Modified salp swarm algorithm for global optimisation

Neural Computing and Applications - Salp swarm algorithm (SSA) is a newly swarm-based metaheuristic algorithm that simulate the swimming and foraging behaviour of salps in oceans so to search for...     

SOA$$^\mathrm{}$$: a new way to design the decision in SOA—based on the new standard Decision Model and Notation (DMN)

In recent years, Service Oriented Architecture (SOA) technologies are emerging as a powerful vehicle for organizations that need to integrate their applications within and across organizational boundaries. In addition, organizations need to make better decisions more quickly. Moreover, they need to change those decisions immediately to adapt to this increasingly dynamic business environment. It is primarily a question in ensuring the decisional aspect by adopting the SOA as a support architecture. In this paper, we describe a new approach called SOA\(^\mathrm{+d}\) based on a certain number of standards. It is going to be studied on three dimensions: The first is related to the definition of the information system implied in the SOA based on the use case model. The second develops the business dimension which is based on the BPMN (Business Process Modeling Notation). The last dimension addresses the need of decision; we use the new standard decision model and notation (DMN) which is recently approved by Object Management Group (OMG) and considered as a simple notation to specify the decision. Finally, Service Oriented Architecture Modeling Language (SoaML) will be used for design of several services. We also present our meta-model Decisional Model of Service (DMS) to define a new set of concepts necessary for modeling the three levels. Some of them are already known, whereas others are new and are proposed as an element of this work. we illustrate our proposal with a real case study in the Pharmacy Inventory Management.     

Regional constrained controllability problem: Approaches and simulations

The aim of this paper is to deal with an output controllability problem. It consists in driving the state of a distributed parabolic system toward a state between two prescribed functions on a boundary subregion of the system evolution domain with minimum energy control. Two necessary conditions are derived. The first one is formulated in terms of subdifferential associated with a minimized functional. The second one is formulated as a system of equations for arguments of the Lagrange systems. Numerical illustrations show the efficiency of the second approach and lead to some conjectures. Recommended by Editorial Board member Fumitoshi Matsuno under the direction of Editor Jae Weon Choi. Zerrik El Hassan is a Professor at the university Moulay Ismail of Meknes in Morocco. He was an Assistant Professor in the faculty of sciences of Meknes and researcher at the university of Perpignan (France). He got his doctorat d etat in system regional analysis (1993) at the University Mohammed V of Rabat, Morocco. Professor Zerrik wrote many papers and books in the area of systems analysis and control. Now he is the Head of the research team MACS (Modeling Analysis and Control of Systems) at the university Moulay Ismail of Meknes in Morocco. Ghafrani Fatima is a Researcher at team MACS at the University Moulay Ismail of Meknes in Morocco. She wrote many papers in the area of systems analysis and control.     

Study of Magnetic Properties of Fe-Doped CuO: Monte Carlo Simulations

Using Monte Carlo simulations, we are studying the magnetic properties of Fe-doped CuO thin films. The total magnetizations and the susceptibilities are studied as a function of the effect doping, external magnetic field, and exchange coupling. The critical temperature is discussed as a function of the effect of iron concentration. On the other hand, we investigate the effect of increasing temperatures on the coercive field for a constant value of exchange coupling and a fixed concentration. The coercive magnetic field is found to decrease with increasing temperature values until reaching its null value. The effect of increasing the exchange coupling amount on the saturation magnetic field H _s is illustrated. A linear growth of the saturation magnetic field is found as a function of the exchange coupling interaction. To complete this study, we presented and discussed the magnetic hysteresis cycle loops.     

Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

The Internet of Medical Things (IoMT) emerges with the vision of the Wireless Body Sensor Network (WBSN) to improve the health monitoring systems and has an enormous impact on the healthcare system for recognizing the levels of risk/severity factors (premature diagnosis, treatment, and supervision of chronic disease i.e., cancer) via wearable/electronic health sensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy plays a very significant role in the detection of gastric cancer. Convolutional Neural Network (CNN) has been widely used to diagnose gastric cancer based on various feature extraction models, consequently, limiting the identification and categorization performance in terms of cancerous stages and grades associated with each type of gastric cancer. This paper proposed an optimized AI-based approach to diagnose and assess the risk factor of gastric cancer based on its type, stage, and grade in the endoscopic images for smart healthcare applications. The proposed method is categorized into five phases such as image pre-processing, Four-Dimensional (4D) image conversion, image segmentation, K-Nearest Neighbour (K-NN) classification, and multi-grading and staging of image intensities. Moreover, the performance of the proposed method has experimented on two different datasets consisting of color and black and white endoscopic images. The simulation results verified that the proposed approach is capable of perceiving gastric cancer with 88.09% sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively.     

