36 research outputs found
A hybrid genetic algorithm with mapreduce technique for cloud computing energy efficiency
Computer clouds generally comprise large power-consuming data centers as they are designed to support the elasticity and scalability required by customers. However, while cloud computing reduces energy consumption for customers, it is an issue for providers who have to deal with increasing demand and performance expectations. This creates the need for mechanisms to improve the energy-efficiency of cloud computing data centers while maintaining desired levels of performance. This research seeks to formulate a hybrid algorithm based on Genetic algorithm and MapReduce algorithm techniques to further promote energy efficiency in the cloud computing platform. The function of the MapReduce algorithm is to optimize scheduling performance which is one of the more efficient techniques for handling large data in servers. Genetic algorithm is effective in optimally measuring the value of operations and allows for the minimization of energy efficiency where it includes the formula for single optimization energy efficiency. A series of simulations were developed to evaluate the effectiveness of the proposed algorithm. The evaluation results show the amount of Information Technology equipment power required for Power Usage Effectiveness values to optimize energy usage where the performance of the proposed algorithm is 6% better than the previous genetic algorithm and 5% better than Hadoop MapReduce scheduling on low load conditions. On the other hand, the proposed algorithm improved energy efficiency in comparison with the previous work
Application of Geographic Information Systems
The importance of Geographic Information Systems (GIS) can hardly be overemphasized in today’s academic and professional arena. More professionals and academics have been using GIS than ever – urban & regional planners, civil engineers, geographers, spatial economists, sociologists, environmental scientists, criminal justice professionals, political scientists, and alike. As such, it is extremely important to understand the theories and applications of GIS in our teaching, professional work, and research. “The Application of Geographic Information Systems” presents research findings that explain GIS’s applications in different subfields of social sciences. With several case studies conducted in different parts of the world, the book blends together the theories of GIS and their practical implementations in different conditions. It deals with GIS’s application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, infrastructure network analysis like transportation and water distribution network, and such. The book is expected to be a useful source of knowledge to the users of GIS who envision its applications in their teaching and research. This easy-to-understand book is surely not the end in itself but a little contribution to toward our understanding of the rich and wonderful subject of GIS
Sustainable | Sustaining City Streets
Streets are an integral part of every city on Earth. They channel the people, vehicles, and materials that help make urban life what it is. They are conduits for the oft-taken-for-granted infrastructures that carry fresh water, energy, and information, and that remove excess stormwater and waste. The very air that we breathe—fresh or foul—flows through our street canyons. That streets are the arteries of the city is, indeed, an apt metaphor. But city streets also function as a front yard, linear ecosystem, market, performance stage, and civic forum, among other duties. In their various forms, streets are places of interaction and exchange, from the everyday to the extraordinary. As the editors affirm, the more we scrutinize, share, and activate sustainable approaches to streets, the greater the likelihood that our streets will help sustain life in cities and, by extension, the planet. While diverse in subject, the papers in this volume are unified in seeing the city street as the complex, impactful, and pliable urban phenomenon that it is. Topics range from greenstreets to transit networks to pedestrian safety and walkability. Anyone seeking interdisciplinary perspectives on what makes for good city streets and street networks should find this book of interest
Educational Technology and Education Conferences, June to December 2012
The conference list contains events such as "Learning and Teaching","Innovation in e-Learning", "Online Teaching", "Distance Learning Administration", "The World Open Educational Resources Congress", "Mobile Health", and "Realizing Dreams"
Efficiency, Fairness and Sustainability in Social Housing Policy and Projects
The provision of affordable housing for low-income households is a very complex issue that has long been debated in many countries around the world. Social housing (SH) is one of the tools for achieving fairness, social sustainability, and economic feasibility, and it is interrelated with politics, ethics, and economics, as well as the environment, architecture, and technology. In other words, national and local policies, as well as public and private financial resources, are all needed to provide SH.SH also involves social and urban transformations and is, consequently, linked to urban planning and redevelopment projects, real estate market dynamics, and cooperation between public and private stakeholders. Furthermore, decision-making on SH policies and projects has to be supported by assessments of economic feasibility and social and environmental sustainability.This volume presents studies on various topics to recompose the multi-faceted subjects of social housing within a unified framework
Advanced Topics in Systems Safety and Security
This book presents valuable research results in the challenging field of systems (cyber)security. It is a reprint of the Information (MDPI, Basel) - Special Issue (SI) on Advanced Topics in Systems Safety and Security. The competitive review process of MDPI journals guarantees the quality of the presented concepts and results. The SI comprises high-quality papers focused on cutting-edge research topics in cybersecurity of computer networks and industrial control systems. The contributions presented in this book are mainly the extended versions of selected papers presented at the 7th and the 8th editions of the International Workshop on Systems Safety and Security—IWSSS. These two editions took place in Romania in 2019 and respectively in 2020. In addition to the selected papers from IWSSS, the special issue includes other valuable and relevant contributions. The papers included in this reprint discuss various subjects ranging from cyberattack or criminal activities detection, evaluation of the attacker skills, modeling of the cyber-attacks, and mobile application security evaluation. Given this diversity of topics and the scientific level of papers, we consider this book a valuable reference for researchers in the security and safety of systems
Enhancing trustability in MMOGs environments
Massively Multiplayer Online Games (MMOGs; e.g., World of Warcraft), virtual worlds
(VW; e.g., Second Life), social networks (e.g., Facebook) strongly demand for more
autonomic, security, and trust mechanisms in a way similar to humans do in the real
life world. As known, this is a difficult matter because trusting in humans and organizations
depends on the perception and experience of each individual, which is difficult to
quantify or measure. In fact, these societal environments lack trust mechanisms similar
to those involved in humans-to-human interactions. Besides, interactions mediated
by compute devices are constantly evolving, requiring trust mechanisms that keep the
pace with the developments and assess risk situations.
