The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Th...The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Therefore,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,Egypt.The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering(PSS/E)software.Where the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered system.The results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power factor.Decreasing total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 microseconds.The connection between solar stations and the national grid makes the system more efficient.展开更多
This article explores the comparison between the probability method and the least squares method in the design of linear predictive models. It points out that these two approaches have distinct theoretical foundations...This article explores the comparison between the probability method and the least squares method in the design of linear predictive models. It points out that these two approaches have distinct theoretical foundations and can lead to varied or similar results in terms of precision and performance under certain assumptions. The article underlines the importance of comparing these two approaches to choose the one best suited to the context, available data and modeling objectives.展开更多
The purpose of this study was to establish factors that lead to poor integration of Information and communication technology （ICT） for teaching and learning in schools in Kenya, despite comprehensive policy, institu...The purpose of this study was to establish factors that lead to poor integration of Information and communication technology （ICT） for teaching and learning in schools in Kenya, despite comprehensive policy, institutional, infrastructural frameworks and capacity building by the Ministry of Education. The subject of this study was administered by use of questionnaires in three categories of public schools： national school, provincial schools and district schools. The respondents were students from each level that is from one, two, three and four and teachers based on the most offered subjects in the secondary schools. The computer assisted learning facilities were classified into computers, internet and content in optical media. In national school Internet based research, optical media content provided by Kenya Institute of Curriculum Development and Cyber School program for science subjects was used in learning. In provincial school, it lacks adequate computers, reliable Internet and content in optical media. In district school, it lacks adequate computer, no internet connection and content in optical media. A learner management system which can be accessed by all learners by use of any internet access devices like mobile phone access will be an ideal tool with over 4,000,000 mobile phone subscribers currently in Kenya.展开更多
Online reviews regarding purchasing services or products offered are the main source of users’opinions.To gain fame or profit,generally,spam reviews are written to demote or promote certain targeted products or servi...Online reviews regarding purchasing services or products offered are the main source of users’opinions.To gain fame or profit,generally,spam reviews are written to demote or promote certain targeted products or services.This practice is called review spamming.During the last few years,various techniques have been recommended to solve the problem of spam reviews.Previous spam detection study focuses on English reviews,with a lesser interest in other languages.Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced.Thus,this study develops an Automated Spam Review Detection using optimal Stacked Gated Recurrent Unit(SRD-OSGRU)on Arabic Opinion Text.The presented SRD-OSGRU model mainly intends to classify Arabic reviews into two classes:spam and truthful.Initially,the presented SRD-OSGRU model follows different levels of data preprocessing to convert the actual review data into a compatible format.Next,unigram and bigram feature extractors are utilized.The SGRU model is employed in this study to identify and classify Arabic spam reviews.Since the trial-and-error adjustment of hyperparameters is a tedious process,a white shark optimizer(WSO)is utilized,boosting the detection efficiency of the SGRU model.The experimental validation of the SRD-OSGRU model is assessed under two datasets,namely DOSC dataset.An extensive comparison study pointed out the enhanced performance of the SRD-OSGRU model over other recent approaches.展开更多
Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and cybercrime.Such malicious software programs come under different classificat...Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and cybercrime.Such malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,etc.Ransomware is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of money.To prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine Learning(ML)algorithm.This study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection(LBAAA-OMLMD)approach in Computer Networks.The presented LBAAA-OMLMDmodelmainly aims to detect and classify the existence of ransomware and goodware in the network.To accomplish this,the LBAAA-OMLMD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality problems.Besides,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is applied.The FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier results.The experimental validation of the LBAAA-OMLMD model is tested using a benchmark dataset,and the outcomes are inspected in distinct measures.The comprehensive comparative examination demonstrated the betterment of the LBAAAOMLMD model over recent algorithms.展开更多