Friction properties of cork

The friction coefficient, , of cork sliding on another material (glass and steel in most experiments and also cork) was measured for various compressive stresses and sliding velocities. There is a strong effect of stress and a negligible effect of velocity on the friction coefficient. Values of are in the range 0.4 to 1.2. The effect of moisture content of cork was also evaluated. For dry cork (6% moisture content) there is anisotropy of the friction coefficient related to the orientation of the sliding plane of cork, with larger values for sliding in the tangential plane (compression in the radial direction) as compared to sliding in planes perpendicular to this. At larger moisture contents, the anisotropy of decreases. No in-plane of sliding anisotropy was detected. The friction coefficients for sliding on glass and on steel are comparable, but an effect of roughness was detected. The friction coefficients for sliding on glass and on steel are comparable, but an effect of roughness was detected. The friction against cork is large, with close to unity. The interplay between the friction coefficient and the compression properties of cork is discussed. © 1998 Chapman & Hall     

Quality Management in Pakistan's Bedwear Industry

Pakistan's bedwear industry contributes significantly to Pakistan's industry in general and to its textile industrial output and exports in particular. The exports of bedwear have increased steadily. However, its key basis of competitive advantage has been low cost. After greater liberalization from 2005 onwards and due to tariffication of quotas, the bedwear industry will not only have to scale higher tariff walls but will be more exposed to the threat of anti-dumping duties as it relies primarily on low prices to penetrate the export markets. To enhance its competitiveness, it will have to combine better quality with low costs and quick response. Research in quality management in Pakistan's bedwear industry was, therefore, undertaken. A postal self-completion questionnaire was mailed to 38 members of Pakistan Bedwear Manufacturers' and Exporters' Association (PBMEA). The response rate was almost 79%. It was found that this industrial segment was in various stages of development. This study demonstrates both the effectiveness and the limits of quality assurance in improving the levels of quality which remain a moving target in a dynamic liberalizing international trade environment that is more competitive since 2005. The bedwear industry, therefore, needs to graduate to advanced practices in quality management in order to remain competitive in rapidly changing times.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

Exposure of Mice to Thirdhand Smoke Modulates In Vitro and In Vivo Platelet Responses

Smoking is a risk factor for a variety of deleterious conditions, such as cancer, respiratory disease and cardiovascular disease. Thrombosis is an important and common aspect of several cardiovascular disease states, whose risk is known to be increased by both first- and secondhand smoke. More recently, the residual cigarette smoke that persists after someone has smoked (referred to as thirdhand smoke or THS) has been gaining more attention, since it has been shown that it also negatively affects health. Indeed, we have previously shown that 6-month exposure to THS increases the risk of thrombogenesis. However, neither the time-dependence of THS-induced thrombus formation, nor its sex dependence have been investigated. Thus, in the present study, we investigated these issues in the context of a shorter exposure to THS, specifically 3 months, in male and female mice. We show that the platelets from 3-month THS-exposed mice exhibited enhanced activation by agonists. Moreover, we also show that mice of both sexes exposed to THS have decreased tail bleeding as well as decreased thrombus occlusion time. In terms of the role of sex, intersex disparities in thrombus development and hemostasis as well as in platelet aggregation were, interestingly, observed. Together, our findings show that exposing mice to THS for 3 months is sufficient to predispose them to thrombosis; which seems to be driven, at least in part, by an increased activity in platelets, and that it does not manifest equally in both sexes.     

Physico-chemical analysis of tannery solid waste and structural characterization of its isolated humic acids after composting

In Marrakech, solid by-products from tanneries are highly polluting, generating large amounts of nitrogenous and organic matter. In the present study composting is tested as a cost-effective method for waste management to overcome many of the environmental hazards and produce a stable, rich material for soil fertilization. Two composting trials were conducted after neutralization by ammonia or lime. The aim of the neutralization was to avoid the antimicrobial effects of the acidity in the tannery waste, thus ensuring correct composting. Different techniques such as elemental analysis and ¹³C NMR spectroscopy were applied to analyse humic acids isolated from raw and composted materials, and to monitor the process of tannery waste composting, and the stability and maturity of the final product according to the means of neutralization. Comparison of data showed similar behaviour in both trials, but the composting process appeared to be more complete following neutralization with lime. The C, H and N content decreased, while the O increased. The FTIR and ¹³C NMR spectra show the decrease of aliphatic compounds demonstrated by the reduction of absorbance around 2922 cm⁻¹ and of the resonance in the C-alkyl area around 0–55 ppm. The humic acids newly formed during composting were richer in the O–N alkyl and oxidized aromatic structures that increased almost twofold on composting after neutralization with lime. The first principal component axis PC1 (54%) separated C-aliphatic, C-carboxylic and other less stable and less polycondensed compounds such as polyphenols from the more polycondensed O–N alkyl and oxidized C-aromatic compounds.