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The Internet of Things ecosystem pertains to web-enabled connected devices that operate built-in processors to record, send, and act on information from their surroundings via embedded communication hardware. IoT applications span from education, healthcare to self-driving cars. The high delay supplied through the connecting network to the data centers and huge data traffic can cause the system to become congested, so the cloud is not suggested for delay-sensitive applications and it is extremely difficult to provide educational applications, particularly in a mix of cloud and fog conditions. Fog computing was created to address this problem and improve time-sensitive applications by considering quality of service (QoS). Allocation of resources and scheduling of tasks are challenging issues for IoT applications in a fog environment. Resources are required for each educational application that includes several modules to run. In this paper, we used Weighted Greedy Knapsack (WGK) based algorithm for the resource allocation to the modules/components in the fog system. We have considered the smart parade application to provide certain services/resources and proposed method was experimented in iFogSim. Proposed method shows a better energy consumption and execution cost than that of concurrent, First-Come-First-Served (FCFS) and Delay-Priority algorithms.

Cloud computing is expanding gradually as the number of educational applications is rapidly increasing. To get Educational cloud services, internet connectivity is predominantly important and Cloud Environment uses one of the basic technology to manage the Physical servers effectively ie; Virtualization Technology. In Cloud Computing, the data centers host numerous Virtual Machines (VMs) on top of the Servers. Due to the rapid growth of Educational platforms, the workload of the VM is computationally getting increased. In the Cloud Educational platforms, to execute the jobs IT resources are provisioned over the network. Since the data generated from the client-side is dynamic in nature, it is difficult to allocate the computational resources efficiently. So to enhance the energy efficiency and to provide the resources in an optimized way, a VM Scheduling mechanism with Hybrid Genetic Algorithm-Modified Particle Swarm Optimization (GA-MPSO) is proposed in this work to achieve QoS parameters like reduced Energy consumption, SLA violation, and cost reduction over the heterogeneous environments. The Hybrid G-MPSO develops the optimal range and improves the best range of scheduling the Virtual resources to VMs from Physical Machines (PMs). The proposed approach, when compared to other VM scheduling algorithms, it intensifies the energy consumption to 105KWH, SLA violation rate of 0.08%, reduces the migrations count to 2122, and consumes the overall cost of 2567.68$. The different scheduling methods for VMs are evaluated against the results, which show that the Hybrid GA-MPSO method is far better than the existing algorithms.

Computer aided diagnosis (CAD) is one of the potential technologies in today’s medical world that assist doctors to interpret and evaluate medical images in a short time. CAD offers support to medical professionals to make decisions on possible diseases. Various systems and approaches are implemented to serve this technology, and many hospitals have deployed the system for diagnosis of diseases. The detection of the proportion of disease would aid in determining if more in-depth tests are required for confirmation of the condition, hence avoiding risky biopsies. This survey focuses on such methodologies implemented by authors of several works to detect lung infections by analyzing tissue patterns and inflammations in lungs and classifying the same. Along with this, work related to the patient database system is also reviewed and a comparison is made between the works. Keywords: Computer aided diagnosis, tissue pattern, biopsy

SQL Injection is one of the top 10 web app vulnerabilities where any unauthorized person directly invokes the malicious SQL query in a database that will raise the issue of integrity and privacy of data which will definitely fail the maintenance of the database. Till now there is no proper provision of providing security in the Infrastructure layer of the cloud. In this paper are trying to provide a solution by Implementing it in cloud computing using the “as-a-service” delivery model which means we are assuring security for databases from malicious SQL queries that will hamper the company’s database. These services can be consumed by any IaaS applications. Problems occurring from SQL injection can be avoided with the correct validation. The validation of the query which is written in SQL form is validated by using Grammar checking using Regular Expressions of the query and it also includes the use of hybrid techniques for detecting malfunctions by passing our query from White List and Black List. The white List test contains the syntax which should always show pass status if the query is not harmful. Black List contains some special symbols such as $, * , -- , ‘ ’ etc and conditions like a=a or 1=1. So, the black list should always show fail status, meaning that the query is safe to run.

A lectin PCL, from Purpureocillium lilacinum a saprophytic, filamentous fungus was purified from the crude extract of the mycelia using 70% ammonium sulphate precipitation followed by affinity chromatography on mucin-Sepharose 4 B column. PCL is a monomer with an apparent molecular mass of 18.5 kDa as revealed by SDS-PAGE under both reducing and non-reducing conditions. PCL is a blood group non-specific lectin and has highest affinity towards chitin, mucin, asialomucin, fetuin with a MIC of 0.15 µg/mL and also recognizes L-fucose, galactose, lactose, N-acetyl galactosamine, hyaluronic acid. PCL is stable up to 60 °C and within the pH range 4-8. To understand its role in pathogenesis, effect of PCL was evaluated on human corneal epithelial cells (HCECs). PCL showed strong glycan mediated binding to HCECs and PCL showed proinflammatory response at lower concentrations by stimulating secretion of IL-6, 8. In contrast PCL at higher concentrations revealed opposite effect of HCECs growth inhibition. All these results collectively support the involvement of PCL in mediating host pathogen interactions possibly leading to pathogenesis. In addition, considering the entomopathogenic effect of Purpureocillium lilacinum, PCL may be attributed for this beneficiary effect, which needs to be explored.

