Hybrid Sine Cosine and Stochastic Fractal Search for Hemoglobin Estimation

The sample's hemoglobin and glucose levels can be determined by obtaining a blood sample from the human body using a needle and analyzing it. Hemoglobin (HGB) is a critical component of the human body because it transports oxygen from the lungs to the body's tissues and returns carbon dioxide from the tissues to the lungs. Calculating the HGB level is a critical step in any blood analysis job. The HGB levels often indicate whether a person is anemic or polycythemia vera. Constructing ensemble models by combining two or more base machine learning (ML) models can help create a more improved model. The purpose of this work is to present a weighted average ensemble model for predicting hemoglobin levels. An optimization method is utilized to get the ensemble's optimum weights. The optimum weight for this work is determined using a sine cosine algorithm based on stochastic fractal search (SCSFS). The proposed SCSFS ensemble is compared to Decision Tree, Multilayer perceptron (MLP), Support Vector Regression (SVR) and Random Forest Regressors as model-based approaches and the average ensemble model. The SCSFS results indicate that the proposed model outperforms existing models and provides an almost accurate hemoglobin estimate.     

An Animated GIF Steganography Using Variable Block Partition Scheme

The paper presents a novel Graphics Interchange Format (GIF) Steganography system. The algorithm uses an animated (GIF) file format video to apply on, a secured and variable image partition scheme for data embedding. The secret data could be any character text, any image, an audio file, or a video file; that is converted in the form of bits. The proposed method uses a variable partition scheme structure for data embedding in the (GIF) file format video. The algorithm estimates the capacity of the cover (GIF) image frames to embed data bits. Our method built variable partition blocks in an empty frame separately and incorporate it with randomly selected (GIF) frames. This way the (GIF) frame is divided into variable block same as in the empty frame. Then algorithm embeds secret data on appropriate pixel of the (GIF) frame. Each selected partition block for data embedding, can store a different number of data bits based on block size. Intruders could never come to know exact position of the secrete data in this stego frame. All the (GIF) frames are rebuild to make animated stego (GIF) video. The performance of the proposed (GIF) algorithm has experimented and evaluated based on different input parameters, like Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) values. The results are compared with some existing methods and found that our method has promising results.     

On the use of textual feature extraction techniques to support the automated detection of refactoring documentation

Innovations in Systems and Software Engineering - Refactoring is the art of improving the internal structure of a program without altering its external behavior, and it is an important task when it...     

Dynamic performance of a series elastic actuator with variable stiffness logarithmic spiral spring

Intelligent Service Robotics - The present paper investigates a variable stiffness elastic actuator, which was adjusted using a special-purpose mechanism. A model was derived to obtain the response...     

Tomato powder impedes the development of azoxymethane‐induced colorectal cancer in rats through suppression of COX‐2 expression via NF‐κB and regulating Nrf2/HO‐1 pathway

Cancer is one of the leading causes of death worldwide. Since dietary factors have been connected to a reduced risk of a diversity of human cancers, in this study we investigated the effects of tomato powder (TP) on the development of azoxymethane (AOM)‐induced colorectal cancer in Wistar rats, and possible mechanism(s) by which TP shows its chemopreventive activity. Here we show that TP added to feed at 5% rate decreases the rate of aberrant crypt foci (ACF) and reduces the development of adenocarcinoma and growth of AOM‐induced colorectal cancer in rats. In addition, we demonstrate that TP supplementation shows its chemopreventive activities through inhibition of cyclooxygenase‐2 (COX‐2) expression via NF‐κB pathway and promotion of apoptosis, as well as regulating Nrf2/HO‐1 signaling pathway in colorectal tissue of AOM‐treated rats. Our findings identify an intimate connection between dietary supplementation of TP and the decreased risk of colorectal cancer in rats, and suggest that consumption of TP would be a natural candidate for the prevention of colorectal cancer in men.     

