Search results for: pectoral muscle sliding window algorithm (PMSWA)

Authors: Conor Mccartney, Mark Lee

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Background: An essential component in ambulatory breast augmentation surgery is good analgesia. The demographic undergoing this operation is usually fit, low risk with few comorbidities. These patients do not require long-term hospitalization and do not want to spend excessive time in the hospital for financial reasons. Opiate analgesia can have significant side effects such as nausea, vomiting and sedation. Reducing volumes of postoperative opiates allows faster ambulation and discharge from day surgery. We have developed two targeted nerve blocks that can be applied by the operating surgeon in a matter of seconds under direct vision, not requiring imaging. Anecdotally we found that these targeted nerve blocks reduced opiate requirements and allowed accelerated discharge and faster return to normal activities. This was then tested in a prospective randomized, double-blind trial. Methods: 20 patients were randomized into saline (n = 10) or Ropivicaine adrenaline solution (n = 10). The operating surgeon and anesthetist were blinded to the solution. All patients were closely followed up and morphine equivalents were accurately recorded. Follow-up pain scores were recorded using the Overall Benefit of Analgesia pain questionnaire. Findings: The Ropivicaine nerve blocks significantly reduced opiate requirements postoperatively (p<0.05). Pain scores were significantly decreased in the study group (p<0.05). There were no side effects attributable to the nerve blocks. Conclusions: Intraoperative targeted nerve blocks significantly reduce postoperative opiate requirements in breast augmentation surgery. This results in faster recovery and higher patient satisfaction.

Keywords: breast augmentation, nerve block, postoperative recovery, opiate analgesia, inter pectoral block, sub serratus block

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Authors: S. Djebali, S. Larbi, A. Bilek

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The present work aims at contributing to the study of the complex phenomenon of wear of pin on disc contact in dry sliding friction between two material couples (bronze/steel and unsaturated polyester virgin and charged with graphite powder/steel). The work consists of the determination of the coefficient of friction, the study of the influence of the tribological parameters on this coefficient and the determination of the mass loss and the wear rate of the pin. This study is also widened to the highlighting of the influence of the addition of graphite powder on the tribological properties of the polymer constituting the pin. The experiments are carried out on a pin-disc type tribometer that we have designed and manufactured. Tests are conducted according to the standards DIN 50321 and DIN EN 50324. The discs are made of annealed XC48 steel and quenched and tempered XC48 steel. The main results are described here after. The increase of the normal load and the sliding speed causes the increase of the friction coefficient, whereas the increase of the percentage of graphite and the hardness of the disc surface contributes to its reduction. The mass loss also increases with the normal load. The influence of the normal load on the friction coefficient is more significant than that of the sliding speed. The effect of the sliding speed decreases for large speed values. The increase of the amount of graphite powder leads to a decrease of the coefficient of friction, the mass loss and the wear rate. The addition of graphite to the UP resin is beneficial; it plays the role of solid lubricant.

Keywords: bronze, friction coefficient, graphite, mass loss, polyester, steel, wear rate

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using backpropagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a two-term algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: neural network, backpropagation, local minima, fast convergence rate

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Authors: Christopher Viens, Bosko Gajic, Steve Krase

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Stick-Slip is a term that is often overused and commonly diagnosed from surface drilling parameters of torque and differential pressure, but the actual magnitude of the condition is rarely captured at the BHA level as the necessary measurements are seldom deployed. Deployment of an accurate stick-slip measurement downhole has led to an interesting discovery that goes against long held traditional drilling lore. A divide has been identified between stick-slip as independent bit and BHA conditions. This phenomenon in horizontal laterals is common, but few M/LWD systems have been able to capture it. Utilizing measurements of downhole RPM bore pressure, high-speed magnetometer data, bending moment, and continuous inclination, the wellbore spiraling phenomenon is able to be captured, quantified, and intimately tied back to systematic effects of BHA stalling and micro-sliding. An operator in the Permian Basin has identified that this phenomenon is contributing to increased tortuosity and drag. Utilizing downhole torque measurements the root causes of the stick-slip and spiraling phenomenon were identified and able to engineered out of the system.

