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| 1 | Vegetation-environment relationships in the forests of Chitral district Hindukush range of Pakistan显示文摘We investigated the composition of plant communities to quantify their relationships with environmental parameters in the Chitral Hindukush range of Pakistan. We sampled tree vegetation using the Point Centered Quarter (PCQ) method while understory vegetation was sampled in 1.5-m circular quadrats. Cedrus deodara is the national symbol of Pakistan and was dominant in the sampled communities. Because environmental variables determine vegetation types, we analyzed and evaluated edaphic and topographic factors. DCA-Ordination showed the major gradient as an amalgam of elevation (p<0.05) and slope (p<0.01) as the topographic factors correlated with species distribution. Soil variables were the factors of environmental significance along DCA axes. However, among these factors, Mg2+ , K + and N2+ contributed not more than 0.054% 0.20% and 0.073%, respectively, to variation along the first ordination axis. We conclude that the principal reason for weak or no correlation with many edaphic variables was the anthropogenic disturbance of vegetation. The understory vegetation was composed of perennial herbs in most communities and was most dense under the tree canopy. The understory vegetation strongly regulates tree seedling growth and regeneration patterns. We recommend further study of the understory vegetation using permanent plots to aid development of forest regeneration strategies. | Nasrullah Khan Syed Shahid Shaukat Moinuddin Ahmed Muhammad Faheem Siddiqui | 2013 | Journal of Forestry Research2013，24，2： | 8 |
| 2 | An efficient method for clonal propagation and in vitro establishment of softwood shoots from epicormic buds of teak(Tectona grandis L.)显示文摘Softwood shoots were produced from 40 cm long stem segments placed horizontally in flat trays containing sterilized sand under natural light or shade conditions for subsequent rooting and micropropagation studies in teak(Tectona grandis L.) . Higher number of shoots(6.17) per log was produced under natural light as compared to shade conditions. Forcing was also better in natural light as compared to shade in terms of shoot length,number of nodes or leaves. For rooting,2-4 cm long softwood shoots were excised and treated with either indole-3-butyric acid(IBA) or α-naphthyl acetic acid(NAA) at 0,1000,2000 or 3000 μmol·L-1 each or with combinations(1000 + 1000,2000 + 2000 or 3000 + 3000 μmol·L-1) and then placed in flat trays containing autoclaved sand at 25 ± 2oC in 16 h photoperiod at 35 μmol·m-2·s-1. After 28 days,softwood cuttings treated with IBA + NAA(3000 + 3000 μmol·L-1) had highest rooting percentage(89.3%) with 5.5 mean roots. Shoot apex and nodal explants of softwood cuttings were pretreated with 0.1%(w/v) ascorbic acid,boric acid,activated charcoal,citric acid,glutamine or polyvinylpolypyrollidone(PVP) for 24 h to remove phenolic compounds before surface disinfestation. Glutamine(Gl) and PVP were equally effective resulting in 60% establishment of shoot apices on MS medium supplemented with 10 μmol·L-1 6-benzylaminopurine(BAP) + 5 μmol·L-1 NAA. Using shoot apices,highest(42.80) number of multiple shoots with 54.33 mm shoot length were obtained on MS + BAP(8.8 μmol·L-1) + IBA(2 μmol·L-1) after 45 days. Shoots were successfully rooted and acclimatized to greenhouse conditions. | Muhammad AKRAM Faheem AFTAB | 2009 | Forestry Studies in China2009，11，2： | 3 |
| 3 | Establishment of Embryogenic Cultures and Efficient Plant Regeneration System from Explants of Forced Softwood Shoots of Teak (Tectona grandis L.)显示文摘The present study highlights an efficient plant regeneration system in teak(Tectona grandis L.) using forced softwood shoots as an initial plant material. Forced softwood shoots of teak were cut to prepare shoot tip, nodal and internodal explants and cultured on Murashige and Skoog(MS) medium + NAA(1, 3, 6, 10, and 15 μmol · L-1) or TDZ(0.001, 0.01, 0.1, 1, 4, 8, 10, 12 μmol · L-1) for callus induction. Such calluses were further grown on the same levels of TDZ or 0.4, 1, 4, 8, 10 μmol · L-1 BA + 1 μmol · L-1 IBA or GA3. Callus induction was the highest with4.55 cm3 callus volume and 5.75 g dry weight at 0.1 μmol · L-1 TDZ from shoot tips after 35 days. Embryogenic calluses were then shifted to 6, 8 or12 μmol · L-1 TDZ + 2 μmol · L-1 BA or IBA along with 5 mmol · L-1 ascorbic acid(AA) for shoot regeneration from embryogenic cultures. The highest embryogenesis(100%) with 36.4 globular and 5.5 heart-shaped embryo-like structures was obtained at 8 μmol · L-1 TDZ + 2 μmol · L-1 BA after 63 days. Such cultures when further maintained on the same medium up to 150 days resulted in 100% shoot regeneration with 16.4 mean shoots.Shoots were elongated up to 50 mm on agar medium + 8 μmol · L-1 BA + 1 μmol · L-1 GA3. An efficient rooting response(70%) was achieved having4.50 mean number and 49.10 mm root length at 8 μmol · L-1 IBA + 8 μmol · L-1 NAA + 0.1% activated charcoal after 36 days. Rooted shoots were acclimatized in glasshouse, achieving 56.6% plantlet survival. | Muhammad Akram Faheem Aftab | 2016 | Horticultural Plant Journal2016，2，5： | 3 |
