Software Defect Prediction Using Hybrid Machine Learning Techniques: A Comparative Study

When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect prediction is elaborated through an innovative hybrid machine learning framework. The proposed technique combines an advanced deep neural network architecture with ensemble models such as Support Vector Machine (SVM), Random Forest (RF), and XGBoost. The study evaluates the performance by considering multiple software projects like CM1, JM1, KC1, and PC1 using datasets from the PROMISE Software Engineering Repository. The three hybrid models that are compared are Hybrid Model-1 (SVM, RandomForest, XGBoost, Neural Network), Hybrid Model-2 (GradientBoosting, DecisionTree, LogisticRegression, Neural Network), and Hybrid Model-3 (KNeighbors, GaussianNB, Support Vector Classification (SVC), Neural Network), and the Hybrid Model 3 surpasses the others in terms of recall, F1-score, accuracy, ROC AUC, and precision. The presented work offers valuable insights into the effectiveness of hybrid techniques for cross-project defect prediction, providing a comparative perspective on early defect identification and mitigation strategies. .

A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

Recently,researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems(HPCs)to achieve exascale by applying parallelism at multiple levels.Combining different programming paradigms,such as Message Passing Interface(MPI),Open Multiple Processing(OpenMP),and Open Accelerators(OpenACC),can increase computation speed and improve performance.During the integration of multiple models,the probability of runtime errors increases,making their detection difficult,especially in the absence of testing techniques that can detect these errors.Numerous studies have been conducted to identify these errors,but no technique exists for detecting errors in three-level programming models.Despite the increasing research that integrates the three programming models,MPI,OpenMP,and OpenACC,a testing technology to detect runtime errors,such as deadlocks and race conditions,which can arise from this integration has not been developed.Therefore,this paper begins with a definition and explanation of runtime errors that result fromintegrating the three programming models that compilers cannot detect.For the first time,this paper presents a classification of operational errors that can result from the integration of the three models.This paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++programming language that uses the triple programming models MPI,OpenMP,and OpenACC.This hybrid technology combines static technology and dynamic technology,given that some errors can be detected using static techniques,whereas others can be detected using dynamic technology.The hybrid technique can detect more errors because it combines two distinct technologies.The proposed static technology detects a wide range of error types in less time,whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC,2023,vol.74,no.2 operating environment are left to the dynamic technology,which completes the validation.

High-yielding Seed Production Techniques of Disease-resistant and High-quality Hybrid Rice Sterile Line Rong 18A

Rong 18A, bred by Crop Research Institute, Chengdu Academy of Agri- culture and Forestry Sciences is a new blast-highly resistant and high-combining ability hybrid rice sterile line. It is currently one of the male sterile lines in Sichuan Province which combine well high grain quality and rice blast resistance. More than 20 combinations of Rong 18A have passed the national and provincial variety iden- tification. Combined with the climate conditions in Chengdu, the key points of high- yielding seed production techniques for Rong18A are analyzed and summarized in this paper.

High-yielding Seed Production Techniques and Characteristics of Hybrid Rice Yanliangyou 888

According to seed production of Yanliangyou 888, a two-line hybrid rice variety, the research reviewed seed production characters, as follows： to improve outcrossing rate and spike size provided sufficient spikes of female/male parents. The seed production techniques include scientific arrangement of seeding interval, cultivating strong multi-tiller seedlings, scientific arrangement of row ratio of inter- cropping with adequate basic seedlings, scientific water and fertilizer management, improving outcrossing rate by synthesis measures, disease/insect control, and rein- forcing production management.

Seed Production Techniques of Two-line Indica Hybrid Rice Yanliangyou 2208

Yanliangyou 2208, bred by the Jiangsu Institute of Agricultural Sciences in Coastal Areas, is a two-line indica hybrid rice combination characterized with strong heterosis, moderate maturity, wide adaptability, good stability and disease resistance. It was identified as a new variety by the National Crop Variety Approval Committee in 2013. According to the characteristics of parents of Yanliangyou 2208 and com- bined with many years of seed production experience, high-yielding seed production techniques of Yanliangyou 2208 are summed up in this paper.

Performance and Cultivation Techniques of a Promising Super Hybrid Rice Combination Chaoyou 1000 in High-latitude Area

The performance and cultivation techniques of Chaoyou 1000 in Junan County, Shandong Province were summed up.

