GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines the scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.Comment: Under review by a conference, 201

Numerical Study of Crystallization Process Using CFD Tools

Crystallization is the formation of solid particles within a homogenous phase. Crystallization is considered a last stage purification step in pharmaceutical, chemical, agrochemical and food industries. Crystallization is mostly used for separation of a pure product from an impure solution and the product formed is suitable for packing and marketing. Good yield and purity are important for crystallization; apart from it crystal size distribution also plays a vital role in the design of crystallization. The energy required for crystallization is less than distillation. The study is made on crystallization process of sucrose in a continuous rectangular flow chamber. The present work is aimed to compare the simulation results with experimental results and to study the parametric sensitivity on mean crystal diameter of sucrose and total crystal production with variation in inlet velocity of solution, inlet mass fraction of sucrose and wall temperature of crystallizer. The transient simulations are carried out to study the crystallization process. The simulation results when validated against experimental results are found to be consistent.The simulation results show that as the inlet mass fraction of sucrose is increased, then the mean crystal size and total crystal production are observed to be increased. The mean crystal size is increased and total crystal production is decreased with decrease in inlet velocity of solution. The mean crystal size is observed to be invariant with change in wall temperature of the crystallizer but the total crystal production is increased with increase in wall temperature

Acute toxicity study of seeds of Achyranthes aspera, bark of Berberis aristata and roots of Coleus forskohlii in Wistar rats

Background: Achyranthes aspera is a species of plant in the family Amaranthaceae. Berberis aristata is a shrub belonging to the family Berberidaceae and the genus Berberis. Plectranthus barbatus is a tropical perennial plant related to the typical coleus species. It produces forskolin, an extract useful for pharmaceutical preparations and research in cell biology. It is belonging to Lamiaceae. The present study has been undertaken to study the toxic effects of hydro alcoholic extracts of A. aspera, B. aristata, C. forskohlii in albino Wistar rats and to establish the hazardous safety category of hydro alcoholic extracts of these plants as per organization for economic cooperation and development (OECD-423) guidelines and GHS classification system respectively.Methods: In acute toxicity study, the hydro-alcoholic extracts of all the above three plants were given orally at the dose of 2000 mg/kg b. w. to three rats in each group respectively in step I. Then, all the animals were observed for initial 4 hours and followed by fourteen days for their clinical signs and mortality in step II.Results: In step I, all the animals were normal and there was no mortality after 48 hours. In step II with the same dose, all the animals showed no adverse effects and no mortality when followed up to 14 days observation period.Conclusions: The result indicates that the hydro alcoholic extracts of A. aspera, B. aristata, C. forskohlii plants can be utilized safely for therapeutic use in pharmaceutical formulations and it falls under category ‘5’ or ‘unclassified’ of GHS system

Growth, yields and nitrogen use of open pollinated and hybrid maize (Zea mays L) as affected by organic matter and its placement in minor seasons of Asia

Sustainable maize (Zea mays L) production in smallholder cropping systems of South Asia require combinations of organic matter and mineral fertilizers, especially nitrogen, when the crop is subjected to water stress in the minor seasons. As the cultivation of hybrid maze is being promoted in these nations, field studies over two minor seasons evaluated the impact of three types of common organic materials and their method on incorporation on root growth, seeds yields and nitrogen use patterns of an open pollinated (OPV) and a hybrid variety of maize. The growth and yields of the OPV were higher than those of the hybrid, illustrating the greater adaptability of this variety to the drier conditions of minor seasons. The least beneficial impact of organic matter on growth, yield and nitrogen use was with rice straw, a low quality organic matter, while Tithonia leaves promoted root growth. Application of Gliricidia leaves produced the highest yields followed by the use of Tithonia. N use patterns were enhanced to similar extents by the addition of Tithonia and Gliricidia leaves, and the beneficial impact was greater than when rice straw was used. Incorporation enhanced the benefits of the organic matter, especially in the hybrid, which produced lower yields, which is considered less adaptable to the environments of this season. The benefits of using good quality organic matter and its incorporation on maize growth, productivity and the utilization patterns of nitrogen in the minor dry seasons of South Asia was evident in this field study

The Competent Service Management and Reliable Trustworthiness in Cloud Environment