| 4 | Effect of auxins on axillary and de novo shoot regeneration from in vitro shoot cultures derived from forced epicormic buds of teak (Tectona grandis L.)显示文摘In this presentation,we report on de novo and axillary shoot regeneration and rooting of shoots maintained over a long term,from cultures of Tectona grandis L.Shoot-tips of teak shoots forced from epicormic buds were used as the starting material for axenic shoot-culture establishment.Long term maintenance of such axenic shoot cultures was carried out by regular sub-culturing on MS media supplemented with N 6-benzyleadenine (BA,8.8 μmol L-1) and indole-3-butyric acid (IBA,2 μmol L-1) for 24 months.Vigorously growing shoot tips (2 3 cm long) were inoculated on the MS basal medium supplemented with different concentrations (0,1,2,4,6,8 or 10 μmol L-1) of either IBA or α-naphthaleneacetic acid (NAA) for rooting.Axillary and de novo shoots were developed from axillary and cut basal ends of shoots,respectively.Shoots growing on auxins were further sub-cultured (every 15 days) and maintained for 45 days.The greatest number of de novo (5.06) as well as axillary shoots (2.85) was observed on the MS medium supplemented with 10 μmol L-1 NAA or 8 μmol L-1 IBA,respectively,after 45 days.The combinations of both IBA (μmol L-1) + NAA (μmol L-1) were tested at different concentrations (4 + 4,6 + 6,8 + 8) supplemented to a half strength MS basal medium with 0.1% activated charcoal for rooting of decapitated and non-decapitated de novo and axillary shoots.Rooting from non-decapitated de novo shoots was highest (93.33%) with a mean number of roots of 4.61 on this medium,supplemented with 6 μmol L-1 IBA + 6 μmol L-1 NAA,after 36 days of initial culture.Individual auxin,however,was not effective for root induction.Rooted shoots were acclimatized in a green house and after four weeks plantlets were transferred to the field. | Akram MUHAMMAD Aftab FAHEEM | 2012 | Forestry Studies in China2012，14，3： | 1 |
| 5 | Using IoT Innovation and Efficiency in Agriculture Monitoring System显示文摘Agriculture is undoubtedly a leading field for livelihoods in China.As the population increases,it is necessary to increase agricultural productivity.By capturing the support and the increment in production on farms,the need for freshwater used for irrigation increases too.Presently,agriculture accounts for 80% of overall water uptake in China.Unexpected overflow of water carelessly leads to waste of water.Therefore we created a programmed plant irrigation system with Arduino that mechanically supplies water to the plants and keeps it updated by transferring the message to user.Plant irrigation system employs the soil moisture sensor which controls a degree of moisture in the soil.If the humidity degree is lower,Arduino activates a pump of water to supply water to the system.The pump of water stops by design when the organism detects sufficient moisture in the ground.Each time the system is switched off or on,an electronic messaging is conveyed to the end-user through the IoT unit,informing the position of the soil moisture and the pump of water.A spray motor and the pump of water are grounded on the crane concept.Widely,this system is applicable for in small fields,gardens farms,etc.This design is entirely programmed and needed no human involvement.Furthermore,transmission of the sensor readings send through a Thing speak frequency to produce graphic elements for better inquiry.This study gathers the ideas of IoT(Internet of Things)with some engineering tools like machinery,artificial intelligence and use of sensors in an efficient way to respond current needs and extraction of resources by availing scientific methods and procedures that work on inputs.Moreover,this study further defines the engineering works that have been part of this field,but it requires more efficiency and reduction of energy as well as costs by adding more contribution of IoT in the field of agriculture engineering. | Muhammad Awais Wei Li Muhammad Ajmal Muhammad Faheem | 2020 | Journal of Botanical Research2020，2，2： | 1 |
