Throughput Analysis of Primary and Secondary Networks in a Shared IEEE 802.11 System

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.Comment: To appear in IEEE Transactions on Wireless Communication

Some methods of numerical integration over a semi-infinite interval

summary:The authors utilize some methods of numerical integration over a finite interval (Clenshaw and Curtic 1960, Filippi 1964, Basu 1971) to solve the quadrature problems over a semi-infinite interval. Technique similar to that presented in the authors' previous paper (Appl. mat. 20 (1975), pp. 216 to 221) has been adopted

Climate change effects on Chickpea yield and its variability in Andhra Pradesh, India

Farmers usually do not know the precise output that is affected by climatic factors such as temperature and rainfall and are characterized by inter-annual variability, part of which is caused by global climate change. No study covers the influences of climate factors on yield and yield risk in the context of chickpea farming in Andhra Pradesh, India. In this context, this study aimed to investigate the trends in climate change variables during Rabi season (October to January, 1996-2020) and evaluated their variability on chickpea yields across different agro-climatic zones in Andhra Pradesh by employing Just and Pope production function. Four non-parametric methods-Alexandersson’s Standard Normal Homogeneity Test, Buishand’s Range Test, Pettitt’s Test and Von Neumann’s Ratio Test are applied to detect homogeneity in the data. Mann–Kendall (MK) test and Sen’s slope (SS) method were employed to analyze monthly rainfall trends and minimum and maximum temperature trends. Results of Just and Pope (panel data) quadratic and Cobb-Douglas methods revealed that monthly minimum temperature positively influenced the mean yield of chickpea (0.22% and 0.16%, respectively). However, rainfall (-0.41% and -0.31%) and maximum temperature (-0.08% and -0.04%) negatively influenced the mean yield of chickpea under quadratic and Cobb-Douglas models, respectively. Accordingly, rainfall (0.08% and 0.06%) and maximum temperature (0.83% and 0.72%) positively influenced the yield variability and minimum temperature (-0.77% and -0.67%) reduced yield variability of chickpea under quadratic and Cobb-Douglas models respectively. In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh

Jute seed production as influenced by dates of sowing and topping in red and laterite zone of West Bengal

An experiment was carried out during thekharif season of two consecutive years 2014 and 2015 at Regional Research Sub-station, Raghunathpur, Bidhan Chandra Krishi Viswavidyalaya, Purulia, West Bengal with the view to maximise the jute seed yield by manipulating certain non-monetary techniques like dates of sowing and topping associated with crop production. The Capsularis variety Bidhan pat-3 was sown in three different dates (1st-25th June, 2nd-15th July and 3rd-5th August) with 3 topping (clipping of apical portion) practices at 30, 45 and 60 days after sowing (DAS) as separate treatment with no topping as control. These different agronomic practices significantly (at 5 % probability level) influenced the performance of the crop in various aspects. The 1st date of sowing showed its supremacy in terms of expression of the crop in the field in all the aspects achieving a seed yield of 709.50 kg ha-1 and 737.85 kg ha-1 during first and second year respectively, whereas, the last date of sowing showed its inferiority obtaining a seed yield of 590.10 kg ha-1 and 647.13 kg ha-1all through the first and second year respectively.1stdate of sowing also recorded higher net return(Rs. 33721.50 ha-1& Rs.35989.50 ha-1 during first and second year) and benefit: cost ratio (1.46 and 1.56 in first and second year) over the other two date of sowing. How-ever, maximum seed yield was achieved when the crop was topped on 45 DAS (728.80 kg ha-1 and 773.57 kg ha-1 during first and second year) irrespective of the date of sowing

Cytoview: development of a cell modelling framework

The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out

The impact of the COVID-19 pandemic on the education of medical, dental and non-medical healthcare professionals in Bangladesh : findings and connotation

Lockdown measures in response to the COVID-19 pandemic had an appreciable impact on the education of all medical, dental, and non-medical healthcare professional (HCP) students. These included the closure of universities necessitating a rapid move to e-learning and new approaches to practical’s. However initially, there was a lack of knowledge and expertise regarding e-learning approaches and the affordability of internet bundles and equipment. We initially con-ducted two pilot studies to assess such current challenges, replaced by a two-stage approach including a full investigation involving 32 private and public universities during the early stages of the pandemic followed by a later study assessing the current environment brought about by the forced changes. Top challenges at the start of the pandemic included a lack of familiarity with e-learning approaches, cost of the internet, lack of IT equipment and the quality of the classes. Universities offered support to staff and students to a varying degree to address identified challenges. Since then, e-learning approaches have widened the possibilities for teaching and learning at convenient times. However, challenges remain. In conclusion, there were considerable challenges at the start of them pandemic. Several key issues have been addressed with hybrid learning here to stay. Remaining challenges include a lack of ICT equipment. However, new innovations will continue