Abstract: The global ascendancy of terrorist attacks on building infrastructure with economic and heritage significance has increased awareness of the possibility of terrorism in Canada. Many structures in Canada that are at risk of terrorist attacks include government buildings, built many years ago of historic stone masonry construction. Although many researchers are investigating ways to retrofit masonry stone buildings to mitigate the effect of blast loadings, lack of knowledge on the dynamic behavior of historic stone masonry structures under blast loads makes it difficult to ascertain the effectiveness of the retrofitting techniques. This paper presents a review of open-source literature for the experimental and numerical stone masonry structures under blast loads. This review yielded very little information of the response of the historic stone masonry structures under blast loads. Thus, a comprehensive study is needed to understand the blast load effects on historic stone masonry buildings. The out-of-plane response of historic masonry structures to blast loads is investigated by using single-degree-of-freedom analysis. This approach presents equations that can be used effectively in the analysis of historic masonry walls to out-of-plane blast loading.
Abstract: In order to determine the importance of small-system riverine heat flux on regional landfast sea ice breakup, our study explores the annual spring freshet of the Sagavanirktok River from 2014-2019. Seasonal heat cycling ultimately serves as the driving mechanism behind the freshet; however, as an emerging area of study, the extent to which inland thermodynamics influence coastal tundra geomorphology and connected landfast sea ice has not been extensively investigated in relation to small-scale Arctic river systems. The Sagavanirktok River is a small-to-midsized river system that flows south-to-north on the Alaskan North Slope from the Brooks mountain range to the Beaufort Sea at Prudhoe Bay. Seasonal warming in the spring rapidly melts snow and ice in a northwards progression from the Brooks Range and transitional tundra highlands towards the coast and when coupled with seasonal precipitation, results in a pulsed freshet that propagates through the Sagavanirktok River. The concentrated presence of newly exposed vegetation in the transitional tundra region due to spring melting results in higher absorption of solar radiation due to a lower albedo relative to snow-covered tundra and/or landfast sea ice. This results in spring flood runoff that advances over impermeable early-season permafrost soils with elevated temperatures relative to landfast sea ice and sub-ice flow. We examine the extent to which interannual temporal variability influences the onset and magnitude of river discharge by analyzing field measurements from the United States Geological Survey (USGS) river and meteorological observation sites. Rapid influx of heat to the Arctic Ocean via riverine systems results in a noticeable decay of landfast sea ice independent of ice breakup seaward of the shear zone. Utilizing MODIS imagery from NASA’s Terra satellite, interannual variability of river discharge is visualized, allowing for optical validation that the discharge flow is interacting with landfast sea ice. Thermal erosion experienced by sediment fast ice at the arrival of warm overflow preconditions the ice regime for rapid thawing. We investigate the extent to which interannual heat flux from the Sagavanirktok River’s freshet significantly influences the onset of local landfast sea ice breakup. The early-season warming of atmospheric temperatures is evidenced by the presence of storms which introduce liquid, rather than frozen, precipitation into the system. The resultant decreased albedo of the transitional tundra supports the positive relationship between early-season precipitation events, inland thermodynamic cycling, and degradation of landfast sea ice. Early removal of landfast sea ice increases coastal erosion in these regions and has implications for coastline geomorphology which stress industrial, ecological, and humanitarian infrastructure.
Abstract: Due to the constant increase in terrorist attacks, the research and engineering communities have given significant attention to building performance under explosions. This paper presents a methodology for studying and simulating the dynamic responses of steel structures during external detonations, particularly for accurately investigating the impact of incrementing charge weight on the members total behavior, resistance and failure. Prediction damage method was introduced to evaluate the damage level of the steel members based on five scenarios of explosions. Johnson–Cook strength and failure model have been used as well as ABAQUS finite element code to simulate the explicit dynamic analysis, and antecedent field tests were used to verify the acceptance and accuracy of the proposed material strength and failure model. Based on the structural response, evaluation criteria such as deflection, vertical displacement, drift index, and damage level; the obtained results show the vulnerability of steel columns and un-braced steel frames which are designed and optimized to carry dead and live load to resist and endure blast loading.
Abstract: Engine exhaust noise is considered one of the largest sources of vehicle exterior noise. Further reduction of noise from the vehicle exhaust system will be required, as the vehicle exterior noise regulations become stricter. Therefore, the present study has been carried out to illustrate the role of engine operating parameters and exhaust system construction factors on exhaust noise emitted. The measurements carried out using different exhaust systems, which are mainly used in today’s vehicle. The effect of engine speed on the spectra level of exhaust noise is recorded at engine speeds of 900 rpm, 1800 rpm, 2700, rpm 3600 rpm and 4500 rpm. The results indicate that the increase of engine speed causes a significant increase in the spectrum level of exhaust noise. The increase in the number of the outlet of the expansion chamber also reduces the overall level of exhaust noise.
