The main idea in ADPCM coding is to remove the redundancies of the speech signal before quantization. One of the important characteristics of this coding scheme is the spectral flatness of the reconstruction noise in spite of its low level. It has been tried, in the present research, to improve the perceptual quality of the reconstructed signal by shaping the spectrum of the reconstruction noise using an all-zero filter in the backward ADPCM coding. By doing so, a useful compromise is achieved between the level and the spectral shape of the reconstruction noise. The obtained results show an improvement in the perceptual quality of the reconstructed signal (higher PESQ score) and an increase in the noise level (lower SNR).

in this paper, the spectral dimensions of two sets of samples including 457 black and 84 white fabrics are compared. White fabrics are treated with variety of fluorescent whitening agents and the blacks are fabrics that dyed with different combinations of suitable dyes and pigments. In this way, the reflectance spectra of blacks as well as the total radiance factors of whites are compressed in one to five compressed spaces using the principal component analyzing technique. The reduced data are then reconstructed and the averages of the percentile relative root mean square errors between the actual and the recovered spectra of each dataset are calculated to show the spectral dimensionality of both groups through the analyzing of spectral errors. Besides, the colorimetric errors between the actual and the compressed-reconstructed spectra are represented by the mean values of DE00 color difference values under D65 illuminant and 1964 standard observer. Results show that the total radiance factors of white samples are smoother than the reflectance spectra of blacks and could be adequately described in a 2-dimensional space, while blacks need to be characterized in higher dimensions i.e., 4, to approximately provide same cumulative energy content as well as spectral and colorimetric errors.

In this paper, the spectral transmittances of different solutions of different dyes in water are reconstructed by their colorimetric data measured by scanner. Different solutions were prepared and their RGB data were measured by scanner. Then, by using principle component analysis technique, the eigenvectors and eigenvalues of different sets of solutions were calculated, using RGB data and a linear modeling. Finally, the transmission behavior of each solution is predicted by using the basis function and the RGB values of desired solution. Although the results depend on the sampling technique, but very successful reconstructions are observed, totally.

Background and Objective: Four percent of fractures were happened in clavicle bone. This study was done to evaluate the outcomes of superior reconstruction plating method in middle third of clavicle fracture.Materials and Methods: This descriptive study was carried out on 31 patients with middle third of clavicle fracture in Tehran-Iran, during 2009-12. The patients were treated surgically with superior reconstruction plating method. The treatment outcomes were determined by regular follow up in constant shoulder score, duration of union and complications of surgery.Results: The mean value of constant shoulder score was 87.6 which are reduced by chronical age. Non union rate and infection occurred in 3.2% and 6.5% of subjects. Duration of union and pre-scapular pain is increased by chronical age.Conclusion: Superior reconstruction plating method is recommended for middle third of clavicle fractures due to low complication, high constant shoulder score and lower treatment cost.

This paper examines the liberal society that Popper lauds, that aims to be truly open, and discusses why another, more communitarian kind of society, particularly societies in Africa, may also reflect the quest for intellectual openness that is Popper’s ideal. Moreover, this paper avers reasons why Popper should be comfortable with such a liberal-communitarian mix. The inter-subjectivity in his critical rationalism is a balance of an explicit individualism, and an implicit social element (Afisi, 2016a). Popper is indeed an author of such a balance. For a society to be truly open requires the careful recognition and protection of individual freedom. However, the extent to which individuals are free to perform actions that they desire without external constraints, and the level of their individuality in relation to others when performing such actions, remain a contentious issue between liberals and more communitarian thinkers. Popper’s critical rationalism provides the necessary impetus to this contention through his view of freedom that I contend can best be viewed as carefully balanced, a view which combines individuality with a social element that upholds community values necessary for openness of society. With this combination, Popper’s politics of liberalism provides an effective model of how a truly open society can be achieved. The values inherent to Popper’s liberalism including those concerning intellectual openness, individual freedom, mutual respect, measured self-respect, welfarism, humanitarianism, accountability, critical debates and feedback from the citizens, together concern the conditions for a society to be truly open. There are many competing thoughts as to what openness might be in Popper’s philosophy. The present study of Popper does not presume to address them all. The focus here is specifically on using Popper’s idea of critical rationalism to balance relations between liberal politics of individual rights and freedom, and communitarian politics of the common good, as it relates to situations about how socio-economic and political conditions in Africa societies should be structured. While I contend that Popper’s works in political philosophy focused centrally on Western political tradition, and not about Africa in its strict sense, significant lessons can be distilled from Popper that can offer suggestions on social reforms in Africa. This paper explores Popper’s project of the open society across the plurality and differences of societies, so that his liberal ideas of individual freedom are not undermined, and the progress of the communitarian idea of the common good, that Africa societies are built upon, is also well enhanced. Liberal individualism and community values inherent to communitarianism are both well accommodated within Popper’s critical rationalism.