In VW/MMOGs, it is widely recognized that users develop trust relationships from their
in-world interactions with others. However, these trust relationships end up not being
represented in the data structures (or databases) of such virtual worlds, though they
sometimes appear associated to reputation and recommendation systems. In addition,
as far as we know, the user is not provided with a personal trust tool to sustain his/her
decision making while he/she interacts with other users in the virtual or game world.
In order to solve this problem, as well as those mentioned above, we propose herein a
formal representation of these personal trust relationships, which are based on avataravatar
interactions. The leading idea is to provide each avatar-impersonated player
with a personal trust tool that follows a distributed trust model, i.e., the trust data is
distributed over the societal network of a given VW/MMOG.
Representing, manipulating, and inferring trust from the user/player point of view certainly
is a grand challenge. When someone meets an unknown individual, the question
is “Can I trust him/her or not?”. It is clear that this requires the user to have access to
a representation of trust about others, but, unless we are using an open source VW/MMOG,
it is difficult —not to say unfeasible— to get access to such data. Even, in an open
source system, a number of users may refuse to pass information about its friends, acquaintances,
or others. Putting together its own data and gathered data obtained from
others, the avatar-impersonated player should be able to come across a trust result
about its current trustee. For the trust assessment method used in this thesis, we use
subjective logic operators and graph search algorithms to undertake such trust inference
about the trustee. The proposed trust inference system has been validated using
a number of OpenSimulator (opensimulator.org) scenarios, which showed an accuracy
increase in evaluating trustability of avatars.
Summing up, our proposal aims thus to introduce a trust theory for virtual worlds, its
trust assessment metrics (e.g., subjective logic) and trust discovery methods (e.g.,
graph search methods), on an individual basis, rather than based on usual centralized
reputation systems. In particular, and unlike other trust discovery methods, our methods
run at interactive rates.MMOGs (Massively Multiplayer Online Games, como por exemplo, World of Warcraft),
mundos virtuais (VW, como por exemplo, o Second Life) e redes sociais (como por exemplo,
Facebook) necessitam de mecanismos de confiança mais autónomos, capazes de
assegurar a segurança e a confiança de uma forma semelhante à que os seres humanos
utilizam na vida real. Como se sabe, esta não é uma questão fácil. Porque confiar em
seres humanos e ou organizações depende da percepção e da experiĂŞncia de cada indivĂduo,
o que Ă© difĂcil de quantificar ou medir Ă partida. Na verdade, esses ambientes
sociais carecem dos mecanismos de confiança presentes em interacções humanas presenciais.
Além disso, as interacções mediadas por dispositivos computacionais estão em
constante evolução, necessitando de mecanismos de confiança adequados ao ritmo da
evolução para avaliar situações de risco.
Em VW/MMOGs, é amplamente reconhecido que os utilizadores desenvolvem relações
de confiança a partir das suas interacções no mundo com outros. No entanto, essas relações
de confiança acabam por não ser representadas nas estruturas de dados (ou bases
de dados) do VW/MMOG especĂfico, embora Ă s vezes apareçam associados Ă reputação
e a sistemas de reputação. Além disso, tanto quanto sabemos, ao utilizador não lhe
é facultado nenhum mecanismo que suporte uma ferramenta de confiança individual
para sustentar o seu processo de tomada de decisĂŁo, enquanto ele interage com outros
utilizadores no mundo virtual ou jogo. A fim de resolver este problema, bem como
os mencionados acima, propomos nesta tese uma representação formal para essas relações
de confiança pessoal, baseada em interacções avatar-avatar. A ideia principal
é fornecer a cada jogador representado por um avatar uma ferramenta de confiança
pessoal que segue um modelo de confiança distribuĂda, ou seja, os dados de confiança
sĂŁo distribuĂdos atravĂ©s da rede social de um determinado VW/MMOG.