Abstract: In this study, a spectral element method (SEM) is employed to predict the free vibration of a Euler-Bernoulli beam resting on a Winkler foundation with elastically restrained ends. The formulation of the dynamic stiffness matrix has been established by solving the differential equation of motion which was transformed to frequency domain. Non-dimensional natural frequencies and shape modes are obtained by solving the partial differential equations, numerically. Numerical comparisons and examples are performed to show the effectiveness of the SEM and to investigate the effects of various parameters, such as the springs at the boundaries and the elastic foundation parameter on the vibration frequencies. The obtained results demonstrate that the present method can also be applied to solve the more general problem of the dynamic analysis of structures with higher order precision.
Abstract: Autism spectrum disorders (ASD) involve myriad aberrant perceptual, cognitive, linguistic, and social behaviors. The term spectrum emphasizes that the disabilities associated with ASD fall on a continuum from relatively mild to severe. People with ASD may display stereotyped behaviors such as twirling, spinning objects, flapping the hands, and rocking. The individuals with ASD exhibit communication problems due to repetitive/restricted behaviors. Children with ASD who lack the motivation to learn, who do not enjoy physical challenges, or whose sensory perception results in confusing or unpleasant feedback from movement may not become sufficiently motivated to practice motor activities. As a result, they may show both a delay in developing certain motor skills. Additionally, attention is an important component of learning. As far as children with ASD have problems in joint attention, many education-based programs are needed to consider some aspects of attention and motor activities development for students with ASD. These programs focus on the basic movement skills that are crucial for the future development of the more complex skills needed in games, dance, sports, gymnastics, active play, and recreational physical activities. The purpose of the present research was to determine the effectiveness of therapeutic exercise on motor skills and attention of male students with ASD. This was an experimental study with a control group. The population consisted of 8-10 year-old male students with ASD and 30 subjects were selected randomly from an available center suitable for the children with ASD. They were evaluated by the Basic Motor Ability Test (BMAT) and Persian version of computerized Stroop color-word test and randomly assigned to an experimental and control group (15 students in per group). The experimental group participated in 16 therapeutic exercise sessions and received therapeutic exercise program (twice a week; each lasting for 45 minutes) designed based on the Spark motor program while the control group did not. All subjects were evaluated by BMAT and Stroop color-word test after the last session again. The collected data were analyzed by using multivariate analysis of covariance (MANCOVA). The results of MANCOVA showed that experimental and control groups had a significant difference in motor skills and at least one of the components of attention (correct responses, incorrect responses, no responses, the reaction time of congruent words and reaction time of incongruent words in the Stroop test). The findings showed that the therapeutic exercise had a significant effect on motor skills and all components of attention in students with ASD. We can conclude that the therapeutic exercise led to promote the motor skills and attention of students with ASD, so it is necessary to design or plan such programs for ASD students to prevent their communication or academic problems.
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.
Abstract: This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.
Abstract: This work presents an improved strategy of control for charging a lithium-ion battery in an electric vehicle charging station using two charger topologies i.e. single ended primary inductor converter (SEPIC) and forward converter. In terms of rapidity and accuracy, the power system consists of a topology/control diagram that would overcome the performance constraints, for instance the power instability, the battery overloading and how the energy conversion blocks would react efficiently to any kind of perturbations. Simulation results show the effectiveness of the proposed topologies operated with a power management algorithm based on voltage/peak current mode controls. In order to provide credible findings, a low power prototype is developed to test the control strategy via experimental evaluations of the converter topology and its controls.
Abstract: The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.
Abstract: Generation of high DC voltages is necessary for testing the insulation material of high voltage AC transmission lines with long lengths. The harmonic and ripple contents of the output DC voltage supplied by high voltage DC circuits require the use of costly capacitors to smooth the output voltage after rectification. This paper proposes a new modular multiplier high voltage DC generator with embedded Cockcroft-Walton circuits that achieve a negligible harmonic and ripple contents of the output DC voltage without the need for costly filters to produce a nearly constant output voltage. In this new topology, Cockcroft-Walton modules are connected in series to produce a high DC output voltage. The modules are supplied by low input AC voltage sources that have the same magnitude and frequency and shifted from each other by a certain angle to eliminate the harmonics from the output voltage. The small ripple factor is provided by the smoothing column capacitors and the phase shifted input voltages of the cascaded modules. The constituent harmonics within each module are determined using Fourier analysis. The viability of the proposed DC generator for testing purposes and the effectiveness of the cascaded connection are confirmed by numerical simulations using MATLAB/Simulink.
