We present a modified examplar-based inpainting method in the framework of PATCH SPARSITY. In the examplar-based algorithms, the unknown blocks of target region are inpainted by the most similar blocks extracted from the source region, using the available information. Defining a priority term to decide the filling order of missing pixels ensures the connectivity of the object boundaries. In the exemplar-based PATCH SPARSITY approach, a sparse representation of missing pixels is considered to define a new priority term and the unknown pixels of the fill-front PATCH is inpainted by a sparse combination of the most similar PATCHes. Here, we modify this representation of the priority term and take a measure to compute the similarities between fill-front and candidate PATCHes. Also, a new definition is proposed for updating the confidence term to illustrate the amount of the reliable information surrounding pixels. Comparative reconstructed test images show the effectiveness of our proposed approach in providing high quality inpainted images.

In order to exploit the advantages of the massive MIMO systems, it is vital to apply the channel estimation task. The huge number of antennas at the base station of a massive MIMO system produces a large set of channel paths which requires to be estimated. Therefore, the channel estimation in such systems is more troublesome. In this paper, we propose to leverage the temporal joint SPARSITY of the massive MIMO channels to offer a more accurate channel estimation. To attain this goal, we would model the problem to exploit the spatial correlation among different antennas of the BS as well as the inter-user similarity of the channel supports. In addition, by assuming a slow time-varying channel, the supports of the channel matrices of various snapshots would be equal which enables us to impose the temporal joint SPARSITY on the channel submatrices. The simulation results validate the efficiency and superiority of the suggested scheme over its rivals.

Contact dermatitis is an inflammatory skin disease due to contact with different substances and caused by two mechanisms: allergy and irritation. Contact dermatitis is a common skin disease and the most common occupational dermatosis. Differentiating between allergic and irritant contact dermatitis is essential in the identification of etiologic factor(s) and hence, its control and prognosis. This differentiation can be done only by PATCH test. Unfortunately, this simple, safe and useful test is always neglected. We review the basics of PATCH test, the method of performance, reading and interpretation of its results, possible side effects and results of studies done with PATCH test in different countries.

Generally, the presence of noise in geophysical measurements is inevitable and depending on the type and the level it affects the results of geophysical studies. So, denoising is an important part of the processing of geophysical data. On the other hand, geophysicists make inferences about the physical properties of the earth interior based on the indirect measurements (data) collected at or near the surface of the earth. So, an inverse problem must be solved in order to take estimates of the physical properties in the earth. The vast majority of inverse problems which arise in geophysics are ill-posed; in other words, they have not unique and stable solutions. Regularization tools are used to find a unique and stable solution for such problems. The regularization uses a priori information about the solution to make it stable and to suppress high-frequency oscillations generated by the noise. One of the common ways to perform the regularization is expanding the unknown model (i.e. solution) with respect to an orthonormal basis, separating the model coefficients from that of the noise, and finally recovering the model.In singular value decomposition, the specific physical nature of the model under study is not considered when defining the basis. For homogeneous operators, such basis does not provide a parsimonious approximation of models which are smooth in some regions while having sharp local changes in others. This is due to the non-localized properties of the SVD basis vectors in space (time) domain.Wavelet-vaguelette decomposition (WVD) was introduced as a first approach for adapting wavelet methods to the framework of ill-posed inverse problems. It is a linear projection method based on wavelet-like function systems which have similar properties as the singular value decompositions. WVD are compared to the SVD construct near the orthogonal basis where the vectors are well localized in space (time) and frequency, thus producing less Gibbs-phenomenon at discontinuities. This property and existence of fast algorithm to compute the basis make wavelets a suitable candidate for solving inverse problems.Vaguelette-wavelet decomposition (VWD) is an alternative to WVD for solving illposed inverse problems. It is a linear projection method based on wavelet function systems. In VWD the noisy data are expanded in a wavelet series, generated wavelet coefficients are thresholded to obtain an estimate of the wavelet expansion of noise free data, and then the resulting coefficients are transformed back for smoothed data. Later on, the smoothed data are inverted for the desired model. In this paper we discuss: 1. The performance of sparsifying transforms (e.g. wavelet transform) for the denoising problem and their application to solve other linear inverse problems including WVD and VWD. 2. Comparing nonlinear Amplitude-scale-invariant Bayes Estimator (ABE) and hard- and soft-shrinkage filters to estimate signal coefficients in sparse domain for different levels of noise. 3. Introducing an efficient method to estimate the standard deviation of noise which is an important task in the experiments with single realization. The obtained standard deviation is then used to determine the regularization parameter in both wavelet- and SVD- based inversion methods. Finally, inversion of integration operator to find the variation rate of a function is used to show the performance of the introduced methods in comparison to the popular SVD method. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods.

