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| 1 | Systematic review of oncological outcomes following laparoscopic vs open total mesorectal excision显示文摘AIM: To systematically analyze the randomized trials comparing the oncological and clinical effectiveness of laparoscopic total mesorectal excision(LTME) vs open total mesorectal excision(OTME) in the management of rectal cancer.METHODS: Published randomized, controlled trials comparing the oncological and clinical effectiveness of LTME vs OTME in the management of rectal cancer were retrieved from the standard electronic medical databases. The data of included randomized, controlled trials was extracted and then analyzed according to the principles of meta-analysis using RevMan? statistical software. The combined outcome of the binary variables was expressed as odds ratio(OR) and the combined outcome of the continuous variables waspresented in the form of standardized mean difference(SMD). RESULTS: Data from eleven randomized, controlled trials on 2143 patients were retrieved from the electronic databases. There was a trend towards the higher risk of surgical site infection(OR = 0.66; 95%CI: 0.44-1.00; z = 1.94; P < 0.05), higher risk of incomplete total mesorectal resection(OR = 0.62; 95%CI: 0.43-0.91; z = 2.49; P < 0.01) and prolonged length of hospital stay(SMD,-1.59; 95%CI:-0.86--0.25; z = 4.22; P < 0.00001) following OTME. However, the oncological outcomes like number of harvested lymph nodes, tumour recurrence and risk of positive resection margins were statistically similar in both groups. In addition, the clinical outcomes such as operative complications, anastomotic leak and all-cause mortality were comparable between both approaches of mesorectal excision.CONCLUSION: LTME appears to have clinically and oncologically measurable advantages over OTME in patients with primary rectal cancer in both short term and long term follow ups. | Muhammad Shafique Sajid Adil Ahamd William FA Miles Mirza Khurrum Baig | 2014 | World Journal of Gastrointestinal Endoscopy2014，6，5： | 7 |
| 2 | Synthesis of graphene materials by electrochemical exfoliation: Recent progress and future potential显示文摘Synthesis of structurally controlled graphene materials is critical for realizing their practical applications.The electrochemical exfoliation of graphite has emerged as a simple method to produce graphene materials.This review examines research progress in the last 5 years,from 2015 to 2019.Graphene material synthesis methods generally have a trade‐off between increasing production yield and achieving better material property control.The synthesis conditions for synthesizing pristine graphene,graphene oxide(GO),and graphene composites are significantly different.Thus,in this review,we first discuss synthesis methods for graphene materials with high C/O ratios from four aspects:graphite electrodes,equipment engineering,electrolytes,and additional reduction methods.Next,we survey synthesis methods for GO and examine how the pretreatment of the graphite electrodes,electrolytes,and operation parameters,such as applied voltages,electrolyte temperatures,and mechanical forces,affect the quality of GO.Further,we summarize electrochemical exfoliation methods used to dope graphene materials,introduce covalent functional groups,incorporate various nanoparticles,and assembly of graphene architectures.For all synthesis methods,we compare the properties of resulting graphene materials such as C/O ratios,lateral size,layer numbers,and quality characterized by Raman spectroscopy.Lastly,we propose our perspectives on further research.We hope this review stimulates more studies to realize the on‐demand production of graphene materials with desired properties using electrochemical exfoliation methods. | Fei Liu Chaojun Wang Xiao Sui Muhammad Adil Riaz Meiying Xu Li Wei Yuan Chen | 2019 | Carbon Energy2019，1，2： | 6 |
| 3 | Combining chlorination and sulfuration strategies for high-performance all-small-molecule organic solar cells显示文摘Three small-molecule donors based on dithieno [2,3-d:2’,3 ’-d’]-benzo[1,2-b:4,5-b’] dithiophene(DTBDT)unit were designed and synthesized by side chain regulation with chlorinated or/and sulfurated substitutions(namely ZR1,ZR1-Cl,and ZR1-S-Cl respectively),along with a crystalline non-fullerene acceptor IDIC-4 Cl with a chlorinated 1,1-dicyanomethylene-3-indanone(IC) end group.Energy levels,molar extinction coefficients and crystallinities of three donor molecules can be effectively altered by combining chlorination and sulfuration strategies.Especially,the ZR1-S-Cl exhibited the best absorption ability,lowest higher occupied molecular orbital(HOMO) energy level and highest crystallinity among three donors,resulting in the corresponding all-small-molecule organic solar cells to produce a high power conversion efficiency(PCE) of 12.05% with IDIC-4 Cl as an acceptor. | Ruimin Zhou Chen Yang Wenjun Zou Muhammad Abdullah Adil Huan Li Min Lv Ziyun Huang Menglan Lv Jianqi Zhang Kun Lu Zhixiang Wei | 2021 | Journal of Energy Chemistry2021，30，1： | 3 |
