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Blockchain (BC) and Software Defined Networking (SDN) are some of the most prominent emerging technologies in recent research. These technologies provide security, integrity, as well as confidentiality in their respective applications. Cloud computing has also been a popular comprehensive technology for several years. Confidential information is often shared with the cloud infrastructure to give customers access to remote resources, such as computation and storage operations. However, cloud computing also presents substantial security threats, issues, and challenges. Therefore, to overcome these difficulties, we propose integrating Blockchain and SDN in the cloud computing platform. In this research, we introduce the architecture to better secure clouds. Moreover, we leverage a distributed Blockchain approach to convey security, confidentiality, privacy, integrity, adaptability, and scalability in the proposed architecture. BC provides a distributed or decentralized and efficient environment for users. Also, we present an SDN approach to improving the reliability, stability, and load balancing capabilities of the cloud infrastructure. Finally, we provide an experimental evaluation of the performance of our SDN and BC-based implementation using different parameters, also monitoring some attacks in the system and proving its efficacy., Comment: 12 Pages 16 Figures 3 Tables

This article on the floating drug delivery system (FDDS) was written with the primary goal of organizing recent literature with the fundamental process of flotation in achieving gastric retention. The two approaches taken in the development of FDDS by creating both effervescent and non-effervescent floating tablets with a buoyancy mechanism as its foundation. With a limited window for absorption in the upper gastrointestinal tract, instability in the lower intestine environment, and low solubility at higher pH levels, FDDS is a way for delivering drugs. Physiological and formulation variability affecting gastric retention, and the utilization of recently produced and invented polymers are some examples of the novel methodologies in FDDS. This review also focuses on different in vivo and in vitro methods in relation to the functionality and use of floating systems. Floating dosage forms can be administered in conventional forms like tablets or capsules by including the gas-generating agent and the proper ingredients. This paper also discusses several methods for creating floating dosage forms, as well as recent and innovative developments.

Deformation and stress characteristics in the upper crust of the fold-and-thrust belt in the Colombian Eastern Cordillera were investigated by numerical analysis. The structural trend of Colombian Eastern Cordillera has long been considered a possible example of a true contraction orogen. The issue of the convergent displacement along an elastic structural body, which controls present-day deformation in this Cordillera is examined here. Modeling results are presented in terms of three parameters: 1) distributions, orientations, and magnitudes of principal stresses; 2) maximum shear stress (_max) contour; and 3) proximity to failure of elements within faults. Mohr-Coulomb failure criteria with bulk rock properties are applied to analyze the faults. The model shows extensional stresses in the crust at shallow crustal levels (from surface to about 6 km) despite overall contraction, and contraction at depth is confirmed. Measurement results indicate that, for homogeneous crustal thickening, extensional stresses are concentrated in the Servita half-gaben and Bucaramanga fault systems, where the vertical thrust faults and thickening processes are located. Our two-dimensional (2D) modeling results emphasize that extensional stresses are still active along the vertical to sub-vertical fault system in the fold-and-thrust belt of the Colombian Eastern Cordillera.

Extrahepatic biliary tract tumors are rare and among them rhabdomyosarcoma is most common. Rhabdomyosarcoma is a soft tissue malignant musculoskeletal tumor and is a very rare malignancy of the common bile duct in children. It usually presents as obstructive jaundice and/or pruritus. If there is no local invasion to the adjacent tissues, the radiological appearance of the tumor lesion is like a choledochal cyst. So the diagnosis is usually made at surgery or by preoperative biopsy. It is important to diagnose early and differentiate it from choledochal cyst and start treatment as early as possible for long time survival of the patient. This case report presented a case of a 10-year-old boy with recurrent onset of obstructive jaundice and fever preoperatively who was diagnosed as choledochal cyst and postoperatively as embryonal rhabdomyosarcoma of the common bile duct. After surgical resection and postoperative chemotherapy, the child had a good prognosis. So it is crucial to know that this rare tumor can mimic congenital choledochal cyst and it should be considered in the differential diagnosis of obstructive jaundice in children.