With the increased advancements of smart industries,cybersecurity has become a vital growth factor in the success of industrial transformation.The Industrial Internet of Things(IIoT)or Industry 4.0 has revolutionized ...With the increased advancements of smart industries,cybersecurity has become a vital growth factor in the success of industrial transformation.The Industrial Internet of Things(IIoT)or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether.In industry 4.0,powerful IntrusionDetection Systems(IDS)play a significant role in ensuring network security.Though various intrusion detection techniques have been developed so far,it is challenging to protect the intricate data of networks.This is because conventional Machine Learning(ML)approaches are inadequate and insufficient to address the demands of dynamic IIoT networks.Further,the existing Deep Learning(DL)can be employed to identify anonymous intrusions.Therefore,the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection(HGSODLID)model for the IIoT environment.The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format.The HGSO algorithm is employed for Feature Selection(HGSO-FS)to reduce the curse of dimensionality.Moreover,Sparrow Search Optimization(SSO)is utilized with a Graph Convolutional Network(GCN)to classify and identify intrusions in the network.Finally,the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model.The proposed HGSODL-ID model was experimentally validated using a benchmark dataset,and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.展开更多
Arabic is one of the most spoken languages across the globe.However,there are fewer studies concerning Sentiment Analysis(SA)in Arabic.In recent years,the detected sentiments and emotions expressed in tweets have rece...Arabic is one of the most spoken languages across the globe.However,there are fewer studies concerning Sentiment Analysis(SA)in Arabic.In recent years,the detected sentiments and emotions expressed in tweets have received significant interest.The substantial role played by the Arab region in international politics and the global economy has urged the need to examine the sentiments and emotions in the Arabic language.Two common models are available:Machine Learning and lexicon-based approaches to address emotion classification problems.With this motivation,the current research article develops a Teaching and Learning Optimization with Machine Learning Based Emotion Recognition and Classification(TLBOML-ERC)model for Sentiment Analysis on tweets made in the Arabic language.The presented TLBOML-ERC model focuses on recognising emotions and sentiments expressed in Arabic tweets.To attain this,the proposed TLBOMLERC model initially carries out data pre-processing and a Continuous Bag Of Words(CBOW)-based word embedding process.In addition,Denoising Autoencoder(DAE)model is also exploited to categorise different emotions expressed in Arabic tweets.To improve the efficacy of the DAE model,the Teaching and Learning-based Optimization(TLBO)algorithm is utilized to optimize the parameters.The proposed TLBOML-ERC method was experimentally validated with the help of an Arabic tweets dataset.The obtained results show the promising performance of the proposed TLBOML-ERC model on Arabic emotion classification.展开更多
Owing to the long propagation delay and high error rate of acoustic channels, it is very challenging to provide reliable data transfer for underwater sensor networks. Moreover, network coding is proved to be an effect...Owing to the long propagation delay and high error rate of acoustic channels, it is very challenging to provide reliable data transfer for underwater sensor networks. Moreover, network coding is proved to be an effective coding technique for throughput and robustness of networks. In this paper, we propose a Reliable Braided Multipath Routing with Network Coding for underwater sensor networks （RBMR-NC）. Disjoint multi-path algorithm is used to build independent actual paths, as called main paths. Some braided paths on each main path are built according to the braided multi-path algorithm, which are called logic paths. When a data packet is transmitted by these nodes, the nodes can employ network coding to encode packets coming from the same group in order to further reduce relativity among these packets, and enhance the probability of successful decoding at the sink node. Braided multi-path can make the main paths to be multiplexed to reduce the probability of long paths. This paper mainly employs successful delivery rate to evaluate RBMR-NC model with theoretical analysis and simulation methods. The results indicate that the proposed RBMR-NC protocol is valuable to enhance network reliability and to reduce system redundancy.展开更多