Keywords: bending moment, downhole dynamics measurements, micro sliding, wellbore spiraling

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Authors: Chengcao Sun, Cuili Yang, Shujun Li, Ruilin Xue, Yongyong Xi, Liang Wang, Dejia Li

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Backgrounds: Inflammation is widely distributed in patients with Duchenne muscular dystrophy (DMD), and ultimately leads to progressive deterioration of muscle function with the co-effects of chronic muscle damage, oxidative stress, and reduced oxidative capacity. NF-E2-related factor 2 (Nrf2) plays a critical role in defending against inflammation in different tissues via activation of phase II enzymes, heme oxygenase-1 (HO-1). However, whether Nrf2/HO-1 pathway can attenuate muscle inflammation on DMD remains unknown. The purpose of this study was to determine the anti-inflammatory effects of Sulforaphane (SFN) on DMD. Methods: 4-week-old male mdx mice were treated with SFN by gavage (2 mg/kg body weight per day) for 4 weeks. Gastrocnemius, tibial anterior and triceps brachii muscles were collected for related analysis. Immune cell infiltration in skeletal muscles was analyzed by H&E staining and immuno-histochemistry. Moreover, the expressions of inflammatory cytokines,pro-inflammatory cytokines and Nrf2/HO-1 pathway were detected by western blot, qRT-PCR, immunohistochemistry and immunofluorescence assays. Results: Our results demonstrated that SFN treatment increased the expression of muscle phase II enzymes HO-1 in Nrf2 dependent manner. Inflammation in mdx skeletal muscles was reduced by SFN treatment as indicated by decreased immune cell infiltration and lower expressions of the inflammatory cytokines CD45, pro-inflammatory cytokines tumour necrosis factor-α and interleukin-6 in the skeletal muscles of mdx mice. Conclusions: Collectively, these results show that SFN can ameliorate muscle inflammation in mdx mice by Nrf2/HO-1 pathway, which indicates Nrf2/HO-1 pathway may represent a new therapeutic target for DMD.

Keywords: sulforaphane, Nrf2, HO-1, inflammation

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Authors: Tudor Deaconescu, Andrea Deaconescu

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Deployment of pneumatic muscles in various industrial applications is still in its early days, considering the relative newness of these components. The field of robotics holds particular future potential for pneumatic muscles, especially in view of their specific behaviour known as compliance. The paper presents and discusses an innovative constructive solution for a gripper system mountable on an industrial robot, based on actuation by a linear pneumatic muscle and transmission of motion by gear and rack mechanism. The structural, operational and constructive models of the new gripper are presented, along with some of the experimental results obtained subsequently to the testing of a prototype. Further presented are two control variants of the gripper system, one by means of a 3/2-way fast-switching solenoid valve, the other by means of a proportional pressure regulator. Advantages and disadvantages are discussed for both variants.

Keywords: gripper system, pneumatic muscle, structural modelling, robotics

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Kevin Worrall, Euan McGookin

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The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Soheil Arash Moghadam, Abdol R. Kashani Nia, Ali Akrami Zade

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Considering numerous applications of Autonomous Underwater Vehicles in various industries, there has been plenty of researches and studies on the motion control of such vehicles. One of the useful aspects for studying is the guidance of these vehicles. In this paper, while presenting motion equations with six degrees of freedom for Autonomous Underwater Vehicles, Proportional Navigation Guidance Law and the first order sliding mode control for TAIPAN AUV was used to address its guidance for the purpose of collision with a moving target.

Keywords: Autonomous Underwater Vehicle (AUV), degree of freedom (DOF), hydrodynamic, line of sight(LOS), proportional navigation guidance(PNG), sliding mode control(SMC)

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Authors: Shivan N. Hussein, Ihsan K. Zangana