Hadoop is one of the standard platforms for managing and storing Big Data in distributed systems. But the lack of good developers to write Map Reduce programs into the development environment has pushed the adoption of SQL based query system into the Hadoop Ecosystem in an attempt to benefit from the traditional relational database systems in terms of the skills, especially in the Business process and Intelligent Analytical process. On top of the Hadoop environment a new framework has arrived ie; Apache Hive as the standard data warehouse engine. This is one of the challenges by the industry-leading developers to work on improvements both in query execution and as well as in data storage paradigms. In this work, various data structure file formats like Avro, Parquet, and ORC are differentiated with text file formats to evaluate the storage optimization, the performance of the database queries. Various kinds of query patterns have been evaluated. The output of the study shows that ORC and Parquet file format takes up less storage space compared with Avro and text files format, it is because of binary data formats and compression techniques used. Furthermore, Aggregate queries of the ORC and Parquet data structures are quicker compared with Avro or text file formats because earlier two formats support well for column-based queries.

There was a time when we had to go to a house or believe the estate seller who can tell false things about the estate but the days are gone when we had to go to the shop and see the products and imagine about its compatibility in our homes. In this paper we describe an application which uses the concept of Augmented Reality which is multi platform compatible, is a real world application which uses augmented reality to display a 3D version of the products so that users can view all the smallest of details of the products on their Mobile Devices and place them according to their desire. This application can be developed in the real world. Here, an application is developed which is having voice-controlled functionalities for the AR Objects. The application’s creation consists of two steps i.e. Creation of 3D Models from real objects using an image based modeling tool and Conversion of 3D Model into an interactive AR element using an AR authoring tool. Our application uses augmented reality to display a 3D version of the products so that users can view all the smallest of details of the products on their Mobile Devices and place them according to their desire. The application can also be used by voice control for several functionalities like opening, closing the roof, to switch to night time, etc. With this cross platform application, people can see the 3D Model of a house with the angles of user’s interest and also with a first person view.

With the extensive growing demand for cloud computing, virtualization plays an important role to provide services to the end users. Due to the increased use of cloud, managing and running multiple VMs on cloud is becoming a difficult task. Therefore, it is important to solve the problem using efficient technique. The task includes reducing the energy cost which can be achieved by reducing the power consumption. Reducing the power consumption decreases the carbon emission that leads to green cloud computing. Our main objective is to decrease power consumption and reduce SLA violations. This objective is achieved by using CPU stipulation for VM selection, modified local regression for VM migration, adaptive utilization threshold base and non-threshold base algorithm for host selection.

Cloud computing is designed to provide a scalable and low cost way to delivering on-demand IT resource services over the internet. Over a period of time cloud computing experienced tremendous development . Nonethless, the economic model centered on hardware and software demand based on technological requirements (CPU utilization, memory...) or strongly contributed to productive use of computer resources. Load balancing is therefore a crucial aspect of cloud computing. Cloud computing requires optimizing the efficiency of the various services provided by the cloud providers to minimize SLA infringement, i.e,.high degree of security, availability and responsivity. As cloud computing is growing increasingly and customers are demanding better performance and more services, cloud resource scheduling and load balancing has become a very interesting and significant research field .Therefore SLAs are emerging as an important factor between consumers and providers. In the existing algorithms there are drawbacks due to their single objective. But in this work, we are considering multiple objectives and multiple parameters for balancing load across virtual machine and to achieve less power consumption and reduce SLA violation.

Background Lectins are known to possess interesting biological properties such as anti microbial, nematicidal, anti tumor and anti viral activities. Lantana camara from verbenaceae family is a medicinal plant known for possessing anti oxidant and anticancer activities. Since anticancer activity is reported in plant lectins, leaves of Lantana camara was used to check the presence of lectin. Methods and results Here we report the purification, characterization and biological properties of a lectin from Lantana camara (LCL) leaves. LCL was purified by ion exchange chromatography on CM-cellulose column followed by affinity chromatography on mucin coupled Sepharose 4B column and gel filtration chromatography on Superdex G75 column. LCL is a glycoprotein with 10% of the carbohydrate and is blood group non specific. SDS-PAGE analysis of affinity purified LCL showed two proteins with apparent molecular weight of 14.49 kDa and 17.4 kDa which were subsequently separated by Gel filtration chromatography on Superdex G75 column. Hapten inhibition studies of LCL revealed its highest affinity for Chitin, Milibiose, α-D-Methyl galactopyranoside and glycoproteins like mucin, asialomucin. LCL showed strong binding to human colon adenocarcinoma HT29 cells with MFI of 242 which was effectively blocked by 68.1 and 62.5% by both mucin and milibiose. LCL showed dose and time dependent growth inhibitory effects on HT29 cells with IC50 of 3.75 μg/ml at 48 h. LCL has potent antibacterial and anti fungal activity. Conclusion LCL can be explored for its clinical potential.