Abstract: Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.
Abstract: The principal objective of this study is the evaluation of the seismic performance of reinforced concrete frame structures, taking into account of the behavior laws, reflecting the real behavior of materials, using CASTEM2000 software. A finite element model used is based in modified Takeda model with Timoshenko elements for columns and beams. This model is validated on a Vecchio experimental reinforced concrete (RC) frame model. Then, a study focused on the behavior of a RC frame with three-level and three-story in order to visualize the positioning the plastic hinge (plastic rotation), determined from the curvature distribution along the elements. The results obtained show that the beams of the 1st and 2nd level developed a very large plastic rotations, or these rotations exceed the values corresponding to CP (Collapse prevention with cp qCP = 0.02 rad), against those developed at the 3rd level, are between IO and LS (Immediate occupancy and life Safety with qIO = 0.005 rad and rad qLS = 0.01 respectively), so the beams of first and second levels submit a very significant damage.
Abstract: Piezoelectric linear motors have the characteristics of great electromagnetic compatibility, high positioning accuracy, compact structure and no deceleration mechanism, which make it promising to applicate in micro-miniature precision drive systems. However, most piezoelectric motors are employed by flexible clamping, which has insufficient rigidity and is difficult to use in rapid positioning. Another problem is that this clamping method seriously affects the vibration efficiency of the vibrating unit. In order to solve these problems, this paper proposes a piezoelectric stack linear motor based on double-end rigid clamping. First, a piezoelectric linear motor with a length of only 35.5 mm is designed. This motor is mainly composed of a motor stator, a driving foot, a ceramic friction strip, a linear guide, a pre-tightening mechanism and a base. This structure is much simpler and smaller than most similar motors, and it is easy to assemble as well as to realize precise control. In addition, the properties of piezoelectric stack are reviewed and in order to obtain the elliptic motion trajectory of the driving head, a driving scheme of the longitudinal-shear composite stack is innovatively proposed. Finally, impedance analysis and speed performance testing were performed on the piezoelectric linear motor prototype. The motor can measure speed up to 25.5 mm/s under the excitation of signal voltage of 120 V and frequency of 390 Hz. The result shows that the proposed piezoelectric stacked linear motor obtains great performance. It can run smoothly in a large speed range, which is suitable for various precision control in medical images, aerospace, precision machinery and many other fields.
Abstract: The aim of this study is to assesses the lifting capabilities of persons experiencing hypoxia. It also examines the behavior of the physiological response induced through the lifting process related to changing in the hypoxia and lifting frequency variables. For this purpose, the study performed two consecutive tests by using; (1) training and acclimatization; and (2) an actual collection of data. A total of 10 male students from King Saud University, Kingdom of Saudi Arabia, were recruited in the study. A two-way repeated measures design, with two independent variables (ambient oxygen (15%, 18% and 21%)) and lifting frequency (1 lift/min and 4 lifts/min) and four dependent variables i.e., maximum acceptable weight of lift (MAWL), Electromyography (EMG) of four muscle groups (anterior deltoid, trapezius, biceps brachii, and erector spinae), rating of perceived exertion (RPE), and rating of oxygen feeling (ROF) were used in this study. The results show that lifting frequency has significantly impacted the MAWL and muscles’ activities. The oxygen content had a significant effect on the RPE and ROE. The study has revealed that acclimatization and training sessions significantly reduce the effect of the hypoxia on the human physiological parameters during the manual materials handling tasks.
