Prospects and Problems of RMG Industry: A study on Bangladesh

The development of Garments Industry is considered as the priority area in the development policy in many countries, especially in Bangladesh. The young entrepreneurs are engaged in varied form of small and medium scale garments industry which comprises of products like shorts, trousers, shirts, sweaters, blouses, skirts, tea-shirts, jackets, sports attire and many more casual and fashion items with the changing times. This study is conducted to analyze the prospects, problems and solution of problems of Readymade Garments Industry in Bangladesh. The findings of this paper show that Bangladesh has a great opportunity to earn a great foreign currency through developing readymade garments industry. The study also suggests some measure for the removal of ongoing crisis of garment sectors. Keywords: Readymade garments, History, Trend, Infrastructural development

Managerial Knowledge and Skills Transfer Practices in Bangladesh

Purpose: The favorable attitude of the trainees and a transfer-friendly climate are highly expected for effective training transfer. Therefore, the purpose of this study was to examine the characteristics of trainees and the work environment in transferring managerial knowledge and skills to the job.   Theoretical framework: This study focuses on three factors considering both the characteristics of trainees and the role played by their peers and supervisors, in relation to the transfer of training based on the theories of training transfer.    Methodology: Data was collected from service holders who completed an MBA degree from a weekend/evening program, using a structured questionnaire. The number of usable questionnaires was 302.The Garret ranking method and structural equation modeling (SEM) with Amos 23 was used to analyze the research data.      Findings: This study found that peer and supervisor assistance for training transfer was not satisfactory. Lack of autonomy, shortage of the required materials in the workplace, as well as an excessive workload, were identified as noteworthy impediments in the transfer of training.   Research, Practical and Social implication: This study could increase recognition among coworkers and managers about the significance of supporting fellow workers in applying their recently acquired knowledge and abilities on the job. Additionally, the authorities might receive advice on how to create a congenial environment for training transfer in their organization.   Originality/Value: Assessment of training application and transfer practices would become helpful for Bangladesh to ensure progress and development as a developing country.

Design of microstrip patch antenna to deploy unmanned aerial vehicle as UE in 5G wireless network

The use of unmanned aerial vehicle (UAV) has been increasing rapidly in the civilian and military applications, because of UAV's high-performance communication with ground clients, especially for its intrinsic properties such as adaptive altitude, mobility, and flexibility. UAV deployment can be monitored and controlled through 5G wireless network as user equipment (UE) along with other devices. A highly directive microstrip patch antenna (MPA) could establish long-distance communication by overcoming air attenuation and reduce co-channel interference in the limited region if UAV uses a specifically dedicated band, which might enhance spatially reuse of the spectrum. Also, MPA is highly recommended for UAV because of its low weight, low cost, compact size, and flat shape. In this paper, we have designed a highly directive single-band 2×2 and 4×4 antenna array for 5.8 GHz and 28 GHz frequency respectively for UAV application in a focus to deploy UAV through 5G wireless network. Here, The Roger RT5880 (lossy) material utilize as a substrate due to its lower dielectric constant which achieves higher directivity and good mechanical stability. Inset feed technique used to feed antenna for lowering input impedance which provides higher antenna efficiency. The results show a wider bandwidth of 702 MHz and 1.596 GHz for 5.8 GHz and 28 GHz antenna array correspondingly with a compact size

Ab-initio insights into the physical properties of XIr3 (X = La, Th) superconductors: A comparative analysis

Here we report the structural, elastic, bonding, thermo-mechanical, optoelectronic and superconducting state properties of recently discovered XIr3 (X = La, Th) superconductors utilizing the density functional theory (DFT). The elastic, bonding, thermal and optical properties of these compounds are investigated for the first time. The calculated lattice and superconducting state parameters are in reasonable agreement to those found in the literature. In the ground state, both the compounds are mechanically stable and possess highly ductile character, high machinability, low Debye temperature, low bond hardness and significantly high melting point. The thermal conductivities of the compounds are found to be very low which suggests that they can be used for thermal insulation purpose. The population analysis and charge density distribution map confirm the presence of both ionic and covalent bonds in the compounds with ionic bond playing dominant roles. The calculated band structure and DOS profiles indicate metallic character. Unlike the significant anisotropy observed in elastic and thermal properties, all the optical constants of these compounds exhibit almost isotropic behavior. The optical constants correspond very well with the electronic band structure and DOS features. We have estimated the superconducting transition temperature of the compounds in this work

