Search results for: manufacturing output

Authors: Xing Lv, Hui-Qin Xu

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The present study aimed to reveal the mechanism in aggravating STZ induced diabetic nephropathy (DN) by AGEs (advanced glycation end products). At the eighth day, 20 diabetic mice were randomly divided into STZ group and combination (combine AGEs with STZ) group. Simultaneously, AGEs group and normal group were set. Only mice in AGEs group, combination group were fed with high-AGEs diets. Mice diabetic conventional indicators, biochemical analysis were measured. Among the indictors, food consumptions, water intake, urine output, blood glucose, urine protein, urine creatinine, serum urea nitrogen were increased significantly in STZ, combination groups. The AGEs levels in combination group increased significantly when compared with STZ group. Weights and insulin levels in the STZ, combination groups were decreased significantly when compared with normal group, and the difference was significantly between AGEs group and STZ group. As a conclusion, AGEs play an important role in the DN development, inducing kidney damages.

Keywords: AGEs, diabetic nephropathy, serum urea nitrogen, urine protein

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Authors: Yasunori Kobori, Li Quan, Shu Wu, Nizam Mohyar, Zachary Nosker, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

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This paper proposes an electrolytic capacitor-less transformer-less AC-DC LED driver with a current ripple canceller. The proposed LED driver includes a diode bridge, a buck-boost converter, a negative feedback controller and a current ripple cancellation circuit. The current ripple canceller works as a bi-directional current converter using a sub-inductor, a sub-capacitor and two switches for controlling current flow. LED voltage is controlled in order to regulate LED current by the negative feedback controller using a current sense resistor. There are two capacitors which capacitance of 5 uF. We describe circuit topologies, operation principles and simulation results for our proposed circuit. In addition, we show the line regulation for input voltage variation from 85V to 130V. The output voltage ripple is 2V and the LED current ripple is 65 mA which is less than 20% of the typical current of 350 mA. We are now making the proposed circuit on a universal board in order to measure the experimental characteristics.

Keywords: LED driver, electrolytic, capacitor-less, AC-DC converter, buck-boost converter, current ripple canceller

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Farzingohar Mehrnaz, Yasemi Mehran, Esmaili Zinat, Baharlouian Maedeh

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Aboozar (Ardeshir) and Bahregansar are the two important Iranian oilfields in Persian Gulf waters. The operation activities cause to create spills which impacted on the marine environment. Assumed spills are molded by ADIOS II (Automated Data Inquiry for Oil Spills) which is NOAA’s weathering oil software. Various atmospheric and marine data with different oil types are used for the modeling. Numerous scenarios for 100 bbls with mean daily air temperature and wind speed are input for 5 days. To find the model sensitivity in each setting, one parameter is changed, but the others stayed constant. In both fields, the evaporated and dispersed output values increased hence the remaining rate is reduced. The results clarified that wind speed first, second air temperature and finally oil type respectively were the most effective factors on the oil weathering process. The obtained results can help the emergency systems to predict the floating (dispersed and remained) volume spill in order to find the suitable cleanup tools and methods.

Keywords: ADIOS, modeling, oil spill, sensitivity analysis

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Authors: Anil Kawan, Soon Jae Yu, Jong Min Park

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GaN-based 365 nm wavelength ultraviolet (UV) light emitting diodes (LED) have various applications: curing, molding, purification, deodorization, and disinfection etc. However, their usage is limited by very low output power, because of the light absorption in the GaN layers. In this study, we demonstrate a method utilizing removal of 365 nm absorption layer buffer GaN and thinning the n-type GaN so as to improve the light extraction efficiency of the GaN-based 365 nm UV LED. The UV flip chip LEDs of chip size 1.3 mm x 1.3 mm were fabricated using GaN epilayers on a sapphire substrate. Via-hole n-type contacts and highly reflective Ag metal were used for efficient light extraction. LED wafer was aligned and bonded to AlN carrier wafer. To improve the extraction efficiency of the flip chip LED, sapphire substrate and absorption layer buffer GaN were removed by using laser lift-off and dry etching, respectively. To further increase the extraction efficiency of the LED, exposed n-type GaN thickness was reduced by using inductively coupled plasma etching.

