Forecasting Volatility of Quality Assessment for High Energy Biscuits (HEB) with ARCH Model

The High Energy Biscuits (HEB) products-310 data were collected from Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka over the year 2007 to 2012 in the method of single stage cluster sampling. Volatility as a measure of risk plays an important role in many qualitative decisions in such a situations. The main purpose of this study is to examine the volatility of the quality of High Energy Biscuits (HEB) products and its related stylized facts using Auto-regressive Conditional Heteoskedastic (ARCH) models. The physiochemical analysis data was used to study the volatility in the quality of High Energy Biscuits (HEB) products over a 5 years period. The adequacy of selected model tested using Auto-regressive Conditional Heteoskedastic-Lagrange Multiplier (ARCH-LM) test. The study concludes that ARCH model explains volatility of the quality of High Energy Biscuits (HEB) products. Keywords: Volatility; ARCH models; ARCH-LM test; Quality of High Energy Biscuits (HEB) products; Single stage cluster sampling; Institute of Food Science and Technology (IFST). DOI: 10.7176/FSQM/121-05 Publication date: January 31st 202

Simultaneous heat and mass transfer on oscillatory free convection boundary layer flow

The problem of simultaneous heat and mass transfer in two-dimensional free convection from a semi-infinite vertical flat plate is investigated. An integral method is used to find a solution for zero wall velocity and for a mass transfer velocity at the wall with small-amplitude oscillatory wall temperature. Low- and high-frequency solutions are developed separately and are discussed graphically with the effects of the parameters Gr (the Grashof number for heat transfer), Gc (the Grashof number for mass transfer) and Sc (the Schmidt number) for Pr = 0–71 representing aid at 20°C

Engineering Lewis acidic materials for biomass conversion and battery applications.

My long-term goal is to develop catalytic systems to produce renewable energy for a sustainable society. The overall research objective of my dissertation is to advance understanding of Lewis acidic materials for (1) conversion of renewable lignin into phenolics and (2) enhanced cycling stability of lithium metal batteries to safely store renewable electricity from wind and solar, thereby laying the groundwork for our transition to a sustainable society. Petroleum is a conventional feedstock for current transportation fuels (gasoline, diesel, and jet fuels). However, petroleum is a finite resource and produces greenhouse gases (CO2 and CH4) upon processing, which contributes to climate change. Therefore, we need to develop ways to tap into alternative feedstocks. Many researchers have investigated the use of catalytic conversion of lignocellulosic biomass to produce biofuels (bioethanol). During bioethanol production, carbohydrates (cellulose and hemicellulose) are digested to produce bioethanol. The residual lignin is left behind. The ability to catalytically convert lignin into high-value chemicals will incentivize biorefineries and promote a sustainable bio-economy. Electricity is another renewable energy that can be produced from wind and solar. The major challenge in using electricity-driven transportations (electric vehicles) lies in their storage in lithium metal batteries. However, chemical and electrochemical reactions in conventional lithium-metal batteries are not stable. The movement of undesired anions promotes capacity decay and hazardous lithium dendrite growth. As a result, these batteries have short lives and short-circuiting, which leads to fire and explosion. The ability to control the reactivity of the ions in the electrolytes will enable safety and promote future electric vehicles for a cleaner environment. My dissertation focuses on the development of Lewis acidic materials to address the challenges in (1) lignin upcycling and (2) the safety and cyclability of lithium metal batteries. First, lignin is an oxygen-rich phenolic polymer. To efficiently release the phenolic monomers from lignin, I developed the Lewis acid catalysts in the form of oxygen vacancies to activate the oxygen functionality of lignin. Second, I grafted the Lewis acidic metal-organic frameworks (MOFs) onto the polypropylene separator to immobilize the TFSI- anions in conventional electrolytes (1M LiTFSI in organic solvents). The developed materials restrict the mobility of anions and polyselenides, thereby improving the lithium-selenium batteries\u27 capacity retention and cycling stability. I divided this dissertation into six chapters to cover background about Lewis acidic materials and their uses for catalytic lignin upgrading and lithium-selenium batteries. The first four chapters of this dissertation describe the engineering/development of the Lewis acidic material for the catalysis of bioderived organics, lignin. Then, chapter five describes the incorporation of the Lewis acidic MOFs into a polypropylene separator to improve battery capacity and safety. Incorporating the Lewis acidic MOFs controlled ion transport properties, thereby restricting the mobility of undesired anions and polyselenides and improving capacity retention in lithium-selenium batteries. Finally, Chapter six suggests future research directions to create next-generation alkali metal-based batteries that are safe and powerful to face future challenges for developing a sustainable carbon zero society