An integrated method for concurrency control in parallel real-time databases has been proposed in this paper. The nested transaction model has been investigated to offer more atomic execution units and finer grained c...An integrated method for concurrency control in parallel real-time databases has been proposed in this paper. The nested transaction model has been investigated to offer more atomic execution units and finer grained control within in a transaction. Based on the classical nested locking protocol and the speculative concurrency control approach, a two-shadow adaptive concurrency control protocol, which combines the Sacrifice based Optimistic Concurrency Control (OPT-Sacrifice) and High Priority two-phase locking (HP2PL) algorithms together to support both optimistic and pessimistic shadow of each sub-transaction, has been proposed to increase the likelihood of successful timely commitment and to avoid unnecessary replication overload.展开更多
Numerous privacy-preserving issues have emerged along with the fast development of Internet, both in theory and in real-life applications. To settle the privacy-preserving problems, secure multi-party computation is e...Numerous privacy-preserving issues have emerged along with the fast development of Internet, both in theory and in real-life applications. To settle the privacy-preserving problems, secure multi-party computation is essential and critical. In this paper, we have solved two problems regarding to how to determine the position relation between points and curves without revealing any private information. Two protocols have been proposed in order to solve the problems in different conditions. In addition, some building blocks have been developed, such as scalar product protocol, so that we can take advantage of them to settle the privacy-preserving computational geometry problems which are a kind of special secure multi-party computation problems. Moreover, oblivious transfer and power series expansion serve as significant parts in our protocols. Analyses and proofs have also been given to argue our conclusion.展开更多
There are some disadvantages, such as complicated wiring, high cost, poor monitoring flexibility, low accuracy and high energy consumption in traditional greenhouse environment monitoring system which based on previou...There are some disadvantages, such as complicated wiring, high cost, poor monitoring flexibility, low accuracy and high energy consumption in traditional greenhouse environment monitoring system which based on previous wireless sensor networks （WSN）. Aiming at these problems, a greenhouse environmental parameter monitoring system had been designed based on internet of things technology in this paper. A set of control system with good robustness, strong adaptive ability and small overshoot was set up by combining the fuzzy proportion-integral-derivative （PID） control. The system was composed of a number of independent greenhouse monitoring systems. The server could provide remote monitoring access management services after the collected data were transmitted. The data transmission part of greenhouse was based on ZigBee networking protocol. And the data were sent to intelligent system via gateway connected to the internet. Compared to the classical PID control and fuzzy control, the fuzzy PID control could quickly and accurately adjust the corresponding parameters to the set target. The overshoot was also relatively small. The simulation results showed that the amount of overshoot was reduced 20% compared with classical PID control.展开更多
To solve the disability of conventional model used in electrical leak location when measurement electrodes were buried under the liner, a new model of high voltage DC leak detection is developed. For single-liner land...To solve the disability of conventional model used in electrical leak location when measurement electrodes were buried under the liner, a new model of high voltage DC leak detection is developed. For single-liner landfill, the waste material layer, the geomembrane liner and the soil under the liner are simulated with infinite horizontal layers. The leak is regarded as two parts, one being negative current source at the entrance, and the other positive current source of the same size at the exit. Comparisons between the new theoretical model and conventional model show that conventional model is efficient in locating leaks in geomembane liner associating the dipole scanning above the liner but is ineffective when the measurement electrodes were buried under the liner. The new theoretical model data are in excellent agreement with experimental data not only above the liner but also under the liner.展开更多
In Chinese, dependency analysis has been shown to be a powerful syntactic parser because the order of phrases in a sentence is relatively free compared with English. Conventional dependency parsers require a number of...In Chinese, dependency analysis has been shown to be a powerful syntactic parser because the order of phrases in a sentence is relatively free compared with English. Conventional dependency parsers require a number of sophisticated rules that have to be handcrafted by linguists, and are too cumbersome to maintain. To solve the problem, a parser using SVM (Support Vector Machine) is introduced. First, a new strategy of dependency analysis is proposed. Then some chosen feature types are used for learning and for creating the modification matrix using SVM. Finally, the dependency of phrases in the sentence is generated. Experiments conducted to analyze how each type of feature affects parsing accuracy, showed that the model can increase accuracy of the dependency parser by 9.2%.展开更多
