Photocatalytic hydrogen evolution over CuCrO2

We have been studying the technical feasibility of a photochemical H₂ evolution based on a dispersion of CuCrO₂ powder in aqueous electrolytes containing various reducing agents (S²⁻, and ). The title oxide combines a fair resistance to corrosion with an optimal band gap E_g of 1.32 eV. The intercalation of a small amount of oxygen should be accompanied by a partial oxidation of Cu⁺ into Cu²⁺ implying a p-type semiconductivity. The S²⁻ oxidation inhibits the photocorrosion and the H₂ evolution increases parallel to polysulfides formation. Most of H₂ is produced when p-CuCrO₂ is connected to n-Cu₂O formed in situ. H₂ liberation proceeds mostly on CuCrO₂ while the oxidation of S²⁻ takes place over Cu₂O surface and the hetero system Cu₂O/CuCrO₂ is optimized with respect to some physical parameters. The photoactivity is dependent on preparation conditions and lowering the synthesis temperature through nitrate route leads to an increase in specific surface area S_sp. The photoelectrochemical H₂ production is a multistep process where the rate determining step is the arrival of electrons at the interface because of their low mobility. Prolonged irradiation (>80 min) leads to a pronounced decrease of the photoactivity; the tendency toward saturation is due to the undesired back reduction of polysulfides in a closed system and to their strong absorption in the visible region (λ_max = 520 nm).     

Expressions approchées aux basses et aux hautes fréquences des tensions induites de mode commun aux extrémités d’une ligne blindée soumise à une injection ponctuelle de courant

With reference to a preceding paper, this paper allows, in a first step, to determine, at low and high frequencies, approached expressions of the induced common mode voltages at the extremities of a shielded line influenced by a punctual current injection along the shield. These expressions are established for the case of a helicoidal screen with four different schemes of earth connections at the extremities. In a second step, the correction function, i.e. the ratio between the exact and approached solution, and the limit of validity of this latter at high frequencies are addressed.     

Hybrid Metamodeling/Metaheuristic Assisted Multi-Transmitters Placement Planning

With every passing day, the demand for data traffic is increasing, and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently. Cell sizes are shrinking with every upcoming communication generation, which makes base station placement planning even more complex and cumbersome. In order to make the next-generation cost-effective, it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service. This paper aims at the development of a new simulation-based optimization approach using a hybrid metaheuristic and metamodel applied in a novel mathematical formulation of the multi-transmitter placement planning (MTPP) problem. We first develop a new mathematical programming model for MTPP that is flexible to design the locations for any number of transmitters. To solve this constrained optimization problem, we propose a hybrid approach using the radial basis function (RBF) metamodel to assist the particle swarm optimizer (PSO) by mitigating the associated computational burden of the optimization procedure. We evaluate the effectiveness and applicability of the proposed algorithm by simulating the MTPP model with two, three, four and five transmitters and estimating the Pareto front for optimal locations of transmitters. The quantitative results show that almost maximum signal coverage can be obtained with four transmitters; thus, it is not a wise idea to use higher number of transmitters in the model. Furthermore, the limitations and future works are discussed.     

Data mining with a simulated annealing based fuzzy classification system

In this paper, the use of simulated annealing (SA) metaheuristic for constructing a fuzzy classification system is presented. In several previous investigations, the capability of fuzzy systems to solve different kinds of problems has been demonstrated. Simulated annealing based fuzzy classification system (SAFCS), hybridizes the learning capability of SA metaheuristic with the approximate reasoning method of fuzzy systems. The objective of this paper is to illustrate the ability of SA to develop an accurate fuzzy classifier. The use of SA in classification is an attempt to effectively explore and exploit the large search space usually associated with classification problems, and find the optimum set of fuzzy if–then rules. The SAFCS would be capable to extract accurate fuzzy classification rules from input data sets, and applies them to classify new data instances in different predefined groups or classes. Experiments are performed with eight UCI data sets. The results indicate that the proposed SAFCS achieves competitive results in comparison with several well-known classification algorithms.     

A parallel algorithm for constrained two-staged two-dimensional cutting problems

In this paper, we solve the two-staged two-dimensional cutting problem using a parallel algorithm. The proposed approach combines two main features: beam search (BS) and strip generation solution procedures (SGSP). BS employs a truncated tree-search, where a selected subset of generated nodes are retuned for further search. SGSP, a constructive procedure, combines a (sub)set of strips for providing both partial lower and complementary upper bounds. The algorithm explores in parallel a subset of selected nodes following the master-slave paradigm. The master processor serves to guide the search-resolution and each slave processor develops its proper way, trying a global convergence. The aim of such an approach is to show how the parallelism is able to efficiently solve large-scale instances, by providing new solutions within a consistently reduced runtime. Extensive computational testing on instances, taken from the literature, shows the effectiveness of the proposed approach.     

