Background and Objectives: Object detection has been a fundamental issue in computer vision. Research findings indicate that object detection aided by convolutional neural NETWORKS (CNNs) is still in its infancy despite -having outpaced other methods . Methods: This study proposes a straightforward, easily implementable, and high-precision object detection method that can detect objects with minimum least error. Object detectors generally fall into one-stage and two-stage detectors . Unlike one-stage detectors, two-stage detectors are often more precise, despite performing at a lower speed. In this study, a one-stage detector is proposed, and the results indicated its sufficient precision . The proposed method uses a feature PYRAMID network (FPN) to detect objects on multiple scales . This network is combined with the ResNet 50 deep neural network. Results: The proposed method is trained and tested on Pascal VOC 2007 and COCO datasets. It yields a mean average precision (mAP) of 41.91 in Pascal Voc2007 and 60.07% in MS COCO. The proposed method is tested under additive noise. The test images of the datasets are combined with the salt and pepper noise to obtain the value of mAP for different noise levels up to 50% for Pascal VOC and MS COCO datasets. The investigations show that the proposed method provides acceptable results. Conclusion: It can be concluded that using deep learning algorithms and CNNs and combining them with a feature network can significantly enhance object detection precision.

Background and Aim: Athletes usePyarmid and Reverse PYRAMID loadings in resistance training to increase training load. Although researches have shown that each loading is effective in increasing strength and muscle mass, from the viewpoint of risk of injury and biomechanics, the differences between these two patterns on athletic performance have not been fully understood. The purpose of the current study was to examine muscular electromyography during deadlift in PYRAMID and reverse PYRAMID loadings. Materials and Methods: A total of 15 amateur female bodybuilders voluntarily participated in the current study taking part in five Repeated Maximum (5RM) calculation test as well as deadlift test with PYRAMID and reverse PYRAMID loading at 60%, 80%, and 100% of 5 RM during three days with 48 hours rest. Rectus Femoris, Vastus Medialis, Biceps Femoris, Tibialis Anterior, Gastrocnemius, Gluteus Maximus, and Erector Spine EMG were collected using MyoMuscle Noraxon system at 1500 Hz frequency during deadlift tasks. The muscular IEMG and hamstring to quadriceps co-contraction during five squat repeats were calculated and compared in similar loads during PYRAMID and reverse PYRAMID loadings. Results: The results of dependent t-test showed that lower extremity muscular EMG did not have significant differences in similar loads at PYRAMID and reverse PYRAMID loadings (P > 0. 05); however, hamstring to quadriceps co-contraction was significantly higher in PYRAMID compared with reverse PYRAMID in similar loadings (P ≤ 0. 05). Conclusion: According to the results, both PYRAMID and reverse PYRAMID loadings in deadlift can cause similar muscular activation in females, and female athletes and coaches can use both these methods to increase muscular force capacity. However, because of higher hamstring to quadriceps co-contraction in PYRAMID, compared with reverse PYRAMID loading, it seems that using PYRAMID loading is more reasonable to increasing joint stability and reducing injuries.

We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio NETWORKS (CRNs) based on simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect channel state information (CSI) on the CBS-PU link.

Background and Aims PYRAMID and reverse PYRAMID loading patterns are used to increase the training load in resistance training. Although physiological studies have attempted to compare the two patterns, the difference between the two loading patterns on the biomechanics of the spine and pelvis has not been determined. This study aimed to investigate the effect of PYRAMID and inverted PYRAMID loadings on spinal and pelvic coordination variability in squat movement. Methods Twelve bodybuilding athletes in Tehran City, Iran, voluntarily participated in this study. The subjects performed squat movements as the PYRAMID and reverse PYRAMID at intensities of 50%, 70%, and 90% of ten maximum repetitions. Then, the kinematic information of the three segments of their spine and pelvis was recorded. Coordination and variability coordination were calculated using a modified vector coding method. Results The results of repeated measures analysis of variance showed a significant difference in the coordination pattern for pelvic-lower back coordination, lower-back to lower-trunk spine, and lower-trunk-to-upper-trunk spine in the intensity of 50%. A significant difference was observed in the coordination pattern, with an intensity of 70% for the lower back and lower trunk spine. Also, no statistical significance was observed between the PYRAMIDal and inverted PYRAMIDal loading types for spine and pelvis coordination. Conclusion According to the results of increasing the load in PYRAMID loading and decreasing the load in reverse loading, the coordination of distal couplings affected the sagittal plane more than the proximal one. It is recommended to use the reverse PYRAMID method for exercises and be more careful when performing PYRAMID exercises.

Background and Aim: Pyarmid and Reverse PYRAMID loadings are used in resistance training to increase training load. Although physiological researches have tried to compare these two patterns, the differences between these two patterns on lower extremity joints biomechanics from injury risk have not been understood. The purpose of the present research was to compare hip and knee kinematics during squat at PYRAMID and reverse PYRAMID loading. Materials and Methods: A total of 15 amateur bodybuilders from Karaj city voluntarily participated in five Repeated Maximum (5RM) calculation tests as well as a squat test with PYRAMID and reverse PYRAMID loading at 60%, 80%, and 100% of 5RM during three days with 48 hours interval. Hip and knee three-dimensional angles were registered with MyoMotion Noraxon motion capture system at 100 Hz frequency during squat tasks. The mean value for peak hip flexion, adduction, and internal rotation, as well as knee flexion and valgus during five squat repeats, were calculated and compared in similar loads during two kinds of PYRAMID and reverse PYRAMID loadings. Results: The results of dependent t-test showed that peak hip flexion, adduction, and internal rotation, as well as knee flexion and valgus at similar loads, had significant increase in reverse PYRAMID loading compared with PYRAMID loading (P ≤ 0. 05). Conclusion: According to the results of the present study, since the increase in peak value of examined angles is an indicator for increase knee joint injuries, regarding the increase in these peak angles during reverse PYRAMID loading as compared with PYRAMID loading, it is suggested that coaches and amateur athletes use PYRAMID loading during their trainings.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social NETWORKS. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these NETWORKS. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

The use of wavelets in denoising, seems to be an advantage in representing well the details. However, the edges are not so well preserved. Total variation technique has advantages over simple denoising techniques such as linear smoothing or median filtering, which reduce noise, but at the same time smooth away edges to a greater or lesser degree.In this paper, an efficient denoising method based on Total Variation model (TV), and Dual-Tree Complex Wavelet Transform (DTCWT) is proposed to incorporate both properties. In our method, TV is employed to refine low-passed coefficients and DTCWT is used to shrink high-passed noisy coefficients to achieve more accurate image recovery. The efficiency of our approach is firstly analyzed by comparing the results with well-known methods such as probShrink, BLS-GSM, SUREbivariate, NL-Means and TV model.Secondly, it is compared to some denoising methods, which have been reported recently.Experimental results show that the proposed method outperforms the Steerable PYRAMID denoising by 8.5% in terms of PSNR and 17.5% in terms of SSIM for standard images.Obtained results convince us that the proposed scheme provides a better performance in noise blocking among reported state-of-the-art methods.

To Editor, As final-year doctoral students of medical education, we have been studying numerous articles citing Edgar Dale’, s learning PYRAMID,therefore, Masters’,perspective on this topic is fascinating to us. 1 According to Masters, increased citations of the Learning PYRAMID are likely caused by poor referencing practices such as failing to study primary sources, misreading articles, or citing rebuttals of the PYRAMID. However, Masters believes that the increased citations of the PYRAMID are primarily due to the authors’,politically conservative styles. Thus, treating the PYRAMID as worthless does not seem appropriate in academic works.