Abstract: Almost all of the domestic refrigerators operate on the principle of the vapor compression refrigeration cycle and removal of heat from the refrigerator cabinets is done via one of the two methods: natural convection or forced convection. In this study, airflow and temperature distributions inside a 375L no-frost type larder cabinet, in which cooling is provided by forced convection, are evaluated both experimentally and numerically. Airflow rate, compressor capacity and temperature distribution in the cooling chamber are known to be some of the most important factors that affect the cooling performance and energy consumption of a refrigerator. The objective of this study is to evaluate the original temperature distribution in the larder cabinet, and investigate for better temperature distribution solutions throughout the refrigerator domain via system optimizations that could provide uniform temperature distribution. The flow visualization and airflow velocity measurements inside the original refrigerator are performed via Stereoscopic Particle Image Velocimetry (SPIV). In addition, airflow and temperature distributions are investigated numerically with Ansys Fluent. In order to study the heat transfer inside the aforementioned refrigerator, forced convection theories covering the following cases are applied: closed rectangular cavity representing heat transfer inside the refrigerating compartment. The cavity volume has been represented with finite volume elements and is solved computationally with appropriate momentum and energy equations (Navier-Stokes equations). The 3D model is analyzed as transient, with k-ε turbulence model and SIMPLE pressure-velocity coupling for turbulent flow situation. The results obtained with the 3D numerical simulations are in quite good agreement with the experimental airflow measurements using the SPIV technique. After Computational Fluid Dynamics (CFD) analysis of the baseline case, the effects of three parameters: compressor capacity, fan rotational speed and type of shelf (glass or wire) are studied on the energy consumption; pull down time, temperature distributions in the cabinet. For each case, energy consumption based on experimental results is calculated. After the analysis, the main effective parameters for temperature distribution inside a cabin and energy consumption based on CFD simulation are determined and simulation results are supplied for Design of Experiments (DOE) as input data for optimization. The best configuration with minimum energy consumption that provides minimum temperature difference between the shelves inside the cabinet is determined.
Abstract: Dimensionality reduction and feature extraction are of
crucial importance for achieving high efficiency in manipulating
the high dimensional data. Two-dimensional discriminant locality
preserving projection (2D-DLPP) and two-dimensional discriminant
supervised LPP (2D-DSLPP) are two effective two-dimensional
projection methods for dimensionality reduction and feature
extraction of face image matrices. Since 2D-DLPP and 2D-DSLPP
preserve the local structure information of the original data and
exploit the discriminant information, they usually have good
recognition performance. However, 2D-DLPP and 2D-DSLPP
only employ single-sided projection, and thus the generated low
dimensional data matrices have still many features. In this paper,
by combining the discriminant supervised LPP with the bidirectional
projection, we propose the bidirectional discriminant supervised LPP
(BDSLPP). The left and right projection matrices for BDSLPP can
be computed iteratively. Experimental results show that the proposed
BDSLPP achieves higher recognition accuracy than 2D-DLPP,
2D-DSLPP, and bidirectional discriminant LPP (BDLPP).
Abstract: In geophysical exploration surveys, the quality of acquired data holds significant importance before executing the data processing and interpretation phases. In this study, 2D seismic reflection survey data of Fort Abbas area, Cholistan Desert, Pakistan was taken as test case in order to assess its quality on statistical bases by using normalized root mean square error (NRMSE), Cronbach’s alpha test (α) and null hypothesis tests (t-test and F-test). The analysis challenged the quality of the acquired data and highlighted the significant errors in the acquired database. It is proven that the study area is plain, tectonically least affected and rich in oil and gas reserves. However, subsurface 3D modeling and contouring by using acquired database revealed high degrees of structural complexities and intense folding. The NRMSE had highest percentage of residuals between the estimated and predicted cases. The outcomes of hypothesis testing also proved the biasness and erraticness of the acquired database. Low estimated value of alpha (α) in Cronbach’s alpha test confirmed poor reliability of acquired database. A very low quality of acquired database needs excessive static correction or in some cases, reacquisition of data is also suggested which is most of the time not feasible on economic grounds. The outcomes of this study could be used to assess the quality of large databases and to further utilize as a guideline to establish database quality assessment models to make much more informed decisions in hydrocarbon exploration field.
Abstract: The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.
Abstract: Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.
