A Short Review on Application of Liquisolid Technology

In this paper we have surveyed about formulation and evaluation of Liquisolid formulations and its work in antidiabetics . Mostly poorly water soluble drugs are in research category despite of less dissolution rate and poor bioavailability. Solubility is a vital parameter to develop new formulation as industries faced serious issue regarding the poor aqueous solubility of the drugs. Various methods for solubility enhancement include modifications of the drug, involvement of co-solvents, complexation, salt formation, size reduction. A propitious technique to solve major challenges like solubility, dissolution rate and their bioavailability. This technique can be defined as the conversion of poorly soluble liquid medications into non-adherent, dry, compressible and free flowing powder mixtures with help of excipients. Many anti-diabetic drugs are belonging to BCS Class-II facing challenges like solubility and bioavailability.

Hybrid Scheduling Strategy in Cloud Computing based on Optimization Algorithms

As a platform for offering on-demand services, cloud computing has increased in relevance and appeal. It has a pay-per-use model for its services. A cloud service provider's primary goal is to efficiently use resources by reducing execution time, cost, and other factors while increasing profit. As a result, effective scheduling algorithms remain a key issue in cloud computing, and this topic is categorized as an NP-complete problem. Researchers previously proposed several optimization techniques to address the NP-complete problem, but more work is needed in this area. This paper provides an overview of strategy for successful task scheduling based on a hybrid heuristic approach for both regular and larger workloads. The previous method handles the jobs adequately, but its performance degrades as the task size becomes larger. The proposed optimum scheduling method employs two distinct techniques to select the suitable VM for the specified job. To begin, it enhances the LJFP method by employing OSIG, an upgraded version of the Genetic Algorithm, to choose solutions with improved fitness factors, crossover, and mutation operators. This selection returns the best machines, and PSO then chooses one for a specific job. The appropriate machine is chosen depending on several factors, including the expected execution time, current load, and energy usage. The proposed algorithm's performance is assessed using two distinct cloud scenarios with various VMs and tasks, and overall execution time and energy usage are calculated. The proposed algorithm outperforms existing techniques in terms of energy and average execution time usage in both scenarios.

Trust-Based Security: Advancement towards Protection of the Adhoc Network

MANET (mobile ad hoc network) is a collection of mobile nodes that interact without the need for a fixed physical foundation. MANETs have grown in popularity as a result of characteristics like dynamic topology, quick setup, multi-hop data transfer, and so on. MANETs are well-suited to various real-time applications, including environmental monitoring, disaster management, and covert and military operations, because of their distinguishing characteristics. MANETs may also be used in conjunction with new technologies like cloud computing, IoT, and machine learning algorithms to help realize the vision of Industry 4.0. Secure and reliable data transfer is essential for any MANET-based sensitive real-time applications that must achieve the requisite QoS. It is challenging to provide safe and efficient data transfer with MANET. As a result, this article examines different Trust-based Approaches that take a step forward in providing secure transmission while simultaneously improving MANET performance. Furthermore, the study's analysis based on many aspects exposes the inadequacies of existing techniques and provides future directions for improvement.

Review various technologies used to manage Traffic Management System using IOT

Internet of things (IoT) is the network of the devices includes the updating in technology, various devices are using sensors, actuators, embedded computing and cloud computing. This type of system leads to smart architecture in the home, cities and smart world. IoT plays an important role in traffic controlling and managing. In this paper, we give an overview of the various methods of traffic control management. With the help of this IOT kit, which includes different sensors to collect the data and process it accordingly with the help of big data analysis and deep learning algorithms, most accurate and efficient results are obtained for traffic management.

Optimized Routing Protocols- Enhancement in Mobile Adhoc Network

The recent developments in wireless technology have piqued academics' curiosity. Mobile Adhoc Networks (MANET) is a fast-growing networking architecture used in emergency, disaster, and tactical operations applications. It covers a wide range of applications with some degradation due to its flexible and expandable nature. Because routing is the primary function of wireless networks, routing protocol design is critical in Adhoc networks. Various methods have been used to improve the performance of current routing protocols in different categories. Technical advances in routing protocols have recently been achieved, combined with optimization approaches to improve the overall performance of MANETs routing protocols. This research initially looked at several sorts of routing protocols before going through their variations for energy economy and latency reduction. The previous protocols, which were created utilizing optimization methods, will then illustrate the current requirement. Finally, the review analysis delves into many aspects such as commonly used protocols, optimization techniques, QoS parameters, performance metrics, and future paths.

