Search results for: intelligent object

Authors: Siamak Eskandari, Neda Ebadi

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Among common electronic parts which have been invented and have made a great revolution in the lighting system through the world, certainly LEDs have no rival. These small parts with their very low power consumption, very dazzling and powerful light and small size and with their extremely high lifetime- compared to incandescent bulbs and compact fluorescent lamp (CFLs) have undoubtedly revolutionized the lighting industry of the world. Based on conducted studies and experiments, in addition to their acceptable light and low power consumption -compared to incandescent bulbs and CFLs-, they have very low and in some cases zero environmental pollution and negative effects on human beings. Because of their longevity, in the case of using high-quality circuits and proper and consistent use of LEDs in conventional and intelligent buildings, there will be no need to replace the burnout lamps, for a long time (10 years). In this study which was conducted on 10-watt power LEDs with suitable heatsink/cooling, considerable amount of heat was generated during lighting after 5 minutes and 45 seconds. The temperature rose to above 99 degrees Celsius and this amount of heat can raise the water temperature to 60 degrees Celsius and more. Based on conducted experiments, this can provide the heat required for bathing, washing, radiators (in cold seasons) easily and only by imposing very low cost and it will be a big step in the optimization of energy consumption in the future.

Keywords: energy, light, water, optimization of power LED

Procedia PDF Downloads 136

Authors: Perizat Balkhimbekova

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Evolutionary changes in cognitive world view taking place in the last decades are followed by changes in perception of the key concepts which are related to the certain lingua-cultural sphere. Also, such concepts reflect the person’s attitude to essential processes in the sphere of concepts, e.g. the opposite operations like creation and destruction. These changes in people’s life and thinking are displayed in a language world view. In order to open the maintenance of mental structures and concepts we should use language means as observable results of people’s cognitive activity. Semantics of words, free phrases and idioms should be considered as an authoritative source of information concerning concepts. The regularized set of concepts in people consciousness forms the sphere of concepts. Cognitive linguistics widely discusses the sphere of concepts as its crucial category defining it as the field of knowledge which is made of concepts. It is considered that a sphere of concepts comprises the various types of association and forms conceptual fields. As a material for the given research, the data from Russian National Corpus and British National Corpus were used. In is necessary to point out that data provided by computational studies, are intrinsic and verifiable; so that we have used them in order to get the reliable results. The procedure of study was based on such techniques as extracting of the context containing concepts of creation|destruction from the Russian National Corpus (RNC), and British National Corpus (BNC); analyzing and interpreting of those context on the basis of cognitive approach; finding of correspondence between the given concepts in the Russian and English world view. The key problem of our study is to find the correspondence between the elements of world view represented by opposite concepts such as creation and destruction. Findings: The concept of "destruction" indicates a process which leads to full or partial destruction of an object. In other words, it is a loss of the object primary essence: structures, properties, distinctive signs and its initial integrity. The concept of "creation", on the contrary, comprises positive characteristics, represents the activity aimed at improvement of the certain object, at the creation of ideal models of the world. On the other hand, destruction is represented much more widely in RNC than creation (1254 cases of the first concept by comparison to 192 cases for the second one). Our hypothesis consists in the antinomy represented by the aforementioned concepts. Being opposite both in respect of semantics and pragmatics, and from the point of view of axiology, they are at the same time complementary and interrelated concepts.

Keywords: creation, destruction, concept, world view

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Authors: Robert O. Abolade, Olumide O. Ajayi, Zacheaus K. Adeyemo, Solomon A. Adeniran

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Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.