Keywords: extraction efficiency, light emitting diodes, n-GaN thinning, ultraviolet

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Authors: Pedro G. Morouço

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One utmost challenge in Tissue Engineering is the production of 3D constructs capable of mimicking the functional hierarchy of native tissues. This is well stated for osteochondral tissue due to the complex mechanical functional unit based on the junction of articular cartilage and bone. Thus, the aim of the present study was to develop a new additive manufacturing system coupling micro-extrusion with hydrogels printing. An integrated system was developed with 2 main features: (i) the printing of up to three distinct hydrogels; (ii) in coordination with the printing of a thermoplastic structural support. The hydrogel printing module was projected with a ‘revolver-like’ system, where the hydrogel selection was made by a rotating mechanism. The hydrogel deposition was then controlled by pressured air input. The use of specific components approved for medical use was incorporated in the material dispensing system (Nordson EDF Optimum® fluid dispensing system). The thermoplastic extrusion modulus enabled the control of required extrusion temperature through electric resistances in the polymer reservoir and the extrusion system. After testing and upgrades, a hydrogel modulus with 3 syringes (3cm3 capacity each), with a pressure range of 0-2.5bar, a rotational speed of 0-5rpm, and working with needles from 200-800µm was obtained. This modulus was successfully coupled to the extrusion system that presented a temperature up to 300˚C, a pressure range of 0-12bar, and working with nozzles from 200-500µm. The applied motor could provide a velocity range 0-2000mm/min. Although, there are distinct printing requirements for hydrogels and polymers, the novel system could develop hybrid scaffolds, combining the 2 moduli. The morphological analysis showed high reliability (n=5) between the theoretical and obtained filament and pore size (350µm and 300µm vs. 342±4µm and 302±3µm, p>0.05, respectively) of the polymer; and multi-material 3D constructs were successfully obtained. Human tissues present very distinct and complex structures regarding their mechanical properties, organization, composition and dimensions. For osteochondral regenerative medicine, a multiphasic scaffold is required as subchondral bone and overlying cartilage must regenerate at the same time. Thus, a scaffold with 3 layers (bone, intermediate and cartilage parts) can be a promising approach. The developed system may give a suitable solution to construct those hybrid scaffolds with enhanced properties. The present novel system is a step-forward regarding osteochondral tissue engineering due to its ability to generate layered mechanically stable implants through the double-printing of hydrogels with thermoplastics.

Keywords: 3D bioprinting, bone regeneration, cartilage regeneration, regenerative medicine, tissue engineering

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Authors: Hassan Mahdi

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The integration of computer-assisted translation (CAT) tools in translation creates several opportunities for translators. However, this integration is not useful in all types of English structures. This study aims at examining the impact of using CAT tools in translating collocations. Seventy students of English as a foreign language participated in this study. The participants were divided into three groups (i.e., CAT tools group, Machine Translation group, and the control group). The comparison of the results obtained from the translation output of the three groups demonstrated the improvement of translation using CAT tools. The results indicated that the participants who used CAT tools outscored the participants who used MT, and in turn, both groups outscored the control group who did not use any type of technology in translation. In addition, there was a significant difference in the use of CAT for translation different types of collocations. The results also indicated that CAT tools were more effective in translation fixed and medium-strength collocations than weak collocations. Finally, the results showed that CAT tools were effective in translation collocations in both types of languages (i.e. target language or source language). The study suggests some guidelines for translators to use CAT tools.

Keywords: machine translation, computer-assisted translation, collocations, technology

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Authors: Yujeong Shin, Seong Jin Cho, Jin Ho Kim

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In the textile-weaving machine, the reed is the core component to separate thousands of strands of yarn and to produce the fabric in a continuous high-speed movement. In addition, the reed affects the quality of the fiber. Therefore, the wire forming analysis of the main raw materials of the reed needs to be considered. Roll-forming is a key technology among the manufacturing process of reed wire using textile machine. A simulation of roll-forming line in accordance with the reduction rate is performed using LS-DYNA. The upper roller, fixed roller and reed wire are modeled by finite element. The roller is set to be rigid body and the wire of SUS430 is set to be flexible body. We predict the variation of the cross-sectional shape of the wire depending on the reduction ratio.

