Nadeem Sarwar

Carbon is an essential chemical element and is widely used in biomedicine and agroecosystems. This chapter deals with the general properties and structural features as well as several factors affecting the functional efficiencies of carbon nanotubes (CNTs). It also describes the fundamental forms of CNTs, including single-walled CNTs, multiwalled carbon nanotubes, and their properties while explaining the strength, purity, and twisting ability to describe its potential antimicrobial characteristics. Moreover, it also elaborates the arc discharge method, the laser ablation method, and flame pyrolysis for synthesis and universal techniques to purify CNTs. Furthermore, we will discuss CNT interactions with the root system, soil microbial communities, and biofilm formation along with its positive and negative impacts on living organisms and plants.

Delay Tolerant Networks (DTN) is a widely used communication standard in recent years, for situations where there is no end to end path available between sender and receiver, higher delays and nodes are sparse with less chance of meetings as compare to traditional networks. A comparatively new standard named Vehicular Delay Tolerant Networks (VDTN) is introduced in recent years which contain many properties of DTN along with others like high mobility, quickly changing dynamic topologies and here nodes are vehicles. PRoPHET, NECTAR, Source Routing, Per-hop Routing and other routing protocols take routing decisions on the basis of multiple parameters like encounter history, buffer occupancy/availability, location information, remaining TTL (time to live) of the bundle, closeness to destination and meeting probability along with many others. In this paper we are introducing a parameter named “connection_time”. This connection_time could also be a worthy candidate for routing protocols ...

The Internet of Health Thing (IoHT) has various applications in healthcare. Modern IoHTintegrates health-related things like sensors and remotely observed medical devices for the assessment and managment of a patient's record to provide smarter and efficient health diagnostics to the patient. In this paper, we proposed an IoT with a cloud-based clinical decision support system for prediction and observation of disease with its severity level with the integration of 5G services and block-chain technologies. A block-chain is a system for storing and sharing information that is secure because of its transparency. Block-chain has many applications in healthcare and can improve mobile health applications, monitoring devices, sharing and storing of the electronic media records, clinical trial data, and insurance information storage. The proposed framework will collect the data of patients through medical devices that will be attached to the patient, and these data will be stored in a ...

Getting quality sleep is important for every person to get better physical health. Irregular sleep patterns may indicate the illness resulting in chronic depression, which makes the evaluation of the sleep cycle mandatory for a healthy body and mind. In the arena of globalization, along with the increased facilities, various other challenges have been probed to provide the quality health care facilities with the use of economical instruments and technology. The development of the Internet of Things (IoT) technology purports the preambles to build a consistent and cost-effective system to monitor the sleep quality of patients. Several other systems are available for this purpose; however, such systems are very costly and difficult to implement. To overcome the issue, this study suggests an inventive system to monitor and analyze the sleep patterns using ambient parameters. The proposed system is effective enough that it can proficiently monitor patient’s sleep using Commercial off th...

In recent times, selection of a suitable hotel location and reservation of accommodation have become a critical issue for the travelers. The online hotel search has been increased at a very fast pace and became very time-consuming due to the presence of huge amount of online information. Recommender systems (RSs) are getting importance due to their significance in making decisions and providing detailed information about the required product or a service. To acquire the hotel recommendations while dealing with textual hotel reviews, numerical ranks, votes, ratings, and number of video views have become difficult. To generate true recommendations, we have proposed an intelligent approach which also deals with large-sized heterogeneous data to fulfill the needs of the potential customers. The collaborative filtering (CF) approach is one of the most popular techniques of the RS to generate recommendations. We have proposed a novel CF recommendation approach in which opinion-based senti...

