Increasing the share of multimodal journeys is becoming more and more urgent in our society in order to guarantee a high level of mobility in the long term. While car drivers are already assisted by advanced guidance and navigation facilities, continuous on-trip assistance for multimodal travelers is still in its infancy. Especially when it comes to situations of modal change, travelers get discouraged by the increased complexity and the lack of adequate information and guidance. Thus, the goal of our research over the past three years has been to integrate existing information systems and to design and implement the prototype of a digital personal travel companion for multimodal travelers. This paper discusses typical travel situations and possible barriers for people traveling on multimodal journeys. To address these challenges, functional requirements for a personal travel companion are derived from the analysis of the situations. The main sections of this paper describe our results focusing on personalized multimodal journey planning, mobile multimodal trip management, and smart-phone-based pedestrian orientation and guidance in complex public transport transfer buildings.

Assisting multimodal travelers : Design and prototypical implementation of a personal travel companion

Recent development and research trends related to the EMC/EMI issues in power electronics system are reviewed. Research activities on EMI characterization of power converters, the EMI power filter design, EMI suppression techniques for drive system and switching power supply, PCB layout, EMI modeling and simulation for power electronics systems are discussed separately in different sections.

Status of electromagnetic compatibility research in power electronics

Ubiquitous nature of Internet services across the globe has undoubtedly expanded the strategies and operational mode being used by cybercriminals to perpetrate their unlawful activities through intrusion on various networks. Network intrusion has led to many global financial loses and privacy problems for Internet users across the globe. In order to safeguard the network and to prevent Internet users from being the regular victims of cyber-criminal activities, new solutions are needed. This research proposes solution for intrusion detection by using the improved hashing-based Apriori algorithm implemented on Hadoop MapReduce framework; capable of using association rules in mining algorithm for identifying and detecting network intrusions. We used the KDD dataset to evaluate the effectiveness and reliability of the solution. Our results obtained show that this approach provides a reliable and effective means of detecting network intrusion.

https://www.mdpi.com/2073-431X/8/4/86/pdf

Network Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduce

Purpose




The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.




Design/methodology/approach




In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.




Findings




The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.




Practical implications




This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.




Originality/value




The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes

The growth and evolution of the World Wide Web (WWW) has been rapid over the last ten years and this has been caused mainly by factors such as the social Web and mobile technology. This growth, which presupposes the satisfaction of millions of users accessing Web applications with an adequate quality of service, requires continuous changes in the infrastructure to improve user experience or to handle new demands. Therefore, studies of Web-based systems aimed at comparing different hardware infrastructures, detecting system bottlenecks, provisioning hardware resources, making capacity planning tests, or software testability, are a matter of huge interest. However, the new trends in the WWW have brought new types of user demands and interactions that produce complex workload patterns. These patterns must be exhaustively studied and considered when designing helpful workload generators able to produce representative traces of the current reality. This survey is aimed at providing a useful guide for researchers of the Web, social networking, and other Internet related issues, regarding the main points and concerns about workload generation for Web-based systems. This paper reviews the predominant characteristics and attributes that define Web workloads, including the special cases of other types of Web applications (e.g., blogs, online social network platforms, and video-sharing services). It also identifies the main challenges for the next generation of Web workload generators, and explores current approaches and solutions suggested in recent works.

Workload Generators for Web-Based Systems: Characteristics, Current Status, and Challenges

Electronic subsystems with present day's technology are quite complex and consists of many printed circuit boards. Incidentally printed circuit boards (PCBs) are the ones, which causes most of the electromagnetic interference (EMI) problems. However each sub systems must maintain electromagnetic compatibility (EMC) with other subsystems in order to perform as per the specifications in its intended electromagnetic environment and to meet international regulations. Identifying the potential problems at an earlier stage of the design cycle minimizes the need for design changes by saving time and money. A knowledge based system called EMC Expert, for predicting EMI problems and offering solutions at the design stage of the PCB is presented. EMC Expert is implemented on a HP9000/735 workstation using C++ under X-Windows/MOTIF and is used to analyze PCBs designed by DRDL/CAD centre.

EMC analysis in PCB designs using an expert system

https://cyberleninka.org/article/n/907768.pdf

Frequent Itemset Generation using Double Hashing Technique

Cluster based bit vector mining algorithm for finding frequent itemsets in temporal databases

An intelligent knowledge based system is being developed in Queen Mary College for the tasks of monitoring, fault diagnosis and safety action in process control. The problem considered is to monitor the process behaviour and diagnose any of the following faults in the system. component faults; sensor faults; and controller faults. The authors discuss the system, looking particularly at qualitative reasoning and system behaviour.

https://ieeexplore.ieee.org/iel3/2146/5376/00209041.pdf

An intelligent knowledge based system for diagnosis based on qualitative reasoning

Frequent item sets is one of the most investigated fields of data mining. The significant feature is to find new techniques to reduce candidate item sets in order to generate frequent item sets efficiently. This paper introduces an efficient algorithm called Enhanced Candidate Generation for Frequent item set Generation (ECG for FIG) for finding frequent item sets from large databases. The existing algorithm for frequent item set generation scan the original database more than once, use more storage space, take more processing time. The proposed algorithm gives a solution to this by representing the transactions in the database with decimal numbers instead of binary values and strings. The original database is scanned only once and is converted into an equivalent decimal value to reduce the storage space. The subset generation concept is used to generate frequent item sets. Thus the proposed algorithm reduces the scanning time, processing time and the storage space respectively. When compared with the existing algorithms, the proposed algorithm takes very less execution time and memory. When implemented the algorithm using java and tested with WEKA tool, for 400 transactions of twenty five items, ECG for FIG is taking only 800 bytes of memory and 2000000000 ns (two seconds), whereas all the other above mentioned algorithms are taking 20800 bytes of memory and more than two seconds.

M. Krishnamurthy

Papers

EMC analysis in PCB designs using an expert system

Frequent Itemset Generation using Double Hashing Technique

Cluster based bit vector mining algorithm for finding frequent itemsets in temporal databases

An intelligent knowledge based system for diagnosis based on qualitative reasoning

Enhanced Candidate Generation for Frequent Item Set Generation