Keywords: textile machine, reed, rolling, reduction ratio, wire

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Abdulkadir Adamu Shehu

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Company’s reputation is an elusive asset. The reputation gained by companies must be preserved for sustainability of the company. However, the construction project is still suffering from declination of character due to the factors that affect their reputation. The problem led to the loss of projects, abandoning of the projects and many more. This contributed to negative impact on the contractors in the construction industry. As for today, previous studies have not investigated in this regards yet. For that reason, this paper examines the factors which could promote contractor’s reputation in the construction industry in Nigeria. To achieve this aim, 140 questionnaires were distributed to the Nigerian contractors. Based on the 67% response rate, descriptive analysis and analysis of variance (ANOVA) were the tools applied for the data obtained to be analysed. The result shows that, good communication system and improve quality of output of products are the most significant variables that can promote contractor’s reputation. The homogenous analyses indicate that there are significant different perceptions of respondents in term of the significant effects. The research concluded that contractor’s reputation in construction industry must be maintained and further research was suggested to focus on the qualitative method to have in-depth knowledge on contractor’s reputation in the construction industry.

Keywords: construction industry, contractor’s reputation, effects of delay, Nigeria

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Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

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In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during changes in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain equal power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: droop control, droop characteristic, grid-connected inverter, microgrid, power control

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Kwon Eunhee, Park Dongcheon, Jung Jaemin

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In countries around the world, environmental regulations are being strengthened, and Korea is no exception to this trend, which means that environment pollution and the environmental load have recently become a significant issue. For this reason, in this study limestone was replaced with cementitious powder to reduce the volume of construction waste as well as the emission of carbon dioxide caused by Tal-carbonate reaction. The research found that cementitious powder can be used as a substitute for limestone. However, the mix proportions of fine aggregate and powder included in the cementitious powder appear to have a great effect on substitution. Thus, future research should focus on developing a technology that can effectively separate and discharge fine aggregate and powder in the cementitious powder.

Keywords: waste cementitious powder, fine aggregate powder, CO2 emission, decarbonation reaction, calcining process

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Sumbal Riaz, Sardar-un-Nisa, Mehreen Sirshar

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5G - The 5th generation of mobile phone and data communication standards is the next edge of innovation for whole mobile industry. 5G is Real Wireless World System and it will provide a totally wireless communication system all over the world without limitations. 5G uses many 4g technologies and it will hit the market in 2020. This research is the comprehensive survey on the quality parameters of 5G technology.5G provide High performance, Interoperability, easy roaming, fully converged services, friendly interface and scalability at low cost. To meet the traffic demands in future fifth generation wireless communications systems will include i) higher densification of heterogeneous networks with massive deployment of small base stations supporting various Radio Access Technologies (RATs), ii) use of massive Multiple Input Multiple Output (MIMO) arrays, iii) use of millimetre Wave spectrum where larger wider frequency bands are available, iv) direct device to device (D2D) communication, v) simultaneous transmission and reception, vi) cognitive radio technology.

Keywords: 5G, 5th generation, innovation, standard, wireless communication

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Taejung Lho, Jonghwan Lee

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Most of the photovoltaic (PV) module manufacturers have recently interested in reducing the manufacturing cost. One of available solution is the use of the thin photovoltaic cell because of reducing of raw material cost. Thin PV cells, however, are damaged large deformation which causes possible microcracks inside PV cell, leading to failure problem. In this paper, deformation characteristics by heat conduction in soldering process of PV cells are analyzed through ANSYS software tool. They have been tested for different PV cell thickness and soldering temperature profile. Accordingly optimal soldering process to minimize the deformation of PV cell has been suggested.

Keywords: photovoltaic (PV) cell, infrared(IR) lamp soldering, optimal soldering temperature profile, deformation, temperature distribution, 3D scanner, ANSYS

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Authors: Rameez Ahmad, Aqib Mehmood, Imran Khan

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Self-directed car (SDC) that can drive itself from one fact to another without support from a driver. Certain trust that self-directed car obligate the probable to transform the transportation manufacturing while essentially removing coincidences, and cleaning up the environment. This study realizes the effects that SDC (also called a self-driving, driver or robotic) vehicle travel demands and ride scheme is likely to have. Without the typical obstacles that allows detection of a audio vision based hardware and software construction (It (SDC) and cost benefits, the vehicle technologies, Gold (Generic Obstacle and Lane Detection) to a knowledge-based system to predict their potential and consider the shape, color, or balance) and an organized environment with colored lane patterns, lane position ban. Discovery the problematic consequence of (SDC) on GT (grand trunk road) road and brand the car further effectual.

