A Hybrid Feature Selection Framework for Predicting Students Performance

Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions,for the improvement of quality of education and to meet the dynamic needs of society.The selection of features for student’s performance prediction not only plays significant role in increasing prediction accuracy,but also helps in building the strategic plans for the improvement of students’academic performance.There are different feature selection algorithms for predicting the performance of students,however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal features.In this paper,a hybrid feature selection framework(using feature-fusion)is designed to identify the significant features and associated features with target class,to predict the performance of students.The main goal of the proposed hybrid feature selection is not only to improve the prediction accuracy,but also to identify optimal features for building productive strategies for the improvement in students’academic performance.The key difference between proposed hybrid feature selection framework and existing hybrid feature selection framework,is two level feature fusion technique,with the utilization of cosine-based fusion.Whereas,according to the results reported in existing literature,cosine similarity is considered as the best similarity measure among existing similarity measures.The proposed hybrid feature selection is validated on four benchmark datasets with variations in number of features and number of instances.The validated results confirm that the proposed hybrid feature selection framework performs better than the existing hybrid feature selection framework,existing feature selection algorithms in terms of accuracy,f-measure,recall,and precision.Results reported in presented paper show that the proposed approach gives more than 90%accuracy on benchmark dataset that is better than the results of existing approach.

Relationship Between Plant Type and Grain Quality of Japonica Hybrid Rice in Northern China

Plant type and grain quality are two major aspects in rice breeding. Using canonical correlation analysis and canonical redundancy analysis, the relationship between plant type traits and rice grain quality traits was studied with 100 crosses derived from 10 sterile lines × 10 restorer lines. There was a complex relationship between parts of the traits of the two aspects. The angle of the 2nd leaf from the top and single panicle weight played important roles in plant type system and amylose content and grain length in grain quality system. The angle of the 2nd leaf from the top, plant height and single panicle weight had a great effect on grain quality traits, and amylose content, brown rice rate and translucency were easily influenced by plant type traits. Selection index model indicated that japonica hybrid rice in Northern China with good quality was characterized by broad flag leaf and 2nd leaf from the top, narrow and short 3rd leaf from the top, low plant height, short culm, long and more panicles and low single panicle weight.

Sex-specific life-history trait expression in hybrids of a cave- and surface-dwelling fish (Poecilia mexicana, Poecilidae)

Evaluating the fitness of hybrids can provide important insights into genetic differences between species or diverging populations.We focused on surface-and cave-ecotypes of the widespread Atlantic molly Poecilia mexicana and raised F1 hybrids of reciprocal crosses to sexual maturity in a common-garden experiment.Hybrids were reared in a fully factorial 2 x 2 design consisting of lighting(light vs.darkness)and resource availability(high vs.low food).We quantified survival,ability to realize their full reproductive potential(i.e.,completed maturation for males and 3 consecutive births for females)and essential life-history traits.Compared to the performance of pure cave and surface fish from a previous experiment,F1s had the highest death rate and the lowest proportion of fish that reached their full reproductive potential.We also uncovered an intriguing pattern of sex-specific phenotype expression,because male hybrids expressed cave molly life histories,while female hybrids expressed surface molly life histories.Our results provide evidence for strong selection against hybrids in the cave molly system,but also sug-gest a complex pattern of sex-specific(opposing)dominance,with certain surface molly genes being dominant in female hybrids and certain cavemollygenes beingdominant in malehybrids.

Enhancing physical-layer security via big-data-aided hybrid relay selection

The explosive growth in data trac presents new challenges to the new generation of wireless communication systems,such as computing capabilities,spectrum eciency and security.In this paper,we use the network structure,which is adaptable for the big data trac,to improve the security of wireless networks.Speci cally,a big-data aided hybrid relay selection scheme is designed and analyzed to enhance physical layer security.First,considering the ideal situation that an eavesdropper's CSI(Channel State Information)is known to the legal nodes,we propose an optimal hybrid relay selection scheme consisting of the optimal mode selection scheme and the optimal relay selection scheme.In this case,we analyze the upper bound of an eavesdropper's capacity in FD(Full-Duplex)mode and the secrecy outage probabilities of the optimal HD(Half-Duplex),FD,and hybrid relay selection schemes.Through the analysis of data,it is clear that the mode selection is decided by the self-interference of the FD technique.However,the instantaneous CSI of an eavesdropper is dicult to obtain due to the passive characteristic of eavesdroppers in practice.Therefore,a more practical hybrid relay selection scheme with only the channel distribution information of an eavesdropper is further studied,where a weighting factor is employed to guarantee that the hybrid mode is no worse than either the FD mode or HD mode when the self-interference grows.Finally,the simulation results show the improved security of our proposed scheme.