| 6 | Multi-material Bio-inspired Soft Octopus Robot for Underwater Synchronous Swimming显示文摘Inspired by the simple yet amazing morphology of the Octopus, we propose the design, fabrication, and characterization of multi-material bio-inspired soft Octopus robot (Octobot). 3D printed molds for tentacles and head were used. The tentacles of the Octobot were casted using Ecoflex-0030 while head was fabricated using relatively flexible material, i.e., OOMOO-25. The head is attached to the functionally responsive tentacles (each tentacle is of 79.12 mm length and 7 void space diameter), whereas Shape Memory Alloy (SMA) muscle wires of 0.5 mm thickness are used in Octobot tentacles for dual thrust generation and actuation of Octobot. The tentacles were separated in two groups and were synchronously actuated. Each tentacle of the developed Octobot contains a pair of SMA muscles (SMA-α and SMA-β). SMA-α muscles being the main actuator, was powered by 9 V, 350 mA power supply, whereas SMA-β was used to provide back thrust and thus helps to increase the actuation frequency. Simulation work of the proposed model was performed in the SolidWorks environment to verify the vertical velocity using the octopus tentacle actuation. The design morphology of Octobot was optimized using simulation and TRACKER software by analyzing the experimental data of angle, displacement, and velocity of real octopus. The as-developed Octobot can swim at variable frequencies (0.5–2 Hz) with the average speed of 25 mm/s (0.5 BLS). Therefore, the proposed soft Octopus robot showed an excellent capability of mimicking the gait pattern of its natural counterpart. | Faheem Ahmed Muhammad Waqas Bushra Shaikh Umair Khan Afaque Manzoor Soomro Suresh Kumar Hina Ashraf Fida Hussain Memon Kyung Hyun Choi | 2022 | Journal of Bionic Engineering2022，19，5： | 1 |
| 7 | Effect of annealing on structural, optical and electrical properties of nanostructured Ge thin films显示文摘 | Abdul Faheem Khan Mazhar Mehmood Anwar M. Rana Taj Muhammad | 2009 | Applied Surface Science2009，，7： | 1 |
| 8 | Vegetation-environment relationship in conifer dominating forests of the mountainous range of Indus Kohistan in northern Pakistan显示文摘Environmental variables play a crucial role in shaping vegetation structure,mainly in mountainous ecosystems.Different studies have attempted to identify the environment-vegetation relationship of Conifer Dominating Forests(CDF)worldwide.However,due to differences in local climate and soil composition,different environmental drivers can be found.By applying multivariate analysis techniques,this study investigated the vegetation-environment relationship of CDF of Indus Kohistan in northern Pakistan.Our results showed that CDF of Indus Kohistan are distributed in five distinct ecological groups,which are dominated by different trees and understory species.A total of 7 trees and 71 understory species were recorded from the sampling sites.Cedrus deodara was the leading species among four groups,having the highest importance value(IV),density and basal area.Group I was dominated by Pinus wallichiana with the second highest importance value,density and basal area.In addition,elevation,slope,maximum water holding capacity(MWHC),soil moisture(SM),total organic matter(TOM),sodium,phosphorus and nickel showed highly significant influence on composition and distribution pattern of Indus Kohistan vegetation.Therefore,this study shows a new evidence of vegetation-environment relationship,pointing out specific drivers of vegetation structure in CDF of Indus Kohistan region in northern Pakistan. | Adam KHAN Moinuddin AHMED Muhammad Faheem SIDDIQI Mohib SHAH Eduardo Soares CALIXTO Afsheen KHAN Paras SHAH Javed IQBAL Muhammad AZEEM | 2020 | Journal of Mountain Science2020，17，8： | 1 |
| 9 | Intelligent Breast Cancer Prediction Empowered with Fusion and Deep Learning显示文摘Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally.According to clinical statistics,one woman out of eight is under the threat of breast cancer.Lifestyle and inheritance patterns may be a reason behind its spread among women.However,some preventive measures,such as tests and periodic clinical checks can mitigate its risk thereby,improving its survival chances substantially.Early diagnosis and initial stage treatment can help increase the survival rate.For that purpose,pathologists can gather support from nondestructive and efficient computer-aided diagnosis(CAD)systems.This study explores the breast cancer CAD method relying on multimodal medical imaging and decision-based fusion.In multimodal medical imaging fusion,a deep learning approach is applied,obtaining 97.5%accuracy with a 2.5%miss rate for breast cancer prediction.A deep extreme learning machine technique applied on feature-based data provided a 97.41%accuracy.Finally,decisionbased fusion applied to both breast cancer prediction models to diagnose its stages,resulted in an overall accuracy of 97.97%.The proposed system model provides more accurate results compared with other state-of-the-art approaches,rapidly diagnosing breast cancer to decrease its mortality rate. | Shahan Yamin Siddiqui Iftikhar Naseer Muhammad Adnan Khan Muhammad Faheem Mushtaq Rizwan Ali Naqvi Dildar Hussain Amir Haider | 2021 | Computers, Materials & Continua2021，，4： | 1 |