Keywords: SDC, gold, GT, knowledge-based system

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Authors: Youssef Babkrani, S. Hiyani, A. Naddami, K. Choukri, M. Hilal

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Power Quality has been a problem ever since electrical power was invented and in recent years, it has become the main interest of researchers who are still concerned about finding ways to reduce its negative influence on electrical devices. In this paper we aim to improve the power quality output for H- bridge multilevel inverter used with solar Photovoltaic (PV) panels, we propose a new switching technique that uses a pulse width modulation method (PWM) aiming to reduce the harmonics. This new method introduces a sinusoidal wave compared with modified trapezoidal carriers used to generate the pulses. This new trapezoid carrier waveform is being implemented with different sinusoidal PWM dispositions such as phase disposition (PWM PD), phase opposition disposition (PWM POD), and (PWM APOD) alternative phase opposition disposition and compared with the conventional ones. Using Matlab Simulink R2014a the line voltage and total harmonic distortions (THD) simulated and the quality are increased in spite of variations of DC introduced.

Keywords: carrier waveform, phase disposition (PD), phase opposition disposition (POD), alternative phase opposition disposition (APOD), total harmonics distortion (THD)

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: Mihika Shivkumar, Krishna Kumar, C. Perisamy

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3D printing is a method of manufacturing wherein materials, such as plastic or metal, are deposited in layers one on top of the other to produce a three dimensional object. 3D printing is most commonly associated with creating engineering prototypes. However, its applications in the field of human health care have been frequently disregarded. Medical applications for 3D printing are expanding rapidly and are envisaged to revolutionize health care. Medical applications for 3D printing, both present and its potential, can be categorized broadly, including: creation of customized prosthetics tissue and organ fabrication; creation of implants, and anatomical models and pharmaceutical research regarding drug dosage forms. This piece breaks down bioprinting in the healthcare sector. It focuses on the better subtle elements of every particular point, including how 3D printing functions in the present, its impediments, and future applications in the health care sector.

Keywords: bio-printing, prototype, drug delivery, organ regeneration

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Authors: Hau-Wei Lee, Yu-Chi Liu, Chien-Hung Liu

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A mathematical model is presented for a system that measures rotational errors in a shaft using a ball lens. The geometric optical characteristics of the ball lens mounted on the shaft allows the measurement of rotation axis errors in both the radial and axial directions. The equipment used includes two quadrant detectors (QD), two laser diodes and a ball lens that is mounted on the rotating shaft to be evaluated. Rotational errors in the shaft cause changes in the optical geometry of the ball lens. The resulting deflection of the laser beams is detected by the QDs and their output signals are used to determine rotational errors. The radial and the axial rotational errors can be calculated as explained by the mathematical model. Results from system calibration show that the measurement error is within ±1 m and resolution is about 20 nm. Using a direct drive motor (DD motor) as an example, experimental results show a rotational error of less than 20 m. The most important features of this system are that it does not require the use of expensive optical components, it is small, very easy to set up, and measurements are highly accurate.

Keywords: ball lens, quadrant detector, axial error, radial error

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: Dinesh Munjurulimana, Anil Tiwari, Tingwen Li, Carlos Pereira, Sreekanth Pannala, John Waters

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With the rapid transition to electric vehicles (EVs) across the globe, car manufacturers are in need of integrated and lightweight solutions for the battery packs of these vehicles. An integral part of a battery pack is the battery tray, which constitutes a significant portion of the pack’s overall weight. Based on the functional requirements, cost targets, and packaging space available, a range of materials –from metals, composites, and plastics– are often used to develop these battery trays. This paper considers the design and development of integrated thermoplastic-intensive battery trays, using the available packaging space from a representative EV battery pack. Presented as a proposed alternative are multiple concepts to integrate several connected systems such as cooling plates and underbody impact protection parts of a multi-piece incumbent battery pack. The resulting digital prototype was evaluated for several mechanical performance measures such as mechanical shock, drop, crush resistance, modal analysis, and torsional stiffness. The performance of this alternative design is then compared with the incumbent solution. In addition, insights are gleaned into how these novel approaches can be optimized to meet or exceed the performance of incumbent designs. Preliminary manufacturing feasibility of the optimal solution using injection molding and other commonly used manufacturing methods for thermoplastics is briefly explained. Then numerical and analytical evaluations are performed to show a representative Pareto front of cost vs. volume of the production parts. The proposed solution is observed to offer weight savings of up to 40% on a component level and part elimination of up to two systems in the battery pack of a typical battery EV while offering the potential to meet the required performance measures highlighted above. These conceptual solutions are also observed to potentially offer secondary benefits such as improved thermal and electrical isolations and be able to achieve complex geometrical features, thus demonstrating the ability to use the complete packaging space available in the vehicle platform considered. The detailed study presented in this paper serves as a valuable reference for researches across the globe working on the development of EV battery packs – especially those with an interest in the potential of employing alternate solutions as part of a mixed-material system to help capture untapped opportunities to optimize performance and meet critical application requirements.

