With the continuous rise of web threats and the increasing growth and adaptability of HTTP/3 and ongoing HTTP/2, identifying malicious web traffic through intrusion detection systems is crucial to ensure network secur...
详细信息
Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is *** security approaches are being constantly developed to protect against evolving *** ensem...
详细信息
Considering the recent developments in the digital environment,ensuring a higher level of security for networking systems is *** security approaches are being constantly developed to protect against evolving *** ensemble model for the intrusion classification system yielded promising results based on the knowledge of many prior *** research work aimed to create a more diverse and effective ensemble *** this end,selected six classification models,Logistic Regression(LR),Naive Bayes(NB),K-Nearest Neighbor(KNN),Decision Tree(DT),Support Vector Machine(SVM),and Random Forest(RF)from existing study to run as independent *** the individual models were trained,a Correlation-Based Diversity Matrix(CDM)was created by determining their *** models for the ensemble were chosen by the proposed Modified Minimization Approach for Model Subset Selection(Modified-MMS)from Lower triangular-CDM(L-CDM)as *** proposed algorithm performance was assessed using the Network Security Laboratory—Knowledge Discovery in Databases(NSL-KDD)dataset,and several performance metrics,including accuracy,precision,recall,and *** selecting a diverse set of models,the proposed system enhances the performance of an ensemble by reducing overfitting and increasing prediction *** proposed work achieved an impressive accuracy of 99.26%,using only two classification models in an ensemble,which surpasses the performance of a larger ensemble that employs six classification models.
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health withou...
详细信息
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health without premature treatment and cause *** the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observa-tion,which has become necessary to classify the type in cancer *** research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature *** paper introduces a Maximal Region-Based Candidate Feature Selection(MRCFS)for early risk diagnosing using Soft-Max Feed Forward Neural Classification(SMF2NC)to solve the above *** predictive model is based on a different relational feature learning model,which is possessed to candidate selection to reduce the *** redundant features are processed marginal weight rates for observing similar features’variants and the absolute *** neural hidden layers are trained using the Sigmoid Activation Function(SAF)to create the logical condition for feed-forward ***,the maximal features are introduced to invite a deep neural network con-structed on the Feed Forward Recurrent Neural Network(FFRNN).The classifier produces higher classification accuracy than the previous methods and observes the cancer detection,which is recommended for early diagnosis.
The 3D Underwater Sensor Network(USNs)has become the most optimistic medium for tracking and monitoring underwater *** and collision are two most critical factors in USNs for both sparse and dense *** to harsh ocean e...
详细信息
The 3D Underwater Sensor Network(USNs)has become the most optimistic medium for tracking and monitoring underwater *** and collision are two most critical factors in USNs for both sparse and dense *** to harsh ocean environment,it is a challenge to design a reliable energy efficient with collision free *** in link qualities may cause collision and frequent communication lead to energy loss;that effects the network *** overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing(FSE2R)is *** proposal’s key idea is based on computation of node distance from the sink,Residual Energy(RE)of each node and Signal to Interference Noise Ratio(SINR).The node distance from sink and RE is computed for reliable forwarder node selection and SINR is used for analysis of *** novel proposal compares with existing protocols like H2AB,DEEP,and E2LR to achieve Quality of Service(QoS)in terms of through-put,packet delivery ratio and energy *** comparative analysis shows that FSE2R gives on an average 30%less energy consumption,24.62%better PDR and 48.31%less end-to-end delay compared to other protocols.
In contemporary times, there has been a notable shift among youth and young adults towards prioritizing their health, encompassing both physical and mental well-being. Recognizing this trend, innovative solutions have...
详细信息
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of ...
详细信息
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage *** potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data *** creates a complex nature to increase the storage consumption under *** resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based Deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud ***,preprocessing is done using the sparse augmentation ***,the preprocessed files are segmented into blocks to make *** block of the contents is compared with other files through Semantic Content Source Deduplication(SCSD),which identifies the similar content presence between the *** on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a ***,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match *** implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.
Word spotting of Gujarati handwritten documents is a highly challenging task due to the complexity of the handwritten text in the Gujarati language. This paper presents a novel approach to word spotting, which include...
详细信息
A fruit valued for its great flavor, scent, and nutritional content;the mango (Mangifera indica L.) is one of the most significant tropical fruits in the world economically. However, several illnesses that compromise ...
详细信息
Social media has transformed into a prominent hub for cyberbullying, particularly impacting the younger demographic. The surge in social networking platforms has led to a corresponding increase in instances of online ...
详细信息
Circular RNAs(circRNAs)are RNAs with closed circular structure involved in many biological processes by key interactions with RNA binding proteins(RBPs).Existing methods for predicting these interactions have limitati...
详细信息
Circular RNAs(circRNAs)are RNAs with closed circular structure involved in many biological processes by key interactions with RNA binding proteins(RBPs).Existing methods for predicting these interactions have limitations in feature *** view of this,we propose a method named circ2CBA,which uses only sequence information of circRNAs to predict circRNA-RBP binding *** have constructed a data set which includes eight ***,circ2CBA encodes circRNA sequences using the one-hot ***,a two-layer convolutional neural network(CNN)is used to initially extract the *** CNN,circ2CBA uses a layer of bidirectional long and short-term memory network(BiLSTM)and the self-attention mechanism to learn the *** AUC value of circ2CBA reaches *** of circ2CBA with other three methods on our data set and an ablation experiment confirm that circ2CBA is an effective method to predict the binding sites between circRNAs and RBPs.
暂无评论