Abstract: Bone metastases are observed in a wide range of cancers leading to intolerable pain. While early detection can help the physicians in the decision of the type of treatment, various radiopharmaceuticals using phosphonates like 68Ga-EDTMP have been developed. In this work, due to the importance of absorbed dose, human absorbed dose of this new agent was calculated for the first time based on biodistribution data in Wild-type rats. 68Ga was obtained from 68Ge/68Ga generator with radionuclidic purity and radiochemical purity of higher than 99%. The radiolabeled complex was prepared in the optimized conditions. Radiochemical purity of the radiolabeled complex was checked by instant thin layer chromatography (ITLC) method using Whatman No. 2 paper and saline. The results indicated the radiochemical purity of higher than 99%. The radiolabelled complex was injected into the Wild-type rats and its biodistribution was studied up to 120 min. As expected, major accumulation was observed in the bone. Absorbed dose of each human organ was calculated based on biodistribution in the rats using RADAR method. Bone surface and bone marrow with 0.112 and 0.053 mSv/MBq, respectively, received the highest absorbed dose. According to these results, the radiolabeled complex is a suitable and safe option for PET bone imaging.
Abstract: Asthma, obesity and overweight are the main factors causing change within the heart and respiratory airways. Asthma symptoms are normally observed during exercising. Epidemiological studies have indicated asthma symptoms occurring due to certain lifestyle habits; for example, a sedentary lifestyle. In this study, eight weeks of aerobic exercises resulted in a positive effect overall in overweight women experiencing mild chronic asthma. The quasi-experimental applied research has been done based on experimental and control groups. The experimental group (seven patients) and control group (n = 7) were graded before and after the test. According to the Borg dyspnea and fatigue Perception Index, the training intensity has determined. Participants in the study performed a sub-maximal aerobic activity schedule (45% to 80% of maximum heart rate) for two months, while the control group (n = 7) stayed away from aerobic exercise. Data evaluation and analysis of covariance compared both the pre-test and post-test with paired t-test at significance level of P≤ 0.05. After eight weeks of exercise, the results of the experimental group show a significant decrease in resting heart rate, systolic blood pressure, minute ventilation, while a significant increase in maximal oxygen uptake and tolerance activity (P ≤ 0.05). In the control group, there was no significant difference in these parameters ((P ≤ 0.05). The results indicate the aerobic activity can strengthen the respiratory muscles, while other physiological factors could result in breathing and heart recovery. Aerobic activity also resulted in favorable changes in cardiovascular parameters, and exercise tolerance of overweight women with chronic asthma.
Abstract: Water quality and heavy metals pollution of the Damietta Nile Branch at Damietta governorate were investigated in the current work. Fourteen different sampling points were selected along the Damietta Nile branch from Ras EL-Bar (sample 1) to Sheremsah (sample 14). Physical and chemical parameters and the concentrations of Cd, Cr, Cu, Ni, Fe, Al, Hg, Pb and Zn were investigated for water quality assessment of Damietta Nile Branch at Damietta Governorate. Most of the samples show that the water is suitable for drinking and irrigation purposes. All locations of samples near the sea are unsuitable water but the samples in the south direction away from the sea are suitable or good water for drinking and irrigation.
Abstract: This paper presents a hybrid system solar cell antenna for 5G mobile communications networks. We propose here a solar cell antenna with either a front face collection grid or mesh patch. The solar cell antenna of our contribution combines both optical and radiofrequency signals. Thus, we propose two solar cell antenna structures in the frequency bands of future 5G standard respectively in both 2.6 and 3.5 GHz bands. Simulation using the Advanced Design System (ADS) software allows us to analyze and determine the antenna parameters proposed in this work such as the reflection coefficient (S11), gain, directivity and radiated power.
Abstract: Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.
