An Empirical Analysis of the Factors Associated with Mushroom Cultivation: A Case of Dhaka

The analysis aimed to identify mushroom production and marketing problems by different stakeholders in Bangladesh, specifically in the Dhaka district. It also seeks to improve the mushroom marketing system for domestic markets. The research was carried out in the Savar Upazila, located in the Dhaka district. One hundred twenty-one farmers were randomly picked and asked questions using an interview schedule to collect data. Pearson's chi-squared test was utilized to investigate the degree to which socio-demographic factors and the response variable are related. In the end, a multivariate method known as logistic regression analysis is used to study the relationships between each predictor variable and the result variable that pertains to the respondents. The result revealed significant effects of gender, farmer's education, and information sources for intermediate and experienced mushroom cultivators. However, land size, scientific cultivation, sources of capital, packaging, and sale were stronger among expert mushroom farmers than the new and mediocre mushroom farmers. This research provides valuable insights to improve the mushroom marketing system for domestic markets

An explorative treatment of idiosyncratic supposition of management values in banking sector in light of Hofstede philosophy

Within the differences in culture, impeccable managing capacities leads to be innovative in business practices, better learning opportunities within the organizations and ensure sustainable sources of competitive advantages. Organizational stability and control mechanism, rules and policies, flexibility, discretion, innovation, creativity, risk taking ability, professional growth and the acquisition of new professional knowledge and skills, result oriented, coordination, efficiency and hard driving competitiveness that are aligned with the culture. This paper is based on the opportunity to make compare cultural dimension in banking sector in Bangladesh with the assist of Hofstede philosophy. Primary data has been used for determining the idiosyncratic supposition of management values in banking sector, but for accomplishing this explorative treatment there is inconsistency and disparity between the two categories in banks in values, philosophy, appreciative people’s conceptions, control mechanism, role and affiliation. Adaptability and appreciating values and attitudes consequence to advancing competencies and capabilities that leads to ensure sustainable growth and achieving competitive advantages. Key words: competitive advantages, innovation, creativity, control mechanism, values, attitud

Immunohistochemical analysis of epidermal growth factor receptor as a predictive biomarker in lung adenocarcinoma – A cross-sectional study of 33 cases on computed tomography-guided core needle biopsy specimens

Background: Lung cancer is the second most common cause of cancer in all ages and both genders and is the leading cause of cancer death. Two major groups of lung cancers are – small cell lung carcinoma (SCLC) and non-SCLC (NSCLC). Due to discovery of driver mutation such as epidermal growth factor receptor (EGFR) mutation in NSCLC, the paradigm of lung cancer therapy has shifted from cytotoxic platinum based therapy to tyrosine kinase inhibitor (TKI) therapy. In this study, we have analyzed EGFR expression in NSCLC by immunohistochemistry (IHC) and studied the response to TKI therapy in terms of progression free survival (PFS) and overall survival (OS). Aims and Objectives: In this study, we have retrospectively analyzed the EGFR overexpression in adenocarcinoma of lung in core needle biopsy (CNB) specimen by IHC analysis and correlated with the therapeutic response and survival rate (OS and PFS) in lung carcinoma patients. Materials and Methods: We have analyzed retrospectively EGFR expression in lung adenocarcinoma cases (computed tomography-guided CNB specimen) by IHC. In our study, we have used monoclonal primary antibodies against two most common EGFR mutations, that is, L858R point mutation and E 746–A 750 deletion. Results: Out of 33 cases, EGFR expression was seen in 28 cases. For EGFR expression assessment by IHC, both cytoplasmic and/or membranous staining taken into consideration. EGFR positivity was interpreted only when >10% tumor cells having 2+ or more intensely staining pattern. The response to TKI therapy in terms of PFS and OS was also studied. Conclusion: IHC analysis of EGFR mutation using specific antibodies has extremely high specificity with good sensitivity. Use of targeted therapy in the form of TKI in EGFR positive lung adenocarcinoma has high response rate and long duration of survival (PFS and OS) with acceptable toxicity profile in contrast to the conventional therapy

A New Step-Up Switched-Capacitor Voltage Balancing Converter for NPC Multilevel Inverter-Based Solar PV System

This paper proposed a grid connected solar Photovoltaic (PV) Systems with a new voltage balancing converter suitable for Neutral-Point-Clamped (NPC) Multilevel Inverter (MLI). The switched-capacitors used in the proposed converter is able to balance the DC link capacitor voltage effectively by using proper switching states. The proposed balancing converter can be extended to any higher levels and it can boost the DC input voltage to a higher voltage levels without using any magnetic components. This feature allows the converter to operate with the boosting capability of the input voltage to the desired output voltage while ensuring the self-balancing. In this paper the proposed converter is used for a grid connected solar PV system with NPC multilevel inverter, which is controlled using vector control scheme. The proposed grid connected solar PV system with associated controllers and maximum power point tracking (MPPT) is implemented in Matlab/SimPowerSystem and experimentally validated using dSPACE system and designed converters. The simulation and experimental results show that the proposed topology can effectively balance the DC link voltage, extract maximum power from PV module and inject power to the grid under varying solar irradiances with very good steady state and dynamic performances