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A total of 2358 sheep and 532 goats were examined for the presence of macrocystis of Sarcocystis. For microcysts, different muscle tissues were randomly taken from 118 sheep and 110 goats. Macrocystis were examined through naked eye inspection, while microcysts were examined microscopically by using histopathology, pepsin digestion, mincing & squeezing, and muscle squash method. Overall prevalence of macrocystis was 1.2% in sheep and 2.6% in goats. The intensity rate of the cysts was 4 cysts/ gram in sheep & 3 cysts/ gram in goats, respectively, while the overall prevalence of microcysts in sheep and goats was 96.5%. The infection rate in sheep was 96.6% and in goats was 96.4%. The total intensity rate of microcysts was 32.4 cysts/ field in sheep and 16.8 cysts/ field in goats, respectively. Histopathological examination found different shapes, size, wall thickness, and intensity rates of microcysts in muscle tissues of sheep & goats. The pathological reaction showed mild to moderate granulocytosis, and mononuclear cells infiltrated surrounding the microcysts with necrotizing and degeneration of myofibrils. The largest average size of spindle and round shaped cysts (290 ± 89.7 x 76.1 ± 10 µm and 88.8 ± 10.3 µm) in goats and (127.2 ± 18.9 x 53.3 ± 5.4 µm and 74.4 ± 7.5 µm) in sheep, was detected in the esophageal muscle. Statistically, there was a significant difference (p < 0.05) in the prevalence of macrocystis in sheep and goats, while no significant difference (p > 0.05) was observed in the prevalence of microcysts between both animal species.

Keywords: macrocystis, microcysts, intensity rate, measurement size

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Hřebíčková Sylva, Grasgruber Pavel, Ondráček Jan, Cacek Jan, Kalina Tomáš

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The aim of this study was to describe typical changes in several parameters of body composition – the amount of skeletal muscle mass (SMM), % body fat (BF) and body mass index (BMI) - in selected age categories (30+ years) of men and women in the Czech Republic, depending on the degree of sports activity. Study (n = 823, M = 343, F = 480) monitored differences in BF, SM and BMI in five age groups (from 30-39 years to 70+ years). Physically inactive individuals have (p < 0.05) higher % BF in comparison with physically active individuals (29.5 ± 0.59 vs. 27 ± 0.38%), higher BMI (27.3 ± 0.32 vs. 26.1 ± 0.20 kg/m2), but lower SM (39.0 ± 0.33 vs. 40.4 ± 0.21%). The results indicate that with an increasing age, there is a trend towards increasing values of BMI and % BF, and decreasing values of SMM.

Keywords: body composition, body fat, physical activity, skeletal muscle

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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Authors: Minjung Maing, Sibei Liu

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This research discusses the results of a study of window opening behavior of large housing developments in the high-density megacity of Hong Kong. The methods used for the study involved field observations using photo documentation of the four cardinal elevations (north, south-east, and west) of two large housing developments in a very dense urban area of approx. 46,000 persons per square meter within the city of Hong Kong. The targeted housing developments (A and B) are large public housing with a population of about 13,000 in each development of lower income. However, the mean income level in development A is about 40% higher than development B and home ownership is 60% in development A and 0% in development B. Mapping of the surrounding amenities and layout of the developments were also studied to understand the available activities to the residents. The photo documentation of the elevations was taken from November 2016 to February 2018 to gather a full spectrum of different seasons and both in the morning and afternoon (am/pm) times. From the photograph, the window opening behavior was measured by counting the amount of windows opened as a percentage of all the windows on that façade. For each date of survey data collected, weather data was recorded from weather stations located in the same region to collect temperature, humidity and wind speed. To further understand the behavior, simulation studies of microclimate conditions of the housing development was conducted using the software ENVI-met, a widely used simulation tool by researchers studying urban climate. Four major conclusions can be drawn from the data analysis and simulation results. Firstly, there is little change in the amount of window opening during the different seasons within a temperature range of 10 to 35 degrees Celsius. This means that people who tend to open their windows have consistent window opening behavior throughout the year and high tolerance of indoor thermal conditions. Secondly, for all four elevations the lower-income development B opened more windows (almost two times more units) than higher-income development A meaning window opening behavior had strong correlations with income level. Thirdly, there is a lack of correlation between outdoor horizontal wind speed and window opening behavior, as the changes of wind speed do not seem to affect the action of opening windows in most conditions. Similar to the low correlation between horizontal wind speed and window opening percentage, it is found that vertical wind speed also cannot explain the window opening behavior of occupants. Fourthly, there is a slightly higher average of window opening on the south elevation than the north elevation, which may be due to the south elevation being well shaded from high angle sun during the summer and allowing heat into units from lower angle sun during the winter season. These findings are important to providing insight into how to better design urban environments and indoor thermal environments for a liveable high density city.