| 4 | Arsenic fractionation in sediments of different origins using BCR sequential and single extraction methods显示文摘 | Jameel Ahmed Baig Tasneem Gul Kazi Muhammad Balal Arain Abdul Qadir Shah Raja Adil Sarfraz Hassan Imran Afridi Ghulam Abbas Kandhro Muhammad Khan Jamali Sumaira Khan | 2009 | Journal of Hazardous Materials2009，，1： | 1 |
| 5 | Deposition and electrical properties of cadmium telluride thin films by thermal vacuum evaporation technique显示文摘 | Nazar Abbas Shah Manzar Abbas Muhammad Bashir Waqar Ahmad Adil Syed Muhammad Ashraf Atta | 2009 | 材料科学与工程(中英文版)2009，3，10： | 1 |
| 6 | Realizing high thermoelectric performance via selective resonant doping in oxyselenide BiCuSeO显示文摘Tuning the charge carrier concentration is imperative to optimize the thermoelectric(TE)performance of a material.For BiCuSeO based oxyselenides,doping efforts have been limited to optimizing the carrier concentration.In the present work,dual-doping of In and Pb at Bi site is introduced for p-type BiCuSeO to realize the electric transport channels with intricate band characteristics to improve the power factor(PF).Herein,the impurity resonant state is realized via doping of resonant dopant In over Pb,where Pb comes forward to optimize the Fermi energy in the dual-doped BiCuSeO system to divulge the significance of complex electronic structure.The manifold roles of dual-doping are used to adjust the elevation of the PF due to the significant enhancement in electrical properties.Thus,the combined experimental and theoretical study shows that the In/Pb dual doping at Bi sites gently reduces bandgap,introduces resonant doping states with shifting down the Fermi level into valence band(VB)with a larger density of state,and thus causes to increase the carrier concentration and effective mass(m*),which are favorable to enhance the electronic transport significantly.As a result,both improved ZTmax=0.87(at 873 K)and high ZTave=0.5(at 300–873 K)are realized for InyBi(1−x)−yPbxCuSeO(where x=0.06 and y=0.04)system.The obtained results successfully demonstrate the effectiveness of the selective dual doping with resonant dopant inducing band manipulation and carrier engineering that can unlock new prospects to develop high TE materials. | Yue-Xing Chen Wenning Qin Adil Mansoor Adeel Abbas Fu Li Guang-xing Liang Ping Fan Muhammad Usman Muzaffar Bushra Jabar Zhen-hua Ge Zhuang-hao Zheng | 2023 | Nano Research2023，16，1： | 1 |
| 7 | Automated Brain Hemorrhage Classification and Volume Analysis显示文摘Brain hemorrhage is a serious and life-threatening condition. It cancause permanent and lifelong disability even when it is not fatal. The wordhemorrhage denotes leakage of blood within the brain and this leakage ofblood from capillaries causes stroke and adequate supply of oxygen to thebrain is hindered. Modern imaging methods such as computed tomography(CT) and magnetic resonance imaging (MRI) are employed to get an idearegarding the extent of the damage. An early diagnosis and treatment can savelives and limit the adverse effects of a brain hemorrhage. In this case, a deepneural network (DNN) is an effective choice for the early identification andclassification of brain hemorrhage for the timely recovery and treatment of anaffected person. In this paper, the proposed research work is divided into twonovel approaches, where, one for the classification and the other for volumecalculation of brain hemorrhage. Two different datasets are used for twodifferent techniques classification and volume. A novel algorithm is proposedto calculate the volume of hemorrhage using CT scan images. In the firstapproach, the ‘RSNA’ dataset is used to classify the brain hemorrhage typesusing transfer learning and achieved an accuracy of 93.77%. Furthermore,in the second approach, a novel algorithm has been proposed to calculate thevolume of brain hemorrhage and achieved tremendous results as 1035.91mm3and 9.25 cm3, using the PhysioNet CT scan tomography dataset. | Maryam Wardah Muhammad Mateen Tauqeer Safdar Malik Mohammad Eid Alzahrani Adil Fahad Abdulmohsen Almalawi Rizwan Ali Naqvi | 2023 | Computers, Materials & Continua2023，，4： | 0 |