Nanobiotechnology is the emerging field of science as it deals with the properties on nanoscale dimension and it can make the revolution in the diagnostic and therapeutic fields. The purpose of this review is to summarize the synthesis, types, properties and applications of gold nanoparticles. Gold nanoparticles are widely studied metal nanoparticles because of their unique physical and chemical properties that are different from bulk materials. Gold nanoparticles possess notable optoelectronic properties that are dependent on the shape and size of nanoparticles. They have large surface-to-volume ratio, excellent biocompatibility, and low toxicity which are very useful and make them an important tool in nanobiotechnology. This review reveals the characterization of gold nanoparticles by using UV–Vis spectroscopy, TEM and DLS. For their ability to target and efficient drug delivery, they have been extensively used for enhanced radiation in the field of radiation therapy. Gold nanoparticles have several other applications in the biomedical field like detection of very sensitive analytes, protein and virus and even they play role in killing cancer cells by hyperthermal treatment. A time is not far for fabrication and manipulation of new nanomaterials to be engineered for applications including therapeutic delivery, biosensors and bioimaging for biomedical use.

Abstract Due to the widespread popularity of cyber-social networks, research on community and social role discovery has drawn immense attention. Most of the available literature consider community and social role detection as areas of a disjoint problem domain. Moreover, existing research on concurrent community and social role detection utilizes a predefined set of roles and lacks in providing enough ground truth information for the proof. Hence, there is a high need for community structure analysis from an independent social perspective. Therefore, we propose a community and social role detection method called SocioRank* using email interaction data crawled from a graduate class of students. SocioRank* detects the underlying communities and ranks individuals on the basis of degree, closeness, and betweenness centrality. We perform extensive graph metrics-based experiments to evaluate the effectiveness of the proposed method. The comparison of results with the ground truth information demonstrates the high accuracy of SocioRank* method in community and role discovery.

—A sorting algorithm is one that puts elements of a list in a certain order. It makes easy searching and locating the information. The most-used orders are numerical order and lexicographical order. An efficient sorting algorithm is that takes less time and space complexity. In this paper I make contrastive analysis of bubble sort and merge sort and tried to show why required some new approach to get best sorting results. In this regard we proposed a hybrid approach that will take minimum number of comparisons, with less time and space complexity to sort. Divide and conquer (merge sort) with bi-directional bubble sort approach is used and an example data is sorted with such hybrid approach.

Sarwar, N and Sandhu, MS and Ricketts, SL and Butterworth, AS and Di Angelantonio, E and Boelcholdt, SM and Ouwehand, W and Watkins, H and Samani, NJ and Saleheen, D and Lawlor, D and Reilly, MP and Hingorani, AD and Talmud, PJ and Danesh, J and Braund, ...

Ransomware (RW) is a distinctive variety of malware that encrypts the files or locks the user’s system by keeping and taking their files hostage, which leads to huge financial losses to users. In this article, we propose a new model that extracts the novel features from the RW dataset and performs classification of the RW and benign files. The proposed model can detect a large number of RW from various families at runtime and scan the network, registry activities, and file system throughout the execution. API-call series was reutilized to represent the behavior-based features of RW. The technique extracts fourteen-feature vector at runtime and analyzes it by applying online machine learning algorithms to predict the RW. To validate the effectiveness and scalability, we test 78550 recent malign and benign RW and compare with the random forest and AdaBoost, and the testing accuracy is extended at 99.56%.

— In the most recent years, we saw the ascent of XQuery, a dialect locally intended to inquiry over XML archives. The Web, as we probably am aware today, makes an enormous utilization of XML reports, To give a coordination between these two universes, our work introduces a device equipped for arrange SQL inquiries into XQuery administrators prepared to be handled by a XQuery motor. Along these lines, we expect to give more flexibility to engineers, offering dialect autonomy by using SAT.

— Robotized model time is a creating examination field. A significant number of representations are furthermore given where model checking has been associated for affirmation of various sorts of model. Such delineations are SAT based checks of UML/OCL models, embeded structures model affirmation, et cetera. In all these kind of employments, the complement is model checking. In later past, UML programming models are created from programming necessities conveyed in a trademark tongue, for instance, English by using NLP technique. Regardless, the diverse sorts of UML models delivered from consistent vernacular programming requirements specific using NLP approach have no technique for check as in the complete and correct models are done. It is a normal learning NLP techniques have been viably associated with make UML models as delineated above, in any case, in this paper, we address the issue of model checking and model affirmation by using NLP strategies. Such sort of changes require package of effort and time that makes the system of model affirmation wild and ambling. We used an approach for model watching that makes the technique of model checking straightforward and additionally the used philosophy should use the present resources used for generation of the UML class model. I. INTRODUCTION hree different sources are utilized for deciding the quality creating programming process. These three are generator structure and transformer. Model Driven Software Engineering is utilized for taking care of the quality issues of code makers and model generators. Model-Driven Software Engineering (MDSE) is a worldview for programming building. Models are considered as essential building obstructs from which segments of a product framework are made consequently. Models are normally more conceptual representations of the framework to be created. MDSE enhances the correspondence and profitability of UML programming items and requires devices and innovations keeping in mind the end goal to be effectively connected for creating UML models.