Keywords: high-density housing, subtropical climate, urban behavior, window opening

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Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp

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Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.

Keywords: sprint, training, performance, exercise

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Authors: S. Sonkham, U. Pinsopon, W. Chatlatanagulchai

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This paper presents a method of sliding mode control (SMC) designing and developing for the servo system in a dual-stage actuator (DSA) hard disk drive. Mathematical modelling of hard disk drive actuators is obtained, extracted from measuring frequency response of the voice-coil motor (VCM) and PZT micro-actuator separately. Matlab software tools are used for mathematical model estimation and also for controller design and simulation. A model-reference approach for tracking requirement is selected as a proposed technique. The simulation results show that performance of a model-reference SMC controller design in DSA servo control can be satisfied in the tracking error, as well as keeping the positioning of the head within the boundary of +/-5% of track width under the presence of internal and external disturbance. The overall results of model-reference SMC design in DSA are met per requirement specifications and significant reduction in %off track is found when compared to the single-state actuator (SSA).

Keywords: hard disk drive, dual-stage actuator, track following, hdd servo control, sliding mode control, model-reference, tracking control

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Authors: Shaban Saad, Syed Ahmed, Suher Aburawi, Isabel Fong

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Ruta graveolens is a plant commonly found in north Africa and south Europe. It is reported that Ruta graveolens is used traditionally for epilepsy and some other illnesses. The acute and sub-acute effects of alcoholic extract residue were tested for possible anti-epileptic and skeletal muscle relaxation activity. The effect of extract on rat spontaneous motor activity (SMA) was also investigated using open filed. We previously proved the anti convulsant activity of the plant against pentylenetetrazol and electrically induced convulsions. Therefore in this study strychnine was used to induce convulsions in order to explore the mechanism of anti-convulsant activity of the plant. The skeletal muscle relaxation activity of Ruta graveolens was studied using pull-up and rod hanging tests in rats. At concentration of 5%w/v the extract protected mice against strychnine induced myoclonic jerks and death. The pull-up and rod hanging tests pointed to a skeletal muscle relaxant activity at higher concentrations. Ruta graveolens extract also significantly decreased the number of squares visited by rats in open field apparatus at all tested concentrations (3.5-20%w/v). However, the significant decrease in number of rearings was only noticed at concentrations of (15 and 20%w/v). The results indicate that Ruta graveolens contains compound(s) capable to inhibit convulsions, decrease SMA and/or diminish skeletal muscle tone in animal models. This data and the previously generated data together point to a general depression trend of CNS produced by Ruta graveolens.

Keywords: Ruta graveolens, open field, skeletal muscle relaxation

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Authors: Thomas Yeboah

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Cloud Computing is newly paradigm in computing that promises a delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a utility (like the electricity grid) over a network (typically the Internet). As Cloud Computing is a newly style of computing on the internet. It has many merits along with some crucial issues that need to be resolved in order to improve reliability of cloud environment. These issues are related with the load balancing, fault tolerance and different security issues in cloud environment.In this paper the main concern is to develop an effective load balancing algorithm that gives satisfactory performance to both, cloud users and providers. This proposed algorithm (hybrid Bee Ant Colony algorithm) is a combination of two dynamic algorithms: Ant Colony Optimization and Bees Life algorithm. Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues whiles the Bees Life algorithm is used for optimization of job scheduling in cloud environment. The results of the proposed algorithm shows that the hybrid Bee Ant Colony algorithm outperforms the performances of both Ant Colony algorithm and Bees Life algorithm when evaluated the proposed algorithm performances in terms of Waiting time and Response time on a simulator called CloudSim.

