On Design and Optimization of Convolutional Neural Network for Embedded Systems

This work presents the research on optimizing neural networks and deploying them for real-time practical applications. We analyze different optimization methods, namely binarization, separable convolution and pruning. We implement each method for the application of vehicle classification and we empirically evaluate and analyze the results. The objective is to make large neural networks suitable for real-time applications by reducing the computation requirements through these optimization approaches. The data set is of vehicles from 4 classes of vehicle types, and a convolutional model was used to solve the problem initially. Our results show that these optimization methods offer many performance benefits in this application in terms of reduced execution time (by up to 5 ×), reduced model storage requirements, with out largely impacting accuracy, making them a suitable tool for use in streamlining heavy neural networks to be used on resource-constrained envrionments. The platforms used in the research are a desktop platform, and two embedded platforms

A New Handover Management Model for Two-Tier 5G Mobile Networks

There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets, smartphones, and laptops. The rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased demand. One solution to the problem is the emergence of fifth-generation (5G) wireless communication, which can address the challenges by offering very broad wireless area capacity and potential cut-power consumption. The application of small cells is the fundamental mechanism for the 5G technology. The use of small cells can enhance the facility for higher capacity and reuse. However, it must be noted that small cells deployment will lead to frequent handovers of mobile nodes. Considering the importance of small cells in 5G, this paper aims to examine a new resource management scheme that can work to minimize the rate of handovers for mobile phones through careful resources allocation in a two-tier network. Therefore, the resource management problem has been formulated as an optimization issue that we aim to overcome through an optimal solution. To find a solution to the existing problem of frequent handovers, a heuristic approach has been used. This solution is then evaluated and validated through simulation and testing, during which the performance was noted to improve by 12% in the context of handover costs. Therefore, this model has been observed to be more efficient as compared to the existing model

Rice growth and yield characteristics under elevated carbon dioxide and nitrogen management

Received: July 16th, 2022 ; Accepted: September 8th, 2022 ; Published: September 12th, 2022 ; Correspondence: [email protected] atmospheric carbon dioxide (CO2) concentration is increasing and the on crop production needs to be investigated. A pot experiment was conducted in open top chambers (OTC) to determine the response of rice to elevated CO2 (eCO2) under varying time of nitrogen (N) application. The results revealed that photosynthesis, root and shoot dry matter production, yield components and nutrient absorption were favored at eCO2 when N applied up to flowering stage (FT) of rice. However, the N application up to FT of rice also significantly improved percent filled grain, reduce spikelet sterility and rice yield increased by 18 to 20% under eCO2. Rice plant absorbed higher amount of Zn, Ca, Mg, and Fe at eCO2 when N was applied up to FT. Amylose was higher but protein percentage was lower at eCO2. These results indicate that to maximize rice yield under eCO2, it is important to supply N up to FT of rice in order to increase grain fertility and reduce spikelet sterility

Duration of low temperature changes physiological and biochemical attributes of rice seedling

Received: June 2nd, 2022 ; Accepted: August 4th, 2022 ; Published: August 18th, 2022 ; Correspondence: [email protected] low temperature (LT) is detrimental to growth of rice seedling during boro season in Bangladesh. An experiment was conducted in growth chamber during June to October, 2021 using BRRI dhan29 as planting material. The aim of this experiment was to determine the effect of variable duration of LT on growth, physiological and biochemical traits of rice seedling and to determine the age of seedling that can tolerate cold effect. In this experiment 5, 10, 15 and 20 days old seedling (DOS) were exposed to 6 °C for 1, 2, 3 and 4 days. Seedlings were also grown under room temperature (25 °C, RT) which consider as control treatment. Seedlings were grown in plastic trays filled with mixture of soil and cowdung. The experiment was conducted following completely randomized design with 3 replications. Data on shoot length and weight, root length and weight, chlorophyll (Chl), carotenoids, malondialdehyde (MDA) and proline contain were determined after 5 days of temperature sock. The results revealed that the LT was injurious to younger rice seedling when they were exposed to LT for 1 to 2 days. The shoot and root length as well as their dry weight were reduced under low temperature. Further, the Chl and carotenoid content of younger rice seedlings degraded within 2 days of LT exposure. On the contrary, the proline and MDA content of rice seedlings increased to reduce the harmful effect of under LT. It could be concluded that the rice seedlings could tolerate the detrimental effect of LT when they attain at least 15 days

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Cost minimisation for multiple-source water supply systems

Management of municipal water supply systems having multiple groundwater sources constrained by water availability is often challenging. Water quantity limitations of the sources cause economic constraints on system operation, requiring more expensive alternative sources. This paper presents a linear cost minimisation model for such a groundwater-based multiple-source water supply system where water demand is relatively high and groundwater availability is limited, while a minimum supply is to be ensured to the local coverage area of each well. The model decides on the optimum production amount from each source with the objective of cost minimisation for a specified set of demand and source constraints. The model would be useful for system analysis, planning and management purposes, such as analysing water production at various levels of system loss or unaccounted-for water (UFW), or determining optimal production schedules under different system operation scenarios. The model is applied to simulate a groundwater-based sub-network of Dhaka city water supply system where seasonal demand from the system is the highest when the groundwater level is relatively low. Model results show that significant cost reduction would be possible under different operational scenarios through optimal production scheduling at various UFW levels

Response of Some Biochemical and Mineral Constituents of the Postharvest Mango (Mangifera indica L.) Influenced by Different Levels of Bavistin DF

An investigation was carried out with the postharvest mangoes (viz., the Langra and the Khirshapat) treating with different levels of Bavistin DF solution (namely, 250, 500, and 750 PPM) for obtaining results on the biochemical and mineral content changes as well as storability of postharvest mango. The results of the experiments exhibited that only the single effect of varieties was found to be significant in most of the parameters studied. The Langra enriched a greater quantity of crude fiber, lipid, water-soluble protein, phosphorus, and potassium constituents over the Khirshapat. It is revealed that the expansion of mineral contents in the mango was intimately associated with ripening during storage. The results also noticed to be an increasing trend of lipid and protein content in mango pulp with the advance of storage period using Bavistin DF