There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

https://romisatriawahono.net/lecture/rm/survey/network%20security/Modi%20-%20Intrusion%20Detection%20in%20Cloud%20-%202013.pdf

Review: A survey of intrusion detection techniques in Cloud

Suggested by the structure of the visual nervous system, a new algorithm is proposed for pattern recognition. This algorithm can be realized with a multilayered network consisting of neuron-like cells. The network, “neocognitron”, is self-organized by unsupervised learning, and acquires the ability to recognize stimulus patterns according to the differences in their shapes: Any patterns which we human beings judge to be alike are also judged to be of the same category by the neocognitron. The neocognitron recognizes stimulus patterns correctly without being affected by shifts in position or even by considerable distortions in shape of the stimulus patterns.

Neocognitron--A New Algorithm for Pattern Recognition Tolerant of Deformations and Shifts in Position

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive, and anticipatory communications. Such innovative interaction paradigms make AmI technology a suitable candidate for developing various real life solutions, including in the healthcare domain. This survey will discuss the emergence of AmI techniques in the healthcare domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of AmI, such as smart environments and wearable medical devices. We will summarize the state-of-the-art artificial intelligence (AI) methodologies used for developing AmI system in the healthcare domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions), and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

/pdf/a-survey-on-ambient-intelligence-in-healthcare-wkvwfodws9.pdf

A Survey on Ambient Intelligence in Healthcare

In the context of e-health, professionals and healthcare service providers in various organisational and geographical locations are to work together, using information and communication systems, for the purpose of providing better patient-centred and technology-supported healthcare services at anytime and from anywhere. However, various organisations and geographies have varying contexts of work, which are dependent on their local work culture, available expertise, available technologies, people's perspectives and attitudes and organisational and regional agendas. As a result, there is the need to ensure that a suggestion - information and knowledge - provided by a professional to support decision making in a different, and often distant, organisation and geography takes into cognizance the context of the local work setting in which the suggestion is to be used. To meet this challenge, we propose a framework for context-aware knowledge modelling in e-health, which we refer to as ContextMorph. ContextMorph combines the commonKADS knowledge modelling methodology with the concept of activity landscape and context-aware modelling techniques in order to morph, i.e. enrich and optimise, a knowledge resource to support decision making across various contexts of work. The goal is to integrate explicit information and tacit expert experiences across various work domains into a knowledge resource adequate for supporting the operational context of the work setting in which it is to be used.

Context-aware knowledge modelling for decision support in e-health

An integrated approach for intrinsic plagiarism detection

The Address Resolution Protocol (ARP) is used by computers to map network addresses (IP) to physical addresses [MAC] and we can't imagine a communications between networks without the support of ARP protocol. However, ARP had been misused by many malicious hosts for illegitimate penetration; ARP Spoofing is one example for such illegal access. ARP Spoofing can enable malicious hosts to perform Man-in-the-Middle attacks [MiM] as well as a Denial of Service attacks [DoS]. Unfortunately, ARP Spoofing has not been focused by security experts or solutions, e.g. Intrusion Detection Systems or Intrusion Protection Systems [IDS/IPS]. In this research we evaluate the most famous & expensive detection and prevention [IDS/IPS] systems for detecting all types of ARP spoofing attacks and introduce an algorithm which can be implemented in IDS/IPS systems to enhance it's security.

Towards more sophisticated ARP Spoofing detection/prevention systems in LAN networks

While we have seen significant success in web search, enterprise search has not yet been widely investigated and as a result the benefits that can otherwise be brought to the enterprise are not fully realized In this paper, we present an integrated framework for enhancing enterprise search This framework is based on open source technologies which include Apache Hadoop, Tika, Solr and Lucene Importantly, the framework also benefits from a Latent Semantic Indexing (LSI) algorithm to improve the quality of search results LSI is a mathematical model used to discover the semantic relationship patterns in a documents collection We envisage that the proposed framework will benefit various enterprises, improving their productivity by meeting information needs effectively

Towards the development of an integrated framework for enhancing enterprise search using latent semantic indexing

Plagiarism is growing increasingly for the last few years due to the rapid proliferation of information through the World Wide Web (WWW) In this paper, we present an integrated approach based on Latent Semantic Indexing (LSI) and Stylometry technique for intrinsic plagiarism detection LSI is used for the term document matrix of dataset, whereas, stylometry is used for intrinsic approximation of human writing style We have conducted a series of experiments to investigate the efficiency of dimensionality reduction (DR) parameter as the core for LSI technique in order to gain insights into its effects using a small corpus Following that, we carried out comparative evaluation of our approach by using the LSI and Stylometry separately, and then applying them together Our results show that the performance of the proposed approach was improved when an integrated approach consisting of LSI and stylometry was applied

Saad Amin

Papers

Context-aware knowledge modelling for decision support in e-health

An integrated approach for intrinsic plagiarism detection

Towards more sophisticated ARP Spoofing detection/prevention systems in LAN networks

Towards the development of an integrated framework for enhancing enterprise search using latent semantic indexing

Intrinsic Plagiarism Detection Using Latent Semantic Indexing and Stylometry