Abstract: This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.
Abstract: E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.
Abstract: This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.
Abstract: This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.
Abstract: The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.
Abstract: In this paper, an attempt has been made for the design
of a robotic library using an intelligent system. The robot works on
the ARM microprocessor, motor driver circuit with 5 degrees of
freedom with Wi-Fi and GPS based communication protocol. The
authenticity of the library books is controlled by RFID. The proposed
robotic library system is facilitated with embedded system and ARM.
In this library issuance system, the previous potential readers’
authentic review reports have been taken into consideration for
recommending suitable books to the deserving new users and the
issuance of books or periodicals is based on the users’ decision. We
have conjectured that the Wi-Fi based robotic library management
system would allow fast transaction of books issuance and it also
produces quality readers.
Abstract: This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.
Abstract: There are real needs to integrate types of Open
Educational Resources (OER) with an intelligent system to extract
information and knowledge in the semantic searching level. The
needs came because most of current learning standard adopted web
based learning and the e-learning systems do not always serve all
educational goals. Semantic Web systems provide educators,
students, and researchers with intelligent queries based on a semantic
knowledge management learning system. An ontology-based learning
system is an advanced system, where ontology plays the core of the
semantic web in a smart learning environment. The objective of this
paper is to discuss the potentials of ontologies and mapping different
kinds of ontologies; heterogeneous or homogenous to manage and
control different types of Open Educational Resources. The important
contribution of this research is that it uses logical rules and
conceptual relations to map between ontologies of different
educational resources. We expect from this methodology to establish
an intelligent educational system supporting student tutoring, self and
lifelong learning system.
Abstract: There is currently a gap in the technology covering the
rapid establishment of control after a reconfiguration in a
Reconfigurable Manufacturing System. This gap involves the
detection of the factory floor state and the communication link
between the factory floor and the high-level software. In this paper, a
thin, hardware-supported Middleware Management System (MMS) is
proposed and its design and implementation are discussed. The
research found that a cost-effective localization technique can be
combined with intelligent software to speed up the ramp-up of a
reconfigured system. The MMS makes the process more intelligent,
more efficient and less time-consuming, thus supporting the
industrial implementation of the RMS paradigm.
Abstract: This research presents the main ideas to implement an
intelligent system composed by communicating wireless sensors
measuring environmental data linked to drought indicators (such as
air temperature, soil moisture , etc...). On the other hand, the setting
up of a spatio temporal database communicating with a Web mapping
application for a monitoring in real time in activity 24:00 /day, 7
days/week is proposed to allow the screening of the drought
parameters time evolution and their extraction. Thus this system
helps detecting surfaces touched by the phenomenon of drought.
Spatio-temporal conceptual models seek to answer the users who
need to manage soil water content for irrigating or fertilizing or other
activities pursuing crop yield augmentation. Effectively, spatiotemporal
conceptual models enable users to obtain a diagram of
readable and easy data to apprehend. Based on socio-economic
information, it helps identifying people impacted by the phenomena
with the corresponding severity especially that this information is
accessible by farmers and stakeholders themselves. The study will be
applied in Siliana watershed Northern Tunisia.
Abstract: Moving into a new era of healthcare, new tools and
devices are developed to extend and improve health services, such as
remote patient monitoring and risk prevention. In this concept,
Internet of Things (IoT) and Cloud Computing present great
advantages by providing remote and efficient services, as well as
cooperation between patients, clinicians, researchers and other health
professionals. This paper focuses on patients suffering from bipolar
disorder, a brain disorder that belongs to a group of conditions
called affective disorders, which is characterized by great mood
swings. We exploit the advantages of Semantic Web and Cloud
Technologies to develop a patient monitoring system to support
clinicians. Based on intelligently filtering of evidence-knowledge and
individual-specific information we aim to provide treatment
notifications and recommended function tests at appropriate times or
concluding into alerts for serious mood changes and patient’s nonresponse
to treatment. We propose an architecture as the back-end
part of a cloud platform for IoT, intertwining intelligence devices
with patients’ daily routine and clinicians’ support.
Abstract: This paper introduces a proposal scheme for an
Intelligent System applied to Pedagogical Advising using Case-Based
Reasoning, to find consolidated solutions before used for the new
problems, making easier the task of advising students to the
pedagogical staff. We do intend, through this work, introduce the
motivation behind the choices for this system structure, justifying the
development of an incremental and smart web system who learns
bests solutions for new cases when it’s used, showing technics and
technology.
