Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%.     

Coil‐Type Asymmetric Supercapacitor Electrical Cables

Cable‐shaped supercapacitors (SCs) have recently aroused significant attention due to their attractive properties such as small size, lightweight, and bendability. Current cable‐shaped SCs have symmetric device configuration. However, if an asymmetric design is used in cable‐shaped supercapacitors, they would become more attractive due to broader cell operation voltages, which results in higher energy densities. Here, a novel coil‐type asymmetric supercapacitor electrical cable (CASEC) is reported with enhanced cell operation voltage and extraordinary mechanical‐electrochemical stability. The CASECs show excellent charge–discharge profiles, extraordinary rate capability (95.4%), high energy density (0.85 mWh cm⁻³), remarkable flexibility and bendability, and superior bending cycle stability (≈93.0% after 4000 cycles at different bending states). In addition, the CASECs not only exhibit the capability to store energy but also to transmit electricity simultaneously and independently. The integrated electrical conduction and storage capability of CASECS offer many potential applications in solar energy storage and electronic gadgets.     

Excited-state absorption of meso-tetrasulfonatophenyl porphyrin: Effects of pH and micelles

The influence of the environment on the excited state transitions of meso-tetrakis(p-sulfonatophenyl) porphyrin (TPPS) is reported. TPPS was investigated in protonated and non-protonated forms, and in the presence of the cationic cetyltrimethylammonium bromide (CTAB) micelles. The singlet excited-state absorption spectra were measured by using the white-light continuum Z-scan technique and the triplet–triplet absorption spectra were acquired employing an association of laser flash photolysis and Z-scan techniques. Our results show that the perseveration of the molecular symmetry, upon excitation, depends on the state of multiplicity of the molecules, as well as on the environment and structural characteristics of the porphyrin. Additionally, it was observed that for excited molecules, the ring distortion caused by the protonation of porphyrin ring has great influence on the changes observed for the symmetry and vibronic structure. The results clearly show that the porphyrin investigated is a promising candidate for optical limiting applications for all investigated environments.     

Computational studies on the radiative and nonradiative processes of luminescent N-heteroleptic platinum(II) complexes

Three N-heteroleptic Pt(II) complexes, [Pt(C^C)(O^O)] [O^O = acetylacetonate, C^C = 1-phenyl-1,2,4-triazol-5-ylidene (1), C^C = 4-phenyl-1,2,4-triazol-5-ylidene (2), C^C = 2-phenylpyrazine (3)] have been investigated with density functional theory (DFT) and time-dependent density functional theory (TDDFT). The radiative decay rate constants of complexes 1–3 have been discussed with the oscillator strength (f_n), the strength of spin–orbit coupling (SOC) interaction between the lowest energy triplet excited state (T₁) and singlet excited states (S_n), and the energy gaps between E(T₁) and E(S_n). To illustrate the nonradiative decay processes, the transition states between triplet metal-centered (³MC) and T₁ states have been optimized and were verified with the calculations of vibrational frequencies and intrinsic reaction coordinate (IRC). In addition, the minimum energy crossing points (MECPs) between ³MC and ground states (S₀) were optimized. At last, the potential energy curves relevant to the nonradiative decay pathways are simulated. The results show that complex 3 has the biggest photoluminescence quantum yield because the complex 3 has the biggest radiative decay rate constant and the smallest nonradiative decay rate constant in complexes 1–3.     

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry, with its persistent quest for high-performance predictive models, is in great need of this new learning methodology. A marginal improvement in the prediction indices of petroleum reservoir properties could have huge positive impact on the success of exploration, drilling and the overall reservoir management portfolio. Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems. However, its performance is a function of the prudent choice of its tuning parameters most especially the regularization parameter, C. Reports have shown that this parameter has significant impact on the performance of SVM. Understandably, no specific value has been recommended for it. This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of petroleum reservoirs using datasets from diverse geological formations. The performance of the proposed SVM ensemble was compared to that of conventional SVM technique, another SVM implemented with the bagging method, and Random Forest technique. The results showed that the proposed ensemble model, in most cases, outperformed the others with the highest correlation coefficient, and the lowest mean and absolute errors. The study indicated that there is a great potential for ensemble learning in petroleum reservoir characterization to improve the accuracy of reservoir properties predictions for more successful explorations and increased production of petroleum resources. The results also confirmed that ensemble models perform better than the conventional SVM implementation.     

A mixed collector system for phosphate flotation

Flotation has been used in industry for more than a half century as the primary technique for upgrading phosphate. While the flotation of phosphate was inefficient when oleic acid was used alone as a collector, therefore a mixed collector of oleic acid (HOl), linoleic acid (LA) and linolenic acid (LNA) was employed to improve the recovery of phosphate flotation. The batch flotation results showed that the optimal composition of the mixed collector was 54 wt.% HOl, 36 wt.% LA and 10 wt.% LNA. Additionally, the effect of pH on the mixed collector application was studied while considering the surface tension, contact angle and micro-flotation. The results showed that the mixed collector should be used at a pH of 9.5. Above a pH of 9.5, the adsorption of fatty acids dimers on the apatite surface hindered phosphate flotation. The influence of the mixed collector assembly on apatite flotation was also investigated. It was demonstrated that due to its low critical micelle concentration, a sufficiently hydrophobic apatite surface could be generated at a collector concentration of 60 mg/L. In addition, zeta potential experiments suggested that collector adsorption was governed by chemisorption. FTIR and XPS spectra studies further indicated that the chemical reaction involved the carboxyl groups of fatty acids and Ca species at the apatite surface for each fatty acid in the mixed collector.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Mixed coordination mechanisms for scheduling games on hierarchical machines

In this paper, we study scheduling games under mixed coordination mechanisms on hierarchical machines. The two scheduling policies involved are ‐ and ‐, where ‐ (resp., ‐) policy sequences jobs in nondecreasing order of their hierarchies, and jobs of the same hierarchy in nonincreasing (resp., nondecreasing) order of their processing times. We first show the existence of a Nash equilibrium. Then we present the price of anarchy and the price of stability for the games with social costs of minimizing the makespan and maximizing the minimum machine load. All the bounds given in this paper are tight.     

Enhanced transduction coefficient in piezoelectric PZT ceramics by mixing powders calcined at different temperatures

Large transduction coefficient ($d_{33}\times g_{33}$) is difficult to obtain in piezoelectric ceramics because these two parameters show opposite trends with compositional modifications. Herein, the Pb(Zr_0.53Ti_0.47)O₃ ceramic powders were calcinated under different temperatures (A:830 °C, B:860 °C, and C:890 °C), and then mixed together according to different weight ratios (1A:1B:1C, 1A:2B:1C, 1A:2B:3C and 3A:2B:1C) for ceramics preparation. Both d₃₃ and g₃₃ are improved successfully, and the transduction coefficient with the weight ratio of 1A:2B:3C reaches up to 17,500 × 10⁻¹⁵ m²/N, which is 60 % higher than that with the powders calcinated under 830 °C, and at least twice those of commercial PZT-4, PZT-5A and PZT-8 ceramics. The improved transduction coefficient is owing to the enhanced piezoelectric constant and spontaneous polarization resulted from the increased grain size, relative density and the fraction of tetragonal phase. These results indicate that this is a simple but effective way to tailor the transduction coefficient in piezoelectric ceramics.