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Wear Rate Comparison of Different Impeller Materials for Pumping Various Types of Slurry
No full textThis thesis is submitted to the Department of Mechanical Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Engineering in Mechanical Engineering, May 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 56-57).Erosive wear can as defined as solid deduction process from a solid superficial due to frictional action between the slurry and surface. It is triggered by the effect of solid particles contains by slurry in contradiction of the surface of a solid body. The impacting solid particles progressively take away material from the solid superficial due to cutting action. Erosive wear is a significant factor for design centrifugal pump impeller and pumping slurry. Impeller wear is a very common phenomenon for every industry and slurry transportation system. Slurry erosion takes place in our civilized life such as thermal power plants, hydro power plants, excavating businesses, food handling productions, construction and civil works, oil field, solid-liquid hydro transportation systems, coal liquefaction plants, and boilers.
As the Slurry erosion related machinery or equipment demand is becoming so acute day-by-day, scientists are giving efforts on the aptitudes of utilizing applicable technologies to reduce erosion from the related machinery or equipment. As a result performance of slurry equipment, dependability and operation lifetime of the slurry equipment are significantly improved.
Slurry erosion tester ordinarily used to investigate the comparative erosion behavior and characteristics of various materials expose to slurry at moderate solid concentrations. Slurry erosion tester is a modest and convenient apparatus to determine slurry erosion of different equipment.
In this project, a pin mill type slurry-pot wear tester has been made. Total four types (aluminum, brass, mild steel and cast iron) of material with two geometries (flat bar and impeller) have been made for test. Slurry has been made by mixing silica sand and water by at required ratio in a GI container (slurry pot). All samples has been tested by the developed apparatus and determined wear rate with respect to various parameters like slurry density, shaft speed, impact angle and time. This apparatus is used for performing experiments on numerous samples of dissimilar materials exposed to slurry erosion.
In this experiment, total four types of impeller material with two geometries is used for testing at different operating condition such as impact angle, velocity, density and time. Among the eight samples brass is more erosive for both type of geometries (Flat bar and Impeller). On the other hand, cast iron is less erosive for impeller type geometry (45-degree impact angle) but for flat bar type geometry (0-degree impact angle) mild steel is less erosive. If impact angle and density are increased, erosion is found to increase for all types of materials and geometries. From the obtained results, it is clear that by this testing apparatus different types of materials can be tested and suitable pump impeller materials for different application can be found out.Sandip KarmokarMaster of Engineering in Mechanical Engineerin
Speech Enhancement Using Convolutional Denoising Auto-Encoder
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, May 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 31-35).Speech signals are complex in nature with respect to other forms of communication media such as text or image. Different forms of noises (e.g., additive noise, channel noise, babble noise) interfere with the speech signals and drastically hamper the quality of the speech. Enhancement of speech signals is a daunting task considering multiple forms of noises while denoising a speech signal. Certain analog noise eliminator models have been studied over the years for this purpose. Researchers have also delved into some machine learning techniques (e.g., artificial neural network) to enhance speech signals. In this study, a speech enhancement system is investigated using Convolutional Denoising Autoencoder (CDAE). Convolutional neural network (CNN) is a special kind of deep neural networks which is suitable for 2D structured input (e.g., image) and CDAE is a CNN based special kind of Denoising Autoencoder. CDAE takes advantages from the 2D structured inputs of the features extracted from speech signals and also considers the local temporal relationship among the features. In the proposed system, CDAE is trained considering features from noisy
speech signal as input and clean speech features as desired output. The proposed CDAE based method has been tested on a benchmark dataset, called Speech Command Dataset, and
attained 80% similarity between denoised speech and actual clean speech. The proposed system achieved perceptual evaluation of speech quality (PESQ) value of 2.43 which outperformed other related existing methods.Shaikh Akib ShahriyarMaster of Science in Computer Science and Engineerin
Analysis and Modeling of Automated Walking Guide to Enhance the Mobility of Visually Impaired People
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, March 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 75-88).The development of walking guides has become a prominent research due to the rapid
growth of visually impaired people in recent decades. Although numerous systems have been
developed to aid the visually impaired people, a considerable portion of these are limited in
their scopes. This thesis has implemented a spectacle prototype to assist these individuals
with safe and efficient walking in the surrounding’s environment. The spectacle prototype is
modeled in SolidWorks (3D model) considering the dimension of each electronic
components. In the modeling, the front ultrasonic sensor is positioned in the spectacle to
detect the front obstacles only, the left and right ultrasonic sensors are set to 45 degree from
the spectacle center point in order to detect obstacles within the shoulder and arm of user;
another ultrasonic sensor is positioned towards the ground facing for the detection of pothole.
The Rpi camera is positioned at the center point of the spectacle. In addition, the right and
left temple of the spectacle is designed to position the raspberry pi and battery respectively.
