Abstract: Using a waste material such as crumb rubber (CR) obtained by waste tires has become an important issue in respect to sustainability. However, the CR modified mixture also requires high manufacture temperature as a polymer modified mixture. For this reason in this study, it is intended to produce a CR modified mixture with warm mix asphalt additives in the same mixture. Asphalt mixtures produced by pure, 10%CR, 10%CR+3% Sasobit and 10%CR+0.7% Evotherm were subjected to aging procedure in the laboratory and the field. The indirect tensile repeated tests were applied to aged and original specimens. It was concluded that the fatigue life of the mixtures increased significantly with the increase of aging time. CR+Sasobit modified mixture aged at the both field and laboratory gave the highest load cycle among the mixtures.
Abstract: In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.
Abstract: Nitrogen accumulates in soils during the process of fertilizer addition to promote the plant growth. When the organic matter decomposes, the form of available nitrogen produced is in the form of nitrate, which is highly mobile. The most significant health effect of nitrate ingestion is methemoglobinemia in infants under six months of age (blue baby syndrome). The mobile nutrients, like nitrate nitrogen, are not stored in the soil as the available forms for the long periods and in large amounts. It depends on the needs for the crops such as vegetables. On the other hand, the vegetables will compete actively for nitrate nitrogen as a mobile nutrient and water. The mobile nutrients must be shared. The fewer the plants, the larger this share is for each plant. Also, this nitrate nitrogen is poisonous for the people who use these vegetables. Nitrate is converted to nitrite by the existing bacteria in the stomach and the Gastro-Intestinal (GI) tract. When nitrite is entered into the blood cells, it converts the hemoglobin to methemoglobin, which causes the anoxemia and cyanosis. The increasing use of pesticides and chemical fertilizers, especially the fertilizers with nitrates compounds, which have been common for the increased production of agricultural crops, has caused the nitrate pollution in the (soil, water, and environment). They have caused a lot of damage to humans and animals. In this research, the nitrate accumulation in different kind of vegetables such as; green pepper, tomatoes, egg plants, watermelon, cucumber, and red pepper were observed in the suburbs of Mashhad, Neisabour, and Sabzevar cities. In some of these cities, the information forms of agronomical practices collected were such as; different vegetable crops fertilizer recommendations, varieties, pesticides, irrigation schedules, etc., which were filled out by some of our colleagues in the research areas mentioned above. Analysis of the samples was sent to the soil and water laboratory in our department in Mashhad. The final results from the chemical analysis of samples showed that the mean levels of nitrates from the samples of the fruit crops in the mentioned cities above were all lower than the critical levels. These fruit crop samples were in the order of: 35.91, 8.47, 24.81, 6.03, 46.43, 2.06 mg/kg dry matter, for the following crops such as; tomato, cucumber, eggplant, watermelon, green pepper, and red pepper. Even though, this study was conducted with limited samples and by considering the mean levels, the use of these crops from the nutritional point of view will not cause the poisoning of humans.
Abstract: For the required function of components with the thermal spray coating, it is necessary to perform additional machining of the coated surface. The paper deals with assessing the surface integrity of Metco 2042, a plasma sprayed coating, after its machining. The selected plasma sprayed coating serves as an abradable sealing coating in a jet engine. Therefore, the spray and its surface must meet high quality and functional requirements. Plasma sprayed coatings are characterized by lamellar structure, which requires a special approach to their machining. Therefore, the experimental part involves the set-up of special cutting tools and cutting parameters under which the applied coating was machined. For the assessment of suitably set machining parameters, selected parameters of surface integrity were measured and evaluated during the experiment. To determine the size of surface irregularities and the effect of the selected machining technology on the sprayed coating surface, the surface roughness parameters Ra and Rz were measured. Furthermore, the measurement of sprayed coating surface hardness by the HR 15 Y method before and after machining process was used to determine the surface strengthening. The changes of strengthening were detected after the machining. The impact of chosen cutting parameters on the surface roughness after the machining was not proven.
Abstract: The construction industry is a renowned latecomer to the efficiency offered by the adoption of information technology. Whereas, the banking, manufacturing, retailing industries have keyed into the future by using digitization and information technology as a new approach for ensuring competitive gain and efficiency. The construction industry has yet to fully realize similar benefits because the adoption of ICT is still at the infancy stage with a major concentration on the use of software. Thus, this study evaluates the awareness and readiness of construction professionals towards embracing a full digitalization of the construction industry using construction 4.0. The term ‘construction 4.0’ was coined from the industry 4.0 concept which is regarded as the fourth industrial revolution that originated from Germany. A questionnaire was utilized for sourcing data distributed to practicing construction professionals through a convenience sampling method. Using SPSS v24, the hypotheses posed were tested with the Mann Whitney test. The result revealed that there are no differences between the consulting and contracting organizations on the readiness for adopting construction 4.0 concepts in the construction industry. Using factor analysis, the study discovers that adopting construction 4.0 will improve the performance of the construction industry regarding cost and time savings and also create sustainable buildings. In conclusion, the study determined that construction professionals have a low awareness towards construction 4.0 concepts. The study recommends an increase in awareness of construction 4.0 concepts through seminars, workshops and training, while construction professionals should take hold of the benefits of adopting construction 4.0 concepts. The study contributes to the roadmap for the implementation of construction industry 4.0 concepts in the South African construction industry.
Abstract: In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.