With the advent of advanced technology, IoT introduces a vast number of devices connecting with each other and collecting a sheer volume of data. Thus, the demands of IoT security is paramount. Cryptography is being used to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint nature of IoT devices, the traditional cryptographic protocols may not be suited in all IoT environments. Researchers, as a result, have been proposing various lightweight cryptographic algorithms and protocols. In this paper, we discuss the state of the art lightweight cryptographic protocols for IoT networks and present a comparative analysis of the existing protocols. In doing so, this paper has classified the most current algorithm into two parts, such as symmetric and asymmetric lightweight cryptography. Additionally, we consider several recent developed block cipher and stream cipher algorithms. Furthermore, various research challenges of lightweight cryptography have been addressed., Comment: 22 pages, 3 figures and 6 tables

Bangla handwriting recognition is becoming a very important issue nowadays. It is potentially a very important task specially for Bangla speaking population of Bangladesh and West Bengal. By keeping that in our mind we are introducing a comprehensive Bangla handwritten character dataset named BanglaLekha-Isolated. This dataset contains Bangla handwritten numerals, basic characters and compound characters. This dataset was collected from multiple geographical location within Bangladesh and includes sample collected from a variety of aged groups. This dataset can also be used for other classification problems i.e: gender, age, district. This is the largest dataset on Bangla handwritten characters yet., Comment: Bangla Handwriting Dataset, OCR

Magnetic resonance imaging (MRI) is an imaging technique used in medical settings for capturing images of the human body or parts of the human body for clinical purposes. The main benefit of this scan is that, it is a non-invasive method because it uses strong magnetic fields and non-ionizing radiation in the radio frequency range. Hence MRI is considered to be safer to the patient when compared with computed tomography (CT) and traditional X-ray scanning methods which involve doses of ionizing radiation that may increase the risk of malignancy. In MRI acquisition, multi-slice MRI approaches are the most widely used and in its acquisition process, multiple 2D slices are captured to form a 3D volume of the desired part of the body. However, the resolution in the slice direction is usually reduced to allow faster acquisition and also reduce the amount of noise. Improving the resolution of MRI images using existing acquisition methods has proven to be challenging and expensive. To deal with this, super resolution (SR) is widely used and is achieved by combining a set of blurred, noisy low resolution (LR) images to improve its resolution. In this thesis, novel SR approaches for MRI are proposed which are capable of taking multiple multi-slice LR MRI image volumes of the same part of the body and combining them together to obtain 3D SR image volumes that are more accurate than any of the original LR volumes. To accommodate this, firstly, a Gaussian scale mixture (GSM) model prior is used. An extension of this prior named as GSM-cTV constraint is then developed by considering the GSM model combined with a total variation constraint. To develop the proposed SR approaches, the priors in a complex wavelet domain are considered as regularization terms because they can reduce noise by using the statistics of the heavy-tailed nature of MRI images and preserve sharp edges while reducing the noise of their more homogeneous regions. A number of quantitative and qualitative measurements are taken to evaluate the performance of the SR algorithms. For real-data analysis, to assess the accuracy of the SR methods, segmented bone from a CT volume and segmented bone from the output from the SR of MRI volumes are compared. Both the qualitative and quantitative analyses of the experimental results demonstrate the accuracy of the proposed SR approaches in terms of improving the resolution of MRI images. The wavelet based priors are considered for use as regularization terms to develop restoration methods for 3D MRI image de-noising and de-blurring. A number of experiments are conducted to validate the priors for MRI image restoration. Experimental results show that using this prior produces good result in terms of MRI image de-blurring and de-noising. These wavelet based priors are also considered for use as regularization priors to reconstruct the multi-slice MRI volume in a compressed sensing framework to allow faster acquisition. Experimental results show that the volumes reconstructed using these approaches are superior, both visually and quantitatively, to those produced by other algorithms.