| 10 | Metal-catalyzed synthesis of ultralong tin dioxide nanobelts: Electrical and optical properties with oxygen vacancy-related orange emission显示文摘 | Faheem K. Butt Chuanbao Cao Tariq Mahmood Faryal Idrees Muhammad Tahir Waheed S. Khan Zulfiqar Ali Muhammad Rizwan M. Tanveer Sajad Hussain Imran Aslam Dapeng Yu | 2014 | Materials Science in Semiconductor Processing2014，，： | 1 |
| 11 | Quino- acridine derivatives with one - dimensional aggregation - induced red emission property 显示文摘 | Iqbal Javed Tianlei Zhou Faheem Muhammad | 2012 | Langmuir: the ACS jounaal of surfacesand colloids2012，28，2： | 1 |
| 12 | Presentation delay in breast cancer patients and its association with sociodemographic factors in North Pakistan显示文摘Background: There is strong evidence that delayed diagnosis of breast cancer is associated with poor survival. The objectives were to determine the frequency of breast cancer patients with delayed presentation, the reasons of delay and its association with different socio-demographic variables in our settings.Methods: We interviewed 315 histologically confirmed breast cancer patients. Delay was defined as more than 3 months from appearance of symptoms to the consultation from doctor. Questions were asked from each patient which could reflect their understanding about the disease and which could be the likely reasons for their delayed presentation.Results: A total of 39.01%(n=123) of patients presented late and out of those, 40.7% wasted time using alternative medicines; 25.2% were not having enough resources; 17.1% presented late due to painless lump; 10.6% felt shyness and 6.5% presented late due to other reasons. Higher age, negative family history, <8 school years of education and low to middle socio-economic status were significantly associated with delayed presentation(P<0.05). Education and socioeconomic status were two independent variables related to the delayed presentation after adjustment for others [odds ratios(OR) of 2.26, 2.29 and 95% confidence intervals(CI) was 1.25-4.10, 1.06-4.94 respectively].Conclusions: Significant percentage of women with breast cancer in North Pakistan is experiencing presentation delay due to their misconceptions about the disease. Coordinated efforts with public health department are needed to educate the focused groups and mitigating the barriers identified in the study. Long term impact will be reduced overall burden of the disease in the region. | Muhammad Aleem Khan Sheharyar Hanif Sundas Iqbal Muhammad Faheem Shahzad Sehrish Shafique Muhammad Taha Khan | 2015 | Chinese Journal of Cancer Research2015，27，3： | 1 |
| 13 | Porous Ruthenium Selenide Nanoparticle as a Peroxidase Mimic for Glucose Bioassay显示文摘Nanozyme is a promising field that offers the substitution for natural enzymes using various nanomaterials.Various nanoma-terials with peroxidase-like activity were investigated.Among them,transition metal chalcogenides were explored as promis-ing nanozymes due to their excellent enzyme-mimicking activities.However,ruthenium selenide has not been studied as a peroxidase mimic because of the difficulty for synthesis.Herein,we prepared ruthenium selenide nanomaterial with ordered mesoporous structure(P-RuSe_(2))employing KIT-6 silica as the template.The composition and structure of P-RuSe_(2) were fully characterized.Further,its peroxidase-like activity was investigated.P-RuSe_(2) possessed excellent peroxidase-mimicking activ-ity,which catalyzed the oxidation of peroxidase substrates,including 3,3′,5,5′-tetramethylbenzidine,o-phenylenediamine,and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)in the presence of H_(2)O_(2).Moreover,P-RuSe_(2) exhibited higher peroxidase-like activity when compared with several representative nanozymes as well as bulk RuSe_(2).To demonstrate its potential applications,the colorimetric detection systems for H_(2)O_(2) and glucose were successfully constructed based on P-RuSe_(2) nanozyme. | Wen Cao Junshu Lin Faheem Muhammad Quan Wang Xiaoyu Wang Zhangping Lou Hui Wei | 2019 | Journal of Analysis and Testing2019，3，3： | 1 |
| 14 | Fusion-Based Machine Learning Architecture for Heart Disease Prediction显示文摘The contemporary evolution in healthcare technologies plays a considerable and signicant role to improve medical services and save human lives.Heart disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes,as numerous people have been suffering from this disease globally.Heart attacks occur when the ranges of vital signs such as blood pressure,pulse rate,and body temperature exceed their normal values.The efcient diagnosis of heart diseases could play a substantial role in the eld of cardiology,while diagnostic time could be reduced.It has been a key challenge for researchers and medical experts to diagnose heart diseases accurately and timely.Therefore,machine learning-based techniques are used for the diagnosis with higher accuracy,using datasets compiled from former medical patients’reports.In recent years,numerous studies have been presented in the literature propose machine learning techniques for diagnosing heart diseases.However,the