Representar, manipular e inferir a confiança do ponto de utilizador/jogador, é certamente
um grande desafio. Quando alguĂ©m encontra um indivĂduo desconhecido, a
pergunta é “Posso confiar ou não nele?”. É claro que isto requer que o utilizador tenha
acesso a uma representação de confiança sobre os outros, mas, a menos que possamos
usar uma plataforma VW/MMOG de cĂłdigo aberto, Ă© difĂcil — para nĂŁo dizer impossĂvel
— obter acesso aos dados gerados pelos utilizadores. Mesmo em sistemas de código
aberto, um número de utilizadores pode recusar partilhar informações sobre seus amigos,
conhecidos, ou sobre outros. Ao juntar seus prĂłprios dados com os dados obtidos de
outros, o utilizador/jogador representado por um avatar deve ser capaz de produzir uma
avaliação de confiança sobre o utilizador/jogador com o qual se encontra a interagir.
Relativamente ao método de avaliação de confiança empregue nesta tese, utilizamos
lógica subjectiva para a representação da confiança, e também operadores lógicos da
lĂłgica subjectiva juntamente com algoritmos de procura em grafos para empreender
o processo de inferência da confiança relativamente a outro utilizador. O sistema de
inferência de confiança proposto foi validado através de um número de cenários Open-Simulator (opensimulator.org), que mostrou um aumento na precisão na avaliação da
confiança de avatares.
Resumindo, a nossa proposta visa, assim, introduzir uma teoria de confiança para mundos
virtuais, conjuntamente com métricas de avaliação de confiança (por exemplo, a
lógica subjectiva) e em métodos de procura de caminhos de confiança (com por exemplo,
através de métodos de pesquisa em grafos), partindo de uma base individual, em
vez de se basear em sistemas habituais de reputação centralizados. Em particular, e ao
contrário de outros métodos de determinação do grau de confiança, os nossos métodos
sĂŁo executados em tempo real
Emotion and Stress Recognition Related Sensors and Machine Learning Technologies
This book includes impactful chapters which present scientific concepts, frameworks, architectures and ideas on sensing technologies and machine learning techniques. These are relevant in tackling the following challenges: (i) the field readiness and use of intrusive sensor systems and devices for capturing biosignals, including EEG sensor systems, ECG sensor systems and electrodermal activity sensor systems; (ii) the quality assessment and management of sensor data; (iii) data preprocessing, noise filtering and calibration concepts for biosignals; (iv) the field readiness and use of nonintrusive sensor technologies, including visual sensors, acoustic sensors, vibration sensors and piezoelectric sensors; (v) emotion recognition using mobile phones and smartwatches; (vi) body area sensor networks for emotion and stress studies; (vii) the use of experimental datasets in emotion recognition, including dataset generation principles and concepts, quality insurance and emotion elicitation material and concepts; (viii) machine learning techniques for robust emotion recognition, including graphical models, neural network methods, deep learning methods, statistical learning and multivariate empirical mode decomposition; (ix) subject-independent emotion and stress recognition concepts and systems, including facial expression-based systems, speech-based systems, EEG-based systems, ECG-based systems, electrodermal activity-based systems, multimodal recognition systems and sensor fusion concepts and (x) emotion and stress estimation and forecasting from a nonlinear dynamical system perspective
A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates
Soil erosion is a major problem around the world because of its effects on
soil productivity, nutrient loss, siltation in water bodies, and degradation
of water quality. By understanding the driving forces behind soil erosion, we
can more easily identify erosion-prone areas within a landscape to address
the problem strategically. Soil erosion models have been used to assist in
this task. One of the most commonly used soil erosion models is the Universal
Soil Loss Equation (USLE) and its family of models: the Revised Universal
Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation
version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE).
This paper reviews the different sub-factors of USLE and RUSLE, and analyses
how different studies around the world have adapted the equations to local
conditions. We compiled these studies and equations to serve as a reference
for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the
strengths and limitations of the different equations are discussed, and
guidance is given as to which equations may be most appropriate for
particular climate types, spatial resolution, and temporal scale. We
investigate some of the limitations of existing (R)USLE formulations, such as
uncertainty issues given the simple empirical nature of the model and many of
its sub-components; uncertainty issues around data availability; and its
inability to account for soil loss from gully erosion, mass wasting events,
or predicting potential sediment yields to streams. Recommendations on how to
overcome some of the uncertainties associated with the model are given.
Several key future directions to refine it are outlined: e.g. incorporating
soil loss from other types of soil erosion, estimating soil loss at
sub-annual temporal scales, and compiling consistent units for the future
literature to reduce confusion and errors caused by mismatching units. The
potential of combining (R)USLE with the Compound Topographic Index (CTI) and
sediment delivery ratio (SDR) to account for gully erosion and sediment yield
to streams respectively is discussed. Overall, the aim of this paper is to
review the (R)USLE and its sub-factors, and to elucidate the caveats,
limitations, and recommendations for future applications of these soil
erosion models. We hope these recommendations will help researchers more
robustly apply (R)USLE in a range of geoclimatic regions with varying data
availability, and modelling different land cover scenarios at finer spatial
and temporal scales (e.g. at the field scale with different cropping
options).</p