Singular Spectrum Analysis (SSA) is a new powerful method in time series analysis. This non-parametric method due to its unique properties, such as there being nonecessity as to making assumptions about stationarity of time series and also about the normality of residuals, has caught the attention of many researchers in the field of Econometrics and time series analysis and its applications are increasingly getting wide spread. Also this method can be used for short time series. The main purpose of SSA method is to decompose time series into interpretable components such as trend, oscillatory component, and unstructured noise. The basis of SSA is singular value decomposition of the trajectory matrix built on the time series. In the basic SSA method the frequency of observations which used in the trajectory matrix is different and so there may be an error in reconstructing and forecasting the time series, especially at the beginning and end of the series. It occurs because the magnitude of eigenvalues, eigenvectors, and consequently, reconstruction and forecasting of future values of time series, is directly related to the trajectory matrix. The purpose of this paper is to improve the trajectory matrix of SSA method to increase the accuracy of the reconstructed time series and forecasting results, which is called singular spectrum decomposition (SSD). In this paper, SSA and SSD methods and their properties are briefly introduced and then the performance of SSD method over SSA method in time series reconstruction and forecasting for simulated and real data is discussed.

Yuan, Shao and Liu proved  that the H-shape tree $H'_n =P_{1,2;n-3}^{1,n-6}$ minimizes the spectral radius among all graphs with order $n\geqslant 9$ and diameter $n-4$. In this paper, we achieve the spectral characterization of all graphs in the set $\mathscr{H}' = \{ H'_n\}_{n\geqslant 8}$. More precisely we show that $H'_n$ is determined by its spectrum if and only if $n \neq 8, 9,12$, and detect all cospectral mates of $H'_8$, $H'_9$ and $H'_{12}$. Divisibility between characteristic polynomials of graphs turns out to be an important tool to reach our goals.

Spectral unmixing of hyperspectral images is one of the most important research fields in remote sensing. Recently, the direct use of spectral libraries in spectral unmixing is on increase by increasing the availability of the libraries. In this way the spectral unmixing problem is converted into a sparse regression problem that is time-consuming. This is due to the existence of irrelevant spectra in the library. So these spectra should be removed in some way. In the mentioned approach which is called sparse unmixing, we do not need an endmember extraction algorithm and determination of the number of endmembers priori. Since spectral libraries usually contain highly correlated spectra, the sparse unmixing approach leads to non-admissible solutions. On the other hand, most of the proposed solutions are not noise-resistant and do not reach to a sufficiently high sparse solution. In this paper, with the purpose of overcoming the problems above, at first a machine learning approach for spectral library pruning is introduced. The spectral library is clustered using k-means algorithm based on a simple and efficient new feature space. Subtractive clustering is used for determining the cluster centers of k-means algorithm. Three distance measures, Spectral angle distance, spectral distance similarity and spectral correlation similarity tested to select the best for k-means. Then the training data needed to learn a classifier are extracted by adding different noise levels to the clustered spectra. The label of the training data is determined based on the results of spectral library clustering. After learning the classifier, each pixel of the image is classified using it. This classified image will be used for pruning the spectral library. For testing the impact of classifier type on the result of unmixing, three classifiers, decision tree classifier, neural networks and k-nearest neighbours are compared. For pruning the library, the spectra with the labels that none of the image pixels belong to, are removed from spectral library. In this way, the candidate spectra present in the image are extracted. Now, a genetic algorithm will be used for sparse unmixing. Experimental results show that spectral library pruning enhances the performance of sparse unmixing algorithms. Moreover, using k-nearest neighbor in image classification step, gives better results in the final unmixing process. Genetic algorithm that used for sparse unmixing compared with OMP and SUnSAL algorithms, works well in noisy images.

Spectral images are the most valuable data than can be achieved using 2D sensors. Spectral estimation using data with a few channel cameras has been the subject of many studies. It is common to use color filters in front of the lens for increasing dimensionality of data. However, spectral estimations are prone to suffer from colorimetric errors. To address this problem it was shown that this problem is a special case of error-free spectral estimation problem. Considering the fact that most of RGB cameras tend to be colorimetric, using geometrical modeling of the problem, it was shown that adding a shoot with bare lens to the sensor’ s data can solve the problem. The notion has been tested in different scenarios and the efficiency of the proposed method has been proved in the scenarios. Results showed that if the camera is acceptably colorimetric, the proposed method can even leads to error-free colorimetric performance. Prog. Color Colorants Coat. 13 (2020), 121-130© Institute for Color Science and Technology.

Background & Aim: Crystalloids represent an attractive strategy to alleviate intravascular volume deficits. Studies have demonstrated that hemodilution with decrease antitrombin III is associated with hypercoagulability. However, there were not any researches about effect of different crystalloids on coagulation. The present study was undertaken to find out which of the used crystalloids has more effect on coagulation. Patients & Methods: In a prospective study on patients undergoing ACL reconstruction normal saline(NS), Ringer(R) and Ringer Lactate(RL)(n=25) were used for intravascular volume replacement based on standard protocol to compensate intravascular volume deficits. PT, PTT, BT, CT and platelet count were used at T0 (after induction of anesthesia), T1 (immediately after anesthesia), T2(6h after surgery) and T3(the morning after surgey), for comparing coagulability in groups.Results: Changes of coagulation at T1 in all groups were not significant. Mean (±SD) of coagulation tests at different times in all groups were statistically significant in PT(P=0.001), PTT(P=0.001), and CT(P=0.001) and not significant in BT & PLT(P>0.05).Conclusion: No differences between NS, R & RL were seen in coagulation tests and coagulability. However, hypercoagulability states were seen after hemodilution.