| 8 | The relationship between timing of admission to a hospital and severity of injuries following 2005 Pakistan earthquake显示文摘 | Qamar Hafeez Kiani Mudassar Qazi Adil Khan Muhammad Iqbal | 2016 | Chinese Journal of Traumatology2016，19，4： | 0 |
| 9 | Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI显示文摘The detection of brain disease is an essential issue in medical and research areas.Deep learning techniques have shown promising results in detecting and diagnosing brain diseases using magnetic resonance imaging(MRI)images.These techniques involve training neural networks on large datasets of MRI images,allowing the networks to learn patterns and features indicative of different brain diseases.However,several challenges and limitations still need to be addressed further to improve the accuracy and effectiveness of these techniques.This paper implements a Feature Enhanced Stacked Auto Encoder(FESAE)model to detect brain diseases.The standard stack auto encoder’s results are trivial and not robust enough to boost the system’s accuracy.Therefore,the standard Stack Auto Encoder(SAE)is replaced with a Stacked Feature Enhanced Auto Encoder with a feature enhancement function to efficiently and effectively get non-trivial features with less activation energy froman image.The proposed model consists of four stages.First,pre-processing is performed to remove noise,and the greyscale image is converted to Red,Green,and Blue(RGB)to enhance feature details for discriminative feature extraction.Second,feature Extraction is performed to extract significant features for classification using DiscreteWavelet Transform(DWT)and Channelization.Third,classification is performed to classify MRI images into four major classes:Normal,Tumor,Brain Stroke,and Alzheimer’s.Finally,the FESAE model outperforms the state-of-theart,machine learning,and deep learning methods such as Artificial Neural Network(ANN),SAE,Random Forest(RF),and Logistic Regression(LR)by achieving a high accuracy of 98.61% on a dataset of 2000 MRI images.The proposed model has significant potential for assisting radiologists in diagnosing brain diseases more accurately and improving patient outcomes. | Umair Muneer Butt Rimsha Arif Sukumar Letchmunan Babur Hayat Malik Muhammad Adil Butt | 2023 | Computers, Materials & Continua2023，76，8： | 0 |
| 10 | Cleavage classification:categorizing a vital feminine aesthetic landmark显示文摘Breast cleavage is defined by the International Federation of Associations of Anatomists(IFAA),as the space present between a woman’s breasts.The width of the inter-mammary cleft is defined by the distance between the points of attachment of the breast tissue to the periosteal tissue.[1-3]. | Muhammad Adil Abbas Khan Ammar Asrar Javed Nigel Mercer | 2016 | Plastic and Aesthetic Research2016，3，1： | 0 |
| 11 | Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content显示文摘Emotion detection from the text is a challenging problem in the text analytics.The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions.However,most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets,resulting in performance degradation.To overcome this issue,this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset.The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision,recall ad f-measure.Finally,a classifier with the best performance is recommended for the emotion classification. | Muhammad Zubair Asghar Fazli Subhan Muhammad Imran Fazal Masud Kundi Adil Khan Shahboddin Shamshirband Amir Mosavi Peter Csiba Annamaria RVarkonyi Koczy | 2020 | Computers, Materials & Continua2020，，6： | 0 |
| 12 | 荫蔽和微生物可在分子水平上调控植物激素以增强植物的耐旱性显示文摘植物在其生命周期内会受到一系列不利环境的影响。其中,干旱胁迫是限制农业生产力的重要因素之一。为了在逆境的环境中得以生存,植物进化出了识别环境胁迫严重性的机制。植物可通过多种方式调节激素活性,以减轻干旱带来的不良影响。受荫蔽和微生物调控,植株的抗旱性提高,产量损失减少。脱落酸、生长素和乙烯等植物激素,可调控多种代谢途径,在荫蔽和微生物介导的植株抗旱性增强过程中起着重要作用。如我们的调控模型所示,CLAVATA3/EMBRYOSURROUNDING REGION-RELATED 25多肽因其可影响ABA合成而在此过程中具有重要作用。 | Muhammad Ahsan Asghar Bushra Ahmad Ali Raza Bilal Adil Hafz Hassan Javed Muhammad Umer Farooq Abuzar Ghafoor Muhammad Iftikhar Hussain Iram Shafq Hassan Karim Xin Sun Wenyu Yang Gábor Kocsy Junbo Du | 2022 | Journal of Plant Ecology2022，15，6： | 0 |
