A huge amount of data is produced in every domain these days. Thus for applying automation on any dataset, the appropriately trained data plays an important role in achieving efficient and accurate results. According to data researchers, data scientists spare 80% of their time in preparing and organizing the data. To overcome this tedious task, IBM Research has developed a Data Quality for AI tool, which has varieties of metrics that can be applied to different datasets (in .csv format) to identify the quality of data. In this paper, we will be representing how the IBM API toolkit will be useful for different variants of datasets and showcase the results for each metrics in graphical form. This paper might be found useful for the readers to understand the working flow of the IBM data purifier tool, thus we have represented the entire flow of how to use IBM data quality for the AI toolkit in the form of architecture.

This paper provides insight to the dynamics that come with the emergence of IoT in the furniture and kitchen manufacturing industry. By implementing the concept of IoT companies are currently evaluating how internal knowledge and skillsets correspond to the new technical requirements that the emerging digital setting outlines and by directing internal research they are learning more about IoT and connected products as they proceed. One current major problem is that there are no open protocols that can connect all products regardless of supplier. Nevertheless, implementation of IoT does not solely involve technical aspects and companies are also faced with the dilemma on how to design and develop corresponding commercial processes. To this point early product implementations have arrived on the consumer markets and the future vision is to achieve full integration that imbeds connectivity and interaction among all products in the home.

In the white paper we strive to cogitate vulnerabilities of one of the most popular big data technology tool Hadoop. The elephant technology is not a bundled one rather by product of the last five decades of technological evolution. The astronomical data today looks like a potential gold mine, but like a gold mine, we only have a little of gold and more of everything else. We can say Big Data is a trending technology but not a fancy one. It is needed for survival for system to exist & persist. Critical Analysis of historic data thus becomes very crucial to play in market with the competitors. Such a state of global organizations where data is going more and more important, illegal attempts are obvious and needed to be checked. Hadoop provides data local processing computation style in which we try to go towards data rather than moving data towards us. Thus, confidentiality of data should be monitored by authorities while sharing it within organization or with third parties so that it does not get leaked out by mistake by naïve employees having access to it. We are proposing a technique of introducing Validation Lamina in Hadoop system that will review electronic signatures from an access control list of concerned authorities while sending & receiving confidential data in organization. If Validation gets failed, concerned authorities would be urgently intimated by the system and the request shall be automatically put on halt till required action is not taken for privacy governance by the authorities.

A variety of technologies in recent years have been developed in designing on-chip networks with the multicore system. In this endeavor, network interfaces mainly differ in the way a network physically connects to a multicore system along with the data path. Semantic substances of communication for a multicore system are transmitted as data packets. Thus, whenever a communication is made from a network, it is first segmented into sub-packets and then into fixed-length bits for flow control digits. To measure required space, energy & latency overheads for the implementation of various interconnection topologies we will be using multi2sim simulator tool that will act as research bed to experiment various tradeoffs between performance and power, and between performance and area requires analysis for further possible optimizations.

The wireless access networks design problem is formulated as a constrained optimization problem, where the goal is to find a network topology such that an objective function is optimized, subject to a set of constraints. The objective function may be the total cost, or some performance measure like utilization, call blocking or throughput. The constraints may be bounds on link capacities, cost elements, or some network performance measure. However, the optimization problem is too complex. In this paper, we propose a novel Ant Colony Optimization (ACO) algorithm to finding the total cost of connecting the BSs to the MSCs, and connecting the MSCs to the LE called by the optimal centralized wireless access network. Numerical results show that performance of our proposed algorithm is much better than previous studies.

A problem of upgrading to the Next Generation Wireless Network (NGWN) is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. In this paper, I propose a new genetic algorithm based on a combination of two populations to solve multi-objective optimization infrastructure upgrade problem in NGWN. Network topology model has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. My objective function is the costs of connection from sources to concentrators such as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. I generate two populations satisfies constraints and combine its to build solutions and evaluate the performance of my algorithm with data randomly generated. The experimental results show that this approach is appropriate and effective Finally, I have applied this algorithm to planning of upgrade infrastructure in telecommunication networks in Haiphong city.

In Next Generation Network (NGN), the backbone of the overall network architecture will be IP network, supporting different access network technologies and types of traffics. NGN will provide advanced services, such as Quality of Service (QoS) guarantees, to users and their applications. Factors affecting the QoS in NGN are speech encoders, delay, jitter, packet loss and echo. The negotiation and dynamic adaptation of QoS is currently considered to be one of the key features of the NGN concept. In this paper, I propose a novel Ant Colony Optimization algorithm to solve model of the optimal QoS for multimedia services in the NGN. Simulation results show that my new approach has achieved near optimal solutions. Comparison of experimental results with a recently researches shows that the proposed algorithm is better performance and it can meets the demand of the optimal QoS for multimedia services in NGN.

The optimal capacity expansion of base station subsystems in Next Generation Wireless Network (NGWN) problem with respect to multi-demand type and system capacity constraints is known to be NP-complete. In this paper, we propose a novel ant colony optimization algorithm to solve a network topology has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. There are two important aspects of upgrading to NGWN. The first importance of backward compatibility with pre-existing networks, and the second is the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. Our objective function is the sources to concentrators connectivity costas well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We evaluate the performance of our algorithm with a set of real world and data randomly generated. Numerical results show that our algorithms is a promising approach to solve this problem.

In this paper, we focus on the network topological design for providing Quality of Service (QoS) in Next Generation Network (NGN) and propose an effective Ant Colony Optimization (ACO) algorithm to solve the capacitated minimum spanning tree (cMTS) problem in dynamic environment. To improve QoS of communication network with considering the network provisioning capability and dynamic environment, we formulate this problem with minimizing the communication cost (as a kind of performance measures for network's QoS). Our objective functions are determined by pheromone matrix of ants satisfies capacity constraints to find good approximate solutions of cMST problems. Numerical experiments show that our algorithm have achieved much better than recent researches.