PMSS: A programmable memory system and scheduler for complex memory patterns

HPC industry demands more computing units on FPGAs, to enhance the performance by using task/data parallelism. FPGAs can provide its ultimate performance on certain kernels by customizing the hardware for the applications. However, applications are getting more complex, with multiple kernels and complex data arrangements, generating overhead while scheduling/managing system resources. Due to this reason all classes of multi threaded machines–minicomputer to supercomputer–require to have efficient hardware scheduler and memory manager that improves the effective bandwidth and latency of the DRAM main memory. This architecture could be a very competitive choice for supercomputing systems that meets the demand of parallelism for HPC benchmarks. In this article, we proposed a Programmable Memory System and Scheduler (PMSS), which provides high speed complex data access pattern to the multi threaded architecture. This proposed PMSS system is implemented and tested on a Xilinx ML505 evaluation FPGA board. The performance of the system is compared with a microprocessor based system that has been integrated with the Xilkernel operating system. Results show that the modified PMSS based multi-accelerator system consumes 50% less hardware resources, 32% less on-chip power and achieves approximately a 19x speedup compared to the MicroBlaze based system.     

Plastic fats with zero trans fatty acids by interesterification of mango,mahua and palm oils

Speciality plastic fats with no trans fatty acids suitable for use in bakery and as vanaspati are prepared by interesterification of blends of palm hard fraction (PSt) with mahua and mango fats at various proportions. It was found that the interesterified samples did not show significant differences in solid fat content (SFC) after 0.5 or 1 h reaction time. The blends containing PSt/mahua (1:1) showed three distinct endotherms, indicating a heterogeneity of triacylglycerols (TG), the proportions of which altered after interesterification. The SFC also showed improved plasticity after interesterification. Similar results were observed with other blends of PSt/mahua (1:2). These changes in melting behavior are due to alterations in TG composition, as the trisaturated‐type TG were reduced and the low‐melting TG increased after interesterification. The blends containing PSt/mango (1:1) showed improvement in plasticity after interesterification, whereas those containing PSt/mango (2:1) were hard and showed high solid contents at higher temperature and hence may not be suitable for bakery or as vanaspati. The blends with palm and mahua oils were softer and may be suitable for margarine‐type products. The results showed that the blends of PSt/mahua (1:1, 1:2) and PSt/mango (1:1) after interesterification for 1 h at 80 °C showed an SFC similar to those of commercial hydrogenated bakery shortenings and vanaspati. Hence, they could be used in these applications in place of hydrogenated fats as they are free from trans acids, which are reported to be risk factors involved in coronary heart disease. For softer consistency like margarine applications, the blends containing palm oil and mahua oil are suitable.     

Design and development of dynamic Agri-ontology for IoT interoperability

In recent years, the usage and applications of Internet of Things (IoT) have increased exponentially. IoT connects multiple heterogeneous devices like sensors, micro controllers, actuators, smart devices like mobiles, watches, etc. IoT contributes the data produced in the context of data collection, including the domains like military, agriculture, healthcare, etc. The diversity of possible applications at the intersection of the IoT and the web semantics has prompted many research teams to work at the interface between these two disciplines. This makes it possible to collect data and control various objects in transparent way. The challenge lies in the use of this data. Ontologies address this challenge to meet specific data needs in the IoT field. This paper presents the implementation of a dynamic agriculture ontology-building tool that parses the ontology files to extract full data and update it based on the user needs. The technology is used to create the angular library for parsing the OWL files. The proposed ontology framework would accept user-defined ontologies and provide an interface for an online updating of the owl files to ensure the interoperability in the agriculture IoT.     

Multi‐agent collaboration based on enhanced cognitive awareness: an architecture for agents' profiling on the semantic web

This paper applies cognitive models, inspired by cognitive science, with the aim to propose architectural and knowledge‐based requirements to structure ontological models for the cognitive profiling of agents. The proposed architecture aims to address the lack of flexibility that most agent‐based collaborations are affected by. The resulting agents, equipped with advanced cognitive profiling, have an increased cognitive awareness of themselves and are more capable of interacting with other agents in a multi‐agents based environment. In this research, cognitive awareness identifies the ability of the web agents to diagnose their processing limitations and to establish interactions with the external environment. The outcome is the enhanced flexibility, reusability and predictability of the agent behaviour; thus contributing towards minimizing human cognitive demands. The concept of cognitive profiling presented in this paper considers the semantic web as an action mediating space, where ontological models provide affordances for improving cognitive awareness through shared knowledge‐base. The conceptual model for the cognitive profile architecture is developed with Protégé Ontology editor to generate OWL Ontology and evaluated through a proof of concept. The results show that agents equipped with cognitive awareness can undertake complex tasks more dynamically.     