The pathogenesis of hypertrophic cardiomyopathy(HCM)is very complicated,particularly regarding the role of circular RNA(circRNA).This research pays special attention to the relationships of the circRNA-mediated networ...The pathogenesis of hypertrophic cardiomyopathy(HCM)is very complicated,particularly regarding the role of circular RNA(circRNA).This research pays special attention to the relationships of the circRNA-mediated network,including RNA-RNA relationships and RNA-RNA binding protein(RNA-RBP)relationships.We use the parameter framework technology proposed in this paper to screen differentially expressed circRNA,messenger RNA(mRNA),and microRNA(miRNA)from the expression profile of samples related to HCM.And 31 pairs of circRNA and mRNA relationship pairs were extracted,combined with the miRNA targeting database;145 miRNA-mRNA relationship pairs were extracted;268 circRNA-mRNA-miRNA triads were established through the common mRNA in the 2 types of relationship pairs.Thus,268 circRNA-miRNA regulatory relationships were deduced and 30 circRNARBP relationship pairs were analyzed at the protein level.On this basis,a circRNA-mediated regulatory network corresponding to the two levels of RNA-RNA and RNA-RBP was established.And then the roles of circRNA in HCM were analyzed through circRNA-mRNA,circRNA-miRNA,and circRNA-RBP,and the possible role in disease development mas inferred.展开更多
The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these p...The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.展开更多
A mobile molecular Doppler wind lidar （DWL） based on double-edge technique is presented for wind measurement at altitudes from 10 km to 40 km. A triple Fabry-Perot etalon is employed as a frequency discriminator to ...A mobile molecular Doppler wind lidar （DWL） based on double-edge technique is presented for wind measurement at altitudes from 10 km to 40 km. A triple Fabry-Perot etalon is employed as a frequency discriminator to determine the Doppler shift proportional to the wind velocity. The lidar operates at 355 nm with a 45-cm aperture telescope and a matching azimuth-over-elevation scanner that can provide full hemispherical pointing. In order to guarantee the wind accuracy, different forms of calibration function of detectors in different count rates response range would be especially valuable. The accuracy of wind velocity iteration is improved greatly because of application of the calibration function of linearity at the ultra low light intensity especially at altitudes from 10 km to 40 km. The calibration functions of nonlinearity make the transmission of edge channel 1 and edge channel 2 increase 38.9% and 27.7% at about 1 M count rates, respectively. The dynamic range of wind field measurement may also be extended because of consideration of the response function of detectors in their all possible operating range.展开更多
This study investigates the steam generating potential of a solar steam generation system and the potential for utility scale implementation in Libya oil for steam demanding enhanced oil recovery (EOR) methods. The pr...This study investigates the steam generating potential of a solar steam generation system and the potential for utility scale implementation in Libya oil for steam demanding enhanced oil recovery (EOR) methods. The proposed system uses parabolic troughs as solar collectors. The technology is proved to be technically feasible. Solar EOR should be seen as an add-on to existing plants due to the abundance of solar energy in Libya. The System Advisor Model (SAM) model system, developed by the National Office of Renewable Energy (NRE), was used to assess the plant’s active and economic performance.展开更多
文摘The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Therefore,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,Egypt.The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering(PSS/E)software.Where the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered system.The results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power factor.Decreasing total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 microseconds.The connection between solar stations and the national grid makes the system more efficient.
文摘This article explores the comparison between the probability method and the least squares method in the design of linear predictive models. It points out that these two approaches have distinct theoretical foundations and can lead to varied or similar results in terms of precision and performance under certain assumptions. The article underlines the importance of comparing these two approaches to choose the one best suited to the context, available data and modeling objectives.