Present days, Cloud Computing is having trust area in innovative work regardless of loads of work in the stream. There are number of research issues in this section including trust management, privacy, security, respectability and power mindful server farms. A noteworthy and loads of work is done under every space still there is tremendous extent of research. Trust management is one of the summed up and enter area in which goliath work is going on. According to the reports and corporate whitepapers, trust alludes to as: "For the most part a substance can be said to "trust" a moment element when the main element makes the supposition that the second element will act precisely as the principal element anticipates. Trust is the foundation of certainty that something will or won't happen in an anticipated or guaranteed way. The empowering of certainty is bolstered by recognizable proof, authentication, responsibility, approval, and accessibility." various calculations and methodologies are produced so far which are incorporated in the trust structures including cryptography, nature motivated methodologies and numerous others. In this examination work, the current approach of quality based design for trust management in cloud is received in which number of chromosomes and quality based libraries are incorporated. The point of solidification is accomplished in a circle of down level temperature. In this work, the mimicked tempering based execution is utilized with the incorporated with element security key for improved security trust management

Breaking RSA Authentication on Zynq-7000 SoC and Beyond: Identification of Critical Security Flaw in FSBL Software

In this report, we perform an in-depth analysis of the RSA authentication feature used in the secure boot procedure of Xilinx Zynq-7000 SoC device. The First Stage Boot Loader (FSBL) is a critical piece of software executed during secure boot, which utilizes the RSA authentication feature to validate all the hardware and software partitions to be mounted on the device. We analyzed the implementation of FSBL (provided by Xilinx) for the Zynq-7000 SoC and identified a critical security flaw, whose exploitation makes it possible to load an unauthenticated application onto the Zynq device, thereby bypassing RSA authentication. We also experimentally validated the presence of the vulnerability through a Proof of Concept (PoC) attack to successfully mount an unauthenticated software application on an RSA authenticated Zynq device. The identified flaw is only present in the FSBL software and thus can be easily fixed through appropriate modification of the FSBL software. Thus, the first contribution of our work is the identification of a critical security flaw in the FSBL software to bypass RSA authentication. Upon bypassing RSA authentication, an attacker can mount any unauthenticated software application on the target device to mount a variety of attacks. Among the several possible attacks, we are interested to perform recovery of the encrypted bitstream in the target boot image of the Zynq-7000 device. To the best of our knowledge, there does not exist any prior work that has reported a practical bitstream recovery attack on the Zynq-7000 device. In the context of bitstream recovery, Ender et al. in 2020 proposed the Starbleed attack that is applicable to standalone Virtex-6 and 7-series Xilinx FPGAs. The design advisory provided by Xilinx as a response to the Starbleed attack claims that the Zynq-7000 SoC is resistant “due to the use of asymmetric and/or symmetric authentication in the boot/configuration process that ensures configuration is authenticated prior to use . Due to the security flaw found in the FSBL, we managed to identify a novel approach to mount the Starbleed attack on the Zynq-7000 device for full bitstream recovery. Thus, as a second contribution of our work, we present the first practical demonstration of the Starbleed attack on the Zynq-7000 SoC. We perform experimental validation of our proposed attacks on the PYNQ-Z1 platform based on the Zynq-7000 SoC

Clinical comparison of different cardiovascular risk scores for cardiovascular risk prediction in Indian patients

Background: Cardiovascular diseases (CVD) are the main cause of mortality and disability in India. Early and sustained exposure to behavioral risk factors leads to development of CVD. The present study was conducted to compare different cardiovascular calculators for CVD risk assessment models in young Indian patients presenting with myocardial infarction.Methods: This study included 85 patients with myocardial infarction (MI). Their predicted 10-year risk of CVD was calculated using three clinically most relevant risk assessment models viz. Framingham Risk score (RiskFRS), American College of Cardiology/American Heart Association (RiskACC/AHA) and the 3rd Joint British Societies risk calculator (RiskJBS).Results: RiskFRS recognized the highest number of patients (15.4%) at high CVD risk while RiskACC/AHA and RiskJBS calculators provided inferior risk assessment but statistically significant relationship. RiskFRS and RiskACC/AHA (Pearson's r 0.870, p<0.001).Conclusions: RiskFRS seems to be as most useful CVD risk assessment model in young Indian patients. RiskFRS is likely to identify the number of patients at ‘high-risk’ as compared to RiskJBS and RiskACC/AHA

SECURITY AND OTHER VULNERABILITY PREDICTION USING NOVEL DEEP REPRESENTATION OF SOURCE CODE WITH ACTIVE FEEDBACK LOOP

Since the cost of fixing vulnerabilities can be thirty times greater after an application has been deployed, it is recognized that properly-written code can yield potentially large savings. Accordingly, approaches presented herein apply machine learning and Artificial Intelligence (AI) techniques to improve developer experience by enabling developers to avoid introducing potential bugs and/or vulnerabilities while coding. Billions of lines of source code, which have already been written, are utilized as examples of how to write functional and secure code that is easy to read and to debug. By leveraging this wealth of available data, which is complemented with state-of-art machine learning models, enterprise-level software solutions can be developed that have a high standard of coding and are potentially bug-free