Optical Character Recognition based on Template Matching

This paper presents an innovative design for Optical Character Recognition (OCR) from text images by using the Template Matching method.OCR is an important research area and one of the most successful applications of technology in the field of pattern recognition and artificial intelligence.OCR provides full alphanumeric visualization of printed and handwritten characters by scanning text images and converts it into a corresponding editable text document. The main objective of this system prototype is to develop a prototype for the OCR system and to implement The Template Matching algorithm for provoking the system prototype. In this paper, we took alphabet (A-Z and a-z), and numbers (0-1), grayscale images, bitmap image format were used and recognized the alphabet and numbers by comparing between two images. Besides, we checked accuracy for different fonts of alphabet and numbers. Here we used Matlab R2018a software for the proper implementation of the system

Simulation and Design of University Area Network Scenario(UANS) using Cisco Packet Tracer

Computer network has become the most significant issue in our day to day life. Networking companies depend on the proper functioning and analysis of their networks for education, administration, communication, e-library, automation, etc. Mainly interfacing with the network is induced by one of the other user/users to share some data with them. So, this paper is about communication among users present at remote sites, sharing this same network UANS. UANS stands for the University Area Network Scenario. So in this work the network is designed using Cisco Packet Tracer. The paper describes how the tool can be used to develop a simulation model of the Pabna University of Science and Technology, Pabna, Bangladesh. The study provides into various concepts such as topology design, IP address configuration and how to send information in the form of packets in a single network and the use of virtual Local Area Network (VLANs) to separate the traffic generated by a different department

Classification of Image using Convolutional Neural Network (CNN)

Computer vision is concerned with the automatic extraction, analysis, and understanding of useful information from a single image or a sequence of images. We have used Convolutional Neural Networks (CNN) in automatic image classification systems. In most cases, we utilize the features from the top layer of the CNN for classification; however, those features may not contain enough useful information to predict an image correctly. In some cases, features from the lower layer carry more discriminative power than those from the top. Therefore, applying features from a specific layer only to classification seems to be a process that does not utilize learned CNN2019;s potential discriminant power to its full extent. Because of this property we are in need of fusion of features from multiple layers. We want to create a model with multiple layers that will be able to recognize and classify the images. We want to complete our model by using the concepts of Convolutional Neural Network and CIFAR-10 dataset. Moreover, we will show how MatConvNet can be used to implement our model with CPU training as well as less training time. The objective of our work is to learn and practically apply the concepts of Convolutional Neural Network

Organoleptic qualities and proximate composition of fish grown in good aquaculture practice-based carp fattening pond

Organoleptic qualities and proximate composition of fish grown in carp fattening pond were studied under three treatments of feed and fertiliser management. Treatment T1 was designed with the use of organic fertiliser and stocking of silver carp, T2 with both organic and inorganic fertilisers and silver carp and T3 with both organic and inorganic fertilisers but excluding silver carp. One day in a week feeding restriction was followed in all the treatments.  Fishes were stocked with a stocking density of 2470 fishes ha–1. Three fishes (Gibelion catla, Labeo rohita and Cirrhinus cirrhosus) were selected for organoleptic and proximate assessment. Cyanobacteria along with total phytoplankton cell density was significantly higher at treatment T2 followed by T3 and T1. However, in terms of productivity (Chl-a) treatment T2 was 27.1 and 13.3% higher compared to T1 and T3 respectively. Parameters assessed for proximate composition analysis did not vary across treatments and organoleptic test revealed comparatively higher acceptability of fishes collected from treatment T1 followed by T2 and T3 for all the fishes. Overall acceptability was higher for L. rohita from treatment T1. This study concluded that, inorganic fertilisation along with silver carp can improve the organoleptic properties of carps in pond

Study and Optimized Simulation of OSPFv3 Routing Protocol in IPv6 Network

Routing is a design way to pass the data packet. User is assigns the path in a routing configuration. A significant role played by the router for providing the dynamic routing in the network. Structure and Configuration are different for each routing protocols. Next generation internet protocol IPv6 which provides large address space, simple header format. It is mainly effective and efficient routing. It is also ensure good quality of service and also provide security. Routing protocol (OSPFv3) in IPv6 network has been studied and implemented using 2018;cisco packet tracer2019;. 2018;Ping2019; the ping command is used to check the results. The small virtual network created in Cisco platform .It is also used to test the OSPFv3 protocol in the IPv6 network. This paper also contains step by step configuration and explanation in assigning of IPv6 address in routers and end devices. The receiving and sending the packet of data in a network is the responsibility of the internet protocol layer. It also contains the data analysis of packet forwarding through IPv6 on OSPFv3 in simulation mode of cisco packet virtual environment to make the decision eventually secure and faster protocol in IPv6 environment