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哈尔滨工业大学学报（英文版）
哈尔滨工业大学
哈尔滨工业大学学报（英文版）

哈尔滨工业大学

王树国

双月刊

1005-9113

hitxuebao_e@hit.edu.cn

0451-86403427

150001

哈尔滨市西大直街92号136信箱

哈尔滨工业大学学报（英文版）/Journal Journal of Harbin Institute of TechnologyEI
查看更多>>本刊是由哈尔滨工业大学主办的面向世界的自然科学与工程技术学术期刊（每年6期）。该期刊欢迎高质量的原创文章，主题主要集中在以下领域：航空航天，控制科学与工程，电子与通信工程，材料科学与工程，计算机科学，机器人技术，机械工程与自动化，能源科学和工程，电气工程等。
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    Size Effect on the Radiation Stability Silicon Dioxide Sphere Particles

    Vitaly NeshchimenkoChundong LiMikhail MikhailovJinpeng Lv...
    1-12页
    查看更多>>摘要：The effect of protons(E=100 keV,F=5×1015 cm-2)exposure on the diffuse reflectance spectra of the SiO2with different size particles in wavelength range from 250 to 2500 nm have been investigated.Particles were nanosphere,submicrosphere,microsphere and submacrosphere,as well as solid micro-and nanocrystals.The synthesis of the particles was carried out by the formation of silica shells and dissolution of the polystyrene core particles.The surface morphology,surface area and crystal structure of the particles have been investigated.When evaluating the changes of the solar absorptance,it was found that the radiation stability of the micro-and submacro-hollow particles is higher than that of the other nanostructured particles,except for solid microcrystals.The low radiation stability of the hollow microparticles is due to the large void inside the hollow particles where radiation defects are not formed.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Recognition and Anticipation of Diabetic Foot Ulcer in Type Ⅱ Diabetic Patients using Multi-layered Fuzzy Model

    Sai Surya Varshith NukalaJayashree JayaramanVijayashree JayaramanRishi Raghu...
    13-23页
    查看更多>>摘要：Diabetes mellitus is associated with foot ulcers,which frequently pave the way to lower-extremity amputation.Neuropathy,trauma,deformity,high plantar pressures,and peripheral vascular disease are the most common underlying causes.Around 15%of diabetic patients are affected by diabetic foot ulcer in their lifetime.64 million people are affected by diabetics in India and 40000 amputations are done every year.Foot ulcers are evaluated and classified in a systematic and thorough manner to assist in determining the best course of therapy.This paper proposes a novel model which predicts the threat of diabetic foot ulcer using independent agents for various input values and a combination of fuzzy expert systems.The proposed model uses a classification system to distinguish between each fuzzy framework and its parameters.Based on the severity levels necessary prevention,treatment,and medication are recommended.Combining the results of all the fuzzy frameworks derived from its constituent parameters,a risk-specific medication is recommended.The work also has higher accuracy when compared to other related models.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Video Recommendation System Using Machine-Learning Techniques

    Meesala SravaniCh VidyadhariS Anjali Devi
    24-33页
    查看更多>>摘要：In the realm of contemporary artificial intelligence,machine learning enables automation,allowing systems to naturally acquire and enhance their capabilities through learning.In this cycle,Video recommendation is finished by utilizing machine learning strategies.A suggestion framework is an interaction of data sifting framework,which is utilized to foresee the"rating"or"inclination"given by the different clients.The expectation depends on past evaluations,history,interest,IMDB rating,and so on.This can be carried out by utilizing collective and substance-based separating approaches which utilize the data given by the different clients,examine them,and afterward suggest the video that suits the client at that specific time.The required datasets for the video are taken from Grouplens.This recommender framework is executed by utilizing Python Programming Language.For building this video recommender framework,two calculations are utilized,for example,K-implies Clustering and KNN grouping.K-implies is one of the unaided AI calculations and the fundamental goal is to bunch comparable sort of information focuses together and discover the examples.For that K-implies searches for a steady'k'of bunches in a dataset.A group is an assortment of information focuses collected due to specific similitudes.K-Nearest Neighbor is an administered learning calculation utilized for characterization,with the given information;KNN can group new information by examination of the'k'number of the closest information focuses.The last qualities acquired are through bunching qualities and root mean squared mistake,by using this algorithm we can recommend videos more appropriately based on user previous records and ratings.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    The Impact of Heat Treatment and Surface Treatment on Thermal Conductivity of Heat Sinks Made of Aluminium Die Casting Alloys

    Rajesh Kumar ManickamDilip Raja Narayana
    34-41页
    查看更多>>摘要：This research contributes to understand the thermal management capabilities of Plate Fin Heat Sinks(PFHS)fabricated from AlSi10Mg.The uniqueness in this study is that the heat sinks were exposed to abrasive blasting,heat treatment,and graphene coating,and a full evaluation of the influence of the aforementioned treatments on the thermal management capacities of PFHS was found.Untreated PFHS is compared with 1)abrasive blasted and graphene coated heat sink,and 2)heat treated and graphene coated heat sink.To assess the thermal efficiency of the PFHS variants,a dedicated experimental set up was meticulously constructed.It is noteworthy that a junction temperature of 60℃was assumed as the reference point for the analysis.The results revealed that the charging cycle time which denotes the time required attaining the junction temperature,increased 1.3 times for the sample being abrasive-blasted at 0.5 MPa pressure and graphene-coated for 0.5 mm when the maximum heat input of 45 W is evaluated.When low heat input of 15 W is evaluated,the results revealed that there is no significant difference in charging cycle when compared to the untreated heat sink.The charging cycle time increased 2 times for the sample which is heat-treated at 450℃and graphene-coated for 0.5 mm at heat input of 15 W.This finding unequivocally underscores the heightened capacity of the heat treated and graphene coated PFHS made of AlSi10Mg to withstand elevated junction temperatures.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Enhancing Software Effort Estimation:A Hybrid Model Combining LSTM and Random Forest