文摘The purpose of this study was to establish factors that lead to poor integration of Information and communication technology （ICT） for teaching and learning in schools in Kenya, despite comprehensive policy, institutional, infrastructural frameworks and capacity building by the Ministry of Education. The subject of this study was administered by use of questionnaires in three categories of public schools： national school, provincial schools and district schools. The respondents were students from each level that is from one, two, three and four and teachers based on the most offered subjects in the secondary schools. The computer assisted learning facilities were classified into computers, internet and content in optical media. In national school Internet based research, optical media content provided by Kenya Institute of Curriculum Development and Cyber School program for science subjects was used in learning. In provincial school, it lacks adequate computers, reliable Internet and content in optical media. In district school, it lacks adequate computer, no internet connection and content in optical media. A learner management system which can be accessed by all learners by use of any internet access devices like mobile phone access will be an ideal tool with over 4,000,000 mobile phone subscribers currently in Kenya.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R263)PrincessNourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4310373DSR58The authors are thankful to the Deanship of ScientificResearch atNajranUniversity for funding thiswork under theResearch Groups Funding program grant code(NU/RG/SERC/11/7).
文摘Online reviews regarding purchasing services or products offered are the main source of users’opinions.To gain fame or profit,generally,spam reviews are written to demote or promote certain targeted products or services.This practice is called review spamming.During the last few years,various techniques have been recommended to solve the problem of spam reviews.Previous spam detection study focuses on English reviews,with a lesser interest in other languages.Spam review detection in Arabic online sources is an innovative topic despite the vast amount of data produced.Thus,this study develops an Automated Spam Review Detection using optimal Stacked Gated Recurrent Unit(SRD-OSGRU)on Arabic Opinion Text.The presented SRD-OSGRU model mainly intends to classify Arabic reviews into two classes:spam and truthful.Initially,the presented SRD-OSGRU model follows different levels of data preprocessing to convert the actual review data into a compatible format.Next,unigram and bigram feature extractors are utilized.The SGRU model is employed in this study to identify and classify Arabic spam reviews.Since the trial-and-error adjustment of hyperparameters is a tedious process,a white shark optimizer(WSO)is utilized,boosting the detection efficiency of the SGRU model.The experimental validation of the SRD-OSGRU model is assessed under two datasets,namely DOSC dataset.An extensive comparison study pointed out the enhanced performance of the SRD-OSGRU model over other recent approaches.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R319)PrincessNourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4310373DSR34The authors are thankful to the Deanship of Scientific Research at Najran University for funding thiswork under theResearch Groups Funding program Grant Code(NU/RG/SERC/11/4).
文摘Malware is a‘malicious software program that performs multiple cyberattacks on the Internet,involving fraud,scams,nation-state cyberwar,and cybercrime.Such malicious software programs come under different classifications,namely Trojans,viruses,spyware,worms,ransomware,Rootkit,botnet malware,etc.Ransomware is a kind of malware that holds the victim’s data hostage by encrypting the information on the user’s computer to make it inaccessible to users and only decrypting it;then,the user pays a ransom procedure of a sum of money.To prevent detection,various forms of ransomware utilize more than one mechanism in their attack flow in conjunction with Machine Learning(ML)algorithm.This study focuses on designing a Learning-Based Artificial Algae Algorithm with Optimal Machine Learning Enabled Malware Detection(LBAAA-OMLMD)approach in Computer Networks.The presented LBAAA-OMLMDmodelmainly aims to detect and classify the existence of ransomware and goodware in the network.To accomplish this,the LBAAA-OMLMD model initially derives a Learning-Based Artificial Algae Algorithm based Feature Selection(LBAAA-FS)model to reduce the curse of dimensionality problems.Besides,the Flower Pollination Algorithm(FPA)with Echo State Network(ESN)Classification model is applied.The FPA model helps to appropriately adjust the parameters related to the ESN model to accomplish enhanced classifier results.The experimental validation of the LBAAA-OMLMD model is tested using a benchmark dataset,and the outcomes are inspected in distinct measures.The comprehensive comparative examination demonstrated the betterment of the LBAAAOMLMD model over recent algorithms.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R319)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR44The authors are thankful to the Deanship of Scientific Research at Najran University for funding thiswork under theResearch Groups Funding program Grant Code(NU/RG/SERC/11/4).
