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Advancements in Liver Tumor detection:A Comprehensive review of Various deep Learning models

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Computer.m.deling in engineering & Sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan d.Anandan murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen deptartment of Artificial Intelligence and data Science Vardhaman College of EngineeringHyderabad501218India deptartment of CSE V.S.B College of EngineeringKarur639111India deptartment of Electrical and Electronics engineering Vardhaman College of EngineeringHyderabad501218India Centre for research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia department of Computer Science and engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia department of Computer Science and Information engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence recognition Industry Service research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

Gradient‑Layered mXene/Hollow Lignin Nanospheres Architecture design for Flexible and Stretchable Supercapacitors

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Nano-micro Letters 2025年第2期17卷 447-462页

作者： Haonan Zhang Cheng Hao Tongtong Fu dian Yu Jane Howe Kaiwen Chen Ning Yan Hao ren Huamin Zhai Jiangsu Provincial Key Lab of Sustainable Pulp and Paper Technology and Biomass materials NanJing Forestry UniversityNanjing 210037People’s Republic of China department of Chemical engineering and Applied Chemistry University of Toronto200 College StreetTorontoON M5S 3E5Canada department of materials Science and engineering University of Toronto184 College StreetTorontoON M5S 3E4Canada college of materials Science and engineering Nanjing Forestry UniversityNanjing 210037People’s Republic of China

With the rapid development of flexible wearable electronics,the demand for stretchable energy storage devices has *** this work,a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres(HLNPs)-intercalated two-dimensional transition metal carbide(Ti_(3)C_(2)T_(x) mXene)for fabricating highly stretchable and durable *** depositing and inserting HLNPs in the mXene layers with a bottom-up decreasing gradient,a multilayered porous mXene structure with smooth ion channels was constructed by reducing the overstacking of mXene ***,the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and mXene to improve ion and electron accessibility,thus better utilizing the pseudocapacitive property of *** these strategies effectively enhanced the capacitive performance of the *** addition,HLNPs,which acted as a protective phase for mXene layer,enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the *** electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600%uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm^(−2)(241 F g^(−1))and 514 mF cm^(−2)(95 F g^(−1)),***,their capacitances were well preserved after 1000 times of 600%stretch-release *** study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials.

关键词： Hollow lignin nanospheres mXene Gradient-layered architecture Wrinkled electrodes Stretchable supercapacitors

An Imbalanced dataset and Class Overlapping Classification model for Big data

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Computer Systems Science & engineering 2023年第2期44卷 1009-1024页

作者： mini Prince P.m.Joe Prathap department of Information Technology St.Peter’s College of Engineering and TechnologyChennai600054TamilnaduIndia department of Information Technology R.M.D Engineering CollegeChennai601206TamilnaduIndia

most modern technologies,such as social media,smart cities,and the internet of things(IoT),rely on big *** big data is used in the real-world applications,two data challenges such as class overlap and class imbalance *** dealing with large datasets,most traditional classiﬁers are stuck in the local optimum *** a result,it’s necessary to look into new methods for dealing with large data *** solutions have been proposed for overcoming this *** rapid growth of the available data threatens to limit the usefulness of many traditional *** such as oversampling and undersampling have shown great promises in addressing the issues of class *** all of these techniques,Synthetic minority Oversampling TechniquE(SmOTE)has produced the best results by generating synthetic samples for the minority class in creating a balanced *** issue is that their practical applicability is restricted to problems involving tens of thousands or lower instances of *** this paper,we have proposed a parallel mode method using SmOTE and mapreduce strategy,this distributes the operation of the algorithm among a group of computational nodes for addressing the aforementioned *** proposed solution has been divided into three ***ﬁrst stage involves the process of splitting the data into different blocks using a mapping function,followed by a pre-processing step for each mapping block that employs a hybrid SmOTE algo-rithm for solving the class imbalanced *** each map block,a decision tree model would be ***,the decision tree blocks would be com-bined for creating a classiﬁcation *** have used numerous datasets with up to 4 million instances in our experiments for testing the proposed scheme’s *** a result,the Hybrid SmOTE appears to have good scalability within the framework proposed,and it also cuts down the processing time.

