Genetic algorithm based feature selection with ensemble methods for student academic performance prediction

Student academic performance is an important factor that affect the achievement of an educational institution. Educational Data Mining (EDM) is a data mining process that is applied to explore educational data that can produce information related to student academic performance. The knowledge produced from the data mining process is used by the educational institutions to improve their teaching processes, which aim to improve student academic performance results. In this paper, a method based on Genetic Algorithm (GA) feature selection technique with classification method is proposed in order to predict student academic performance. Almost all previous feature selection techniques apply local search technique throughout the process, so the optimal solution is quite difficult to achieve. Therefore, GA is apply as a technique of features selection with ensemble classification method in order to improve classification accuracy value of student academic performance prediction, as well as it can be used for datasets with high dimensional and imbalanced class. In this paper, the data used for experiments comes from Kaggle repository datasets which consists of three main categories: behaviour, academic, and demographic. The performances evaluation used to evaluate the proposed method is the Area Under the Curve (AUC). Based on the results obtained from the experiments, shows that the proposed method makes an impressive result in the predictions of student academic performance

On Relative Convex Sequences

In this paper, we introduce the concept of relative convex sequences and establish their fundamental properties, highlighting their similarities to those of convex sequences. Additionally, we prove new inequalities of the Lupas and Hermite-Hadamard-Fej\'er type for relative convex sequences. In certain cases, and as an application, we show how the concept of relative convexity can facilitate the derivation of new inequalities for convex sequences.Comment: 12 page

Alfalfa and Its Symbiosis Responses to Osmotic Stress

Alfalfa (Medicago sativa L.) is one of the most cultivated forage legumes in Morocco thanks to its great adaptation to the climatic conditions of this country, its high protein content and its ability to fix atmospheric nitrogen in symbiosis with rhizobia. Environmental stresses such as drought and salinity constitute a major factor limiting the symbiotic nitrogen fixation and legume productivity. In the last decades, this process has interested scholars in understanding the implication of these strains in legume stress tolerance in order to make these symbioses more efficient under difficult conditions. Seed osmopriming is a great technique in the amelioration of seed germination and seedlings growth in responses to several abiotic stress conditions. In this chapter, the effects of water deficit on the Moroccan alfalfa populations and their symbiotic association with rhizobia were discussed. Besides, osmopriming could make these symbioses more efficient especially under stress conditions

Removal of RR-23 dye from industrial textile wastewater by adsorption on cistus ladaniferus seeds and their biochar

The use of low-cost, easily obtained and eco-friendly adsorbents has been employed as an ideal alternative for the methods of removing dyes from wastewater. Cistus ladaniferus seeds (CLS) and their biochar (BCCLS) are the biomaterials used as a bio-adsorbent for removing of Reactive red 23 (RR-23). The bio-char of cistus seed is prepared by a thermo-chemical route known as pyrolysis under optimum conditions, temperature equal to 450 °C, heating rate 21 °C.min-1 and particle sizes of 0.3 to 0.6 mm after the BCCLS is grinded with a ceramic grinder until the particle size is between 0.1 and 0.2 mm. The kinetics adsorption of dye by CLS and BCCLS are correctly described by the pseudo-2nd-order model with a correlation factor (R2 = 0.997) and (R2 = 0.998) respectively. As for the modeling of the adsorption isotherm, among the four models tested, Lungmuir type II and type I is most appropriate with a correlation factor equal to 0.999 and 0.98 for the BCCLS and the CLS respectively. On the other hand, the ability to remove the dye by the BCCLS is advantageous and the elimination efficiency reaches a maximum value of 99.237% for the BCCLS and 82% for the CLS. Keywords: Biochar, Isotherm, Adsorption, Cistus Seed, pyrolysis, Technical analysis

Modified Chitosan Immobilized on Modified Sand for Industrial Wastewater Treatment in Multicomponent Sorption: Shrimp Biowaste Processing

