One of the key challenges in applying deep learning to solve real-life problems is the lack of large annotated datasets. Furthermore, for a deep learning model to perform well on the test set, all samples in the training and test sets should be independent and identically distributed (i.i.d.), which means that test samples should be similar to the samples that were used to train the model. In many cases, however, the underlying training and test set distributions are different. In such cases, it is common to adapt the test samples by transforming them to their equivalent counterparts in the

Wireless video sensor networks (WVSNs) are opening the door for many applications, such as industrial surveillance, environmental tracking, border security, and infrastructure health monitoring. In WVSN, energy conservation is very essential because: 1) sensors are usually battery-operated and 2) each sensor node needs to compress the video prior to transmission, which consumes more power than conventional wireless sensor networks. In this paper, we study the problem of minimizing the total power consumption in a cluster-based WVSN, leveraging cross-layer design to optimize the encoding power

We consider a time-slotted primary system where both the primary channel and primary activity are modeled as two independent two-state Markov chains. The primary transmitter can be idle or busy, whereas the channel can be in erasure or not. Moreover, the sensing channel between the primary transmitter and secondary transmitter is modeled as a two-state Markov chain to represent two levels of sensing reliability. At the beginning of each time slot, the secondary transmitter may remain idle, transmit directly, or probe the channel and access the channel only if it is sensed to be free. At the

Visualization of genome comparison data is valuable for identifying genomic structural variations and determining evolutionary events. Although there are many software tools with varying degrees of sophistication for displaying such comparisons, there is no tool for displaying dot plots of multiple genome comparisons. The dot plot mode of visualization is more appropriate and convenient than the traditional linear mode, particularly for detecting large scale genome deletions, duplications, and rearrangements. In this paper, we present VisCHAINER, which addresses this limitation, and displays

Biomedical applications of nanomaterials have received considerable attention and interest from many researchers over the past decade due to the key role they can play in enhancing public health. Different types of nanomaterials possess both diagnostic and therapeutic potential owing to their outstanding properties compared to their bulk counterparts. Herein, we present, analyze and provide significant insights and recent advances about the promising biomedical applications of nanoparticles including bioimaging of biological environments and its role as a significant tool for early detection

Treatment of burn wounds has many requirements to ensure wound closure with healthy tissue, increased vascularization, guarantee edema resolution, and control bacterial infection. We propose that titanium oxide (TiO2) nanoparticles (NPs) will be more efficient than silver dioxide (Ag2O) in the treatment of burn wounds. Herein, gelatin loaded NPs (GLT-NPs) were evaluated for their efficacy to regenerate second-degree burn wound in rabbit skin. TEM results revealed that the average particle sizes were ⁓ 7.5 and 17 nm for Ag2O and TiO2 NPs, respectively. The results of the in vivo application of

Magnesium oxide (MgO) nanoparticles are one of the highly significant compounds in construction. The novelty concentrated on using sol–gel technique coupled with ultrasonication for synthesis of MgO nanoparticles to prevent the agglomeration and its effect on the size was investigated. The synthesized samples were characterized by TGA, DSC, XRD, FTIR, SEM, EDX mapping, DLS, and HRTEM. Antimicrobial and antibiofilm activities of MgO nanoparticles were investigated against multidrug-resistant microbes causing-urinary tract infection (UTI). TGA, XRD, and FTIR characterization were used to

It seems that the use of mathematical models is not suitable for pharmaceutical production line optimisation and the use of simulation leads to better outputs and provides more flexibility than mathematical models. Therefore, in this study, a novel methodology based on the integration of simulation and data envelopment analysis is developed for performance optimisation of a pharmaceutical production line. For this purpose, first, an actual pharmaceutical production line was simulated, verified and validated. Afterwards, Data Envelopment Analysis (DEA) was developed for the scenario analysis

Early diagnosis of malignant leukemia can enormously help the physicians in choosing the right treatment for the patient. A lot of diagnostic techniques are available to identify leukemia disease, but these techniques are costly. Hence, there is a need for a less time-consuming and cost-effective method for the classification of leukemia blood cells. In this paper, application of graphical user interface technique for the differentiation of acute lymphoblastic leukemia nucleus from healthy lymphocytes in a medical image is described. This method employs backtrack search optimization algorithm

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