A Literature Review On NoSQL Database For Big Data Processing

Abstract Objective:Aim of the present study was to literature review on the NoSQL Database for Big Data processing including the structural issues and the real-time data mining techniques to extract the estimated valuable information.Methods:We searched the Springer Link and IEEE Xplore online databases for articles published in English language during the last seven years (between January 2011 and December 2017).We specifically searched for two keywords (“NoSQL” and “Big Data”) to find the articles.The inclusion criteria were articles on the use of performance comparison on valuable information processing in the field of Big Data through NoSQL databases.Results:In the 18 selected articles,this review identified 8 articles which provided various suitable recommendations on NoSQL databases for specific area focus on the value chain of Big Data,5 articles described the performance comparison of different NoSQL databases, 2 articles presented the background of basics characteristics data model for NoSQL,1 article denoted the storage in respect of cloud computing and 2 articles focused the transactions of NoSQL.Conclusion:In this literature,we presented the NoSQL databases for Big Data processing including its transactional and structural issues. Additionally, we highlight research directions and challenges in relation to Big Data processing. Therefore,we believe that the information contained in this review will incredible support and guide the progress of the Big Data processing

Comprehensive first-principles insights into the physical properties of intermetallic Zr3_3Ir: a noncentrosymmetric superconductor

We have looked into the structural, mechanical, optoelectronic, superconducting state and thermophysical aspects of intermetallic compound Zr$_3$Ir using the density functional theory (DFT). Many of the physical properties, including direction dependent mechanical properties, Vickers hardness, optical properties, chemical bonding nature, and charge density distributions, are being investigated for the first time. According to this study, Zr$_3$Ir exhibits ductile features, high machinability, significant metallic bonding, a low Vickers hardness with low Debye temperature, and a modest level of elastic anisotropy. The mechanical and dynamical stabilities of Zr$_3$Ir have been confirmed. The metallic nature of Zr$_3$Ir is seen in the electronic band structures with a high electronic energy density of states at the Fermi level. The bonding nature has been explored by the charge density mapping and bond population analysis. The tetragonal Zr$_3$Ir shows a remarkable electronic stability, as confirmed by the presence of a pseudogap in the electronic energy density of states at the Fermi level between the bonding and antibonding states. Optical parameters show very good agreement with the electronic properties. The reflectivity spectra reveal that Zr$_3$Ir is a good reflector in the infrared and near-visible regions. Zr$_3$Ir is an excellent ultra-violet (UV) radiation absorber. High refractive index at visible photon energies indicates that Zr$_3$Ir could be used to improve the visual aspects of electronic displays. All the optical constants exhibit a moderate degree of anisotropy. Zr$_3$Ir has a moderate melting point, high damage tolerance, and very low minimum thermal conductivity. The thermomechanical characteristics of Zr$_3$Ir reveal that it is a potential thermal barrier coating material. The superconducting state parameters of Zr$_3$Ir are also explored

A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction

Globally, many studies on machine learning (ML)-based flood susceptibility modeling have been carried out in recent years. While majority of those models produce reasonably accurate flood predictions, the outcomes are subject to uncertainty since flood susceptibility models (FSMs) may produce varying spatial predictions. However, there have not been many attempts to address these uncertainties because identifying spatial agreement in flood projections is a complex process. This study presents a framework for reducing spatial disagreement among four standalone and hybridized ML-based FSMs: random forest (RF), k-nearest neighbor (KNN), multilayer perceptron (MLP), and hybridized genetic algorithm-gaussian radial basis function-support vector regression (GA-RBF-SVR). Besides, an optimized model was developed combining the outcomes of those four models. The southwest coastal region of Bangladesh was selected as the case area. A comparable percentage of flood potential area (approximately 60% of the total land areas) was produced by all ML-based models. Despite achieving high prediction accuracy, spatial discrepancy in the model outcomes was observed, with pixel-wise correlation coefficients across different models ranging from 0.62 to 0.91. The optimized model exhibited high prediction accuracy and improved spatial agreement by reducing the number of classification errors. The framework presented in this study might aid in the formulation of risk-based development plans and enhancement of current early warning systems