Integration of DEM, ETM+, Geologic, and Magnetic Data for Geological Investigations in the Jifara Plain, Libya

We used an integrated approach to constrain the geological structure of the Jifara Plain in northwest Libya. The analysis of surface data, including a digital elevation model (DEM), Landsat Enhanced Thematic Mapper Plus images, and geologic maps, was combined with subsurface data, including well logs and magnetic data. The DEM data were used for the identification of geological lineaments in the study area. The interpretation and analysis of the lineaments indicate that the Jifara Plain is controlled by three main fault systems, trending northwest-southeast, east-west, and northeast-southwest. The three trends represent the remnants of reactivated structures that formed under the stress regimes generated during the tectonic evolution of North Africa. The magnetic data reveal three northwest- and northeast-trending sedimentary basins in the study area. The depth of the basement inside the main basin ranges from 1 to 5 km. The results indicate that the Jifara Basin is shallower than the surrounding basins. The integration of the results reflects different periods of tectonic activity in the Jifara Plain and the adjacent Jabal Nafusah.     

Quality of water in hemodialysis centers in Baghdad,Iraq

Dialysis water quality is one of the important parameters all over the world because of its direct influence on the health of kidney patients. In Iraq, there are more than 20 dialysis centers; most of them contain identical units for the production of dialysis water. In this work, the quality of water used for dialysis in six dialysis centers located within Baghdad hospitals was evaluated. Samples of product water from each of the six dialysis centers were examined for total heterotrophic bacteria, endotoxin, and chemical contaminants. Endotoxin was measured on‐site using a portable instrument. Bacteriological and chemical examinations were done in the laboratory after collecting samples from each dialysis center. The results showed a fluctuation in the produced water quality that makes the produced water unaccepted when compared with international standards. Bacterial counts for 60% of the analyzed samples were above the action level (50 colony‐forming units[CFU]/mL), while five out of the six dialysis centers showed values higher than the maximum value (100 CFU/mL). Chemical analysis showed that the dialysis water quality suffers from elevated aluminum concentration for all dialysis centers. All hemodialysis centers need thorough monitoring and preventive maintenance to ensure good water quality. In addition, it is important to revise the design of the water treatment units according to the feed and product water quality.     

Evolutions in machine learning technology for financial distress prediction: A comprehensive review and comparative analysis

In recent years, financial distress prediction (FDP), also known as corporate failure prediction or bankruptcy prediction, has gained significant importance due to its impact on organizations, especially during unexpected events like pandemics and wars. Machine learning (ML) models have emerged as innovative and essential tools in predicting financial distress, leveraging the ever-increasing volume of databases and computing power. This study utilizes bibliographic techniques to contribute to the field's literature review to address the disorganized nature of the existing literature on FDP, reduce confusion, and provide clarity to domain researchers. These techniques enable identifying the progress of articles published over the years, influential authors, and highly cited articles. Additionally, the study examines crucial aspects of data preprocessing, such as missing data, imbalanced data, feature selection, and outliers, as they significantly impact the robustness and performance of ML models. Furthermore, it discusses essential models employed in FDP, focusing on recent advancements that represent promising trends. In conclusion, this study contributes to the field by uncovering novel trends and proposing possible directions for advancing FDP research. These findings will guide researchers, practitioners, and stakeholders in their quest for improved prediction and decision-making in financial distress.     

On IEC 61850 communication networks in smart grids system: Methodology of implementation and performances analysis on an experimental platform

The increasing installation of distributed energy resources during the last years has led to a fundamental change in the power system structure. As a consequence, utility operators are faced with new challenges in grid planning and control. The consideration of smart grids show promising results in increasing the hosting capacity for distributed and renewable resources. Standardized automation, control, and communication systems are important keys to realize such intelligent methods. This paper focuses on a deployment methodology of IEC 61850 on an experimental platform for smart grid system. We were interested in evaluating the performance of the GOOSE communication. A standard-based communication approach for distributed energy resources is introduced and implemented. It uses the IEC 61850 interoperability approach as well as the GOOSE communication for distributed automation. The implementation methodology is provided to handle the hierarchical architecture of distributed control applications. In order to show the advantages of the proposed methodology, a combined analytical and experimental approach is demonstrated for evaluation of GOOSE communication performances.     

Contribution to the declination of the dependability requirements using a three-dimensional decomposition of complex systems

The declination of the dependability requirements of the complex systems is one of the most critical processes of systems conception as well as systems engineering. We consider that these dependability requirements must be globally considered at the complete system level if they are to be respected before being allocated on the components of the system. Our approach is based on a three-dimensional decomposition model of the system whose purpose is to describe the way in which the system operates in order to deduce its dysfunction that serves as a basic support for the declination of the dependability requirements. The proposed method is applied to a nitric acid cooling system before being introduced into a chemical reactor.