Simulation of natural convection heat transfer in an enclosure by the lattice-Boltzmann method

This paper presents the simulation of natural heat convection in an enclosure using Cubic-Interpolated-Pseudo-Particle (CIP) lattice-Boltzmann method. A D2Q9 lattice model was coupled with the simplest D2Q4 lattice model to represent density and internal energy distribution function, respectively. The effects of the Rayleigh number on the flow pattern were studied. The enclosure is filled with air heated by a small localized source of heat at two different positions on the bottom wall. The results explain the mechanism of natural convection rate increasing due to the Rayleigh number and heat source position changing. The comparison of the results was in excellent agreement with results from the literature.     

Synthesis and Structural Properties of Ce(OH)3 for Useful Applications

Rare earth compounds are the subject of many recent experimental investigations because of the nature and variety of their physical properties. Cerium oxide (CeO₂) was the starting material for the fabrication of nanostructures. Ce(OH)₃ was synthesised and structural characterisation was done. A hydrothermal method was used to prepare the nanostructures. The synthesised samples were examined by X-ray diffraction (XRD), atomic force microscopy (AFM) and differential scanning calorimetry (DSC). The phase of the material was confirmed by the X-ray diffraction. Two solvents (nitric acid and sulphuric acid) were used to dissolve CeO₂. The phase and structural properties were studied as a function of the solvent. The sulphuric acid was found to be a better solvent to achieve the required phase of Ce(OH)₃. Synthesised material has potential application in bio-labelling.     

Empowerment scheduling for a field workforce

Employee empowerment is a flexible management concept. As in traditional scheduling, the employer is still in charge of assigning jobs to staff. However, employees are allowed to express their preferences for the jobs they want to do. The hope is that empowerment will improve morale, which will improve productivity. The challenge is to design such an empowerment scheduling system without undesirable outcomes.     

A hybrid approach for learning concept hierarchy from Malay text using artificial immune network

A concept hierarchy is an integral part of an ontology but it is expensive and time consuming to build. Motivated by this, many unsupervised learning methods have been proposed to (semi-) automatically develop a concept hierarchy. A significant work is the Guided Agglomerative Hierarchical Clustering (GAHC) which relies on linguistic patterns (i.e., hypernyms) to guide the clustering process. However, GAHC still relies on contextual features to build the concept hierarchy, thus data sparsity still remains an issue in GAHC. Artificial Immune Systems are known for robustness, noise tolerance and adaptability. Thus, an extension to the GAHC is proposed by hybridizing it with Artificial Immune Network (aiNet) which we call Guided Clustering and aiNet for Learning Concept Hierarchy (GCAINY). In this paper, we have tested GCAINY using two parameter settings. The first parameter setting is obtained from the literature as a baseline parameter setting and second is by automatic parameter tuning using Particle Swarm Optimization (PSO). The effectiveness of the GCAINY is evaluated on three data sets. For further validations, a comparison between GCAINY and GAHC has been conducted and with statistical tests showing that GCAINY increases the quality of the induced concept hierarchy. The results reveal that the parameters value found by using PSO significantly produce better concept hierarchy than the vanilla parameter. Thus it can be concluded that the proposed approach has greater ability to be used in the field of ontology learning.     

Institutional challenges for integrated river basin management in Langat River Basin,Malaysia

This paper reports on a study of the institutional challenges and factors affecting policy processes and outcomes of integrated river basin management (IRBM) in the Langat River Basin (LRB), Malaysia. A case study approach using institutional analysis and development (IAD) framework was used, and field observations and interviews with local stakeholders of LRB were carried out. The study revealed that polycentric institutional arrangements under the Federal administration are likely capable of coordinating and integrating river basin management by extending the scope of an iterative learning through participation of individual stakeholder at the lowest appropriate level. There should also be an iterative learning mechanism within the interorganizational network for IRBM in LRB. This learning approach is conceptualized as social learning and accordingly a framework is recommended for LRB. The findings of this study would be useful to those who are concerned with successful IRBM implementation in LRB and elsewhere.