Keywords: channel quality indicator, fuzzy logic, link adaptation, MIMO, spatial multiplexing, transmit diversity

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Authors: Panagiotis Roupas, Yota Passia

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This paper aims at establishing an index of design mechanisms - immanent in spatial objects - based on the affective capacity of their material formations. While spatial objects (design objects, buildings, urban configurations, etc.) are regarded as systems composed of interacting parts, within the premises of assemblage theory, their ability to affect and to be affected has not yet been mapped or sufficiently explored. This ability lies in excess, a latent potentiality they contain, not transcendental but immanent in their pre-subjective aesthetic power. As spatial structures are theorized as assemblages - composed of heterogeneous elements that enter into relations with one another - and since all assemblages are parts of larger assemblages, their components' ability to engage is contingent. We thus seek to unfold the mechanisms inherent in spatial objects that allow to the constituent parts of design assemblages to perpetually enter into new assemblages. To map architectural assemblage's affective ability, spatial objects are analyzed in two axes. The first axis focuses on the relations that the assemblage's material and expressive components develop in order to enter the assemblages. Material components refer to those material elements that an assemblage requires in order to exist, while expressive components includes non-linguistic (sense impressions) as well as linguistic (beliefs). The second axis records the processes known as a-signifying signs or a-signs, which are the triggering mechanisms able to territorialize or deterritorialize, stabilize or destabilize the assemblage and thus allow it to assemble anew. As a-signs cannot be isolated from matter, we point to their resulting effects, which without entering the linguistic level they are expressed in terms of intensity fields: modulations, movements, speeds, rhythms, spasms, etc. They belong to a molecular level where they operate in the pre-subjective world of perceptions, effects, drives, and emotions. A-signs have been introduced as intensities that transform the object beyond meaning, beyond fixed or known cognitive procedures. To that end, from an archive of more than 100 spatial objects by contemporary architects and designers, we have created an effective mechanisms index is created, where each a-sign is now connected with the list of effects it triggers and which thoroughly defines it. And vice versa, the same effect can be triggered by different a-signs, allowing the design object to lie in a perpetual state of becoming. To define spatial objects, A-signs are categorized in terms of their aesthetic power to affect and to be affected on the basis of the general categories of form, structure and surface. Thus, different part's degree of contingency are evaluated and measured and finally, we introduce as material information that is immanent in the spatial object while at the same time they confer no meaning; they only convey some information without semantic content. Through this index, we are able to analyze and direct the final form of the spatial object while at the same time establishing the mechanism to measure its continuous transformation.

Keywords: affective mechanisms index, architectural assemblages, a-signifying signs, cartography, virtual

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Authors: Dhea Kothari

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There is an extensive amount of research that has examined the positive relationship between creativity and hypomania in terms of creative accomplishments, eminence, behaviors, occupations. Previous research had recruited participants based on creative occupations or stages of hypomania or bipolar disorder. This thesis focused on the relationship between hypomania and creative cognitive potential, such as divergent thinking and insight problem-solving. This was examined at an undergraduate educational level by recruiting students majoring in art, majoring in natural sciences (NSCI) and those double majoring in arts and NSCI. Participants were given a modified Alternate Uses Task (AUT) to measure divergent thinking and a set of rebus puzzles to measure insight problem-solving. Both tasks involved a level of overcoming functional fixedness. A negative association was observed between hypomania and originality of responses on the AUT when an object with low functional fixedness was given to all participants. On the other hand, a positive association was found between hypomania and originality of responses on the AUT when an object with high functional fixedness was given to the participants majoring in NSCI. Therefore, the research suggests that an increased ability to overcome functional fixedness might be central to individuals with hypomania and individuals with higher creative cognitive potential.

Keywords: creative cognition, convergent thinking, creativity, divergent thinking, insight, major type, problem-solving

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

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Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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Authors: Pooja Verma, Sumana Ghosh

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There is a growing need for alternative way of power generation worldwide. The reason can be attributed to limited resources of fossil fuels, environmental pollution, increasing cost of conventional fuels, and lower efficiency of conversion of energy in existing systems. In this context, one of the potential alternatives for power generation is wave energy. However, it is difficult to estimate the amount of electrical energy generation in an irregular sea condition by experiment and or analytical methods. Therefore in this work, a numerical wave tank is developed using the computational fluid dynamics software Open FOAM. In this software a specific utility known as waves2Foam utility is being used to carry out the simulation work. The computational domain is a tank of dimension: 5m*1.5m*1m with a floating object of dimension: 0.5m*0.2m*0.2m. Regular waves are generated at the inlet of the wave tank according to Stokes second order theory. The main objective of the present study is to validate the numerical model against existing experimental data. It shows a good matching with the existing experimental data of floater displacement. Later the model is exploited to estimate energy extraction due to the movement of such a point absorber in real sea conditions. Scale down the wave properties like wave height, wave length, etc. are used as input parameters. Seasonal variations are also considered.