Keywords: thermoplastics, lightweighting, part integration, electric vehicle battery packs

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Authors: Komal Babbar

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Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

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Authors: Essia Sebai, Amel Abidi, Hayet benyeddem, Akkari Hafidh

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Herbal extracts are of particular interest to the drug industry; essential oil with significant anthelmintic activity has the potential to be used as an alternative to conventional chemical drugs. In the present study, we describe the chemical profile of Laurus nobilis essential oil (EO), the in vitro anthelmintic activity of laurel oil against Haemonchus contortus and its in vivo anthelmintic effect against the murine helminth parasite model Heligmosomoides polygyrus. The chromatographic profile of L. nobilis (EO) extracted from the leaves of L. nobilis has shown the presence of monoterpenes 1,8-cineol (Eucalyptol) (29.47%), D-Limonène (18.51%) and Linalool (10.84%) in high fractions. The in vitro anthelmintic potential was expressed by an ovicidal effect against H. contortus egg hatching with an inhibition value of 3.23 mg/mL and 87.5% of immobility of adult worms after 8 hours of exposure to 8 mg/mL of L. nobilis EO. Regarding the in vivo anthelmintic potential, L. nobilis (EO) at 2400 mg/kg completely eliminated the egg output of H. polygyrus after seven days of oral treatment, together with a 79.2% of reduction in total worm counts. Based on the obtained funding, L. nobilis EO showed promising in vitro and in vivo anthelmintic capacities against gastrointestinal parasites.

Keywords: lauris nobilis, anthelmintic, haemonchus, pylogyrus

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity and the required nozzle pressure is presented.

Keywords: aerodynamic feeding system, genetic algorithm, multi-objective optimization, workpiece orientation

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Authors: Mantas Sakalas, Paulius Sakalas

Abstract:

This paper presents an analysis and design of a ultrawideband 1.8GHz to 43GHz Low Noise Amplifier (LNA) in 0.1 μm Galium Arsenide (GaAs) pseudomorphic High Electron Mobility Transistor (pHEMT) technology. The feedback based bandwidth extension techniques is analyzed and based on the outcome, a two stage LNA is designed. The impedance fine tuning is implemented by using Transmission Line (TL) structures. The measured performance shows a good agreement with simulation results and an outstanding wideband noise matching. The measured small signal gain was 12 dB, whereas a 3 dB gain flatness in range from 1.8 - 43 GHz was reached. The noise figure was below 4 dB almost all over the entire frequency band of 1.8GHz to 43GHz, the output power at 1 dB compression point was 6 dBm and the DC power consumption was 95 mW. To the best knowledge of the authors the designed LNA outperforms the State of the Art (SotA) reported LNA designs in terms of combined parameters of noise figure within the addressed ultra-wide 3 dB bandwidth, linearity and DC power consumption.

Keywords: feedback amplifiers, GaAs pHEMT, monolithic microwave integrated circuit, LNA, noise matching

Procedia PDF Downloads 211

Authors: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

Abstract:

The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, firefly algorithm, PVDG, voltage fluctuation

Procedia PDF Downloads 317

Authors: Özlem Erzurumlu, Nazan Oskay, Ece Melek

Abstract:

Knitting which is one of the textile manufacturing techniques is manufactured by using the system of single yarn. Knitting wares consisting of loops structurally have flexible structures. Knitting can be shaped and given volume easily due to increasing or decreasing the number of loops, being manufactured in circular form and its flexible structure. While the knitting wares are basically being manufactured to meet the requirements, it takes its place in the art field overflowing outside of industrial production later. Textile artist ensures his ideas to convert into artistic product by using textiles and non-textiles with aesthetic concerns and creative impulses. When textile crafts are observed at the present time we see that knitting technique has an extensive area of use such as sculpture, panel, installation art and performing art. It is examined how the knitting technique is used in textile crafts observing patterns obtained by this technique in textile crafts in this study.

Keywords: art, textile, knitting art, textile crafts

Procedia PDF Downloads 698