| 13 | An Intelligent Cluster Optimization Algorithm for Smart Body Area Networks显示文摘Body Area Networks(BODYNETs)or Wireless Body Area Networks(WBAN),being an important type of ad-hoc network,plays a vital role in multimedia,safety,and traffic management applications.In BODYNETs,rapid topology changes occur due to high node mobility,which affects the scalability of the network.Node clustering is one mechanism among many others,which is used to overcome this issue in BODYNETs.There are many clustering algorithms used in this domain to overcome this issue.However,these algorithms generate a large number of Cluster Heads(CHs),which results in scarce resource utilization and degraded performance.In this research,an efficient clustering technique is proposed to handle these problems.The transmission range of BODYNET nodes is dynamically tuned accordingly as per their operational requirements.By optimizing the transmission range,the packet loss ratio is minimized,and link quality is improved,which leads to reduced energy consumption.To select optimal CHs the Whale Optimization Algorithm(WOA)is used based on their fitness,which enhances the network performance by reducing routing overhead.Our proposed scheme outclasses the existing state-of-the-art techniques,e.g.,Ant Colony Optimization(ACO),Gray Wolf Optimization(GWO),and Dragonfly Optimization Algorithm(DFA)in terms of energy consumption and cluster building time. | Adil Mushtaq Muhammad Nadeem Majeed Farhan Aadil Muhammad Fahad Khan Sangsoon Lim | 2021 | Computers, Materials & Continua2021，，6： | 0 |
| 14 | Polarization-based optimal detection scheme for digital self-interference cancellation in full-duplex system显示文摘In order to detect and cancel the self-interference(SI)signal from desired binary phase-shift keying(BPSK)signal,the polarization-based optimal detection(POD)scheme for cancellation of digital SI in a full-duplex(FD)system is proposed.The POD scheme exploits the polarization domain to isolate the desired signal from the SI signal and then cancel the SI to obtain the interference-free desired signal at the receiver.In FD communication,after antenna and analog cancellation,the receiver still contains residual SI due to non-linearities of hardware imperfections.In POD scheme,a likelihood ratio expression is obtained,which isolates and detects SI bits from the desired bits.After isolation of these signal points,the POD scheme cancels the residual SI.As compared to the conventional schemes,the proposed POD scheme gives significantly low bit error rate(BER),a clear constellation diagram to obtain the boundary between desired and SI signal points,and increases the receiver's SI cancellation performance in low signal to interference ratio(SIR)environment. | Adil Khan Zhang Jinling Muhammad Ayzed Mirza Sibghat Ullah Erum Ab basi Babar Hayat | 2020 | The Journal of China Universities of Posts and Telecommunications2020，27，3： | 0 |
| 15 | Effects of lead(Pb)-induced oxidative stress on morphological and physio-biochemical properties of rice显示文摘In rice,high concentration of lead(Pb)can cause phyto-toxicity affecting several physiological functions.Cultivation of rice varieties that are resistant to Pb-induced oxidative stress is an important management strategy in Pb-contaminated soils.In the current study,we evaluated four different rice cultivars for their response to Pb-induced stress.Three japonica type cultivars X-Jigna,Ediget,and Furat,and one Indica type cultivar Amber 33 were grown in soil containing different Pb concentrations(0 mM,0.6 mM,and 1.2 mM).The soil was treated with 0 mM or 0.6 mM or 1.2 mM Pb solution one month prior to rice seedling transplantation.Thereafter,four-week-old rice seedlings were transplanted into the treated soil and their responses were observed until maturity.The data revealed that a highest concentration of Pb(1.2 mM)induced significant reduction in agronomic traits such as plant height,number of tillers per plant,number of panicles per plant,and number of spikelets per panicle in all the rice cultivars.However,least reduction in the agronomic traits was observed in X-Jigna,whereas the highest reduction in the agronomic traits was observed in Ediget.Antioxidant activity of catalase(CAT),peroxidase(POD),polyphenol oxidase(PPO),and superoxide dismutase(SOD),was evaluated along with the accumulation of superoxide ions(O2.