EXPRESS is a standard graphical documentation for data models. It is a helpful buddy to the EXPRESS dialect for showing element and sort definitions, connections and cardinality. This graphical documentation underpins a subset of the EXPRESS dialect. One of the preferences of utilizing EXPRESS over EXPRESS is that the structure of an information model can be exhibited in a more reasonable way. In software engineering the graphical representation of the software structure is very necessary because understanding of coding is very difficult. Semantic Business Vocabulary Rules (SBVR) specifications many authors have done model to model transformation. SBVR2EXPRESS is also possible. In this study we propose an EXPRESS data model using Natural language. That model manually implements on two case studies and generate the EXPRESS diagram using SBVR rules. That diagram full fills the all software requirement of the Software engineers. Model representation is very helpful to develop large scale of systems like, Aerospace, medical science and other industries where the representation of system working is very important. This work is very helpful to the Data manger and IT managers to represent their organization structure.

—Today, web based applications have transform into problematical, famous and vital in each organization which needs high consistency and high quality of web based application. Effective development involving software system based on to the quality of any requirement engineering process. This research focus on in what way to elicit and specify the necessities of software to be developed. These events (activities) are supported with in the field called requirement engineering. The study present now aims at refining a specific practice in requirement engineering called UML modelling. In this research we proposed a module based integrated model. This model is further demonstrated with the help of UML modelling. By this technique we achieve the efficient requirement engineering for small scale project. This research investigate the role connected with use case diagram and sequence diagram modelling and also class diagram throughout requirement engineering process. The outcome obtained in this research offer more help for in what way to effectively put on requirement engineering with UML modelling as an essential basis for software development.

—In this paper, we have proposed a model that will help in improving the CPU scheduling of a uni-processor system. The model will use Bayesian Decision Theory as classifier tool that will select an appropriate process from a ready queue. This selection process consists of a two phases; in the first phase its compares the static and dynamic properties of the new processes in the queue with the properties of dataset of the previously executed processes. The dataset is divided into two categories of processes; useful processes and not-useful processes. The new process will be categorized as either useful or not-useful depending on the results of comparison of properties. Our proposed model is applicable in the low-level language such as Assembly at kernel level. Unix/Linux are the better platform for the implementation of our model because Linux/Unix environments are open source and their kernels are editable.

—A sorting algorithm is one that puts elements of a list in a certain order. It makes easy searching and locating the information. The most-used orders are numerical order and lexicographical order. An efficient sorting algorithm is that takes less time and space complexity. In this paper I make contrastive analysis of bubble sort and merge sort and tried to show why required some new approach to get best sorting results. In this regard we proposed a hybrid approach that will take minimum number of comparisons, with less time and space complexity to sort. Divide and conquer (merge sort) with bi-directional bubble sort approach is used and an example data is sorted with such hybrid approach.

—Now a days, web based applications have become intricate, popular and crucial in every organization which requires high quality and high reliability of web based application. Quality of web based applications effects security and functionalities (including functional and non-functional requirements). Web applications are complex due to its heterogeneous and distributed nature. With the increasing complexity, development of web applications requires arduous testing techniques which are cost effective and efficient. Modelling and testing is very essential for development to quality of web based applications. In our paper we proposed an approach for testing of medium scale web based applications. In our approach, the weights of flows (derived from UML activity diagram) calculated using weight based graph [1] and then ideal distance is calculated based on weights of flows. Next we find the trade-off between the effort levels required for testing of medium scale web based applications and exhaustiveness of testing using ideal distance represented by graph. The proposed approach is demonstrated by the mean of case studies.