Artificial Neural Network Based Prediction Mechanism for Wireless Network on Chips Medium Access Control

As per Moore’s law, continuous improvement over silicon process technologies has made the integration of hundreds of cores on to a single chip possible. This has resulted in the paradigm shift towards multicore and many-core chips where, hundreds of cores can be integrated on the same die and interconnected using an on-chip packet-switched network called a Network-on-Chip (NoC). Various tasks running on different cores generate different rates of communication between pairs of cores. This lead to the increase in spatial and temporal variation in the workloads, which impact the long distance data communication over multi-hop wire line paths in conventional NoCs. Among different alternatives, due to the CMOS compatibility and energy-efficiency, low-latency wireless interconnects operating in the millimeter wave (mm-wave) band is nearer term solution to this multi-hop communication problem in traditional NoCs. This has led to the recent exploration of millimeter-wave (mm-wave) wireless technologies in wireless NoC architectures (WiNoC). In a WiNoC, the mm-wave wireless interconnect is realized by equipping some NoC switches with an wireless interface (WI) that contains an antenna and transceiver circuit tuned to operate in the mm-wave frequency. To enable collision free and energy-efficient communication among the WIs, the WIs is also equipped with a medium access control mechanism (MAC) unit. Due to the simplicity and low-overhead implementation, a token passing based MAC mechanism to enable Time Division Multiple Access (TDMA) has been adopted in many WiNoC architectures. However, such simple MAC mechanism is agnostic of the demand of the WIs. Based on the tasks mapped on a multicore system the demand through the WIs can vary both spatially and temporally. Hence, if the MAC is agnostic of such demand variation, energy is wasted when no flit is transferred through the wireless channel. To efficiently utilize the wireless channel, MAC mechanisms that can dynamically allocate token possession period of the WIs have been explored in recent time for WiNoCs. In the dynamic MAC mechanism, a history-based prediction is used to predict the bandwidth demand of the WIs to adjust the token possession period with respect to the traffic variation. However, such simple history based predictors are not accurate and limits the performance gain due to the dynamic MACs in a WiNoC. In this work, we investigate the design of an artificial neural network (ANN) based prediction methodology to accurately predict the bandwidth demand of each WI. Through system level simulation, we show that the dynamic MAC mechanisms enabled with the ANN based prediction mechanism can significantly improve the performance of a WiNoC in terms of peak bandwidth, packet energy and latency compared to the state-of-the-art dynamic MAC mechanisms

Diethyl 2-{[3-(2-meth­oxy­benz­yl)thio­phen-2-yl]methyl­idene}malonate

In the title compound, C20H22O5S, the dihedral angle between the mean planes through the thio­phene and benzene rings is 75.2 (1)°. The meth­oxy group is essentially coplanar with the benzene ring, the largest deviation from the mean plane being 0.019 (2) Å for the O atom. The malonate group assumes an extended conformation

PHYTOCHEMICAL ANALYSIS AND ANTIOXIDANT PROPERTIES OF LEAF EXTRACTS OF CARICA PAPAYA

Objective: The objective of the present study aimed at investigating the phytochemical and antioxidant properties of Carica papaya leaf extracts. Methods: As phytochemicals are biologically active compounds and a powerful group of plant chemicals, believed to stimulate the immune system along with antioxidants, the molecules which hinder oxidation of other molecules by the process of inhibiting or by generating the oxidizing chain reactions and preventing diseases. The total phenolic content (TPC) was determined by Folin-Ciocalteu method and total flavonoid contents (TFC) were determined aluminum chloride method and antioxidant by 2,2,1-diphenyl-1-picrylhydrazyl method. Results: The results of phytochemical screening revealed the presence of bioactive compounds such as alkaloid, carbohydrates, and amino acids and TPC and TFC varied among the different solvent extracts, in which methanolic extracts showed highest amount of phytochemicals and TPC and TFC and antioxidants compared to other solvents. Conclusion: The isolation and purification of specific bioactive compound may account as natural and promising medicines in exploration of new drug

Edible vaccines: A novel approach to oral immunization and their application in clinical trails

Infectious diseases cause more than one million deaths every year. Fifty percent of these diseases are caused by bacteria that infect the mucosal membrane of the mammalian host. Vaccines are recognized worldwide as one of the most effective resources against infectious diseases. It is a biological product that can improve the immune response to specific diseases. Edible vaccines are referred to the use of edible parts of the genetically modified plants. It effects on the lining of the gastrointestinal tract allows the activation of systemic immunity and mucosal immunity (GIT). Edible vaccines are used to prevent various diseases, such as hepatitis B, measles, malaria, cholera, Norwalk disease, anthrax, foot-and-mouth disease, rabies, rotavirus, HIV, HPV, diabetes, and sexually transmitted diseases. The purpose of this review is to introduce edible vaccines as a novel oral immunization method, the types and uses of edible vaccines in clinical trials