The culture of education

[서평]「The Unified Modeling Language User Guide」

Several physico-mechanical designs evolved in fish are currently inspiring robotic devices for propulsion and maneuvering purposes in underwater vehicles. Considering the potential benefits involved, this paper presents an overview of the swimming mechanisms employed by fish. The motivation is to provide a relevant and useful introduction to the existing literature for engineers with an interest in the emerging area of aquatic biomechanisms. The fish swimming types are presented, following the well-established classification scheme and nomenclature originally proposed by Breder. Fish swim either by body and/or caudal fin (BCF) movements or using median and/or paired fin (MPF) propulsion. The latter is generally employed at slow speeds, offering greater maneuverability and better propulsive efficiency, while BCF movements can achieve greater thrust and accelerations. For both BCF and MPF locomotion, specific swimming modes are identified, based on the propulsor and the type of movements (oscillatory or undulatory) employed for thrust generation. Along with general descriptions and kinematic data, the analytical approaches developed to study each swimming mode are also introduced. Particular reference is made to lunate tail propulsion, undulating fins, and labriform (oscillatory pectoral fin) swimming mechanisms, identified as having the greatest potential for exploitation in artificial systems.

/pdf/review-of-fish-swimming-modes-for-aquatic-locomotion-12dkkh88vr.pdf

Review of fish swimming modes for aquatic locomotion

The effective application of sliding mode control to mechanical systems is not straightforward because of the sensitivity of these systems to chattering. Higher-order sliding modes can counteract this phenomenon by confining the switching control to the higher derivatives of the mechanical control variable, so that the latter results are continuous. Generally, this approach requires the availability of a number of time derivatives of the sliding variable, and, in the presence of noise, this requirement could be a practical limitation. A class of second-order sliding mode controllers, guaranteeing finite-time convergence for systems with relative degree two between the sliding variable and the switching control, could be helpful both in reducing the number of differentiator stages in the controller and in dealing with unmodelled actuator dynamics. In this paper different second-order sliding mode controllers, previously presented in the literature, are shown to belong to the above cited class, and some cha...

A survey of applications of second-order sliding mode control to mechanical systems

One of the most important control problems is control under heavy uncertainty conditions. While there are a number of sophisticated methods like adaptation based on identification and observation, or absolute stability methods, the most obvious way to withstand the uncertainty is to keep some constraints by "brutal force". Indeed any strictly kept equality removes one " uncertainty dimension". The most simple way to keep a constraint is to react immediately to any deviation of the system stirring it back to the constraint by a sufficiently energetic effort. Implemented directly, the approach leads to so-called sliding modes, which become main operation modes in the variable structure systems (VSS) [55]. Having proved their high accuracy and robustness with respect to various internal and external disturbances, they also reveal their main drawback: the so-called chattering effect, i.e., dangerous high-frequency vibrations of the controlled system. Such an effect was considered as an obvious intrinsic feature of the very idea of immediate powerful reaction to the minutest deviation from the chosen constraint. Another important feature is proportionality of the maximal deviation from the constraint to the time interval between the measurements (or to the switching delay).

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rnc.1229

Higher order sliding modes

This paper discusses possible motivations to adopt cognitive computing-based solutions in the field of healthcare and surveys some recent experiences From a very practical point of view, the use of cognitive computing techniques can provide machines with human-like reasoning capabilities, thus allowing them to face heavy uncertainties and to cope with problems whose solution may require computing intensive tasks Moreover, empowered by reliable networking infrastructures and cloud environments, cognitive computing enables effective machine-learning techniques, resulting in the ability to find solutions on the basis of past experience, taking advantage from both errors and successful findings Owing to these special features, it is perceptible that healthcare can greatly benefit from such a powerful technology In fact, clinical diagnoses are frequently based on statistics and significant research advancements were accomplished through the recursive analysis of huge quantity of unstructured data such as in the case of X-ray images or computerized axial tomography scans As another example, let us consider the problem of DNA sequence classification with the uncountable combinations that derive from such a complex structure

Adopting Cognitive Computing Solutions in Healthcare

Privacy problems with Web 2.0

Social environments were already present in the original web vision, but nowadays are mainly available through online social networks OSNs, which are a real cultural phenomenon. However, their actual deployment is very heterogeneous, reflecting into different development choices and functional architectures. Such aspects, jointly with the intrinsic sharing of personal information, lead to severe risks both in terms of security and privacy. In this perspective, our work proposes a taxonomy-based approach to describe and model the complex security space characterising OSNs. The contributions of this paper are: 1 to introduce a systematic approach to define the 'problem space' of an OSN; 2 to showcase basic models for organising the engineering and the needed checking procedures.

A taxonomy-based model of security and privacy in online social networks

While the innovation and phenomenon of social network applications has greatly impacted society, the economy, and the technological pool of the internet; these platforms are not only used for content sharing purposes. They are also used to support and develop new services and applications.Social Network Engineering for Secure Web Data and Services provides empirical research on the engineering of social network infrastructures, the development of novel applications, and the impact of social network- based services over the internet. This comprehensive collection highlights issues and solutions developed to prevent security threats and introduce proper countermeasures for attacks on every level. This book is useful for professionals and researchers in the field of social network and web security.

Social Network Engineering for Secure Web Data and Services

Cognitive computing is the new wave of Artificial Intelligence (AI), relying on traditional techniques based on expert systems and also exploiting statistics and mathematical model. In particular, cognitive computing systems can be regarded as a "more human" artificial intelligence. In fact, they mimic human reasoning methodologies, showing special capabilities in dealing with uncertainties and in solving problems that typically entail computation consuming processes. Moreover, they can evolve, exploiting the accumulated experience to learn from the past, both from errors and from successful findings. From a theoretical point of view, cognitive computing could replace existing calculators in many fields of application but hardware requirements are still high, even if the cloud infrastructure, which is expected to uphold its rapid growth in the very next future, can support their diffusion and ease the penetration of such a novel variety of systems, fostering new services as well as changes in many settled paradigms. In this paper, we focus on benefits that this technology can bring when applied in the education field and we make a short review of relevant experiences.

/pdf/cognitive-computing-in-education-4dgghdt62v.pdf

Mauro Coccoli

Papers

Adopting Cognitive Computing Solutions in Healthcare

Privacy problems with Web 2.0

A taxonomy-based model of security and privacy in online social networks

Social Network Engineering for Secure Web Data and Services

Cognitive computing in education