The usage of spectacle based walking guide would help the visually impaired people to scan
the surroundings. Three pieces of distance measurement sensors (ultrasonic sensor) is used
in the walking guide in order to detect the obstacle in each direction including front, left and
right. In addition, the system detects the potholes on the road surface using sensor and
convolutional neural network (CNN). Overall, the spectacle prototype consists of four
ultrasonic sensors; raspberry pi, Rpi camera and battery. CNN technique, runs on raspberry
pi, is used to detect the pothole on the road surface. The pothole images are trained initially
using convolutional neural network in a host computer and the potholes are detected by
capturing a single image each time. The experimental study demonstrates that 98.73%
accuracy is achieved by the front sensor with an error rate of 1.26% when the obstacle is at
50 cm distance. In addition, the results reveal that the system obtains the highest accuracy,
precision and recall 92.67%, 92.33% and 93% respectively for potholes detection. The
electronic spectacle gives a direct audio signal to the user via headphone for avoiding
hindrances effectively.Md. Milon IslamMaster of Science in Computer Science and Engineerin
In Silico Characterization and Homology Modeling of Histamine Receptors
No full textThis thesis is submitted to the Department of Biomedical Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Masters of Science in Biomedical Engineering, February 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 75-86).Histamine plays vital role in molecular mechanism of allergic reactions. Therefore, characterization and homology modeling of Histamine receptor is of great importance to design effective vaccines. In this thesis, different methods are applied to analyse biomolecular features of histamine receptors and design best models of these receptors. In addition to this, the study tried to identify potential B cell and T cell epitope based vaccine of an allergen and consequently, emphasized on to develop a B cell prediction tool. Identified four histamine receptors, such as Histamine H1, Histamine H2, Histamine H3 and Histamine H4 have been analysed through ProtParam to extract physiochemical properties and ClastalW algorithm has been applied to identify conserved regions. Motif and Transmembrane regions have been identified through MEME suit and TMHMM servers, respectively. For homology modeling, I-tasser has been used and generated models have been validated through RAMPAGE, ERRAT and PROCHECK. Targeted api m3 allergen then rendered through self-optimized prediction method with alignment for physiochemical feature extraction. NetCTL 1.2 has been applied to identify preliminary T cell epitope candidates and then scrutinized by Stabilized Matrix Base Method, relative to IC50 values. Predicted T cell epitopes have been further analysed for conservancy and population coverage via IEDB tools. B cell epitopes of api m3 allergen have been predicted through, BCPREDS, ABCpred, Bepipred and Bcepred. In addition, classifier based single interface B cell epitope prediction and/or validation tool has been developed through establishing efficient MATLAB algorithms to classify beta turn regions, hydrophilic regions, surface accessible regions and antigenic regions. Lastly, with superimposing graphical representation of these four criteria in a single interface graph plotted to identify B cell epitopes via this tool. Extracted results denotes that, Histamine receptors possess molecular weight around 55.7 KDa, theoretical pI 9.33-9.62, instability index 34.93-47.00, aliphatic index (AI) was above 90 and the receptors were hydrophobic except histamine H1 receptor. Moderately conserved region was found in 75-94 amino acid position. A profound motif has been identified from 84-149 amino acid position for four histamine receptors with significantly lower E-value. It has been identified that, these receptors are seven pass transmembrane protein and a gap between transmembrane helix number five and six was found in each histamine receptor except Histamine H2 receptor, which can be potential drug target candidate. Generated 3D models have been passed through every spheres of validation. Api m3 allergen has been found relative thermostable nature and only 10.46% of the overall secondary structure consisted of beta turn region. Five MHC class I T-cell epitopes were identified and scrutinized and YTEESVSAL found out as the best epitope. For MHC class II T-cell epitopes YPKDPYLYYDFYPLE and GGPLLRIFTKHMLDV have been found as most prominent T-cell epitopes of api m3 allergen. This study also revealed that, GDRIPDEKN and PHVPEYSSS, as the most effective B-cell epitopes of api m3. The proposed tool efficiently identified B cell epitopes and provided result in a single interface. The tool can aid in B cell research and vaccine development. Finally, the suggested potential drug targets can be applied in designing more sustainable antihistamines and relevant drugs in treating allergic diseases. Predicted T-cell and B-cell epitopes of api m3 allergen could help the researchers to test these vaccines further for immunoreactivity applying in vivo analysis. As still there is no report of T-cell and B-cell epitopes of Apis mellifera, this study can be the pioneer in finding effective vaccine against allergens of honeybee. This research also predicted potential B cell epitope regions from an antigenic protein. The most exciting feature of this part of the study is, it presents results of potential B cell epitopes on a single interface, so that, researchers don‘t need to search for every feature (e.g., hydrophilicity, antigenicity, beta turn, surface accessibility etc.) separately. Finally, the study can certainly aid in B cell epitope-based vaccine design research.Md. Nayem ZobayerMasters of Science in Biomedical Engineerin
Development of Strategic Fit Model of Manufacturing Unit for Garments Industry
No full textThis thesis is submitted to the Department of Industrial Engineering and Management, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Industrial Engineering and Management, April 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 55-63).Though Bangladesh is one of the largest garments manufacturing country in the world and
there happened revolutionary changes more than four decades ago, they couldn’t achieve
sustainable platform yet. The failure to achieve up to the requirement level for the competitive
capabilities/manufacturing metrics is the common phenomenon for the manufacturers. Even
there is an alarming issue that the manufactures yet don’t know how they are affected by these
failures and also can’t measure how much they are statistically fit. The manufacturers fail to
compete with their competitors, since they can’t achieve their manufacturing metrics up to the
requirements. To proceed towards world class manufacturing and to create a sustainable
platform considering highly competitive business market, the manufacturer should aware
about their metrics capabilities, competitive capabilities and reasons of metrics failure. By
being motivated from manufacturer’s failure, we worked on a manufacturing unit of a garments
industry where we aggregated manufacturing metrics and determined how the manufacturers
are affected by the failure of these metrics. This research work will conclude by proposing few
models with their mathematical and graphical explanation. By using these models, the
manufacturers will be able to determine their strategic fitness, security level and associated
loss/penalty.Md. Habibur RahmanMaster of Science in Industrial Engineering and Managemen