Lifetime Maximization of Sensor Networks Through Optimal Data Collection Scheduling of Mobile Sink

The problem of maximizing lifetime of a sensor network is still challenging mainly due to the stringent delay-deadline of real-time applications and heterogeneity of sensor devices. The problem is further complicated when the network contains many obstacles. In maximizing network lifetime, existing literature works either merely address issues of application delay-deadline and presence of obstacles, or analyze primitive data collection approaches for such an environment. In this paper, we formulate optimal data collection schedule of a mobile sink in an obstructed sensor network as a mixed-integer linear programming (MILP) problem. The proposed data collection scheduling finds an optimal set of rendezvous nodes over a preformed Starfish routing backbone, and corresponding sojourn duration so as to maximize the network lifetime while maintaining delay-deadline constraint in an obstructed network. The proposed Starfish-scheduling ensures a loop-free traveling path for a mobile sink across the network. The results of performance evaluation, performed in network simulator-2, depict the suitability of Starfish scheduling as it outperforms state-of-the-art-works in terms of extending network lifetime and data delivery throughput as well as reducing average end-to-end delay

Fault modelling, detection and identification in power systems

© 2011 Dr. Sajeeb SahaPower system is one of the largest interconnected dynamic systems in modern world, consisting of thousands of electrical sources, loads, transmission and distribution lines, power transformers, circuit breakers etc. Faults in any component of the power system may cause significant disruption to power supply and thus financial losses and disruption to way of life. In this thesis we will present comprehensive suite of nonlinear and linearised fault dependent models of various types of power systems. The models are novel and generic in the way they are derived, which make them applicable to various types of power systems studies such as planning, protection, fault analysis, dynamic, transient and steady stability, voltage collapse and contingency analysis to name a few. Unlike other fault detection models that have been used in the literature, our developed models include the dynamics of the exciter and governor associated with each generator. Thus the generic nature of the developed models stems from their ability to accurately describe the system behavior under normal and abnormal conditions. The abnormal conditions include faults of symmetrical and unsymmetrical types, ground and ground free faults. Nonlinear as well linear models are developed in form of differential and algebraic equations and also in form of state space where the fault appears in a separate channel to control inputs and disturbances, i.e. separable. The later feature is a necessary requirement for using model-based techniques for the design of either fault detection schemes or any other control schemes. The veracity of these models is vindicated through comparison studies carried out on similar systems using the developed models and commercial available packages producing exactly the same outcome. The above models are then used to design fault detection systems that are proven to be able to detect and reconstruct faults in near real time. Both symmetrical and unsymmetrical faults of various types and combinations are tested and highly accurate results are obtained. Furthermore novel approaches to fault detection using knowledge based training algorithms are developed and used on nonlinear and linear models of a large power system. The novelty in the developed scheme is that they use only the voltage profile of the power system and simple logic to detect and identify any fault anywhere in the system. Once a fault is detected its exact location is found through the use of a simple least square support vector machine based training system. The accuracy of the fault location identification system is remarkably high, around 99.9% accuracy

Evaluating rail transit\u27s comparative advantages in travel cost and time over taxi with open data in two U.S. cities

This paper presents a comparative analysis of rail transit and taxi by travel cost and time based on the large-scale taxi trip data and public transit schedule information in two major U.S. cities. To quantify the relative advantage of one mode over the other, we introduce the notion of travel gradient, which is travel cost difference divided by travel time difference. Based on the signs of travel cost and time differences, we classify all trips into four quadrants. Quadrant II trips are selected for further analysis because rail transit is identified to be competitive with taxi for such trips. We also explore the relation between various trip characteristics and travel gradient with and without considering the spatial variation of such a relation. Main research findings include: (1) around 70% of the taxi trips in the considered datasets can be substituted with rail transit trips if the maximum walking distance is 0.5 miles at each trip end; (2) for around 10% of taxi trips with both modes being viable, rail transit dominates taxi in both travel cost and time; for the rest, rail transit is competitive with taxi; (3) the marginal travel cost saving due to mode switching from taxi to rail transit is about $70; and (4) there exist clearly spatial variations of the relation between trip characteristics and travel gradient. The main policy recommendation from this study is that rail transit can be better marketed by highlighting its relative advantage over taxi in travel time and cost, especially for travels in certain directions and time periods

Sensor fault resilient control of electronically coupled distributed energy resources in islanded microgrids

In this paper a sensor fault resilient control approach for electronically interfaced distributed energy resource (DER) in islanded (autonomous) microgrids is proposed. The proposed control strategy consists of sliding mode observer (SMO) and output feedback control law to ensure resiliency of DER units against erroneous measurements associated with sensor malfunctioning. The error in measurements results from malfunctioning of sensors are modelled as sensor faults in this paper. The SMO in the proposed approach estimates (reconstructs) sensor faults, and the reconstructed faults are used to devise fault tolerant control strategy. In order to demonstrate that the proposed control strategy is resilient to sensor malfunctioning, various simulation studies are carried out on single DER unit and multi DER units in an islanded microgrid