Abstract: Introduction: Endometrial Cancer is a common gynecologic malignancy primarily treated with complete surgical staging, which may include complete pelvic and para-aortic lymphadenectomy. The role of lymphadenectomy is controversial, especially the intraoperative indications for the procedure. Three factors are important in decision to proceed with lymphadenectomy: Myometrial invasion, maximum tumor dimension, and histology. Many institutions incorporate these criteria in varying degrees in the decision to proceed with lymphadenectomy. This investigation assesses the use of intraoperatively measured MTD with and without pre-operative histologic grade. Methods: This study compared retrospectively EEC patients with intraoperatively measured MTD ≤2 cm to those with MTD >2 cm from January 1, 2002 to August 31, 2017. This assessment compared those with MTD ≤ 2cm with endometrial biopsy (EB) grade 1-2 to patients with MTD > 2cm with EB grade 3. Lymph node metastasis (LNM), recurrence, and survival were compared in these groups. Results: This study reviewed 222 patient cases. In tumors > 2 cm, LNM occurred in 20% cases while in tumors ≤ 2 cm, LNM was found in 6% cases (p=0.04). Recurrence and mean survival based on last follow up visit in these two groups were not statistically different (p=0.78 and 0.36 respectively). Data demonstrated a trend that when combined with preoperative EB International Federation of Gynecology and Obstetrics (FIGO) grade, a higher proportion of patients with EB FIGO Grade 3 and MTD > 2 cm had LNM compared to those with EB FIGO Grade 1-2 and MTD ≤ 2 cm (43% vs, 11%, p=0.06). LNM was found in 15% of cases in which lymphadenectomy was performed based on current practices, whereas if the criteria of EB FIGO 3 and MTD > 2 cm were used the incidence of LNM would have been 44% cases. However, using this criterion, two patients would not have had their nodal metastases detected. Compared to the current practice, the sensitivity and specificity of the proposed criteria would be 60% and 81%, respectively. The PPV and NPV would be 43% and 90%, respectively. Conclusion: The results indicate that MTD combined with EB FIGO grade can detect LNM in a higher proportion of cases when compared to current practice. MTD combined with EB FIGO grade may eliminate the need of frozen section sampling in a substantial number of cases.
Abstract: In this paper, we propose an optimized brain computer
interface (BCI) system for unspoken speech recognition, based on
the fact that the constructions of unspoken words rely strongly on the
Wernicke area, situated in the temporal lobe. Our BCI system has four
modules: (i) the EEG Acquisition module based on a non-invasive
headset with 14 electrodes; (ii) the Preprocessing module to remove
noise and artifacts, using the Common Average Reference method;
(iii) the Features Extraction module, using Wavelet Packet Transform
(WPT); (iv) the Classification module based on a one-hidden layer
artificial neural network. The present study consists of comparing
the recognition accuracy of 5 Arabic words, when using all the
headset electrodes or only the 4 electrodes situated near the Wernicke
area, as well as the selection effect of the subbands produced by
the WPT module. After applying the articial neural network on the
produced database, we obtain, on the test dataset, an accuracy of
83.4% with all the electrodes and all the subbands of 8 levels of the
WPT decomposition. However, by using only the 4 electrodes near
Wernicke Area and the 6 middle subbands of the WPT, we obtain
a high reduction of the dataset size, equal to approximately 19% of
the total dataset, with 67.5% of accuracy rate. This reduction appears
particularly important to improve the design of a low cost and simple
to use BCI, trained for several words.
Abstract: The flue gas from fossil fuels combustion contains harmful pollutants dangerous for human health and environment. One of the air pollution control methods to restrict the emission of these pollutants is based on using the nanoparticle in adsorption process. In the present research, gamma nano-alumina particle is added to polyacrylonitrile (PAN) polymer through simple loading method, and the adsorption capacity of the wet spun fiber is investigated. The results of exposure the fiber to the acid gases including SO2, CO, NO2, NO, and CO2 show the noticeable increase of gas adsorption capacity on fiber contains nanoparticle. The research has been conducted in Acrylic II Plant of Polyacryl Iran Corporation.