Keywords: OpenFOAM, numerical wave tank, regular waves, floating object, point absorber

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Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

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Authors: Wei Chen Chang, Ming Yu Hsiao

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The commodity takes one kind of mark, the designer how to construction and interpretation the user how to use the process and effectively convey message in design education has always been an important issue. Cultural-creative design refers to signifying cultural heritage for product design. In terms of Peirce’s Semiotic Triangle: signifying elements-object-interpretant, signifying elements are the outcomes of design, the object is cultural heritage, and the interpretant is the positioning and description of product design. How to elaborate the positioning, design, and development of a product is a narrative issue of the interpretant, and how to shape the signifying elements of a product by modifying and adapting styles is a rhetoric matter. This study investigated the rhetoric of elements signifying products to develop a rhetoric model with cultural style. Figures of speech are a rhetoric method in narrative. By adapting figures of speech to the interpretant, this study developed the rhetoric context of cultural context by narrative means. In this two-phase study, phase I defines figures of speech and phase II analyzes existing cultural-creative products in terms of figures of speech to develop a rhetoric of style model. We expect it can reference for the future development of Cultural-creative design.

Keywords: cultural-creative design, cultural-creative products, figures of speech, Peirce’s semiotic triangle, rhetoric of style model

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Authors: Jeansou Moun

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This study argues that constructivism and structuralism, which have been the two important schools of mathematical philosophy since the mid-19th century, can and should be synthesized into structure-constructivism. In fact, the philosophy of mathematics is divided into more than ten schools depending on the point of view. However, the biggest trend is Platonism which claims that mathematical objects are "abstract entities" that exists independently of the human mind and material objects. Its opposite is constructivism. According to the latter, mathematical objects are products of the construction of the human mind. However, whether the basis of the construction is a logical device, a symbolic system, or an empirical perception, it is subdivided into logicism, formalism, and intuitionism. However, these three schools themselves are further subdivided into various variants, and among them, structuralism, which emerged in the mid-20th century, is receiving the most attention. On the other hand, structuralism which emphasizes structure instead of individual objects, is divided into non-eliminative structuralism, which supports the a priori of structure, and non-eliminative structuralism, which rejects any abstract entity. In this context, it is believed that the structure itself is not an a priori entity but a result of the construction of the cognitive subject and that no object has ever been given to us in its full meaning from the outset. In other words, concepts are progressively structured through a dialectical cycle between sensory perception, imagination (abstraction), concepts, judgments, and reasoning. Symbols are needed for formal operation. However, without concrete manipulation, the formal operation cannot have any meaning. However, when formal structurization is achieved, the reality (object) itself is also newly structured. This is the "structure-constructivism".

Keywords: philosophy of mathematics, platonism, logicism, formalism, constructivism, structuralism, structure-constructivism

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: Ahmed Fradi

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Nowadays, recent technological advances in the acquisition, modeling, and processing of three-dimensional (3D) objects data lead to the creation of models stored in huge databases, which are used in various domains such as computer vision, augmented reality, game industry, medicine, CAD (Computer-aided design), 3D printing etc. On the other hand, the industry is currently benefiting from powerful modeling tools enabling designers to easily and quickly produce 3D models. The great ease of acquisition and modeling of 3D objects make possible to create large 3D models databases, then, it becomes difficult to navigate them. Therefore, the indexing of 3D objects appears as a necessary and promising solution to manage this type of data, to extract model information, retrieve an existing model or calculate similarity between 3D objects. The objective of the proposed research is to develop a framework allowing easy and fast access to 3D objects in a CAD models database with specific indexing algorithm to find objects similar to a reference model. Our main objectives are to study existing methods of similarity calculation of 3D objects (essentially shape-based methods) by specifying the characteristics of each method as well as the difference between them, and then we will propose a new approach for indexing and comparing 3D models, which is suitable for our case study and which is based on some previously studied methods. Our proposed approach is finally illustrated by an implementation, and evaluated in a professional context.