Abstract: The viewpoint towards the use of drugs or vaccines against avian parasitic diseases is one of the most striking challenges in avian medical parasitology. This includes many difficulties associated with drug resistance and in developing prophylactic vaccines. In many instances, the potential success of a vaccination in controlling parasitic diseases in poultry is well-documented. However, some medical, technical and financial limitations are still paramount. On the other hand, chemotherapy is not very well-recommended due to a number of medical limitations. But in the absence of an effective vaccine, drugs are used against parasitic diseases. This paper sheds light on some the advantages and disadvantages of using vaccination and drugs in controlling parasitic diseases in poultry species. The usage of chemotherapeutic drugs is discussed with some examples. Then, more light will be shed on using vaccines as a potentially effective and promising control tool.
Abstract: There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.
Abstract: This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.
Abstract: Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.
Abstract: Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.
Abstract: This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.
Abstract: Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.
Abstract: Fukushima disaster is one of the most publicly exposed accidents in a nuclear facility which has changed the outlook of people towards nuclear power. Some have used it as an example to establish nuclear energy as an unsafe source, while others have tried to find the real reasons behind this accident. Many papers have tried to shed light on the possible causes, some of which are purely based on assumptions while others rely on rigorous data analysis. To our best knowledge, none of the works can say with absolute certainty that there is a single prominent reason that has paved the way to this unexpected incident. This paper attempts to compile all the apparent reasons behind Fukushima disaster and tries to analyze and identify the most likely one.
Abstract: Acoustic sensors are extensively used in recent days not only for sensing and condition monitoring applications but also for small scale energy harvesting applications to power wireless sensor networks (WSN) due to their inherent advantages. The natural frequency of the structure plays a major role in energy harvesting applications since the sensor key element has to operate at resonant frequency. In this paper, circular diaphragm based MEMS acoustic sensor is modelled by Lumped Element Model (LEM) and the natural frequency is compared with the simulated model using Finite Element Method (FEM) tool COMSOL Multiphysics. The sensor has the circular diaphragm of 3000 µm radius and thickness of 30 µm to withstand the high SPL (Sound Pressure Level) and also to withstand the various fabrication steps. A Piezoelectric ZnO layer of thickness of 1 µm sandwiched between two aluminium electrodes of thickness 0.5 µm and is coated on the diaphragm. Further, a channel with radius 3000 µm radius and length 270 µm is connected at the bottom of the diaphragm. The natural frequency of the structure by LEM method is approximately 16.6 kHz which is closely matching with that of simulated structure with suitable approximations.
Abstract: Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.
Abstract: In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.
Abstract: A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.
Abstract: Production of specific antibody responses against hTSH is a cumbersome process due to the high identity between the hTSH and the other members of the glycoprotein hormone family (FSH, LH and HCG) and the high identity between the human hTSH and host animals for antibody production. Therefore, two polyclonal antibodies were purified against two recombinant proteins. Four possible ELISA tests were designed based on these antibodies. These ELISA tests were checked against hTSH and other glycoprotein hormones, and their sensitivity and specificity were assessed. Bioinformatics tools were used to analyze the immunological properties. After the immunogen region selection from hTSH protein, c terminal of B hTSH was selected and applied. Two recombinant genes, with these cut pieces (first: two repeats of C terminal of B hTSH, second: tetanous toxin+B hTSH C terminal), were designed and sub-cloned into the pET32a expression vector. Standard methods were used for protein expression, purification, and verification. Thereafter, immunizations of the white New Zealand rabbits were performed and the serums of them were used for antibody titration, purification and characterization. Then, four ELISA tests based on two antibodies were employed to assess the hTSH and other glycoprotein hormones. The results of these assessments were compared with standard amounts. The obtained results indicated that the desired antigens were successfully designed, sub-cloned, expressed, confirmed and used for in vivo immunization. The raised antibodies were capable of specific and sensitive hTSH detection, while the cross reactivity with the other members of the glycoprotein hormone family was minimum. Among the four designed tests, the test in which the antibody against first protein was used as capture antibody, and the antibody against second protein was used as detector antibody did not show any hook effect up to 50 miu/l. Both proteins have the ability to induce highly sensitive and specific antibody responses against the hTSH. One of the antibody combinations of these antibodies has the highest sensitivity and specificity in hTSH detection.
Abstract: The ultimate load analysis of RC pile groups has assumed a lot of significance under liquefying soil conditions, especially due to post-earthquake studies of 1964 Niigata, 1995 Kobe and 2001 Bhuj earthquakes. The present study reports the results of numerical simulations on pile groups subjected to monotonically increasing lateral loads under design amounts of pile axial loading. The soil liquefaction has been considered through the non-linear p-y relationship of the soil springs, which can vary along the depth/length of the pile. This variation again is related to the liquefaction potential of the site and the magnitude of the seismic shaking. As the piles in the group can reach their extreme deflections and rotations during increased amounts of lateral loading, a precise modeling of the inelastic behavior of the pile cross-section is done, considering the complete stress-strain behavior of concrete, with and without confinement, and reinforcing steel, including the strain-hardening portion. The possibility of the inelastic buckling of the individual piles is considered in the overall collapse modes. The model is analysed using Riks analysis in finite element software to check the post buckling behavior and plastic collapse of piles. The results confirm the kinds of failure modes predicted by centrifuge test results reported by researchers on pile group, although the pile material used is significantly different from that of the simulation model. The extension of the present work promises an important contribution to the design codes for pile groups in liquefying soils.