-),protein,proline,chlorophyll,sucrose,glucose,and fructose contents in all the rice cultivars.A significant increase in antioxidant activity and in the accumulation of proline and sucrose contents with the least reduction in the chlorophyll and protein contents was observed in X-Jigna suggesting that X-Jigna is the most tolerant among all the rice cultivars tested against Pb-stress.On the other hand,non-significant and slightly significant increase in the antioxidant activity,less accumulation of proline and sucrose contents,and higher reduction in the chlorophyll and protein contents was observed in Ediget,which further suggest that Ediget is the most susceptible rice cultivar to Pb-stress.In addition,the other rice cultivars Furat and Amber 33,were found to be moderately tolerant to Pb-induced oxidative stress.In summary,our results suggest that tolerance to Pb-induced oxidative stress would be a result of a synergetic action of both enzymatic and non-enzymatic antioxidant systems,leading to a balanced redox status in rice. | MURTAZA KHAN IBA NAZAR IBRAHIM AL AZZAWI MUHAMMAD IMRAN ADIL HUSSAIN BONG-GYU MUN ANJALI PANDE BYUNG-WOOK YUN | 2021 | BIOCELL2021，45，5： | 0 |
| 16 | Multi Sensor-Based Implicit User Identification显示文摘Smartphones have ubiquitously integrated into our home and work environments,however,users normally rely on explicit but inefficient identification processes in a controlled environment.Therefore,when a device is stolen,a thief can have access to the owner’s personal information and services against the stored passwords.As a result of this potential scenario,this work proposes an automatic legitimate user identification system based on gait biometrics extracted from user walking patterns captured by smartphone sensors.A set of preprocessing schemes are applied to calibrate noisy and invalid samples and augment the gait-induced time and frequency domain features,then further optimized using a non-linear unsupervised feature selection method.The selected features create an underlying gait biometric representation able to discriminate among individuals and identify them uniquely.Different classifiers are adopted to achieve accurate legitimate user identification.Extensive experiments on a group of 16 individuals in an indoor environment show the effectiveness of the proposed solution:with 5 to 70 samples per window,KNN and bagging classifiers achieve 87–99%accuracy,82–98%for ELM,and 81–94%for SVM.The proposed pipeline achieves a 100%true positive and 0%false-negative rate for almost all classifiers. | Muhammad Ahmad Rana Aamir Raza Manuel Mazzara Salvatore Distefano Ali Kashif Bashir Adil Khan Muhammad Shahzad Sarfraz Muhammad Umar Aftab | 2021 | Computers, Materials & Continua2021，，8： | 0 |
| 17 | Dehydration and volume depletion:How to handle the misconceptions显示文摘Dehydration and volume depletion describe two distinct body fluid deficit disorders with differing pathophysiology,clinical manifestations and treatment approaches.However,the two are often confused or equated with each other.Here,we address a number of commonly encountered misconceptions about body-fluid deficit disorders,analyse their origins and propose approaches to overcome them. | Muhammad Asim Mohamad M Alkadi Hania Asim Adil Ghaffar | 2019 | World Journal of Nephrology2019，8，1： | 0 |
| 18 | An Intelligent Hybrid Mutual Authentication Scheme for Industrial Internet of Thing Networks显示文摘Internet of Things(IoT)network used for industrial management is vulnerable to different security threats due to its unstructured deployment,and dynamic communication behavior.In literature various mechanisms addressed the security issue of Industrial IoT networks,but proper maintenance of the performance reliability is among the common challenges.In this paper,we proposed an intelligent mutual authentication scheme leveraging authentication aware node(AAN)and base station(BS)to identify routing attacks in Industrial IoT networks.The AAN and BS uses the communication parameter such as a route request(RREQ),node-ID,received signal strength(RSS),and round-trip time(RTT)information to identify malicious devices and routes in the deployed network.The feasibility of the proposed model is validated in the simulation environment,where OMNeT++was used as a simulation tool.We compare the results of the proposed model with existing field-proven schemes in terms of routing attacks detection,communication cost,latency,computational cost,and throughput.The results show that our proposed scheme surpasses the previous schemes regarding these performance parameters with the attack detection rate of 97.7%. | Muhammad Adil Jehad Ali Muhammad Sajjad Khan Junsu Kim Ryan Alturki Mohammad Zakarya Mukhtaj Khan Rahim Khan Su Min Kim | 2021 | Computers, Materials & Continua2021，，7： | 0 |