The paper discusses the energy consumption and energy saving potential for a major energy-intensive product in the chemical industry-ammonia, based on technologies currently in use and possible process improvements. The paper consists of four parts. In the first part, mainly references to various ammonia production technologies are given. Energy consumption, emissions and saving potentials are discussed in the second part. Thereby, the situation in Europe, the US and India is highlighted and various data sources are compared. In the third part of the paper, a novel approach for modeling energy efficiency improvements is described that accounts for uncertainties and unobserved heterogeneity in the production processes. Besides new investments, revamping investments are also included in the modeling and the development of the production stock is accounted for. Finally, in the fourth part, this approach is applied to the modeling of energy efficiency improvements and CO2 emission reductions in ammonia production. Thereby, considerable improvements in specific energy use and CO2 emissions are found in the reference scenario, yet under the assumption of high oil and gas prices, a partial switch to coal based technologies is expected which lowers notably the CO2 efficiency. Introduction of a CO2 penalty under a certificate trading or other regime is on contrary found to foster energy efficiency and the use of low carbon technologies.

Co-liquefaction of a Chinese bituminous coal with bagasse — a biomass waste — has been carried out in an autoclave of 300-ml capacity at a temperature range of 350–450°C, reaction time 15–45 min and cool hydrogen pressure 300–700 psig (2.04–4.76 MPa). The addition of baggasse and tetralin are beneficial to liquefaction. Optimization of the co-liquefaction process was carried out with respect to oil yield by the Factorial Experiment Design Method. The oil yield reached 48% at optimum conditions of temperature 420°C, cool hydrogen pressure of 500 psig and reaction time of 40 min. A polynomial mathematical model-second order response surface model has been obtained for correlating the oil yield response factor as well as conversion with the major process variables. The equation derived by us holds well in determining the effect of process variables on response factors for any regime condition in the range of our experimental design within ±5%.

Precipitation was collected on an event basis from July 1994 to August 1995 at towns around the capital Dhaka of Bangladesh. The major chemical components were determined by atomic absorption spectrophotometry, UV-Visible spectrophotometry and ion selective electrode method. The concentrations of nitrate and sulphate were found to be below the minimum detection limit of 1.0 mg L- 1; the concentrations of Cl-, Na+, K+, Ca+2, Mg+2 and NH4+ ranged from

An operational low cost system is developed for mapping daily and monthly mean daily global solar radiation reaching the ground over a big geographical area from APT (Automatic Picture Transmission) images of NOAA polar orbiting satellite. The system is suitable for use in south and southeast Asia and is said to be acceptable for engineering, agricultural, and climatological applications requiring the knowledge of geographical and temporal variation of solar radiation. It is alterable for use in other locations. The system comprises a personal computer attached with a small APT receiver along with other peripherals such as monochrome monitors and simple printer. An improved empirical bispectral method which applies visible and far infrared APT images is used to calculate the cloudiness of the sky. The empirical coefficients obtained by correlating cloudiness with ground measured solar radiation are used to estimate solar radiation at a target on the ground knowing the cloudiness of its sky from a satellite image. The geographical coverage of the map can be as big as 15° latitude by 20° longitude near the Equator. The spatial resolution of the radiation map is 111 km. The mean standard error of estimation of daily global radiation is 12.9% with a range of 6–19% of the measured mean. This accuracy is acceptable and comparable to other similar methods developed so far.

During thermal oil recovery the elevated reservoir temperature and pressure in combination with rock matrix could cause significant changes in oil composition and its physical properties, especially the viscosity. This paper presents the results of static laboratory experiments on the thermal alteration of two heavy crude oils of different chemical compositions (one rich in resin content, the other one rich in asphaltenes) as a function of temperature, pressure and admixture of water and/rock matrix. Especially the effects of heating time and temperature were studied. Thermal cracking at temperatures up to 380 °C led to the formation of a gas phase consisting mainly of methane. The generation of CO 2 , H 2 S and the hydrocarbon gases depended on oil composition. The production of CO 2 was enhanced in the presence of water. During a 24 h test, the resin rich crude oil yielded significant amounts of insoluble organic material (pyrobitumen) at temperatures above 340 °C. For the asphaltene rich crude oil this occurred above 360 °C. Both qualitative and quantitative analyses of the products formed during the thermal degradation show their dependence on the chemical composition of the crude oils.