Abstract: In this paper, we propose an intelligent system that is
used for monitoring the health conditions of patients. Monitoring the
health condition of patients is a complex problem that involves
different medical units and requires continuous monitoring especially
in rural areas because of inadequate number of available specialized
physicians. The proposed system will improve patient care and drive
costs down comparing to the existing system in Jordan. The proposed
system will be the start point to faster and improve the
communication between different units in the health system in
Jordan. Connecting patients and their physicians beyond hospital
doors regarding their geographical area is an important issue in
developing the health system in Jordan. The ability of making
medical decisions, the quality of medical is expected to be improved.
Abstract: In this paper, we propose a multi-agent intelligent
system that is used for monitoring the health conditions of elderly
people. Monitoring the health condition of elderly people is a
complex problem that involves different medical units and requires
continuous monitoring. Such expert system is highly needed in rural
areas because of inadequate number of available specialized
physicians or nurses. Such monitoring must have autonomous
interactions between these medical units in order to be effective. A
multi-agent system is formed by a community of agents that
exchange information and proactively help one another to achieve the
goal of elderly monitoring. The agents in the developed system are
equipped with intelligent decision maker that arms them with the
rule-based reasoning capability that can assist the physicians in
making decisions regarding the medical condition of elderly people.
Abstract: The focus of this paper is to compare common approaches for Systems of Innovation (SI) and identify proactive alternatives for driving the innovation. Proactive approaches will also consider short and medium term perspectives with developments in the field of Computer Technology and Artificial Intelligence. Concerning Computer Technology and Large Connected Information Systems, it is reasonable to predict that during current or the next century intelligence and innovation will be separated from the constraints of human driven management. After this happens, humans will be no longer driving the innovation and there is possibility that SI for new intelligent systems will set its own targets and exclude humans. Over long time scale these developments could result in scenario, which will lead to the development of larger, cross galactic (universal) proactive SI and Intelligence.
Abstract: This article analyzes the applicability of known renewable energy technical means as mobile power sources under the field and extreme conditions. The requirements are determined for the parameters of mobile micro HPP. The application prospectively of the mobile micro HPP with intelligent control systems is proved for this purpose. Variants of low-speed electric generators for micro HPP are given. Variants of designs for mobile micro HPP are presented with direct (gearless) transfer of torque from the hydraulic drive to the rotor of the electric generator. Variant of the hydraulic drive for micro HPP is described workable at low water flows. A general structure of the micro HPP intelligent system control is offered that implements the principle of maximum energy efficiency. The legitimacy of construction and application of mobile micro HPP is proved as electrical power sources for life safety of people under the field and extreme conditions.
Abstract: Educational data mining is a specific data mining field applied to data originating from educational environments, it relies on different approaches to discover hidden knowledge from the available data. Among these approaches are machine learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.
In our research, we propose a “Student Advisory Framework” that utilizes classification and clustering to build an intelligent system. This system can be used to provide pieces of consultations to a first year university student to pursue a certain education track where he/she will likely succeed in, aiming to decrease the high rate of academic failure among these students. A real case study in Cairo Higher Institute for Engineering, Computer Science and Management is presented using real dataset collected from 2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.
Abstract: Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed
Abstract: The future of business intelligence (BI) is to integrate
intelligence into operational systems that works in real-time
analyzing small chunks of data based on requirements on continuous
basis. This is moving away from traditional approach of doing
analysis on ad-hoc basis or sporadically in passive and off-line mode
analyzing huge amount data. Various AI techniques such as expert
systems, case-based reasoning, neural-networks play important role
in building business intelligent systems. Since BI involves various
tasks and models various types of problems, hybrid intelligent
techniques can be better choice. Intelligent systems accessible
through web services make it easier to integrate them into existing
operational systems to add intelligence in every business processes.
These can be built to be invoked in modular and distributed way to
work in real time. Functionality of such systems can be extended to
get external inputs compatible with formats like RSS. In this paper,
we describe a framework that use effective combinations of these
techniques, accessible through web services and work in real-time.
We have successfully developed various prototype systems and done
few commercial deployments in the area of personalization and
recommendation on mobile and websites.
Abstract: The paper attempts to contribute to the largely
neglected social and anthropological discussion of technology development on the one hand, and to redirecting the emphasis in
anthropology from primitive and exotic societies to problems of high
relevance in contemporary era and how technology is used in
everyday life. It draws upon multidimensional models of intelligence
and ideal type formation. It is argued that the predominance of
computational and cognitive cosmovisions have led to technology alienation. Injection of communicative competence in artificially
intelligent systems and identity technologies in the coming
information society are analyzed