Morphology, Morphometry, Growth Performance and Carcass Characteristics of Pekin, Nageswari and Their F₁ Crossbred Ducks under Intensive Management

Md. Tanvir Ahmad,Drishti Nandita,Tanvir Mohammad Maruf,Mohammad Hasanuzzaman Pabitra,Sabrina Islam Mony,Md. Shawkat Ali,Md. Sarwar Ahmed,Mohammad Shamsul Alam Bhuiyan 한국가금학회 2021 韓國家禽學會誌 Vol.48 No.2

This study investigated the morphological features, growth, and meat yield performance of Pekin (P), Nageswari (N), and their reciprocal F1 crossbreds (P♂×N♀ and N♂×P♀). A total of 301-day-old ducklings were reared in four different pens up to 20 weeks of age under intensive management conditions. Feeding and management practices were similar for all individuals throughout the experimental period. The morphology and plumage pattern of F1 crossbreds were similar to those of indigenous Nageswari ducks because of the dominant inheritance of the extended Black allele (E locus). Genotype had significant differences (P<0.05) among the four genotypes in morphometric measurements, except wing and shank length. Growth performance was highly significant among the four genotypes (P<0.001) from one-day to 12 weeks of age. The average live weights of P, N, P♂×N♀ and N♂×P♀ crossbred genotypes at 12 weeks of age were 2038.35±29.74, 1542.44±33.61, 1851.85±28.59 and 1691.08±27.80 g, respectively. Meat yield parameters varied significantly (P<0.05) among the different genotypes for all studied traits, except for liver and gizzard weight. Moreover, no significant differences (P>0.05) were observed between P and P♂×N♀ crossbred for important meat yield traits such as hot carcass weight, dressing%, back half weight, drumstick with thigh weight and breast meat weight. Remarkably, the P♂×N♀ crossbreed possesses 50% native inheritance, which contributes to better adaptation in a hot-humid environment. Our results revealed that the P♂×N♀ genotype could be suitable for higher meat production with better adaptability in the agro-climatic conditions of Bangladesh.

EEMD assisted supervised learning for the fault diagnosis of BLDC motor using vibration signal

Tanvir Alam Shifat,허장욱 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.10

Predictive maintenance (PdM) has become a major issue in system health monitoring, as machines are operating under more complex and diverse conditions nowadays. Besides minimizing the risk of a catastrophic failure, a proper maintenance scheme can amplify system yield as well as largely reduce production and maintenance costs. This paper presents a comprehensive study of a permanent magnet brushless DC (BLDC) motor’s fault diagnosis using vibration signals. Based on the degree of deviation from the normal operating condition, three health states are chosen from the entire lifecycle of motor. Acquired signals are decomposed using ensemble empirical mode decomposition (EEMD) and the appropriate intrinsic mode function (IMF) is selected based on the similarity index. Later, selected IMF is analyzed in time-frequency domain by using continuous wavelet transform (CWT) for better localization of fault frequencies. Several statistical features that indicate the health state of the motor are also extracted to diagnose different fault states. Later, feature dimensions were reduced using principal component analysis (PCA) technique and classified using a supervised machine learning technique named k-nearest neighbor (KNN). Extracted IMF from EEMD provides significant fault related information to detect and diagnose different fault states. Proposed method is effectively used to diagnose fault at the incipient stage as well as classify different fault states at incipient stage and severe stage.

Characteristics of Bottom Ash Produced from Fixed Bed Gasification of Polyurethane

( Tanvir Alam ),( Jang-soo Lee ),( Won-seok Yang ),( Se-won Park ),( Jae-jun Kang ),( Yong-chil Seo ) 한국폐기물자원순환학회(구 한국폐기물학회) 2015 한국폐기물자원순환학회 심포지움 Vol.2015 No.2

With the booming of economy, consumption of electronic products have increased rapidly and so do the generation rate of electronic waste. A common type of electronic waste in the final stage at recycling facilities is polyurethane. Polyurethane could be utilized as valuable fuel, since it has higher heating value and low hazardous contents. Gasification experiment was conducted on pellet type SRF made of polyurethane at 1000℃ using a fixed bed reactor. One of the final product in gasification experiment is bottom ash, which usually discarded on landfill. In this study, we tried to figure out the characteristics of bottom ash, which will enable us to know about the recycling possibilities of this residue.

Simple, Robust & User Friendly CAPTCHA ‘InstaCap’ for Web Security

Tanvir Ahmed,Kaiser Ahmed Tushar,Sunjida Islam Nova,Md. Mahbubur Rahman 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.1

Nowadays security matter is a great challenge in web-based systems and we are using various types of HIP to defend malwares in web. But today’s conventional HIP models are able to defend bots but make a user ireful. This paper will focus on a new and simple model of CAPTCHA to defend bot-attack. This model makes a user easily to pass and also amuse them with its simplicity. Considering computational complexity, we are using a thin algorithm with some other technical tricks to make it both robust & simple.

The Hybrid Pseudo Random Number Generator

Tanvir Ahmed,Md. Mahbubur Rahman 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.7

Random number generation is an art and science of deterministically generating a Sequence of numbers that is difficult to distinguish from a true random sequence. It is become important tool in cryptography to generate secrete key. There are so many approaches to generate a pseudo random number. But they have some limitations too. In this paper we represent a new random number generation algorithm with the help of existing conventional methods & some new tricks to enhance the programs randomness. We already know some methods like mid-square or congruent. But, in our random numbers, we just use a congruential method which is pretty much different with conventional methods. That’s why we can consider it as a hybrid method of pseudo random number generator.