Supermarkets play a significant role in modern urban living in developed and developing nations worldwide. Technology has made it possible to provide peoples’ daily needs such as food either fresh, preserved or cooked, at the hand reach in these supermarkets. This easy lifestyle however, comes with a burden to the environment and natural resources. There are growing concerns for the sustainability of modern lifestyle in connection to worldwide population growth, increasing impact of climate change due to human activities, predicted shortage of traditional energy sources and uncertainty in alternative energy resource, New generation supermarket equipments such as refrigeration, air conditioning, lighting and other processes must aim for effectively reducing such sustainability burden in their application, individually and integrally. This paper investigates sustainablity targets for supermarkets and identifies some sensible choices amongst many of that are possible using emerging technologies.

Sand production is a major problem being faced by operating oil companies for many years. Sand problems are known to have increased production costs considerably. To-date, the roles of shear and tensile failure modes have been well thought out in studying sand production, but the contribution of volumetric failure mechanism in this phenomenon has been ignored. Even though volumetric failure mechanism has been well studied in looking into the phenomenon of land subsidence, but its role in sand production has been neglected in the past. In this paper, the contribution of this mechanism in sand production is addressed. In numerical studies, a finite difference based program was used. This program captures the fluid/solid interaction with complete rigor. In the experimental part, uniaxial strain condition was applied on some synthetic samples to examine volumetric failure mechanism, while traditional triaxial tests were performed on the same type of samples to learn about shear characteristic of the material. The mechanical parameters obtained from these tests were used in the numerical model that covers all tensile, shear and volumetric failure mechanisms. By using numerical and experimental means, it was discovered that volumetric failure mode, i.e. pore collapse, has a significant contribution in sanding. Initially at the well face, only shear and tensile failure may take place, but pore collapse can be triggered in a zone very close to the cavity hole. Subsequent to production of shear or tensile failed material from the open face, pore collapse induced disintegrated material may be exposed to cavity face, and potentially massive sanding may take place.

Mobile robots need to automatically generate a safe, goal-oriented, and fast collision-free trajectory in real-time during the movement in an indoor/outdoor environment. A planned trajectory must be adaptable and drivable with environmental changes where various static and moving obstacles may be present. The ultimate goal of a robot is to reach the destination without hitting any obstacles, therefore, a reactive local path planning algorithm is needed. In this paper, a novel local algorithm is proposed by integrating dynamic window approach (DWA) and improved follow the gap method (IFGM) to generate a collision-free trajectory for a mobile robot which is capable to avoid any moving obstacles presenting in the surrounding environment. In this proposed method, first, a safety distance is maintained according to the relative position of obstacles and the robot. Moreover, find a feasible gap to direct the robot toward the desired goal. Besides, the heading angle is calculated to change the direction of the robot for avoiding collision with nearby obstacles. After that, calculate the appropriate velocity for the robot. Finally, a robust, safe, and goal-directed trajectory is generated which does not suffer from global convergence and local minima problems. The performance and effectiveness of this proposed algorithm are evaluated by experimental results. Refereed/Peer-reviewed

Refereed/Peer-reviewed Visual place recognition is a core component for relocalization and loop closure detection of a visual SLAM system. Over the last few years, many state-of-the-art methods have been proposed, which mainly use random feature information. However, not all the features equally contribute to the place recognition task, i.e., dynamic objects, textureless area, repetitive patterns. Therefore in this study, we proposed a semantically aware place recognition method that is suitable for efficient place recognition with the meaningful feature. A deep neural network is used to filter out the most meaningful and informative region of an image for better scene understanding. Finally, meaningful features and their geometrical information are extracted and saved in the database for loop detection. For experimental validation, the proposed method has been tested on four well-known public datasets. The extensive experimental results considering all standard evaluation matrices show our method produces superior performance than the other state-of-the-art methods.

Refereed/Peer-reviewed