Hybrid Model Testing Technique for Deep-Sea Platforms Based on Equivalent Water Depth Truncation

In this paper, an inner turret moored FPSO which works in the water of 320 m depth, is selected to study the socalled ＂passively-truncated ＋ numerical-simulation＂ type of hybrid model testing technique while the tnmcated water depth is 160 m and the model scale ）, = 80. During the investigation, the optimization design of the equivalent-depth truncated system is performed by using the similarity of the static characteristics between the truncated system and the full depth one as the objective function. According to the truncated system, the corresponding physical test model is made. By adopting the coupling time domain simulation method, the tnmcated system model test is numerically reconstructed to carefully verify the computer simulation software and to adjust the corresponding hydrodynamic parameters. Based on the above work, the numerical extrapolation to the full depth system is performed by using the verified computer software and the adjusted hydrodyrmmic parameters. The full depth system model test is then performed in the basin and the results are compared with those from the numerical extrapolation. At last, the implementation procedure and the key technique of the hybrid model testing of the deep-sea platforms are summarized and printed. Through the above investigations, some beneficial conclusions are presented.

Enhancing rock fragmentation prediction in mining operations:A hybrid GWO-RF model with SHAP interpretability

In the mining industry,precise forecasting of rock fragmentation is critical for optimising blasting processes.In this study,we address the challenge of enhancing rock fragmentation assessment by developing a novel hybrid predictive model named GWO-RF.This model combines the grey wolf optimization(GWO)algorithm with the random forest(RF)technique to predict the D_(80)value,a critical parameter in evaluating rock fragmentation quality.The study is conducted using a dataset from Sarcheshmeh Copper Mine,employing six different swarm sizes for the GWO-RF hybrid model construction.The GWO-RF model’s hyperparameters are systematically optimized within established bounds,and its performance is rigorously evaluated using multiple evaluation metrics.The results show that the GWO-RF hybrid model has higher predictive skills,exceeding traditional models in terms of accuracy.Furthermore,the interpretability of the GWO-RF model is enhanced through the utilization of SHapley Additive exPlanations(SHAP)values.The insights gained from this research contribute to optimizing blasting operations and rock fragmentation outcomes in the mining industry.

Substructure hybrid testing of reinforced concrete shear wall structure using a domain overlapping technique

An online hybrid test was carried out on a 40-story 120-m high concrete shear wall structure. The structure was divided into two substructures whereby a physical model of the bottom three stories was tested in the laboratory and the upper 37 stories were simulated numerically using ABAQUS. An overlapping domain method was employed for the bottom three stories to ensure the validity of the boundary conditions of the superstructure. Mixed control was adopted in the test. Displacement control was used to apply the horizontal displacement, while two controlled force actuators were applied to simulate the overturning moment, which is very large and cannot be ignored in the substructure hybrid test of high-rise buildings. A series of tests with earthquake sources of sequentially increasing intensities were carried out. The test results indicate that the proposed hybrid test method is a solution to reproduce the seismic response of high-rise concrete shear wall buildings. The seismic performance of the tested precast high-rise building satisfies the requirements of the Chinese seismic design code.

Optimization of Friction and Wear Behaviour in Hybrid Metal Matrix Composites Using Taguchi Technique

Al-7075 alloy-base matrix, reinforced with mixtures of silicon carbide (SiC) and boron carbide (B4C) particles, know as hybrid composites have been fabricated by stir casting technique (liquid metallurgy route) and optimized at different parameters like sliding speed, applied load, sliding time, and percentage of reinforcement by Taguchi method. The specimens were examined by Rockwell hardness test machine, Pin on Disc, Scanning Electron Microscope (SEM) and Optical Microscope. A plan of experiment generated through Taguchi’s technique is used to conduct experiments based on L27 orthogonal array. The developed ANOVA and the regression equations were used to find the optimum wear as well as co-efficient of friction under the influence of sliding speed, applied load, sliding time and percentage of reinforcement. The dry sliding wear resistance was analyzed on the basis of “smaller the best”. Finally, confirmation tests were carried out to verify the experimental results.

Seed Production Techniques for a New Two-line Hybrid Rice Combination, Benliangyou 3113

According to seed production practice, the seed production techniques for BenIiangyou 3113, a new two-Iine hybrid rice combination, were summarized. In or-der to obtaln high and stabIe yielding, the seed production of BenIiangyou 3113 re-quires appropriate site seIection, rational sowing period, rational ratio between parental Iines, enhanced water and fertiIizer management, appropriate Ieaf cutting, strict weeding, good artificial poI ination and good pests and diseases controI.