Burnt Clay Brick Aggregate for Internal Curing of Concrete under Adverse Curing Conditions

Tanvir Manzur,Sayedur Rahman,Tafannum Torsha,Munaz Ahmed Noor,Khandaker M. Anwar Hossain 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.12

In this study, properties of concrete with brick aggregate as internal curing medium has been investigated under adverse curing conditions. Brick aggregates, commonly known as brick chips (BC), have high porosity and absorption capacity. Desorption tests of different sizes of BC revealed that BC could desorb about 90% of its absorbed water. It was also observed that smaller size BC had higher desorption capacity than that of larger ones. Moreover, higher internal relative humidity was observed for all internally cured (IC) samples as compared to control samples made with 100% rock aggregate particles commonly known as stone chips (SC). Internally cured samples with three different percent replacements (15%, 20% and 25%) of SC with BC were prepared and subjected to six simulated adverse curing conditions. The performance of internally cured concrete under different curing conditions was evaluated in terms of compressive strength, rapid chloride permeability test (RCPT) and linear shrinkage test. The internally cured samples exhibited higher strength and less permeability and shrinkage as compared to their control counterparts under all adverse curing conditions considered in the study. Based on the findings of the study, 20% partial replacement of SC with BC of 9.5 mm in size can be recommended as a guideline for producing internally cured concrete under adverse curing conditions.

Optimum Mix Ratio for Carbon Nanotubes in Cement Mortar

Tanvir Manzur,Nur Yazdani 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.5

Cementitious composites have high compressive strength and modulus of elasticity, but relatively low tensile strength, toughness and ductility. They are amenable to enhancement through nanotechnology due to the physical behavior and size of hydration products. Carbon Nanotube (CNT) is a very efficient reinforcing agent due to its extremely high aspect ratio and ultra-high strength. So, there is a high potential to utilize CNT in producing new cement based composite materials. In this study, a parametric experimental investigation was undertaken to determine optimum mix dosage of CNT for cement mortar. Different dosage rates of surface treated Multi-Walled Nanotubes (MWNT), water/cement ratios and plasticizer amounts (as surfactant for the MWNT) were investigated through compressive and flexural strength determinations. A mixing technique was proposed to address the issues related to dispersion of nanotubes within the cement matrix. The proposed mixing technique and design mix significantly enhanced the compressive and flexural strengths, as compared to control samples with no MWNT

Spatiotemporal variations of precipitation in Bangladesh revealed by nationwide rain gauge data

Tanvir Ahmed,Han-Gyul Jin,Jong-Jin Baik 한국기상학회 2019 한국기상학회 학술대회 논문집 Vol.2019 No.10

Effect of Low Cost Natural Minerals on Solid Refuse Fuel Gasification

( Tanvir Alam ),( Jang-soo Lee ),( Won-seok Yang ),( Se-won Park ),( Sang-yeop Lee ),( Gun-ho Han ),( Youn-ouk Jeong ),( Yong-chil Seo ) 한국폐기물자원순환학회(구 한국폐기물학회) 2017 한국폐기물자원순환학회 심포지움 Vol.2017 No.1

Waste gasification is a promising pathway to convert carbonaceous materials into valuable end products through different synthesis routes, besides the efficient production of power and useable heat. Solid refuse fuel (SRF), which is an alternative fuel produced from the combustibles in municipal solid waste (MSW) and composed of waste plastic, paper, textiles, wood, etc., is one of the main topics in waste gasification nowadays. In this study, an effort was made to do SRF gasification using low cost natural minerals as a bed material to analyze the effect of low cost minerals on gas quality and yield. It is believed that low cost minerals like dolomite and lime usually shows some catalytic effect in promoting hydrocarbon destruction; by cracking reaction, steam reforming reaction and CO₂ reforming reactions. From our previous study, we found that optimum conditions for SRF gasification is ER 0.2, at 950 ℃ temperature in a fixed bed reactor. Thus, experiments were conducted at these conditions by measuring the characteristics of producer gas, concentration of gaseous pollutants and tar. Also, the lower heating value (LHV) of product gas, cold gas efficiency (CGE), carbon conversion (Cc), and residue yield (Ry) were analyzed. Results showed that uses of low cost natural minerals increased the syngas yield. It also increased LHV, CGE and Cc of producer gas. Uses of minerals also successfully decreased the residue yield and tar concentration. However, it increased the concentration of gaseous pollutants a bit, but still the concentration was much less than the allowable limit. In terms of overall performance, dolomite showed comparatively better performance than lime.

A Practical Condition Monitoring Approach Using Normalized Modal Current and Support Vector Machine

Tanvir Alam Shifat,Jang Wook Hur 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2

Current signature analysis is a proven method to diagnose motor-related faults at the incipient stage as well as to model a prognostics framework. Due to three-phase operational complexity, selecting a suitable phase current is a challenging task. Working with all three phases will increase computational expense and decision making will become time-consuming. Therefore, a method is required that guarantees accurate condition monitoring in a shorter period is necessary. In this paper, we present an improved fault diagnosis and prognostics framework of electric motors using a single-phase normalized modal current computation that preserves the characteristics of all three-phases. The normalized modal current ensures the presence of three-phase currents as it is calculated using a linear phase relationship and normalized current amplitudes. The effectiveness of this method is verified using a brushless DC (BLDC) motor at different health states. Using the modal current analysis, anomalies were detected through the third harmonic analysis in different health states of the motor. Also, for future predictions, a support vector machine (SVM) classifier is trained and validated for the features computed from the motor current.