关键词： Imbalanced dataset class overlapping SmOTE mapreduce parallel programming oversampling

modified mackenzie Equation and CVOA Algorithm reduces delay in UASN

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Computer Systems Science & engineering 2022年第5期41卷 829-847页

作者： r.Amirthavalli S.Thanga ramya N.r.Shanker department of Computer Science and engineering Velammal Engineering CollegeChennai66India department of Information Technology R.M.D Engineering CollegeTiruvallur1206India department of Computer Science and engineering Aalim Muhammed Salegh College of EngineeringChennai55India

In Underwater Acoustic Sensor Network(UASN),routing and propagation delay is affected in each node by various water column environmental factors such as temperature,salinity,depth,gases,divergent and rotational *** sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound *** dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN *** this paper,the modified mackenzie Sound equation calculates the sound velocity in each node for energy-efficient *** ratio Optimization method(GrOm)and Gaussian Process regression(GPr)predicts propagation delay of each node in UASN using temperature,salinity,depth,dissolved gases *** gases,rotational and divergent winds,and stress plays a major problem in UASN,which increases propagation delay and energy *** values from GPr and GrOm leads to node selection and Corona Virus Optimization Algorithm(CVOA)routing is performed on the selected *** proposed GPr-CVOA and GrOm-CVOA algorithm solves the problem of propagation delay and consumes less energy in nodes,based on appropriate tolerant delays in transmitting packets among nodes during high rotational and divergent *** simulation results,CVOA Algorithm performs better than traditional dF and LION algorithms.

关键词： Gaussian process regression(GPr) golden ratio optimization method(GrOm) corona virus optimization algorithm(CVOA) water column variation dissolved gases acoustic speed divergent wind rotational wind

A Novel Approach to design distribution Preserving Framework for Big data

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Intelligent Automation & Soft Computing 2023年第3期35卷 2789-2803页

In several fields like financial dealing,industry,business,medicine,et cetera,Big data(Bd)has been utilized extensively,which is nothing but a collection of a huge amount of ***,it is highly complicated along with time-consuming to process a massive amount of ***,to design the distribution Preserving Framework for Bd,a novel methodology has been proposed utilizing manhattan distance(md)-centered Partition Around medoid(md–PAm)along with Conjugate Gradient Artificial Neural Network(CG-ANN),which undergoes various steps to reduce the complications of ***,the data are processed in the pre-processing phase by mitigating the data repetition utilizing the map-reduce function;subsequently,the missing data are handled by substituting or by ignoring the missed *** that,the data are transmuted into a normalized ***,to enhance the classification performance,the data’s dimensionalities are minimized by employing Gaussian Kernel(GK)-Fisher discriminant Analysis(GK-FdA).Afterwards,the processed data is submitted to the partitioning phase after transmuting it into a structured *** the partition phase,by utilizing the md-PAm,the data are partitioned along with grouped into a ***,by employing CG-ANN,the data are classified in the classification phase so that the needed data can be effortlessly retrieved by the *** analogize the outcomes of the CG-ANN with the prevailing methodologies,the NSL-Kdd openly accessible datasets are *** experiential outcomes displayed that an efficient result along with a reduced computation cost was shown by the proposed *** proposed work outperforms well in terms of accuracy,sensitivity and specificity than the existing systems.

关键词： Big data artiﬁcial neural network ﬁsher discriminant analysis distribution preserving framework manhattan distance

SF-CNN: deep Text Classification and retrieval for Text documents

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Intelligent Automation & Soft Computing 2023年第2期35卷 1799-1813页

作者： r.Sarasu K.K.Thyagharajan N.r.Shanker Computer Science and engineering Dhanalaksmi College of EngineeringAnna UniversityChennaiIndia r.m.d engineering college Anna UniversityChennaiIndia Computer Science and engineering Aalim Muhammed Salegh College of EngineeringAnna UniversityChennaiIndia

researchers and scientists need rapid access to text documents such as research papers,source code and *** research documents are available on the Internet and need more time to retrieve exact documents based on *** efficient classification algorithm for retrieving documents based on keyword words is *** traditional algorithm performs less because it never considers words’polysemy and the relationship between bag-of-words in *** solve the above problem,Semantic Featured Convolution Neural Networks(SF-CNN)is proposed to obtain the key relationships among the searching keywords and build a structure for matching the words for retrieving correct text *** proposed SF-CNN is based on deep semantic-based bag-of-word representation for document *** deep learning methods such as Convolutional Neural Network and recurrent Neural Network never use semantic representation for *** experiment is performed with different document datasets for evaluating the performance of the proposed SF-CNN ***-CNN classifies the documents with an accuracy of 94%than the traditional algorithms.