Forest Fire Danger/Risk Forecasting: A Remote Sensing Approach

Forest/wildland fires are natural disasters that create a significant threat to the communities living in the vicinity of the forested landscape. To minimize the risk concerning resiliency of those urban communities to forest fires, my overall objective was to develop primarily remote sensing (RS)-based models assessing potential risks at the wildland-urban interface (WUI) and making predictions of danger conditions in the environs forest/vegetation. I investigated the risks associated with WUI for the Fort McMurray community and danger conditions in the northern part of Alberta, Canada. For developing the risk modelling framework at WUI, I employed primarily a WorldView-2 satellite image acquired on June 06, 2016. I estimated structural damages due to the devastating 2016 Horse River wildland fire (HRF) that entered the community on May 03, 2016. Besides, I analyzed the presence of vegetation at the WUI to identify the associated risks according to the FireSmart Canada guidelines. My remote sensing-based estimates of the number of structural damages identified a strong linear relationship (i.e., r2 value of 0.97) with the ground-based estimates. Besides, all damaged structures were found associated with the existence of vegetation within the 30m buffer/priority zone of the WUI. It was revealed that approximately 30% of the areas of the WUI were vulnerable due to the presence of vegetation, in which approximately 7% were burned during the 2016 HRF event that led the structural damages. In addition, I developed a new medium-term (i.e., four days) model to forecast forest fire danger conditions using RS-derived biophysical variables of vegetation. I primarily employed Terra MODIS (moderate resolution imaging spectroradiometer)-derived four-day composites of daily surface temperature, normalized difference vegetation index and normalized difference water index. The model was able to detect about 75% of the fire events in the top two danger classes (i.e., very high and high) when evaluated with the historical ground-based forest fire occurrences during the fire seasons of 2015–2017. Besides, the model was able to predict the 2016 HRF event with about 67% agreement. Finally, I developed an operational near real-time (NRT) model to forecast forest fire danger conditions for a day to the next 8 days. Here, I employed Terra MODIS-acquired NRT data from NASA's LANCE (land, atmosphere near real-time capability for earth observing system), where data are made available to the public domain within 2.5 hours of satellite observation. The NRT model was successful in producing forecasted forest fire danger maps at any given time. These developed risk/forecast models would be very useful for the stakeholders in the forest fires management strategies of saving life, property, and community

Effective Processing Time & Cost Management of Dyes, Chemicals & Utilities Used in the Combed & Compact Knit Fabric Colouration in the Dyeing Textile Industries

Industrialization is an inevitable feature of economic intensification in a developing country. The textile dyeing industries uses huge amount of water, steam electricity and substantial quantities of complex chemicals. Textile dyeing house operating in this sector are facing significant challenges to reduce their natural resources and energy consumption. The main purposes of this investigation is to reduce the process time, cost of chemicals, cost of utilities and cost of effluent treatment. In the very beginning of this research, properties of compact and combed yarn were investigated. Then wet processing and process time required for both the compact and combed fabric are compared. Later on different costs associated with the wet processing of both compact and combed yarn fabric are also analyzed. Through this work it is tried to focus on the use of compact yarn fabric instead of combed yarn could be the best possible way to meet the challenges faced by the textile dyeing as well as textile industrie

Remote Sensing of Wildland Fire-induced Risk Assessment Framework

Wildland fire is one of the critical natural hazards that pose a significant threat to the communities located in the vicinity of forested/vegetated areas. In this report, our overall goal was to use very high spatial resolution (0.5-2.4m) satellite images to develop wildland fire-induced risk framework. We considered two extreme fire events, such as the 2016 HRF over Fort McMurray, and 2011 Lesser Slave Lake fire in Alberta. Thus, our activities included the: (i) estimation of the structural damages; and (ii) delineation of the wildland-urban interface (WUI) and its associated buffers at certain intervals, and their utilization in assessing potential risks. Our proposed method of remote sensing-based estimates was compared with the ground-based information available from the Planning and Development Recovery Committee Task Force of Regional Municipality of Wood Buffalo (RMWB) and National Fire Information Database (NFID); and found strong linear relationships (i.e., r2-value of 0.97 with a slope of 0.97 for the 2016 HRF over Fort McMurray; and 378 from satellite image vs. 407 from 378 from satellite image vs. 407 from NFID system for the 2011 Lesser Slave Lake fire). Upon delineating the WUI and its associated buffer zones at 10m, 30m, 50m, 70m and 100m distances; we found existence of vegetation within the 30m buffers from the WUI for all of the damaged structures. In addition, we noticed that the relevant authorities had removed vegetation in some areas between 30m and 70m buffers from the WUI in case of Fort McMurray area, which was proven to be effective in order to protect the structures in the adjacent communities. Furthermore, we mapped the wildland fire-induced vulnerable areas upon considering the WUI and its associated buffers. We found that there were still some communities that had the existence of vegetation within the buffer zones; thus such vegetation should be removed and monitored regularly in order to reduce the wildland fire-induced risks.Othe