Keywords: ant colony optimization algorithm, bees life algorithm, scheduling algorithm, performance, cloud computing, load balancing

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Authors: Vahid Anari, Leila Shahmohammadi

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Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: digital pathology, cell segmentation, immunohistochemically, noise reduction

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Authors: Sardar Ameer Akram Khan, Shahzad Amin Sheikh

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Blind equalization is an important technique amongst equalization family. Multimodulus algorithms based on blind equalization removes the undesirable effects of ISI and cater ups the phase issues, saving the cost of rotator at the receiver end. In this paper a new algorithm combination of recursive least square and Multimodulus algorithm named as RLSMMA is proposed by providing few assumption, fast convergence and minimum Mean Square Error (MSE) is achieved. The excellence of this technique is shown in the simulations presenting MSE plots and the resulting filter results.

Keywords: blind equalizations, constant modulus algorithm, multi-modulus algorithm, recursive least square algorithm, quadrature amplitude modulation (QAM)

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Authors: Safa Adi

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This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: database, GTC algorithm, PSP algorithm, sequential patterns, time constraints

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Authors: Ali Nourollah, Mohsen Movahedinejad

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In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

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Authors: Che Hsiu Chen, Su Yun Chen, Hon Wen Cheng

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Traditional core stability, core endurance, and balance exercises on a stable surface with isometric muscle actions, low loads, and multiple repetitions, which may not improvements the swimming and running economy performance. However, the effects of high intensity core muscle exercise training on jump height, sprint, and aerobic fitness remain unclear. The purpose of this study was to examine whether high intensity core muscle exercises training could improve sport performances in dancers. Thirty healthy university dancer students (28 women and 2 men; age 20.0 years, height 159.4 cm, body mass 52.7 kg) were voluntarily participated in this study, and each participant underwent five suspension exercises (e.g., hip abduction in plank alternative, hamstring curl, 45-degree row, lunge and oblique crunch). Each type of exercise was performed for 30-second, with 30-second of rest between exercises, two times per week for eight weeks and each exercise session was increased by 10-second every week. We measured agility, explosive force, anaerobic and cardiovascular fitness in dancer performance before and after eight weeks of training. The results showed that the 8-week high intensity core muscle training would significantly increase T-test agility (7.78%), explosive force of acceleration (3.35%), vertical jump height (8.10%), jump power (6.95%), lower extremity anaerobic ability (7.10%) and oxygen uptake efficiency slope (4.15%). Therefore, it can be concluded that eight weeks of high intensity core muscle exercises training can improve not only agility, sprint ability, vertical jump ability, anaerobic and but also cardiovascular fitness measures as well.

Keywords: balance, jump height, sprint, maximal oxygen uptake

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Authors: Ying Li, Yan Li

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A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

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Authors: Wullapa Wongsinlatam

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Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Camila Lemos Pinto, Juliana Alves Carneiro, Patrícia Borges Botelho, João Felipe Mota

Abstract:

Sarcopenia, a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, currently affects over 50 million people and increases the risk of adverse outcomes such as physical disability, poor quality of life and death. The aim of this study was to examine the efficacy of creatine supplementation associated with resistance training on muscle mass in the elderly. A 12-week, double blind, randomized, parallel group, placebo controlled trial was conducted. Participants were randomly allocated into one of the following groups: placebo with resistance training (PL+RT, n=14) and creatine supplementation with resistance training (CR + RT, n=13). The subjects from CR+RT group received 5 g/day of creatine monohydrate and the subjects from the PL+RT group were given the same dose of maltodextrin. Participants were instructed to ingest the supplement on non-training days immediately after lunch and on training days immediately after resistance training sessions dissolved in a beverage comprising 100 g of maltodextrin lemon flavored. Participants of both groups undertook a supervised exercise training program for 12 weeks (3 times per week). The subjects were assessed at baseline and after 12 weeks. The primary outcome was muscle mass, assessed by dual energy X-ray absorptiometry (DXA). The secondary outcome included diagnose participants with one of the three stages of sarcopenia (presarcopenia, sarcopenia and severe sarcopenia) by skeletal muscle mass index (SMI), handgrip strength and gait speed. CR+RT group had a significant increase in SMI and muscle (p<0.0001), a significant decrease in android and gynoid fat (p = 0.028 and p=0.035, respectively) and a tendency of decreasing in body fat (p=0.053) after the intervention. PL+RT only had a significant increase in SMI (p=0.007). The main finding of this clinical trial indicated that creatine supplementation combined with resistance training was capable of increasing muscle mass in our elderly cohort (p=0.02). In addition, the number of subjects diagnosed with one of the three stages of sarcopenia at baseline decreased in the creatine supplemented group in comparison with the placebo group (CR+RT, n=-3; PL+RT, n=0). In summary, 12 weeks of creatine supplementation associated with resistance training resulted in increases in muscle mass. This is the first research with elderly of both sexes that show the same increase in muscle mass with a minor quantity of creatine supplementation in a short period. Future long-term research should investigate the effects of these interventions in sarcopenic elderly.