文摘With the increased advancements of smart industries,cybersecurity has become a vital growth factor in the success of industrial transformation.The Industrial Internet of Things(IIoT)or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether.In industry 4.0,powerful IntrusionDetection Systems(IDS)play a significant role in ensuring network security.Though various intrusion detection techniques have been developed so far,it is challenging to protect the intricate data of networks.This is because conventional Machine Learning(ML)approaches are inadequate and insufficient to address the demands of dynamic IIoT networks.Further,the existing Deep Learning(DL)can be employed to identify anonymous intrusions.Therefore,the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection(HGSODLID)model for the IIoT environment.The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format.The HGSO algorithm is employed for Feature Selection(HGSO-FS)to reduce the curse of dimensionality.Moreover,Sparrow Search Optimization(SSO)is utilized with a Graph Convolutional Network(GCN)to classify and identify intrusions in the network.Finally,the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model.The proposed HGSODL-ID model was experimentally validated using a benchmark dataset,and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R263)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR36The authors are thankful to the Deanship of Scientific Research at Najran University for funding thiswork under theResearch Groups Funding program grant code(NU/RG/SERC/11/7).
文摘Arabic is one of the most spoken languages across the globe.However,there are fewer studies concerning Sentiment Analysis(SA)in Arabic.In recent years,the detected sentiments and emotions expressed in tweets have received significant interest.The substantial role played by the Arab region in international politics and the global economy has urged the need to examine the sentiments and emotions in the Arabic language.Two common models are available:Machine Learning and lexicon-based approaches to address emotion classification problems.With this motivation,the current research article develops a Teaching and Learning Optimization with Machine Learning Based Emotion Recognition and Classification(TLBOML-ERC)model for Sentiment Analysis on tweets made in the Arabic language.The presented TLBOML-ERC model focuses on recognising emotions and sentiments expressed in Arabic tweets.To attain this,the proposed TLBOMLERC model initially carries out data pre-processing and a Continuous Bag Of Words(CBOW)-based word embedding process.In addition,Denoising Autoencoder(DAE)model is also exploited to categorise different emotions expressed in Arabic tweets.To improve the efficacy of the DAE model,the Teaching and Learning-based Optimization(TLBO)algorithm is utilized to optimize the parameters.The proposed TLBOML-ERC method was experimentally validated with the help of an Arabic tweets dataset.The obtained results show the promising performance of the proposed TLBOML-ERC model on Arabic emotion classification.
基金the National High-Tech Research and Development Plan of China under Grant No.2007AA01Z203(国家高技术研究发展计划(863))the National Basic Research Program of China under Grant No.2007CB307101-4(国家重点基础研究发展计划(973))
基金supported by the National Natural Science Foundation of China (Grant Nos.60472060 and 60473039)the National High Technology Research and Development Programof China (863 Program,Grant No.2006AA01Z119)the Innovation Fund of Chinese Academy of Space Technology (Grant No.CAST20090801)
文摘Owing to the long propagation delay and high error rate of acoustic channels, it is very challenging to provide reliable data transfer for underwater sensor networks. Moreover, network coding is proved to be an effective coding technique for throughput and robustness of networks. In this paper, we propose a Reliable Braided Multipath Routing with Network Coding for underwater sensor networks （RBMR-NC）. Disjoint multi-path algorithm is used to build independent actual paths, as called main paths. Some braided paths on each main path are built according to the braided multi-path algorithm, which are called logic paths. When a data packet is transmitted by these nodes, the nodes can employ network coding to encode packets coming from the same group in order to further reduce relativity among these packets, and enhance the probability of successful decoding at the sink node. Braided multi-path can make the main paths to be multiplexed to reduce the probability of long paths. This paper mainly employs successful delivery rate to evaluate RBMR-NC model with theoretical analysis and simulation methods. The results indicate that the proposed RBMR-NC protocol is valuable to enhance network reliability and to reduce system redundancy.