Hybrid Security Techniques for Internet of Things Healthcare Applications

The Internet of Things (IoT) describes the future where every day physical objects will be connected to the internet and be able to identify themselves to other devices. IoT is a new revolution of the Internet and It will effect in a large number of applications such as smart living, smart home, healthcare systems, smart manufacturing, environment monitoring, and smart logistics. This paper provides integration, summarizes and surveys some of the security techniques especially hybrid techniques that can be applied with healthcare applications in IoT environment.

A Triple-Channel Encrypted Hybrid Fusion Technique to Improve Security of Medical Images

Assuring medical images protection and robustness is a compulsory necessity nowadays.In this paper,a novel technique is proposed that fuses the wavelet-induced multi-resolution decomposition of the Discrete Wavelet Transform(DWT)with the energy compaction of the Discrete Wavelet Transform(DCT).The multi-level Encryption-based Hybrid Fusion Technique(EbhFT)aims to achieve great advances in terms of imperceptibility and security of medical images.A DWT disintegrated sub-band of a cover image is reformed simultaneously using the DCT transform.Afterwards,a 64-bit hex key is employed to encrypt the host image as well as participate in the second key creation process to encode the watermark.Lastly,a PN-sequence key is formed along with a supplementary key in the third layer of the EbHFT.Thus,the watermarked image is generated by enclosing both keys into DWT and DCT coefficients.The fusions ability of the proposed EbHFT technique makes the best use of the distinct privileges of using both DWT and DCT methods.In order to validate the proposed technique,a standard dataset of medical images is used.Simulation results show higher performance of the visual quality(i.e.,57.65)for the watermarked forms of all types of medical images.In addition,EbHFT robustness outperforms an existing scheme tested for the same dataset in terms of Normalized Correlation(NC).Finally,extra protection for digital images from against illegal replicating and unapproved tampering using the proposed technique.

Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis:Evidence from Shimla district of North-west Indian Himalayan region

The Indian Himalayan region is frequently experiencing climate change-induced landslides.Thus,landslide susceptibility assessment assumes greater significance for lessening the impact of a landslide hazard.This paper makes an attempt to assess landslide susceptibility in Shimla district of the northwest Indian Himalayan region.It examined the effectiveness of random forest(RF),multilayer perceptron(MLP),sequential minimal optimization regression(SMOreg)and bagging ensemble(B-RF,BSMOreg,B-MLP)models.A landslide inventory map comprising 1052 locations of past landslide occurrences was classified into training(70%)and testing(30%)datasets.The site-specific influencing factors were selected by employing a multicollinearity test.The relationship between past landslide occurrences and influencing factors was established using the frequency ratio method.The effectiveness of machine learning models was verified through performance assessors.The landslide susceptibility maps were validated by the area under the receiver operating characteristic curves(ROC-AUC),accuracy,precision,recall and F1-score.The key performance metrics and map validation demonstrated that the BRF model(correlation coefficient:0.988,mean absolute error:0.010,root mean square error:0.058,relative absolute error:2.964,ROC-AUC:0.947,accuracy:0.778,precision:0.819,recall:0.917 and F-1 score:0.865)outperformed the single classifiers and other bagging ensemble models for landslide susceptibility.The results show that the largest area was found under the very high susceptibility zone(33.87%),followed by the low(27.30%),high(20.68%)and moderate(18.16%)susceptibility zones.The factors,namely average annual rainfall,slope,lithology,soil texture and earthquake magnitude have been identified as the influencing factors for very high landslide susceptibility.Soil texture,lineament density and elevation have been attributed to high and moderate susceptibility.Thus,the study calls for devising suitable landslide mitigation measures in the study area.Structural measures,an immediate response system,community participation and coordination among stakeholders may help lessen the detrimental impact of landslides.The findings from this study could aid decision-makers in mitigating future catastrophes and devising suitable strategies in other geographical regions with similar geological characteristics.