Ear recognition with feed-forward artificial neural networks

Biometrics has become one of the most important techniques in recognizing a person’s identity. A person’s face, iris and fingerprint are mostly used in biometrics today. It has been established that there are no two ears exactly alike, even in the cases of identical twins. In this paper, we define a 7-element ear feature set and design and train a feed-forward artificial neural network to recognize a human ear. We train and test the network with 51 ear pictures from 51 different persons. Simulation experiments with various networks with various number of layers and number of neurons per layer and with and without noise are conducted. Results indicate that a 95 % ear recognition accuracy is achieved with a simple 3-layer feed-forward neural network with only a total of 18 neurons even in the presence of some noise. This design outstands previous work in simplicity and implementation cost.     

Enzymatic interesterification of palm and coconut stearin blends

Hard fractions of palm oil and coconut oil, blended in the ratios of 90:10, 85:15, 80:20 and 75:25, were interesterified for 8 h using Lipozyme TL IM. Major fatty acids in the blends were palmitic acid (41.7–48.4%) and oleic acid (26.2–30.8%). Medium‐chain fatty acids accounted for 4.5–13.1% of the blends. After interesterification (IE), slip melting point was found to decrease from 44.8–46.8 °C to 28.5–34.0 °C owing to reduction in solids content at all temperatures. At 37.5 °C, the blends containing 25% coconut stearins had 17.4–19% solids, which reduced to 0.4–1.5% on IE, and the slip melting point (28.6 and 28.8 °C) indicated their suitability as margarine base. The reduction in solid fat index of the interesterified fats is attributed to the decrease in high‐melting triacylglycerols in palm oil (GS₃ and GS₂U type) and increase in triolein (GU₃) content from 1 to 9.2%. Retention of tocopherols and β‐carotene during IE was 76 and 60.1%, respectively, in 75:25 palm stearin and coconut stearin blend.     

Effects of feeding bentonite clay upon ochratoxin A–induced immunosuppression in broiler chicks

A presence of mycotoxins in feed is one of the most alarming issues in the poultry feed industry. Ochratoxins, produced by several Aspergillus and Penicillium species, are important mycotoxin regarding the health status of poultry birds. Ochratoxins are further classified into to several subtypes (A, B, C, etc) depending on their chemical structures, but ochratoxin A (OTA) is considered the most important and toxic. Bentonite clay, belonging to phyllosilicates and formed from weathering of volcanic ashes, has adsorbent ability for several mycotoxins. The present study was designed to study the effects of bentonite clay upon OTA-induced immunosuppression in broiler chicks. For this, 480 day-old broiler chicks were procured from a local hatchery and then different combinations of OTA (0.15, 0.3, or 1.0 mg/kg) and bentonite clay (5, 10, and 20 g/kg) were incorporated into their feed. At 13, 30, and 42 days of age, parameters such as antibody responses to sheep red blood cells, in situ lymphoproliferative responses to mitogen (PHA-P), and in situ phagocytic activity (i.e., via carbon clearance) were determined respectively. The results indicated there was a significant reduction of total antibody and immunoglobulin titres, lymphoproliferative responses, and phagocytic potential in OTA-treated birds, suggesting clear immunosuppression by OTA in birds in a dose-dependent manner. These results were also significantly lower in all combination groups (OTA with bentonite clay), suggesting few to no effects of feeding bentonite clay upon OTA- induced alterations in different immune parameters.     

Low temperature synthesis of <Emphasis Type="Italic">Manganese tungstate</Emphasis> nanoflowers with antibacterial potential: Future material for water purification

Pure water is the fundamental requisite for human life. The water has been recycled naturally but not in an adequate amount for consumption. Nanotechnology with extraordinary applications provides competent ways for the decontamination of contaminated water. In the present study MnWO₄ nanoflowers endorsed with inherent antibacterial activity were successfully synthesized by facile hydrothermal approach. XRD, SEM, EDX spectroscopy and UVDRS were used to characterize the as-synthesized nanoflowers. Gram negative Escherichia coli ATCC 52922 bacterium was used as model organism to test antibacterial activity of as-synthesized MnWO₄ nanoflowers. This study was conducted to optimize minimum concentration of MnWO₄ nanoflowers and maximum contact time required to achieve complete inactivation of bacteria present in contaminated water. Minimum inhibitory concentration (MIC) of MnWO₄ nanoflowers was found to be 10 μg/ml. The assessment and interpretation of bacterial viability was done using dual fluorescent staining. The synthesized 3D-nanoflowers were found as potent bactericides. Thus, MnWO₄ nanoflowers emerged to be very good future material for disinfection of biological pollutants present in the contaminated water reservoirs and as an anti-biofouling agent.