In this paper, modified chitosan immobilized on modified sand (MCs/MS) was synthesized and characterized by infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscope (SEM) and energy dispersive X-ray analysis (EDXA). MCs/MS composite was used to remove Reactive Red 23 (RR23), Reactive Blue 19 (RB19) and Iron III (Fe3+) in three single-component and three binary, RR23+RB19, RR23+Fe3+ and RB19+Fe3+. Batch experiments were carried out for adsorption kinetics, isotherms and thermodynamics. Operational parameters studied were pH, contact time, temperature, adsorbate and adsorbent concentrations. Adsorption kinetics in single and binary systems of components followed pseudo- second-order kinetics model. The isotherm data in single and binary systems followed Freundlich isotherm model. Thermodynamic parameters have disclosed that the adsorption is exothermic and not spontaneous with a physical adsorption for both single and binary systems. The results showed that MCs/MS composite was an effective adsorbent to remove hazardous pollutants with a removal rate between 80% and 99.6%, the optimal contact time was between 120 and 180 min for all components in single and multicomponent system. Keywords : Modified chitosan immobilized on modified sand, Multicomponent system, Reactive Red 23, Reactive Blue 19, Iron III, Hydrothermo-Chemical method

Profiling the Volatile and Non-Volatile Compounds along with the Antioxidant Properties of Malted Barley

In this work, the stability of antioxidant compounds in malting barley seeds before and after the production of the final products is reported. In this reflection, the findings revealed that the process of fermentation had a significant impact on antioxidant activity. In vitro, antioxidant capacities were evaluated using DPPH free radical scavenging assay. The results obtained from the spectrophotometric analysis showed that the lowest inhibition value was observed in the samples that were obtained by the classical fermentation process (ABC) and the samples of non-alcoholic beer obtained by the thermal process (NABT), with free radical inhibition capacity values of 8.50% and 5.50%, respectively. The samples of hopped wort (HW) and malted barley seeds extract (BSE) showed very high antioxidant activity with free radical inhibition capacity of 14% and 12.60%, respectively. The obtained extracts were analyzed by gas chromatography and high-performance liquid chromatography, both combined with mass spectrometry detection (GC-MS, HPLC-MS). GC-MS analysis of the SPME extraction showed the presence of 29 compounds with isopentyl alcohol in major concentration (18.19%) in the alcoholic beer; on the other hand, the HPLC-DAD-ESI/MS analysis of the ethyl acetate extract showed the presence of 13 phenolic compounds. Interestingly, the degradation of 3-Hydroxyphloretin 2'-O-glucoside in the final products of the non-alcoholic beers was found. Finally, the FTIR analysis was also employed in order to detect the type of efficient groups present in the extracts

Rationale and design of SAVI-AoS:A physiologic study of patients with symptomatic moderate aortic valve stenosis and preserved left ventricular ejection fraction

Background: Moderate aortic valve stenosis occurs twice as often as severe aortic stenosis (AS) and carries a similarly poor prognosis. Current European and American guidelines offer limited insight into moderate AS (MAS) patients with unexplained symptoms. Measuring valve physiology at rest while most patients experience symptoms during exertion might represent a conceptual limitation in the current grading of AS severity. The stress aortic valve index (SAVI) may delineate hemodynamically significant AS among patients with MAS. Objectives: To investigate the diagnostic value of SAVI in symptomatic MAS patients with normal left ventricular ejection fraction (LVEF ≥ 50%): aortic valve area (AVA) > 1 cm2 plus either mean valve gradient (MG) 15–39 mmHg or maximal aortic valve velocity (AOV max) 2.5–3.9 m/s. Short-term objectives include associations with symptom burden, functional capacity, and cardiac biomarkers. Long-term objectives include clinical outcomes. Methods and results: Multicenter, non-blinded, observational cohort. AS severity will be graded invasively (aortic valve pressure measurements with dobutamine stress testing for SAVI) and non-invasively (echocardiography during dobutamine and exercise stress). Computed tomography (CT) of the aortic valve will be scored for calcium, and hemodynamics simulated using computational fluid dynamics. Cardiac biomarkers and functional parameters will be serially monitored. The primary objective is to see how SAVI and conventional measures (MG, AVA and Vmax) correlate with clinical parameters (quality of life survey, 6-minute walk test [6MWT], and biomarkers). Conclusions: The SAVI-AoS study will extensively evaluate patients with unexplained, symptomatic MAS to determine any added value of SAVI versus traditional, resting valve parameters