

关键词： flood continued globally

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Sludge granulation and efficiency of phase separator in UASB reactor treating combined industrial effluent

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Journal of Environmental Sciences 2007年第5期19卷 553-558页

作者： abdullah Yasar Nasir Ahmad muhammad Nawaz Chaudhry Aamir Amanat Ali Khan Directorate of Research and Development University of the Punjab41-Kamran BlockAllama Iqbal TownLahore-Pakistan.

Sludge granulation and the effect of gas-liquid-solid separator （GLSS） design on the efficiency of upflow anaerobic sludge blanket （UASB） and upflow anaerobic sludge filter （UASF） reactors, operating at HRTs ranging from 3 to 12 h was investigated. VSS/TS ratio gradually increased in both the reactors with increasing sludge age （from 0.5 to more than 0.7 for UASB reactor and 0.012 to 0.043 for UASF reactor）. X-Ray diffraction analysis of the UASF sludge showed the presence of expanding clays revealing its additional absorption capability. Fuoraphyllite and albite precipitation related to excellular polymers of the microbial shell structure, showed the extended growth of microorganisms during sludge granulation. A gradual decrease （82%-69%） in COD removal with decreasing HRT was apparent in UASF reactor. In case of UASB reactor, this decrease was marginal because addition of GLSS device significantly improved （14%-20%） the overall efficiency of the UASB reactor. GLSS enhanced the efficiency of the UASB reactor by increasing the settleability of suspended particles and accelerating the coagulation of colloidal particles due to the velocity gradient.

关键词： sludge granulation gas-liquid-solid (GLS) phase separator UASB microbial growth

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Roasted fox nuts (Euryale Ferox L.) contain higher concentration of phenolics, flavonoids, minerals and antioxidants, and exhibit lower Glycemic Index (GI) in human subjects

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Food Production, Processing and Nutrition 2022年第1期4卷 1-12页

作者： Marrium Liaquat Imran Pasha muhammad Ahsin abdullah Salik National Institute of Food Science and Technology Faculty of FoodNutrition and Home SciencesUniversity of AgricultureFaisalabad38000Pakistan

Fox nut (Euryale ferox) is categorized among superior quality foods because of its highly nutritious profile. It also serves as a good protein source for vegetarian diets. However, it is not widely consumed, due to soggy texture and bland flavor as compared to other nuts. In this study, we used roasting and seasoning to enhance its consumer acceptance. Furthermore, we have also compared biochemical, nutritional and physical properties of the roasted and unroasted fox nuts;and their Glycemic Index (GI) in human subjects. Results showed that roasting significantly (P ≤ 0.05) improved the minerals content (from 0.58 to 0.66%), protein content (from 11.40 to 14.57%), total phenolics (from 346.02 to 470.62 mg GAE/100 g), flavonoids (from 4.15 to 4.43 mg CE/g), 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity (from 48.54 to 79.13% inhibition) and Ferric Reducing Antioxidant Power (from 662.46 to 957.14 μmol FeSO4/g). Consumer acceptance was evaluated with and without seasoning;both salt and spice seasoned roasted nuts had greater overall acceptability as compared to plain roasted and unroasted nuts. Fox nuts also reported low GI (37%) in human subjects (ethical approval #1772/01-06-2020). Thus, roasted fox nuts can be consumed as nutrient rich and low GI snack;not only as a component of healthy diet but can also be served to patients with metabolic disorders like obesity and diabetes.

关键词： Euryale ferox seeds Fox nuts Roasting Nutritious snack and low glycemic index foods

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A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan Ullah Xuexia Zhang Mansoor Khan muhammad Abid abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

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Emergency Decision-Making Based on q-Rung Orthopair Fuzzy Rough Aggregation Information

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Computers, Materials & Continua 2021年第12期69卷 4077-4094页

作者： Ahmed B.Khoshaim Saleem abdullah Shahzaib Ashraf muhammad Naeem Department of Mechanical Engineering King Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Abdul Wali Khan University MardanMardan23200Pakistan Department of Mathematics and Statistics Bacha Khan UniversityCharsadda24420Pakistan Deanship of Combined First Year Umm Al-Qura UniversityMakkahSaudi Arabia

With the frequent occurrences of emergency events,emergency decision making(EDM)plays an increasingly significant role in coping with such situations and has become an important and challenging research area in recent *** is essential for decision makers to make reliable and reasonable emergency decisions within a short span of time,since inappropriate decisions may result in enormous economic losses and social *** handle emergency effectively and quickly,this paper proposes a new EDM method based on the novel concept of q-rung orthopair fuzzy rough(q-ROPR)set.A novel list of q-ROFR aggregation information,detailed description of the fundamental characteristics of the developed aggregation operators and the q-ROFR entropy measure that determine the unknown weight information of decision makers as well as the criteria weights are *** an algorithm is given to tackle the uncertain scenario in emergency to give reliable and reasonable emergency *** using proposed list of q-ROFR aggregation information all emergency alternatives are ranked to get the optimal *** this,the q-ROFR entropy measure method is used to determine criteria and experts’weights objectively in the EDM ***,through an illustrative example of COVID-19 analysis is compared with existing EDM *** results verify the effectiveness and practicability of the proposed methodology.