文摘An integrated method for concurrency control in parallel real-time databases has been proposed in this paper. The nested transaction model has been investigated to offer more atomic execution units and finer grained control within in a transaction. Based on the classical nested locking protocol and the speculative concurrency control approach, a two-shadow adaptive concurrency control protocol, which combines the Sacrifice based Optimistic Concurrency Control (OPT-Sacrifice) and High Priority two-phase locking (HP2PL) algorithms together to support both optimistic and pessimistic shadow of each sub-transaction, has been proposed to increase the likelihood of successful timely commitment and to avoid unnecessary replication overload.
基金Supported by the National Natural Science Foundation of China (No. 61070189, 60673065)the National High Technology Development Program (No. 2008AA01Z419)
文摘Numerous privacy-preserving issues have emerged along with the fast development of Internet, both in theory and in real-life applications. To settle the privacy-preserving problems, secure multi-party computation is essential and critical. In this paper, we have solved two problems regarding to how to determine the position relation between points and curves without revealing any private information. Two protocols have been proposed in order to solve the problems in different conditions. In addition, some building blocks have been developed, such as scalar product protocol, so that we can take advantage of them to settle the privacy-preserving computational geometry problems which are a kind of special secure multi-party computation problems. Moreover, oblivious transfer and power series expansion serve as significant parts in our protocols. Analyses and proofs have also been given to argue our conclusion.
基金Supported by the 13th Five-year National Key R&D Program:Development and Verification of Information Perception and Environment Intelligent Control System for Dairy Cattle and Beef Cattle(2016YFD0700204-02)Quality and Brand Construction of "Internet+County Characteristic Agricultural Products"(ZY17C06)
文摘There are some disadvantages, such as complicated wiring, high cost, poor monitoring flexibility, low accuracy and high energy consumption in traditional greenhouse environment monitoring system which based on previous wireless sensor networks （WSN）. Aiming at these problems, a greenhouse environmental parameter monitoring system had been designed based on internet of things technology in this paper. A set of control system with good robustness, strong adaptive ability and small overshoot was set up by combining the fuzzy proportion-integral-derivative （PID） control. The system was composed of a number of independent greenhouse monitoring systems. The server could provide remote monitoring access management services after the collected data were transmitted. The data transmission part of greenhouse was based on ZigBee networking protocol. And the data were sent to intelligent system via gateway connected to the internet. Compared to the classical PID control and fuzzy control, the fuzzy PID control could quickly and accurately adjust the corresponding parameters to the set target. The overshoot was also relatively small. The simulation results showed that the amount of overshoot was reduced 20% compared with classical PID control.
基金Project supported by the National High-Technology Research and Development Program of China (Grant No. 863-2001AA644010)
文摘To solve the disability of conventional model used in electrical leak location when measurement electrodes were buried under the liner, a new model of high voltage DC leak detection is developed. For single-liner landfill, the waste material layer, the geomembrane liner and the soil under the liner are simulated with infinite horizontal layers. The leak is regarded as two parts, one being negative current source at the entrance, and the other positive current source of the same size at the exit. Comparisons between the new theoretical model and conventional model show that conventional model is efficient in locating leaks in geomembane liner associating the dipole scanning above the liner but is ineffective when the measurement electrodes were buried under the liner. The new theoretical model data are in excellent agreement with experimental data not only above the liner but also under the liner.
文摘In Chinese, dependency analysis has been shown to be a powerful syntactic parser because the order of phrases in a sentence is relatively free compared with English. Conventional dependency parsers require a number of sophisticated rules that have to be handcrafted by linguists, and are too cumbersome to maintain. To solve the problem, a parser using SVM (Support Vector Machine) is introduced. First, a new strategy of dependency analysis is proposed. Then some chosen feature types are used for learning and for creating the modification matrix using SVM. Finally, the dependency of phrases in the sentence is generated. Experiments conducted to analyze how each type of feature affects parsing accuracy, showed that the model can increase accuracy of the dependency parser by 9.2%.
基金the National Natural Science Foundation of China under Grant No.61872405the Key R&D program of Sichuan Province under Grant No.2020YFS0243the Key Project of Natural Science Foundation of Guangdong Province under Grant No.2016A030311040.