existing techniques have some limitations in terms of their accuracy.In this paper,a novel Support Vector Machine(SVM)based architecture for heart disease prediction,empowered with a fuzzy based decision level fusion,is presented.The SVMbased architecture has improved the accuracy signicantly as compared to existing solutions,where 96.23%accuracy has been achieved. | Muhammad Waqas Nadeem Hock Guan Goh Muhammad Adnan Khan Muzammil Hussain Muhammad Faheem Mushtaq Vasaki a/p Ponnusamy | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 15 | Coronavirus: A “Mild” Virus Turned Deadly Infection显示文摘Coronaviruses are a family of viruses that can be transmitted from one person to another.Earlier strains have only been mild viruses,but the current form,known as coronavirus disease 2019(COVID-19),has become a deadly infection.The outbreak originated in Wuhan,China,and has since spread worldwide.The symptoms of COVID-19 include a dry cough,sore throat,fever,and nasal congestion.Antimicrobial drugs,pathogen–host interaction,and 2 weeks of isolation have been recommended for the treatment of the infection.Safe operating procedures,such as the use of face masks,hand sanitizer,handwashing with soap,and social distancing,are also suggested.Moreover,travel bans for cities,states,and countries have been put in place,along with lockdowns to control the outbreak.Travel restrictions,mask use,sanitizer or soap use,and avoidance of touching the face and nose have produced encouraging results,whereas the effectiveness of antibiotics has not been proved.The results of isolation for the recovery of infected people have also been promising.Travel bans and lockdowns have caused a slump in economies,and unemployment has risen sharply,resulting in an increase in mental health cases globally.To date,vaccines have been developed and are in use in certain countries,but following standard operating procedures remain critical.The countries following the guidelines can eradicate this virus.New Zealand was the rst country to eliminate the virus from their territory. | Rizwan Ali Naqvi Muhammad Faheem Mushtaq Natash Ali Mian Muhammad Adnan Khan Atta-ur-Rahman Muhammad Ali Yousaf Muhammad Umair Rizwan Majeed | 2021 | Computers, Materials & Continua2021，，5： | 0 |
| 16 | Intelligent Model for Predicting the Quality of Services Violation显示文摘Cloud computing is providing IT services to its customer based on Service level agreements(SLAs).It is important for cloud service providers to provide reliable Quality of service(QoS)and to maintain SLAs accountability.Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it.Cloud users’major concerns;the factors for service reliability are based on response time,accessibility,availability,and speed.In this paper,we,therefore,experiment with the parallel mutant-Particle swarm optimization(PSO)for the detection and predictions of QoS violations in terms of response time,speed,accessibility,and availability.This paper also compares Simple-PSO and Parallel MutantPSO.In simulation results,it is observed that the proposed Parallel MutantPSO solution for cloud QoS violation prediction achieves 94%accuracy which is many accurate results and is computationally the fastest technique in comparison of conventional PSO technique. | Muhammad Adnan Khan Asma Kanwal Sagheer Abbas Faheem Khan T.Whangbo | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 17 | Two-Stream Deep Learning Architecture-Based Human Action Recognition显示文摘Human action recognition(HAR)based on Artificial intelligence reasoning is the most important research area in computer vision.Big breakthroughs in this field have been observed in the last few years;additionally,the interest in research in this field is evolving,such as understanding of actions and scenes,studying human joints,and human posture recognition.Many HAR techniques are introduced in the literature.Nonetheless,the challenge of redundant and irrelevant features reduces recognition accuracy.They also faced a few other challenges,such as differing perspectives,environmental conditions,and temporal variations,among others.In this work,a deep learning and improved whale optimization algorithm based framework is proposed for HAR.The proposed framework consists of a few core stages i.e.,frames initial preprocessing,fine-tuned pre-trained deep learning models through transfer learning(TL),features fusion using modified serial based approach,and improved whale optimization based best features selection for final classification.Two pre-trained deep learning models such as InceptionV3 and Resnet101 are fine-tuned and TL is employed to train on action recognition datasets.The fusion process increases the length of feature vectors;therefore,improved whale optimization algorithm is proposed and selects the best features.The best selected features are finally classified usingmachine learning(ML)classifiers.Four publicly accessible datasets such as