Pollination Methods and Embryo Rescue Techniques of Hybridization between Lilium Oriental Hybrids

The pollination methods and embryo rescue techniques of hybridization between I.ilium Oriental hybrids were studied in this paper. The results showed that ： （ 1 ） in the combination of ＇ Justina＇ x ＇ Shala＇, pollen tubes were observed to grow downward in styles and target to ovules in ovaries when normal sti^na 13o1- lination method was used; pollen tubes were found to grow directionless to a different degree at stylar cuts and in ovaries when cut-style pollination method was used; the longer the styles were left, the more pollen tubes toward to ovules were observed and more plump seeds were produced; the maximum plump seeds were obtained via normal stigma pollination. （2） Hybridization experiments were performed for the 56 combinations of Lilium Oriental hybrids with normal stigma pollina- tion, and one combination generated no plump ovule and three combinations generated fewer than 10 plump ovules while the other 52 combinations generated plenty of plump ovules, which preliminarily indicated that normal stigma pollination method could be used as an universal pollination technique for hybridization between Lilium Oriental hybrids. The experiment results of different embryo rescue techniques showed that using cut-ovule inoculation about 70 d after pollination had a fas- ter germination speed and a higher germination rate of hybrid embryo than normal ovule inoculation, and embryo rescue efficiency of the former method was obviously higher than ＂embryo isolated inoculation＂ on 40 d after pollination. The research suggested that ＂cut-ovule inoculation＂ about 70 d after pollination could be regarded as an universal embryo rescue technique for hybridization between Lilium Oriental hybrids.

High-yield Production Techniques of High-quality and Early Maturity Hybrid Rice Xiangzaoyou 2017

Xiangzaoyou 2017 is an excellent early maturing variety bred from the combination of Neixiang 3A and the self-fertile restorer QN 2017 by Qiannan Institute of Agricultural Sciences of Guizhou Province,and it has been approved by the Guizhou Crop Variety Approval Committee( Approval No.: Qianshendao 2006001).In order to promote its application in production,the research on the seed production techniques of Xiangzaoyou 2017 was carried out,and the key technical points of high-yield seed production of Xiangzaoyou 2017 were put forward.

USING Hybrid Adaptive Techniques to Reduce Multipath Effects in S-PCN Mobile Terminals

Multipath signal processing is a promising technique for increasing the capacity of downlink frequency of satellite communication networks (S-PCN). The paper presents an approach to processing and reducing multipath signals received from S-PCN typified of mobile terminal users in clustered or mountainous environment. Use of hybrid linear adaptive antenna array technique and adaptive filtering technique provides improved performance by eliminating uncorrelated signal residing in antenna sidelobes.

Detection of Behavioral Patterns Employing a Hybrid Approach of Computational Techniques

As far as the present state is concerned in detecting the behavioral pattern of humans(subject)using morphological image processing,a considerable portion of the study has been conducted utilizing frontal vision data of human faces.The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach.In this example,hybridization includes an artificial neural network(ANN)with a genetic algorithm(GA).We researched the geometrical properties extracted from side-vision human-face data.An additional study was conducted to determine the ideal number of geometrical characteristics to pick while clustering.The close vicinity ofminimum distance measurements is done for these clusters,mapped for proper classification and decision process of behavioral pattern.To identify the data acquired,support vector machines and artificial neural networks are utilized.A method known as an adaptiveunidirectional associative memory(AUTAM)was used to map one side of a human face to the other side of the same subject.The behavioral pattern has been detected based on two-class problem classification,and the decision process has been done using a genetic algorithm with best-fit measurements.The developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET,Multi-PIE,Yale Face database,RTR,CASIA,etc.The complexity measures have also been calculated under worst-case and best-case situations.

Characteristics of Early-maturing Hybrid Rice Anyou 08 and Its Cultivation Technique

Anyou 08 is an early-maturing hybrid rice variety bred by crossing high- quality resistant sterile line Anfeng A as female parent with high-combining ability restoring line QN2058 as male parent. Its average yield in regional trail in Guizhou Province in 2009-2010 reached 9.11t/hm^2, which was higher than control by 11.31%. Anyou 08 shows good comprehensive traits of population. It is suitable for high cold mountainous areas and middle-early maturing rice areas.

Performance and High-Yield Cultural Techniques of Two-Line Hybrid Rice Xinlingyou998 at Direct Seeding Cultivation

Xinliangyou 998 is a new indica two-line hybrid rice variety using Xin＇er Sx H0998 as parent. The variety was introduced and demonstrated in Yingshan County in 2016, and showed intermediate growth duration, strong tillering ability, firm culm, tolerance to high fertility and resistance to lodging, tolerance to high tempera- ture and wide range of adaptation, etc. The high-yield cultural techniques were con- cluded.