Prediction of Symptom Based Health Cautionary by using Machine Learning

Conceptual - Machine learning is the subset of man-made reasoning that goes under information science. Without expressly customized, getting PCs to learn is a science known as Machine Learning. The proposal frameworks present in the market are believed to be working in popular applications like YouTube web-based media applications like Facebook, Instagram or item based applications like Flipkart. Essentially, these frameworks help to focus on data that is concerned or valuable for a specific client. One area where such frameworks can be exceptionally helpful is infection cautioning system. In light of an illness the client contributions to the framework, that he thinks they are inclined to or they are experiencing they will be proposed top 5 or top 3 sicknesses they are generally inclined to dependent on the likeness between the infection client inputted and the illness client is being suggested for this situation being cautioned. As of now, everything is accessible on the web, each infection and its data around there. Specialists are there yet at the same time the tally of sicknesses, number of patients for an illness is expanding. An individual has one sickness then there are chances they will get another. Illness include among youngsters in this age bunch is expanding at a huge rate. There is the fix of sicknesses or possibly not however shouldn't something be said about notice. On the off chance that we caution somebody before they are really experiencing an infection. It will make him/her much more mindful than previously. This paper analyzes existing recommender frameworks and furthermore features the disadvantages of such frameworks. Disadvantages can be versatility, cold beginning and sparsely. The proposed framework enjoys its benefits however isn't yet accessible on the lookout. Examination has been done on how this infection cautioning framework utilizing content-based suggestion under AI is removing highlights from dataset and how this framework presents highlights like client autonomy, straightforwardness and no virus start.

Teaching Learning Based Optimization (TLBO) for energy efficiency in Fog Computing

Fog Computing is eminent to ensure quality of service in handling huge volume and variety of data and to display output, or for closed loop process control. It comprises of fog devices to manage huge data transmission but results in high energy consumption, end-to end-delay, latency. In this paper, an energy model for fog computing environment has been proposed and implemented based on teacher student learning model called Teaching Learning Based Optimization (TLBO) to improve the responsiveness of the fog network in terms of energy optimization. The results show the effectiveness of TLBO in choosing the shortest path with least energy consumption.

Botanical Pesticides: Use of Plants in pest management

Plants play a vital role in human life since the beginning of life on earth. Plants are not only directly used as a feed and fodder for humans and animals but are also used as drugs, food additives, pesticides, in flavor and fragrances and dye and pigments. The plants produce compounds for their growth and development and also produce secondary metabolites which provide additional properties to plants. These secondary metabolites produced by plant are responsible for these activities. Plants as a whole or in extracts/fractions form have been used as pesticides for protection of plants since thousands of years. Pyrethrum, neem, rotenone are such plants which has been used in many cultures and traditions for crop protection since ages and hold relevance in today’s world as well. The plant extracts contain secondary metabolites which provide protection to plants against pests by either causing mortality of pests or act as repellent to them. They can also impact pests by causing anti-feedancy, toxicity, alters insects behavior during oviposition and mating and inhibition of progeny emergence in pests. Essential oils isolated from the plants have also pesticidal properties. Lemongrass essential oil, Citronella essential oils, Tea tree essential oils and Oregano essential oils are the commonly used essential oils against the pests. In this review, botanical pesticides are discussed and their role in pest management and their advantageous over synthetic pesticides in terms of biodegradability, posing no or low risk to humans, environment and non-target organisms. Also, the future of botanical pesticides is discussed where they can be an alternative to synthetic pesticides if more research is done on their stability, efficacy, safety, modes of action, cost reduction is done.

Analysis of Various Network Traffic Classification Techniques

There are several interconnected entities present within the networked data for which the generation of inferences is important. For instance, hyperlinks are used to interconnect the web pages, calls are used to link the phone accounts, and references are used to connect the research papers and so on. Almost every existing application includes networks within it. The daily lives of individuals include social networking, making financial transactions, generating networks that show physical systems and so on. The manner in which the nodes present within the system influence each other can be known through this research. On the basis of observed attributed of an object within the system, another attributed is predicted using new model. The various network traffic classification techniques are reviewed in terms of certain parameters.

Techniques to Determine Powder Flow Properties

The goal of the current work was to do an orderly assessment of flow of powders and granules using compendial and non-compendial procedure. Angle of repose, Tapped density, Carr's compressibility file, Bulk density, Hausner’s ratios were assessed. Moreover, flow was described utilizing powder rheometer wherein delicate force transducer screens the forces created as consequence of the sample displacement, another technique FT4 powder rheometer. The Freeman Technology (FT4 powder rheometer) is intended to describe powders undergoing different circumstances in manners that look like wide scale creation climate. Techniques incorporate security and irregular flow rate, compressibility, shear cell, air circulation, porousness, divider contact and union. The FT4 has demonstrated application on the whole powders preparing ventures, including drugs, fine synthetic substances, cosmetics, food, additives and powder covering. The FT4 application connect to filling, hopper flow, Tablet pressure, wet granulation, end point, flow added substance determination and enhancement, moisture impacts, static change, feeding, stirring, separation, caking, processing, Wall grating, grip, hopper configuration etc.