Background: Various environmental factors can induce or exaggerate hand eczema. Objective: Evaluation of PATCH test results in hand eczema patients. Patients and Methods: In this descriptive study 100 patients with hand eczema referred to Loghman Hakim & Booali Hospital in Tehran underwent PATCH testing with 23 allergens obtained from Hennal Company. Results: 240 positive reactions observed in 86 patients. The most common positive reactions were related to nickel sulfate (30 patients, 13.5%) and potassium dichromate (28 patients, 11.7%). In positive group 28 patients were male and 58 were female. In negative group 3 patients were male and 11 were female (P>0.05). The mean age was 31.7±11.9 years and 24.8± 9.2 years for positive group and negative group, respectively (P<0.05). In positive PATCH test group 49 patients had subacute and 37 patients had chronic eczema. In negative PATCH test 11 patients had subacute eczema and 3 patients had chronic eczema (P>0.05). Conclusion: Performing PATCH test, the allergens involved in hand eczema can be detected. Detecting type of allergens, patients will be able to avoid those materials which can lead to improvement of disease.        

Deep neural networks (DNNs) have achieved great interest due to their success in various applications. However, the computation complexity and memory size are considered to be the main obstacles for implementing such models on embedded devices with limited memory and computational resources. Network compression techniques can overcome these challenges. Quantization and pruning methods are the most important compression techniques among them. One of the famous quantization methods in DNNs is the multi-level binary quantization, which not only exploits simple bit-wise logical operations, but also reduces the accuracy gap between binary neural networks and full precision DNNs. Since, multi-level binary can’t represent the zero value, this quantization does’nt take advantage of SPARSITY. On the other hand, it has been shown that DNNs are sparse, and by pruning the parameters of the DNNs, the amount of data storage in memory is reduced while computation speedup is also achieved. In this paper, we propose a pruning and quantization-aware training method for multi-level ternary quantization that takes advantage of both multi-level quantization and data SPARSITY. In addition to increasing the accuracy of the network compared to the binary multi-level networks, it gives the network the ability to be sparse. To save memory size and computation complexity, we increase the SPARSITY in the quantized network by pruning until the accuracy loss is negligible. The results show that the potential speedup of computation for our model at the bit and word-level SPARSITY can be increased by 15x and 45x compared to the basic multi-level binary networks.

Introduction: Decreasing pain elicited by injections in children results in patient comfort during dental procedures and produces a positive experience towards dental procedures. The aim of the present study was to compare the effect of DentiPATCH and 20% benzocaine gel in decreasing injection pain in children referring to Isfahan Faculty of Dentistry.Materials and Methods: Simple sampling method was used in the present clinical trial to select fifty-four 9-12 year-old children (24 males and 30 females). The injection site was dried with air spray for 5 seconds; then DentiPATCH was placed by a dentist on the palate for 12 minutes at a distance of 5-10 mm from the gingival margin. A total of 1.8 mL of 2% lidocaine was injected; 10 minutes after the injection the same procedure was repeated on the contra-lateral side with the use of benzocaine gel. Data was collected and analyzed with pained t-test and Wilcoxon test using CPS and VAS scales (a=0.05).Results: Means of CPS in non-anxious children in the benzocaine and DentiPATCH groups were 6.4 and 5.8, respectively, with no statistically significant differences (p value=0.081). Means of VAS in non-anxious children in the benzocaine and DentiPATCH groups were 39.2 and 32.5, respectively, with no statistically significant differences (p value=0.068).Conclusion: Under the limits of the present study, it was concluded that there is no difference between the two methods regarding children’s reaction. Further evaluations are recommended with different application times, especially with the new Dentipatech method.

Many roads in forest areas are located along the steep hills. The cut and fill method is currently used for construction of these roads. Settlement or consolidation in not enough compacted soil or creep in down slope, can lead to subsidence and cracks in roads. General methods for solving settlement related problems such as reconstruction, retaining structure and … are expensive. Deep PATCH method is a low- cost method for increasing the stability of slopes. In this method, the upper parts of the subsided area are excavated and replaced with reinforcement materials such as Geo grid in accordance with compacted soil. In this paper, limit equilibrium method has been implemented for determining the safety factor of a planar slip surface in a slope. Furthermore, graphs for determining safety factor of reinforced soil slope with Geo synthetics have been proposed.