With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

In vivo study revealed that ZnO nanoparticles treatment of Streptococcus SPP contaminated injured skin showed good prognosis and good healing process include complete regeneration of the epithelial cells of the epidermis and increase of cellulartiy of the dermal content compared with untreated group. In conclusion, treatment of S. pyogenes infected skin with Zinc oxide nanoparticles concentration (2 mg/ml) limit the skin damage and localized the lesion to the incision site with good healing process

Nanoparticles have gained considerable interest in recent times for oil recovery purposes owing to significant capabilities in wettability alteration of reservoir rocks. Wettability is a key factor controlling displacement efficiency and ultimate recovery of oil. The present study investigates the influence of zirconium (IV) oxide (ZrO2) and nickel (II) oxide (NiO) nanoparticles on the wetting preference of fractured (oil-wet) limestone formations. Wettability was assessed through SEM, AFM and contact angle. The potentials of the nanoparticles to alter oil-wet calcite substrates water wet, was experimentally tested at low nanoparticle concentrations (0.004–0.05 wt%). Quite similar behaviour was observed for both nanoparticles at the same

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

Pseudoephedrine (PSE), often known as Sudafed, belongs to a class of medications known as sympathomimetic amines, which affect the digestive system, respiratory system, and cardiovascular system. This drug has a long history of medical use; it is helpful in treating symptoms of the common cold and flu, sinusitis, asthma, and bronchitis. Due to its central nervous system (CNS) stimulant properties and structural similarity to amphe­tamine, it is also used for non-medical purposes such as doping agent, to increase focus, and as a substance that gets rid of exhaustion and drowsiness. Nevertheless only a few studies, backed up its impact on solid abdominal organs. The aim of this task is to investigate the effect of some dosages of PSE

Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and

The present study deals with the experimental investigation of buried concrete pipes. Concrete pipes are buried in loose and dense conditions of gravelly sand soil and subjected to different surface loadings to study the effects of the backfill compaction on the pipe. The experimental investigation was accomplished using full-scale precast unreinforced concrete pipes with 300 mm internal diameter tested in a laboratory soil box test facility set up for this study. Two loading platforms are used namely, uniform loading platform and patch loading platform. The wheel load was simulated through patch loading platform which have dimensions of 254 mm *508 mm, which is used by AASHTO to model the wheel load of a HS20 truck. The pipe-soil system