文摘The pathogenesis of hypertrophic cardiomyopathy(HCM)is very complicated,particularly regarding the role of circular RNA(circRNA).This research pays special attention to the relationships of the circRNA-mediated network,including RNA-RNA relationships and RNA-RNA binding protein(RNA-RBP)relationships.We use the parameter framework technology proposed in this paper to screen differentially expressed circRNA,messenger RNA(mRNA),and microRNA(miRNA)from the expression profile of samples related to HCM.And 31 pairs of circRNA and mRNA relationship pairs were extracted,combined with the miRNA targeting database;145 miRNA-mRNA relationship pairs were extracted;268 circRNA-mRNA-miRNA triads were established through the common mRNA in the 2 types of relationship pairs.Thus,268 circRNA-miRNA regulatory relationships were deduced and 30 circRNARBP relationship pairs were analyzed at the protein level.On this basis,a circRNA-mediated regulatory network corresponding to the two levels of RNA-RNA and RNA-RBP was established.And then the roles of circRNA in HCM were analyzed through circRNA-mRNA,circRNA-miRNA,and circRNA-RBP,and the possible role in disease development mas inferred.
文摘The basic unit in life is cell.?It contains many protein molecules located at its different organelles. The growth and reproduction of a cell as well as most of its other biological functions are performed via these proteins. But proteins in different organelles or subcellular locations have different functions. Facing?the avalanche of protein sequences generated in the postgenomic age, we are challenged to develop high throughput tools for identifying the subcellular localization of proteins based on their sequence information alone. Although considerable efforts have been made in this regard, the problem is far apart from being solved yet. Most existing methods can be used to deal with single-location proteins only. Actually, proteins with multi-locations may have some special biological functions that are particularly important for drug targets. Using the ML-GKR (Multi-Label Gaussian Kernel Regression) method,?we developed a new predictor called “pLoc-mGpos” by in-depth extracting the key information from GO (Gene Ontology) into the Chou’s general PseAAC (Pseudo Amino Acid Composition)?for predicting the subcellular localization of Gram-positive bacterial proteins with both single and multiple location sites. Rigorous cross-validation on a same stringent benchmark dataset indicated that the proposed pLoc-mGpos predictor is remarkably superior to “iLoc-Gpos”, the state-of-the-art predictor for the same purpose.?To maximize the convenience of most experimental scientists, a user-friendly web-server for the new powerful predictor has been established at http://www.jci-bioinfo.cn/pLoc-mGpos/, by which users can easily get their desired results without the need to go through the complicated mathematics involved.
文摘A mobile molecular Doppler wind lidar （DWL） based on double-edge technique is presented for wind measurement at altitudes from 10 km to 40 km. A triple Fabry-Perot etalon is employed as a frequency discriminator to determine the Doppler shift proportional to the wind velocity. The lidar operates at 355 nm with a 45-cm aperture telescope and a matching azimuth-over-elevation scanner that can provide full hemispherical pointing. In order to guarantee the wind accuracy, different forms of calibration function of detectors in different count rates response range would be especially valuable. The accuracy of wind velocity iteration is improved greatly because of application of the calibration function of linearity at the ultra low light intensity especially at altitudes from 10 km to 40 km. The calibration functions of nonlinearity make the transmission of edge channel 1 and edge channel 2 increase 38.9% and 27.7% at about 1 M count rates, respectively. The dynamic range of wind field measurement may also be extended because of consideration of the response function of detectors in their all possible operating range.
文摘This study investigates the steam generating potential of a solar steam generation system and the potential for utility scale implementation in Libya oil for steam demanding enhanced oil recovery (EOR) methods. The proposed system uses parabolic troughs as solar collectors. The technology is proved to be technically feasible. Solar EOR should be seen as an add-on to existing plants due to the abundance of solar energy in Libya. The System Advisor Model (SAM) model system, developed by the National Office of Renewable Energy (NRE), was used to assess the plant’s active and economic performance.