Keywords: creatine, dietetic supplement, elderly, resistance training

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Authors: Che Hsiu Chen, Kuo Wei Tseng, Zih Jian Huang, Hon Wen Cheng

Abstract:

A typical warm-up contains both stretching exercises and jogging. The static stretching prior to training or competition may cause detrimental effects to athletic performance. However, it is unclear whether different types of dynamic stretching exercises had different acute effects on knee flexors stiffness, flexibility, and strength. The purpose of this study was to analyze the knee flexors stiffness, flexibility, and strength gains after dynamic straight leg raise (DSLR) and dynamic modified toe-touch (MTT) stretching. Sixteen healthy university active men (height 176.27 ± 4.03 cm; weight 72.27 ± 8.90 kg; age 22.09 ± 2.31 years). After 5 minutes (8km/h) of running subjects performed 2 randomly ordered stretching protocols: DSLR and MTT stretching protocols. There were a total of six, 30 seconds bouts of dynamic stretching (15 repetitions) with 30seconds rest between bouts. The outcome measures were maximal voluntary isokinetic concentric hamstring strength (60°/s), muscle flexibility test by passive straight leg raise (PSLR), active straight leg raise (ASLR), and muscle stiffness using ultrasound Acoustic Radiation Forced Impulse (ARFI) elastography before and immediately after stretching. The muscle stiffness and concentric strength decreased significantly (p < .05), the flexibility no significant change after DSLR protocol (p > .05). The concentric strength decreased significantly (p < .05), the flexibility and muscle stiffness no significant change after MTT protocol (p > .05), whereas no significant differences were found for the DSLR and MTT. Our findings suggest that dynamic stretching (30s x 6 bouts) resulted in change in muscle stiffness or may be induced slack in the musculotendinous unit thereby, reducing force production. Therefore, 30s x 6 bouts of dynamic stretching adversely affects efforts of hamstring muscle maximal concentric strength.

Keywords: sport injury, ultrasound, eccentric exercise, performance

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Authors: Trevor R. Higgins

Abstract:

The aim of this study was to compare muscle activation of the latissimus dorsi between pin-loaded machine (Lat Pull Down), resistance band (Lat Pull Down) and body-weight (Chin Up) exercises. A convenient sample of male college students with >2 years resistance training experience volunteered for the study. A paired t-test with repeated measures designs was carried out on results from EMG analysis. EMG analysis was conducted with Trigno wireless sensors (Delsys) placed laterally on the latissimus dorsi (left and right) of each participant. By conventional criteria the two-tailed P value suggested that differences between pin-loaded and body-weight was not significantly different (p = 0.93) and differences between pin-loaded and resistance band was not significantly different (p = 0.17) in muscle activity. In relation to conventional criteria the two-tailed P value suggested differences between body-weight and resistance band was not quite significantly different (p = 0.06) in muscle activity. However, effect size trends indicated that both body-weight and pin-loaded exercises where more effective in stimulating muscle electrical activity than a resistance band with male college athletes with >2 years resistance training experience. Although, resistance bands have increased in popularity in health and fitness centres, that for well-trained participants, they may not be effective in stimulating muscles of the latissimus dorsi. Therefore, when considering equipment and exercise selection for experienced resistance training participants pin-loaded machines and body-weight should be prescribed.

Keywords: pin-loaded, resistance bands, body weight, EMG analysis

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