    Badana MaheshMandava Kranthi Kiran
    42-51页
    查看更多>>摘要：Effort estimation plays a crucial role in software development projects,aiding in resource allocation,project planning,and risk management.Traditional estimation techniques often struggle to provide accurate estimates due to the complex nature of software projects.In recent years,machine learning approaches have shown promise in improving the accuracy of effort estimation models.This study proposes a hybrid model that combines Long Short-Term Memory(LSTM)and Random Forest(RF)algorithms to enhance software effort estimation.The proposed hybrid model takes advantage of the strengths of both LSTM and RF algorithms.To evaluate the performance of the hybrid model,an extensive set of software development projects is used as the experimental dataset.The experimental results demonstrate that the proposed hybrid model outperforms traditional estimation techniques in terms of accuracy and reliability.The integration of LSTM and RF enables the model to efficiently capture temporal dependencies and non-linear interactions in the software development data.The hybrid model enhances estimation accuracy,enabling project managers and stakeholders to make more precise predictions of effort needed for upcoming software projects.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Optimizing Spatial Pattern Analysis in Serial Remote Sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

    J SrinivasanS UmaSaleem Raja Abdul SamadJayabrabu Ramakrishnan...
    52-60页
    查看更多>>摘要：Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Thermodynamic Analysis and Optimization of Flat Plate Solar Collector Using TiO2/Water Nanofluid

    Firas F.QaderFalah Z.MohammedBarhm Mohamad
    61-73页
    查看更多>>摘要：To research solar energy's efficiency and environmental benefits,the thermal efficiency,exergy,and entropy of solar collectors were calculated.The experiment involved two glass-topped collectors,fluid transfer tubes,and aluminum heat-absorbing plates.Glass wool insulation minimized heat loss.A 0.5%TiO2/Water nanofluid was created using a mechanical and ultrasonic stirrer.Results showed that solar radiation increased thermal efficiency until midday,reaching 48.48%for water and 51.23%for the nanofluid.With increasing mass flow rates from 0.0045 kg/s to 0.02 kg/s,thermal efficiency improved from 16.26%to 47.37%for water and from 20.65%to 48.76%for the nanofluid.Filtered water provided 380 W and 395 W of energy in March and April,while the nanofluid increased it to 395 W and 415 W during these months.Mass flow generated energy,and the Reynolds number raised entropy.The noon exergy efficiency for nanofluids was 50%-55%,compared to 30%for water.At noon,the broken exergy measured 877.53 W for the nanofluid and 880.12 W for water.In Kirkuk,Iraq,the 0.5%TiO2/Water nanofluid outperformed water in solar collectors.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Predictive Modeling of Sedentary Behavior Patterns in Adults Using Stacked LSTM

    P Sanju
    74-84页
    查看更多>>摘要：A new health concern in recent periods has seen the evolution of uncertain sedentary behavior.Remaining sedentary for extended durations is regarded as a notable hazard across various adult age brackets,especially the excessive dependence on automobiles for transportation.Throughout the active period,monitoring seating habits has been made easier by sensors.Nevertheless,there exists a disagreement among professionals regarding the most suitable quantifiable criteria for encompassing the comprehensive data on sedentary behavior throughout the day.Owing to variations in measurement methodologies,data analysis approaches,and the lack of essential outcome indicators such as the total sedentary duration,the assessment of sedentary patterns in numerous research investigations was considered unfeasible.The research suggested fleeting granularity distinguish occurrences of regular human activities.Sophisticated units(essential cells)acquire multivariate transitory information.Frequent Behavior Patterns(FBPs)can be identified with a estimation of timeframe using our proposed scalable algorithms that employ collected widespread multivariate data(fleeting granularity).The research outcome,supported by rigorous analyses on two validated datasets,mark a significant progression.In the final stages of the study,a stacked Long Short-Term Memory(LSTM)model was utilized to replicate and forecast repetitive sedentary behavior patterns,leveraging data from the preceding six-hour window blocks of sedentary activity.The model effectively replicated state traits,previous action sequences,and duration,attaining an impressive 99%accuracy level as assessed through RMSE,MSE,MAPE,and r-correlation metrics.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
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    Systematic Review on Critical Factors and Their Optimization for Solar Cell Performance Enhancement

    Nidhi ShuklaSatish Kumar
    85-98页
    查看更多>>摘要：Solar cells and other renewable energy sources are crucial in today's world where sustainability and environmental consciousness is at peak.Because of this,creating the optimal capacity is a fair aim for the operators of such technologies.The transformation of solar energy into either electricity by means of photovoltaics or into useable fuel by means of photo electrochemical cells remained a primary objective for research organizations and development sectors.In this piece,we will take a look back at the history of solar cells and examine their progression through the generations.The significant aspects which have an impact on the solar cells'performance are also discussed.This article provides a comprehensive and in-depth overview of the important aspects that affect the solar cells'performance,as well as a discussion of the application of bio-inspired optimization algorithms to improve the parameters of solar cells.Reviewing critical factors and their optimization for solar cell performance enhancement is crucial.It helps identify key performance factors,understand limitations,and challenges,and identify effective optimization strategies.By evaluating trade-offs and synergies,it guides future research and informs industrial applications,leading to more efficient and sustainable solar cell technologies.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

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