Ut-interaction,Hollywood,Free Viewpoint Action Recognition usingMotion History Volumes(IXMAS),and centre of computer vision(UCF)Sports,are employed and achieved the testing accuracy of 100%,99.9%,99.1%,and 100%respectively.Comparison with state of the art techniques(SOTA),the proposed method showed the improved accuracy. | Faheem Shehzad Muhammad Attique Khan Muhammad Asfand E.Yar Muhammad Sharif Majed Alhaisoni Usman Tariq Arnab Majumdar Orawit Thinnukool | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 18 | Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble显示文摘Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text.This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus.Furthermore,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic criteria.Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus.Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to baselines.Finally,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances.The proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText alone.The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances. | Muhammad Rizwan Muhammad Faheem Mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran Ashraf | 2024 | Computers, Materials & Continua2024，78，2： | 0 |
| 19 | Enabling Smart Cities with Cognition Based Intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine显示文摘The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries,including the transportation sector.The worldwide transport departments face many obstacles following the implementation and integration of different vehicle features.One of these tasks is to ensure that vehicles are autonomous,intelligent and able to grow their repository of information.Machine learning has recently been implemented in wireless networks,as a major artificial intelligence branch,to solve historically challenging problems through a data-driven approach.In this article,we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try to focus on this emerging field.Deep Extreme Learning Machine(DELM)framework is introduced in this article to be incorporated in vehicles so they can take human-like assessments.The present GPS compatibility issues make it difficult for vehicles to take real-time decisions under certain conditions.It leads to the concept of vehicle controller making self-decisions.The proposed DELM based system for self-intelligent vehicle decision makes use of the cognitive memory to store route observations.This overcomes inadequacy of the current in-vehicle route-finding technology and its support.All the relevant route-related information for the ride will be provided to the user based on its availability.Using the DELM method,a high degree of precision in smart decision taking with a minimal error rate is obtained.During investigation,it has been observed that proposed framework has the highest accuracy rate with 70%of training(1435 samples)and 30%of validation(612 samples).Simulation results validate the intelligent prediction of the proposed method with 98.88%,98.2%accuracy during training and validation respectively. | Dildar Hussain Muhammad Adnan Khan Sagheer Abbas Rizwan Ali Naqvi Muhammad Faheem Mushtaq Abdur Rehman Afrozah Nadeem | 2021 | Computers, Materials & Continua2021，，1： | 0 |
| 20 | Mobile Devices Interface Adaptivity Using Ontologies显示文摘Currently,many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces.The context offers the information base for the development of Adaptive user interface(AUI)frameworks to overcome the heterogeneity.For this purpose,the ontological modeling has been made for specific context and environment.This type of philosophy states to the relationship among elements(e.g.,classes,relations,or capacities etc.)with understandable satisfied representation.The contextmechanisms can be examined and understood by anymachine or computational framework with these formal definitions expressed in Web ontology language(WOL)/Resource description frame work(RDF).The Protégéis used to create taxonomy in which system is framed based on four contexts such as user,device,task and environment.Some competency questions and use-cases are utilized for knowledge obtaining while the information is refined through the instances of concerned parts of context tree.The consistency of the model has been verified through the reasoning software while SPARQL querying ensured the data availability in the models for defined use-cases.The semantic context model is focused to bring in the usage of adaptive environment.This exploration has finished up with a versatile,scalable and semantically verified context learning system.This model can be mapped to individual User interface(UI)display through smart calculations for versatile UIs. | Muhammad Waseem Iqbal Muhammad Raza Naqvi Muhammad Adnan Khan Faheem Khan T.Whangbo | 2022 | Computers, Materials & Continua2022，，6： | 0 |
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