Abstract: Missing values in real-world datasets are a common
problem. Many algorithms were developed to deal with this
problem, most of them replace the missing values with a fixed
value that was computed based on the observed values. In
our work, we used a distance function based on Bhattacharyya
distance to measure the distance between objects with missing
values. Bhattacharyya distance, which measures the similarity of
two probability distributions. The proposed distance distinguishes
between known and unknown values. Where the distance between
two known values is the Mahalanobis distance. When, on the other
hand, one of them is missing the distance is computed based on the
distribution of the known values, for the coordinate that contains
the missing value. This method was integrated with Wikaya, a
digital health company developing a platform that helps to improve
prevention of chronic diseases such as diabetes and cancer. In order
for Wikaya’s recommendation system to work distance between users
need to be measured. Since there are missing values in the collected
data, there is a need to develop a distance function distances between
incomplete users profiles. To evaluate the accuracy of the proposed
distance function in reflecting the actual similarity between different
objects, when some of them contain missing values, we integrated it
within the framework of k nearest neighbors (kNN) classifier, since
its computation is based only on the similarity between objects. To
validate this, we ran the algorithm over diabetes and breast cancer
datasets, standard benchmark datasets from the UCI repository. Our
experiments show that kNN classifier using our proposed distance
function outperforms the kNN using other existing methods.
Abstract: The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.
Abstract: Thermal injuries remain a global health problem and a common issue encountered in forensic pathology. They are a devastating cause of morbidity and mortality in children and adults especially in developing countries, causing permanent disfigurement, scarring and grievous hurt. Burns have always been a matter of legal concern in cases of suicidal burns, self-inflicted burns for false accusation and homicidal attempts. Assessment of burn injuries as well as rating permanent disabilities and disfigurement following thermal injuries for the benefit of compensation claims represents a challenging problem. This necessitates the development of reliable scoring systems to yield an expected likelihood of permanent disability or fatal outcome following burn injuries. The study was designed to identify the risk factors of mortality in acute burn patients and to evaluate the applicability of FLAMES (Fatality by Longevity, APACHE II score, Measured Extent of burn, and Sex) and BOBI (Belgian Outcome in Burn Injury) model scores in predicting the outcome. The study was conducted on 100 adult patients with acute burn injuries admitted to the Burn Unit of Alexandria Main University Hospital, Egypt from October 2014 to October 2015. Victims were examined after obtaining informed consent and the data were collected in specially designed sheets including demographic data, burn details and any associated inhalation injury. Each burn patient was assessed using both BOBI and FLAMES scoring systems. The results of the study show the mean age of patients was 35.54±12.32 years. Males outnumbered females (55% and 45%, respectively). Most patients were accidently burnt (95%), whereas suicidal burns accounted for the remaining 5%. Flame burn was recorded in 82% of cases. As well, 8% of patients sustained more than 60% of total burn surface area (TBSA) burns, 19% of patients needed mechanical ventilation, and 19% of burnt patients died either from wound sepsis, multi-organ failure or pulmonary embolism. The mean length of hospital stay was 24.91±25.08 days. The mean BOBI score was 1.07±1.27 and that of the FLAMES score was -4.76±2.92. The FLAMES score demonstrated an area under the receiver operating characteristic (ROC) curve of 0.95 which was significantly higher than that of the BOBI score (0.883). A statistically significant association was revealed between both predictive models and the outcome. The study concluded that both scoring systems were beneficial in predicting mortality in acutely burnt patients. However, the FLAMES score could be applied with a higher level of accuracy.
Abstract: In this paper, we have developed a sliding mode
controller for PUMA 600 manipulator robot, to control the remote
robot a teleoperation system was developed. This system includes
two sites, local and remote. The sliding mode controller is installed
at the remote site. The client asks for a position through an interface
and receives the real positions after running of the task by the remote
robot. Both sites are interconnected via the Internet. In order to verify
the effectiveness of the sliding mode controller, that is compared with
a classic PID controller. The developed approach is tested on a virtual
robot. The results confirmed the high performance of this approach.
Abstract: This paper concerns with the modeling, simulation, and emulation of a wind turbine emulator for standalone wind energy conversion systems. By using emulation system, we aim to reproduce the dynamic behavior of the wind turbine torque on the generator shaft: it provides the testing facilities to optimize generator control strategies in a controlled environment, without reliance on natural resources. The aerodynamic, mechanical, electrical models have been detailed as well as the control of pitch angle using Fuzzy Logic for horizontal axis wind turbines. The wind turbine emulator consists mainly of an induction motor with AC power drive with torque control. The control of the induction motor and the mathematical models of the wind turbine are designed with MATLAB/Simulink environment. The simulation results confirm the effectiveness of the induction motor control system and the functionality of the wind turbine emulator for providing all necessary parameters of the wind turbine system such as wind speed, output torque, power coefficient and tip speed ratio. The findings are of direct practical relevance.
Abstract: Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.