Keywords: CAD, 3D object retrieval, shape based retrieval, similarity calculation

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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Authors: M. Al-Shamery, R. Young, P. Birch, C. Chatwin

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Computer Generated Holography (CGH) is employed to create digitally defined coherent wavefronts. A CGH can be created by using different techniques such as by using a detour-phase technique or by direct phase modulation to create a kinoform. The detour-phase technique was one of the first techniques that was used to generate holograms digitally. The disadvantage of this technique is that the reconstructed image often has poor quality due to the limited dynamic range it is possible to record using a medium with reasonable spatial resolution.. The kinoform (phase-only hologram) is an alternative technique. In this method, the phase of the original wavefront is recorded but the amplitude is constrained to be constant. The original object does not need to exist physically and so the kinoform can be used to reconstruct an almost arbitrary wavefront. However, the image reconstructed by this technique contains high levels of noise and is not identical to the reference image. To improve the reconstruction quality of the kinoform, iterative techniques such as the Gerchberg-Saxton algorithm (GS) are employed. In this paper the GS algorithm is described for the optimisation of a kinoform used for the reconstruction of a complex wavefront. Iterations of the GS algorithm are applied to determine the phase at a plane (with known amplitude distribution which is often taken as uniform), that satisfies given phase and amplitude constraints in a corresponding Fourier plane. The GS algorithm can be used in this way to enhance the reconstruction quality of the kinoform. Different images are employed as the reference object and their kinoform is synthesised using the GS algorithm. The quality of the reconstructed images is quantified to demonstrate the enhanced reconstruction quality achieved by using this method.

Keywords: computer generated holography, digital holography, Gerchberg-Saxton algorithm, kinoform

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Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

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Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

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Authors: Nur Afiqah Mohd Kamal, Khamarrul Azahari Razak

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The earthquake aftermath has become a major concern, especially in high seismicity region. In Kundasang, Sabah, the earthquake on 5th June 2015 resulted in several catastrophes; landslides, rockfalls, mudflows and major slopes affected regardless of the series of the aftershocks. Certainly, the consequences of earthquake generate and induce the episodic disaster, not only life-threatening but it also affects infrastructure and economic development. Therefore, a need for investigating the change in land use and land cover (LULC) of post-earthquake geohazard is essential for identifying the extent of disastrous effects towards the development in Kundasang. With the advancement of remote sensing technology, post-earthquake geohazards (landslides, mudflows, rockfalls, debris flows) assessment can be evaluated by the employment of object-based image analysis in investigating the LULC change which consists of settlements, public infrastructure and vegetation cover. Therefore, this paper discusses the preliminary results on post-earthquakes geohazards distribution in Kundasang and evaluates the LULC classification effect upon the occurrences of geohazards event. The result of this preliminary analysis will provide an overview to determine the extent of geohazard impact on LULC. This research also provides beneficial input to the local authority in Kundasang about the risk of future structural development on the geohazard area.