关键词： q-rung orthopair fuzzy rough set q-ROFR entropy measure aggregation information emergency decision making

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An Architecture Supporting Intelligent Mobile Healthcare Using Human-Computer Interaction HCI Principles

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Computer Systems Science & Engineering 2022年第2期40卷 557-569页

作者： Mesfer Alrizq Shauban Ali Solangi abdullah Alghamdi muhammad Ali Nizamani muhammad Ali Memon Mohammed Hamdi College of Computer Science and Information Systems Najran UniversityNajranSaudi Arabia Faculty of Engineering&Technology University of SindhJamshoro78060Pakistan

Recent advancements in the Internet of Things IoT and cloud computing have paved the way for mobile Healthcare(mHealthcare)services.A patient within the hospital is monitored by several ***,upon leaving the hospital,the patient can be remotely monitored whether directly using body wearable sensors or using a smartphone equipped with sensors to monitor different user-health *** raises potential challenges for intelligent monitoring of patient's *** this paper,an improved architecture for smart mHealthcare is proposed that is supported by HCI design *** HCI also provides the support for the User-Centric Design(UCD)for smart mHealthcare ***,the HCI along with IoT's(Internet of Things)5-layered architecture has the potential of improving User Experience(UX)in mHealthcare design and help saving *** intelligent mHealthcare system is supported by the IoT sensing and communication layers and health care providers are supported by the application layer for the medical,behavioral,and health-related *** care providers and users are further supported by an intelligent layer performing critical situation assessment and performing a multi-modal communication using an intelligent *** HCI design focuses on the ease-of-use,including user experience and safety,alarms,and error-resistant displays of the end-user,and improves user's experience and user satisfaction.

关键词： Human computer interaction mhealthcare user-centric design sensor network nternet-of-things

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Ebola, the killer virus

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Infectious Diseases of Poverty 2015年第1期4卷 146-151页

作者： Haider Ghazanfar Fizza Orooj muhammad Ahmed abdullah Ali Ghazanfar Shifa College of Medicine Pitras Bukhari Road H-8/4IslamabadPakistan Federal Medical and Dental College Prime Minister’s National Health ComplexChak ShahzadIslamabadPakistan

Ebola virus disease(EVD)has mostly affected economically deprived countries as limited resources adversely affect a country’s infrastructure and *** into the factors that led to the widespread outbreak,setting forth plans to counter EVD cases in developing countries,and devising definitive measures to limit the spread of the disease are essential steps that must be immediately *** this review we summarize the pathogenesis of EVD and the factors that led to its *** also highlight interventions employed by certain countries that have successfully limited the epidemic,and add a few preventive measures after studying the current *** to the available data,barriers to prevent and control the disease in affected countries include irresolute and disorganized health systems,substandard sanitary conditions,poor personal hygiene practices,and false beliefs and stigma related to *** public health sector along with the respective chief authorities in developing countries must devise strategies,keeping the available resources in mind,to deal with the outbreak before it *** a first step,communities should be educated on EVD’s symptoms,history,mode of transmission,and methods of protection,including the importance of personal hygiene practices,via seminars,newspapers,and other social media.A popular opinion leader(POL)giving this information would further help to remove the misconception about the nature of the disease and indirectly improve the quality of life of affected patients and their families.

关键词： Ebola hemorrhagic fever Epidemiology Ebola virus/physiology Hemorrhagic fever Ebola/transmission Ebola/prevention and control

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An Optimized Neural Network with Bat Algorithm for DNA Sequence Classification

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Computers, Materials & Continua 2022年第10期73卷 493-511页

作者： muhammad Zubair Rehman muhammad Aamir Nazri Mohd.Nawi abdullah Khan Saima Anwar Lashari Siyab Khan Faculty of Computing and Information Technology Sohar UniversitySohar311Sultanate of Oman Soft Computing&Data Mining Centre(SMC) Faculty of Computer Science&Information TechnologyUniversiti Tun Hussein Onn Malaysia(UTHM)Batu Pahat86400Malaysia School of Electronics Computing and MathematicsUniversity of DerbyDerbyDE221GBUnited Kingdom Institute of Computer Sciences and Information Technology The University of Agriculture25120PeshawarPakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Recently, many researchers have used nature inspired metaheuristicalgorithms due to their ability to perform optimally on complex problems. Tosolve problems in a simple way, in the recent era bat algorithm has becomefamous due to its high tendency towards convergence to the global optimummost of the time. But, still the standard bat with random walk has a problemof getting stuck in local minima. In order to solve this problem, this researchproposed bat algorithm with levy flight random walk. Then, the proposedBat with Levy flight algorithm is further hybridized with three differentvariants of ANN. The proposed BatLFBP is applied to the problem ofinsulin DNA sequence classification of healthy homosapien. For classificationperformance, the proposed models such as Bat levy flight Artificial NeuralNetwork (BatLFANN) and Bat levy Flight Back Propagation (BatLFBP) arecompared with the other state-of-the-art algorithms like Bat Artificial NeuralNetwork (BatANN), Bat back propagation (BatBP), Bat Gaussian distribution Artificial Neural Network (BatGDANN). And Bat Gaussian distributionback propagation (BatGDBP), in-terms of means squared error (MSE) andaccuracy. From the perspective of simulations results, it is show that theproposed BatLFANN achieved 99.88153% accuracy with MSE of 0.001185,and BatLFBP achieved 99.834185 accuracy with MSE of 0.001658 on *** on WL10 the proposed BatLFANN achieved 99.89899% accuracy withMSE of 0.00101, and BatLFBP achieved 99.84473% accuracy with MSE of0.004553. Similarly, on WL15 the proposed BatLFANN achieved 99.82853%accuracy with MSE of 0.001715, and BatLFBP achieved 99.3262% accuracywith MSE of 0.006738 which achieve better accuracy as compared to the otherhybrid models.

关键词： DNA sequence classification bat algorithm levy flight back propagation neural network hybrid artificial neural networks(HANN)

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