| 19 | Modifiable determinants of attitude towards dengue vaccination among healthy inhabitants of Aceh,Indonesia:Findings from a community-based survey显示文摘Objective:To explore and understand the attitude towards dengue vaccination and its modifiable determinants among inhabitants of Aceh(northern Sumatra Island,Indonesia),the region that was most severely affected by the earthquake and tsunami of 26 December 2004.Methods:A communitybased,cross-sectional study was conducted among 535 healthy inhabitants in nine regencies(Kabupaten or Kotamadya) of Aceh that were selected randomly from November 2014 to March 2015.A set of validated,pre-tested,structured questionnaires was used to guide the interviews.The questionnaires covered a range of explanatory variables and one outcome variable(attitude to dengue vaccination).Multi-step logistic regression analysis and Spearman's rank correlation were used to test the role of explanatory variables for the outcome variable.Results:More than 70%of the participants had a poor attitude towards dengue vaccination.Modifiablc determinants associated with poor attitude to dengue vaccination were low education level,working as farmers and traditional market traders,low socioeconomic status and poor knowledge,attitude and practice regarding dengue fever(P<0.05).The KAP domain scores were correlated strongly with attitude to dengue vaccination,r_s=0.25,r_S=0.67 and r_s=0.20,respectively(P<0.001).Multivariate analysis found that independent predictors associated with attitude towards dengue vaccination among study participants were only sex and attitude towards dengue fever(P<0.001).Conclusions:This study reveals that low KAP regarding dengue fever,low education level and low socioeconomic status are associated with a poor attitude towards dengue vaccination.Therefore,inhabitants of suburbs who are working as larmers or traditional market traders with low socioeconomic status are the most appropriate target group for a dengue vaccine introduction program. | Harapan Harapan Samsul Anwar Aslam Bustaman Arsil Radiansyah Pradiba Angraini Riny Fasli Salwiyadi Salwiyadi Reza Akbar Bastian Ade Oktiviyari Imaduddin Akmal Muhammad Iqbalamin Jamalul Adil Fenni Henrizal Darmayanti Darmayanti Rovy Pratama Jhony Karunia Fajar Abdul Malik Setiawan Mandira Lamichhane Dhimal Ulrich Kuch David Alexander Groneberg R.Tedjo Sasmono Meghnath Dhimal Ruth Mueller | 2016 | Asian Pacific Journal of Tropical Medicine2016，9，11： | 0 |
| 20 | Adaptive Power Control Aware Depth Routing in Underwater Sensor Networks显示文摘Underwater acoustic sensor network(UASN)refers to a procedure that promotes a broad spectrum of aquatic applications.UASNs can be practically applied in seismic checking,ocean mine identification,resource exploration,pollution checking,and disaster avoidance.UASN confronts many difficulties and issues,such as low bandwidth,node movements,propagation delay,3D arrangement,energy limitation,and high-cost production and arrangement costs caused by antagonistic underwater situations.Underwater wireless sensor networks(UWSNs)are considered a major issue being encountered in energy management because of the limited battery power of their nodes.Moreover,the harsh underwater environment requires vendors to design and deploy energy-hungry devices to fulfil the communication requirements and maintain an acceptable quality of service.Moreover,increased transmission power levels result in higher channel interference,thereby increasing packet loss.Considering the facts mentioned above,this research presents a controlled transmission power-based sparsity-aware energy-efficient clustering in UWSNs.The contributions of this technique is threefold.First,it uses the adaptive power control mechanism to utilize the sensor nodes’battery and reduce channel interference effectively.Second,thresholds are defined to ensure successful communication.Third,clustering can be implemented in dense areas to decrease the repetitive transmission that ultimately affects the energy consumption of nodes and interference significantly.Additionally,mobile sinks are deployed to gather information locally to achieve the previously mentioned benefits.The suggested protocol is meticulously examined through extensive simulations and is validated through comparison with other advanced UWSN strategies.Findings show that the suggested protocol outperforms other procedures in terms of network lifetime and packet delivery ratio. | Ghufran Ahmed Saiful Islam Ihsan Ali Isra Adil Hayder Abdelmuttlib Ibrahim Abdalla Ahmed Muhammad Talha Sultan S.Alshamrani Ag Asri Ag Ibrahim | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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