Keywords: geohazard, land use land cover, object-based image analysis, remote sensing

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Priyanka Gupta, Bipin Kumar

Abstract:

Recent developments in smart materials motivate researchers to create novel textile products for innovative and functional applications, which have several potential uses beyond the conventional. This study investigates the memory behavior of shape memory filaments integrated into a knitted textile structure. The research advances the knowledge of how these intelligent materials respond within textile structures. This integration may also open new avenues for developing smart fabrics with unique sensing and actuation capabilities. A shape memory filament and polyester yarn were knitted to produce a shape memory knitted fabric (SMF). Thermo-mechanical tensile test was carried out to quantify the memory behavior of SMF under different conditions. The experimental findings demonstrate excellent shape recovery (100%) and shape fixity up to 88% at different strains (20% and 60%) and temperatures (30 ℃ and 50 ℃). Experimental results reveal that memory filament behaves differently in a fabric structure than in its pristine condition at various temperatures and strains. The cycle test of SMF under different thermo-mechanical conditions indicated complete shape recovery with an increase in shape fixity. So, the utterly recoverable textile structure was achieved after a few initial cycles. These intelligent textiles are beneficial for the development of novel, innovative, and functional fabrics like elegant curtains, pressure garments, compression stockings, etc. In addition to fashion and medical uses, this unique feature may also be leveraged to build textile-based sensors and actuators.

Keywords: knitting, memory filament, shape memory, smart textiles, thermo-mechanical cycle

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Hao-Wei Fu, Chung-Feng Kao

Abstract:

In the era of rapid technological advancement, information technology (IT) has become integral to modern life, exerting significant influence across diverse sectors and serving as a catalyst for development in various industries. Within agriculture, the integration of IT offers substantial benefits, notably enhancing operational efficiency. Real-time monitoring systems, for instance, have been widely embraced in agriculture, effectively improving crop management practices. This study specifically addresses the management of rice panicle fertilizer, presenting the development of a web application tailored to handle data associated with rice panicle fertilizer management. Leveraging the normalized difference red edge index, this application optimizes the quantity of rice panicle fertilizer used, providing recommendations to agricultural stakeholders and service providers in the agricultural information sector. The overarching objective is to minimize costs while maximizing yields. Furthermore, a robust database system has been established to store and manage relevant data for future reference in rice cultivation management. Additionally, the study utilizes the Representational State Transfer software architectural style to construct an application programming interface (API), facilitating data creation, retrieval, updating, and deletion for users via the HyperText Transfer Protocol methods. Future plans involve integrating this API with third-party services to incorporate it into larger frameworks, thus catering to the diverse requirements of various third-party services.

Keywords: application programming interface, HyperText Transfer Protocol, nitrogen fertilizer intelligent management, web-based application

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Authors: Marco Castagna

Abstract:

Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.Proposed paper is aimed to inquire about the relation between text and reader, focusing on the concept of ‘attestation’. Indeed, despite being widely accepted in semiotic research, even today the concept of text remains uncertainly defined. So, it seems to be undeniable that what is called ‘text’ offers an image of internal cohesion and coherence, that makes it possible to analyze it as an object. Nevertheless, this same object remains problematic when it is pragmatically activated by the act of reading. In fact, as for the T.A.R:D.I.S., that is the unique space-temporal vehicle used by the well-known BBC character Doctor Who in his adventures, every text appears to its own readers not only “bigger inside than outside”, but also offering spaces that change according to the different traveller standing in it. In a few words, as everyone knows, this singular condition raises the questions about the gnosiological relation between text and reader. How can a text be considered the ‘same’, even if it can be read in different ways by different subjects? How can readers can be previously provided with knowledge required for ‘understanding’ a text, but at the same time learning something more from it? In order to explain this singular condition it seems useful to start thinking about text as a device more than an object. In other words, this unique status is more clearly understandable when ‘text’ ceases to be considered as a box designed to move meaning from a sender to a recipient (marking the semiotic priority of the “code”) and it starts to be recognized as performative meaning hypothesis, that is discursively configured by one or more forms and empirically perceivable by means of one or more substances. Thus, a text appears as a “semantic hanger”, potentially offered to the “unending deferral of interpretant", and from time to time fixed as “instance of Discourse”. In this perspective, every reading can be considered as an answer to the continuous request for confirming or denying the meaning configuration (the meaning hypothesis) expressed by text. Finally, ‘attestation’ is exactly what regulates this dynamic of request and answer, through which the reader is able to confirm his previous hypothesis on reality or maybe acquire some new ones.