关键词： Semantic classiﬁcation convolution neural networks semantic enhancement

Suicide Ideation detection of Covid Patients Using machine Learning Algorithm

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Computer Systems Science & engineering 2023年第4期45卷 247-261页

作者： r.Punithavathi S.Thenmozhi r.Jothilakshmi V.Ellappan Islam md Tahzib Ul m Kumarasamy college of engineering KarucrTamil NaduIndia dayananda Sagar college of engineering BangaloreKarnatakaIndia r.m.d engineering college KavaraipettaiTamil NaduIndia Adama Science and Technology University AdamaEthiopia dhaka International University DhakaBangaladesh

during Covid pandemic,many individuals are suffering from suicidal ideation in the *** distancing and quarantining,affects the patient *** computing is the study of recognizing human feelings and *** technology can be used effectively during pandemic for facial expression recognition which automatically extracts the features from the human *** system plays a very important role to detect the patient condition and to recognize the patterns of expression from the safest *** this paper,a new method is proposed for emotion recognition and suicide ideation detection in COVId *** helps to alert the nurse,when patient emotion is fear,cry or *** research presented in this paper has introduced Image Processing technology for emotional analysis of patients using machine learning *** proposed Convolution Neural Networks(CNN)architecture with dnCNN preprocessing enhances the performance of *** system can analyze the mood of patients either in real time or in the form of video files from CCTV *** proposed method accuracy is more when compared to other *** detects the chances of suicide attempt based on stress level and emotional recognition.

关键词： HOG ACO-CS optimizedKNN PCA emotion detection covid face recognition

High‑Entropy Electrode materials:Synthesis,Properties and Outlook

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Nano-micro Letters 2025年第1期17卷 472-506页

作者： dongxiao Li Chang Liu Shusheng Tao Jieming Cai Biao Zhong Jie Li Wentao deng Hongshuai Hou Guoqiang Zou Xiaobo Ji college of Chemistry and Chemical engineering Central South UniversityChangsha 410083People’s Republic of China School of Chemistry and Chemical engineering Hunan Institute of EngineeringXiangtan 411104People’s Republic of China

High-entropy materials represent a new category of high-performance materials,first proposed in 2004 and extensively investigated by researchers over the past two *** definition of high-entropy materials has continuously *** the last ten years,the discovery of an increasing number of high-entropy materials has led to significant advancements in their utilization in energy storage,electrocatalysis,and related domains,accompanied by a rise in techniques for fabricating high-entropy electrode ***,the research emphasis has shifted from solely improving the performance of high-entropy materials toward exploring their reaction mechanisms and adopting cleaner preparation ***,the current definition of high-entropy materials remains relatively vague,and the preparation method of high-entropy materials is based on the preparation method of single metal/low-or.m.dium-entropy *** should be noted that not all methods applicable to single metal/low-or.m.dium-entropy materials can be directly applied to high-entropy *** this review,the definition and development of high-entropy materials are briefly ***,the classification of high-entropy electrode materials is presented,followed by a discussion of their applications in energy storage and catalysis from the perspective of synthesis ***,an evaluation of the advantages and disadvantages of various synthesis methods in the production process of different high-entropy materials is provided,along with a proposal for potential future development directions for high-entropy materials.

关键词： High-entropy Energy storage Electrode materials

Haemoglobin measurement from Eye Anterior Ciliary Arteries through Borescope Camera

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Computer Systems Science & engineering 2023年第2期44卷 1763-1774页

作者： mohamed Abbas Ahamed Farook S.rukmanidevi N.r.Shanker department of Electronics and Communication engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering CollegeChennai600062India department of Electronics and Communication engineering R.M.D Engineering CollegeChennai601206India department of Computer Science and engineering Aalim Muhammed Salegh College of EngineeringChennai600055India

Nowadays,smartphones are used as self-health monitoring devices for ***-health monitoring devices help clinicians with big data for accurate diagnosis and guidance for treatment through repetitive *** measurement of haemoglobin requires for pregnant women,pediatric,pulmonary hypertension and obstetric *** haemoglobin measurement through conjunctiva leads to inaccurate *** inaccuracy is due to a decrease in the density of goblet cells and acinar units in meibomian glands in the human eye as age ***,conjunctivitis is a disease in the eye due to inﬂammation or infection at the *** is in the form of lines in the eyelid and covers the white part of the ***,small blood vessels in eye regions of conjunctiva inﬂammations are not visible to the human eye or standard *** paper proposes smartphone-based hae-moglobin(SBH)measurement through a borescope camera from anterior ciliary arteries of the eye for the above *** proposed SBH method acquires images from the anterior ciliary arteries region of the eye through a smartphone attached with a high megapixel borescope *** anterior ciliary arteries are projected through transverse dyadic wavelet transform(TdyWT)and applied with delta segmentation to obtain blood cells from the ciliary arteries of the ***,the Gaussian regression algorithm measures haemoglobin(Hb)with more accuracy based on the person,eye arteries,red pixel statistical parameters obtained from the left and right eye,age,and ***,the experimen-tal result of the proposed SBH method has an accuracy of 96%in haemoglobin measurement.

关键词： Hemoglobin measurement borescope camera smartphone anterior ciliary arteries region