In the estimation of a probability density function (PDF) by kernel method, two inherent problems are the choice of sampling methods and the selection of a bandwidth. In this article, we use the balanced and unbalanced ranked set sampling (RSS) methods and Bayesian bandwidth to estimate a PDF by kernel method. To compare our method with existing methods, we use an extensive simulation study to compare the RSS with simple random sampling (SRS) PDF estimator and also Bayesian bandwidth with other existing bandwidths. As an application, we use the household expenses and income data of the Statistical Center of Iran in 2021 to estimate the PDF of the total expenses of the households in Tehran province.

As wireless networks with high data rate get widely deployed, improving the performance of TCP over these networks plays vital role. Wireless link losses have dramatic adverse impact on TCP performance due to the difficulty in distinguishing the congestion losses from wireless link losses. We first, studied the various existing Bandwidth Estimation Algorithms over the wireless networks. In this paper, we propose an enhanced bandwidth estimation technique with congestion control algorithms to improve TCP performance over wireless link with random loss. We propose, a new technique called TCP- BWIW to estimate the bandwidth and the congestion window is set accordingly. The performance of TCP-BWIW is analyzed, and it mitigates the Network congestion.

One of the obvious reasons for most disorders in network service provisioning is network path congestion. Congestion avoidance in today's networks is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN networks. At first, ESV-DBRA monitors the traffic load and delay of all network paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the network paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.

Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will be merged, and vice versa, they will remain fine with severe variability. Bandwidth variation can be effective in upscaling results. Therefore, determining the optimal bandwidth in this method is essential. For each bandwidth, the upscaled model has a number of upscaled blocks and an upscaling error. Obviously, higher thresholds or bandwidths cause a lower number of upscaled blocks and a higher sum of squares error (SSE). On the other hand, using the smallest bandwidth, the upscaled model will remain in a fine scale, and there will be practically no upscaling. In this work, different approaches are used to determine the optimal bandwidth or threshold for upscaling. Investigation of SSE changes, the intersection of two charts, namely SSE and the number of upscaled block charts, and the changes of SSE values versus bandwidths, are among these approaches. In this particular case, if the goal of upscaling is to minimize the upscaling error, the intersection method will obtain a better result. Conversely, if the purpose of upscaling is computational cost reduction, the SSE variation approach will be more appropriate for the threshold setting.

This paper presents a Transimpedance Amplifier (TIA) for high sensitivity Near Infrared Spectroscopy (NIRS). The proposed TIA is based on the Regulated Cascode (RGC) structure with an extra transistor employed to implement additional feed-forward path and achieve higher gain values. The extra transistor senses a partially amplified input signal, available in the conventional circuit, and conveys an additional ac current into the load, which provides a higher gain. In addition, a bandwidth extension method is introduced using a capacitor and resistor, which can improve amplifier’s bandwidth by 40%. The proposed TIA is designed in 0.18µm CMOS technology and achieves a transimpedance gain of 101.9dB with a -3dB bandwidth of 91.2 MHz considering 2pF of photodiode capacitance at the TIA input. The input referred noise is 4.4pA/√Hz while dissipating 151µW power.

The purpose of the present study was to examine the effects of Bandwidth Modeling on learning a simple timing task. Twenty eight right handed subjects (14 males, 14 females, aged 19-20) voluntarily participated in the study and were assigned randomly to two groups of bandwidth and yoked. The task was pressing the keys number 2, 6, 8 and 4 on a sequential timing apparatus while keeping certain absolute timing. People in the bandwidth group received the model whenever their performance went out from predetermined bandwidth around the goal movement time (a 10 percent bandwidth), while subjects in the other group were yoked with bandwidth group. The experiment consisted of acquisition, retention and transfer phases and absolute timing error was used as dependent variable. The results of retention and transfer tests showed that bandwidth group had less errors than yoked group. The findings of present experiment were in accordance with anticipations of Challenge Point Theory, and showed that bandwidth modeling is an appropriate technique for adjusting learning condition with learner’s needs. Also advantages of bandwidth method that in past just had been confirmed in KR presentation scheduling domain, nicely generalized to observational learning domain.

In this paper two recently developed meta-heuristic optimization methods, known as Colliding Bodies Optimization (CBO) and Enhanced Colliding Bodies Optimization (ECBO), are used for optimum nodal ordering to minimize bandwidth of sparse matrices. The CBO is a simple optimization algorithm which is inspired by a collision between two objects in one-dimension. Each agent is modeled as a body with a specified velocity and mass. A collision happens between pairs of bodies and the new positions of the colliding bodies are updated based on the collision laws. The enhanced colliding bodies optimization (ECBO) utilizes memory to save some best so-far-solution to improve the performance of the CBO without increasing the computational cost. This algorithm utilizes a mechanism to escape from local optima. The bandwidth of some graph matrices, which have equivalent pattern to structural matrices, is minimized using these approaches. Comparison of the obtained results with those of some existing methods shows the robustness of these two new meta-heuristic algorithms for bandwidth optimization.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

This study aimed to estimate the genetic parameters of body weight traits in Markhoz goats, using B-spline random regression models. The data used in this study included 19549 records collected during 29 years (1992-2021) in Markhoz goat Breeding Research Station, located in Sanandaj, Iran. The model used to analyze data included fixed effects (year of birth, sex, type of birth and age of dam) and random effects including direct additive genetic, maternal additive genetic, permanent environmental and maternal permanent environmental assuming homogeneous and heterogeneous residual variance during the time. Akaike (BIC) and Bayesian (BIC) information criteria were used to compare the models and bspq.4.4.4.4 was selected as the best model. The direct heritability values for birth, 3-month, 6-month, 9-month and 12-month weights were estimated to be 0.14, 0.16, 0.08, 0.28 and 0.26, respectively. Genetic correlation between body weights at birth and 3-month, birth and 6-month, birth and 9-month, birth and 12-month, 3-month and 6-month, 3-month and 9-month, 3-month and 12-month, 6-months and 9-month and 9-month and 12-month were 0.22, 0.38, 0.21, 0.56, -0.26, 0.30, 0.62, 0.86 and 0.77, respectively. The highest phenotypic correlation was between the weight of 9-month and 12-month (0.82) and the lowest correlation was between birth weight and 3-month and 6-month (0.12). The results showed that the 9-month weight is a good criterion for selection in Markhoz goats.