Abstract: This paper uses the analytic hierarchy process to study the execution effect of the minimum purchase price of grain in different regions and various grain crops. Firstly, for different regions, five indicators including grain yield, grain sown area, gross agricultural production, grain consumption price index, and disposable income of rural residents were selected to construct an evaluation index system. We collect data of six provinces including Hebei Province, Heilongjiang Province and Shandong Province from 2006 to 2017. Then, the judgment matrix is constructed, and the hierarchical single ordering and consistency test are carried out to determine the scoring standard for the minimum purchase price of grain. The ranking of the execution effect from high to low is: Heilongjiang Province, Shandong Province, Hebei Province, Guizhou Province, Shaanxi Province, and Guangdong Province. Secondly, taking Shandong Province as an example, we collect the relevant data of sown area and yield of cereals, beans, potatoes and other crops from 2006 to 2017. The weight of area and yield index is determined by expert scoring method. And the average sown area and yield of cereals, beans and potatoes in 2006-2017 were calculated, respectively. On this basis, according to the sum of products of weights and mean values, the execution effects of different grain crops are determined. It turns out that among the cereals, the minimum purchase price had the best execution effect on paddy, followed by wheat and finally maize. Moreover, among major categories of crops, cereals perform best, followed by beans and finally potatoes. Lastly, countermeasures are proposed for different regions, various categories of crops, and different crops of the same category.
Abstract: E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).
Abstract: This work aims to investigate the properties and microstructure of diamond-like carbon film deposited by pulsed laser deposition by ablation of a graphite target in a vacuum chamber on a steel substrate. The equipment was mounted to provide one laser beam. The target of high purity graphite and the steel substrate were polished. The mechanical and tribological properties of the film were characterized using Raman spectroscopy, nanoindentation test, scratch test, roughness profile, tribometer, optical microscopy and SEM images. It was concluded that the pulsed laser deposition (PLD) technique associated with the low-pressure chamber and a graphite target provides a good fraction of sp3 bonding, that the process variable as surface polishing and laser parameter have great influence in tribological properties and in adherence tests performance. The optical microscopy images are efficient to identify the metallurgical bond.
Abstract: This paper considers the modelling of a non-stationary
bivariate integer-valued autoregressive moving average of order
one (BINARMA(1,1)) with correlated Poisson innovations. The
BINARMA(1,1) model is specified using the binomial thinning
operator and by assuming that the cross-correlation between the
two series is induced by the innovation terms only. Based on
these assumptions, the non-stationary marginal and joint moments
of the BINARMA(1,1) are derived iteratively by using some initial
stationary moments. As regards to the estimation of parameters of
the proposed model, the conditional maximum likelihood (CML)
estimation method is derived based on thinning and convolution
properties. The forecasting equations of the BINARMA(1,1) model
are also derived. A simulation study is also proposed where
BINARMA(1,1) count data are generated using a multivariate
Poisson R code for the innovation terms. The performance of
the BINARMA(1,1) model is then assessed through a simulation
experiment and the mean estimates of the model parameters obtained
are all efficient, based on their standard errors. The proposed model
is then used to analyse a real-life accident data on the motorway in
Mauritius, based on some covariates: policemen, daily patrol, speed
cameras, traffic lights and roundabouts. The BINARMA(1,1) model
is applied on the accident data and the CML estimates clearly indicate
a significant impact of the covariates on the number of accidents on
the motorway in Mauritius. The forecasting equations also provide
reliable one-step ahead forecasts.
Abstract: Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.
Abstract: Both hydrophilic-oleophobic and hydrophobic-oleophilic membranes were obtained by coating of the substrate of membranes, presented by stainless steel meshes with various dimensions of their openings, with a composition that forms the special type of their surface wettability via spray-coating method. The surface morphology of resulting membranes was studied using SEM, the type of their wettability was identified by measuring the contact angle between the surface of membrane and a drop of studied liquid (water or organic liquid) and efficiency of continuous separation of water and organic liquid was studied on self-assembled setup.