Keywords: attestation, meaning, reader, text

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Authors: Michael Smalenberger

Abstract:

Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

Abstract:

A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

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Authors: Pedro Mario Gonzalez Jimenez

Abstract:

The novelties introduced by the last Notice on agreements of minor importance tighten the application of the ‘De minimis’ safe harbour in the European Union. However, the undetermined legal concept of effect on trade between the Member States becomes importance at the same time. Therefore, the current analysis that the jurist should carry out in the European Union to determine if an agreement appreciably restrict competition under Article 101 of the Treaty on the Functioning of the European Union is double. Hence, it is necessary to know how to balance the significance in competition and the significance in effect on trade between the Member States. It is a crucial issue due to the negative delimitation of restriction of competition affects the positive one. The methodology of this research is rather simple. Beginning with a historical approach to the ‘De Minimis Rule’, their main problems and uncertainties will be found. So, after the analysis of normative documents and the jurisprudence of the Court of Justice of the European Union some proposals of ‘Lege ferenda’ will be offered. These proposals try to overcome the contradictions and questions that currently exist in the European Union as a consequence of the current legal regime of agreements of minor importance. The main findings of this research are the followings: Firstly, the effect on trade is another way to analyze the importance of an agreement different from the ‘De minimis rule’. In point of fact, this concept is singularly adapted to go through agreements that have as object the prevention, restriction or distortion of competition, as it is observed in the most famous European Union case-law. Thanks to the effect on trade, as long as the proper requirements are met there is no a restriction of competition under article 101 of the Treaty on the Functioning of the European Union, even if the agreement had an anti-competitive object. These requirements are an aggregate market share lower than 5% on any of the relevant markets affected by the agreement and turnover lower than 40 million of Euros. Secondly, as the Notice itself says ‘it is also intended to give guidance to the courts and competition authorities of the Member States in their application of Article 101 of the Treaty, but it has no binding force for them’. This reality makes possible the existence of different statements among the different Member States and a confusing perception of what a restriction of competition is. Ultimately, damage on trade between the Member States could be observed for this reason. The main conclusion is that the significant effect on trade between Member States is irrelevant in agreements that restrict competition because of their effects but crucial in agreements that restrict competition because of their object. Thus, the Member States should propose the incorporation of a similar concept in their legal orders in order to apply the content of the Notice. Otherwise, the significance of the restrictive agreement on competition would not be properly assessed.

Keywords: De minimis rule, effect on trade, minor importance agreements, safe harbour

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Authors: Ekpeti Bukola Grace, Mahmoudi Sabar Esmail, Chaer Issa

Abstract:

Global energy consumption has been increasing steadily over the last half - century, and this trend is projected to continue. As energy demand rises in many countries throughout the world due to population growth, natural ventilation in buildings has been identified as a viable option for lowering these demands, saving costs, and also lowering CO2 emissions. However, natural ventilation is driven by forces that are generally unpredictable in nature thus, it is important to manage the resulting airflow in order to maintain pleasant indoor conditions, making it a complex system that necessitates specific control approaches. The effective application of fuzzy logic technique amidst other intelligent systems is one of the best ways to bridge this gap, as its control dynamics relates more to human reasoning and linguistic descriptions. This article reviewed existing literature and presented practical solutions by applying fuzzy logic control with optimized techniques, selected input parameters, and expert rules to design a more effective control system. The control monitors used indoor temperature, outdoor temperature, carbon-dioxide levels, wind velocity, and rain as input variables to the system, while the output variable remains the control of window opening. This is achieved through the use of fuzzy logic control tool box in MATLAB and running simulations on SIMULINK to validate the effectiveness of the proposed system. Comparison analysis model via simulation is carried out, and with the data obtained, an improvement in control actions and energy savings was recorded.

Keywords: fuzzy logic, intelligent control systems, natural ventilation, optimization

Procedia PDF Downloads 113