Search results for: intelligent node

Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

Procedia PDF Downloads 137

Authors: Fatema Akram, Mohammad Golam Rasul, Mohammad Masud Kamal Khan, Md. Sharif Imam Ibne Amir

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A variety of routing techniques are available to develop surface runoff hydrographs from rainfall. The selection of runoff routing method is very vital as it is directly related to the type of watershed and the required degree of accuracy. There are different modelling softwares available to explore the rainfall-runoff process in urban areas. XPSTORM, a link-node based, integrated storm-water modelling software, has been used in this study for developing surface runoff hydrograph for a Golf course area located in Rockhampton in Central Queensland in Australia. Four commonly used methods, namely SWMM runoff, Kinematic wave, Laurenson, and Time-Area are employed to generate runoff hydrograph for design storm of this study area. In runoff mode of XPSTORM, the rainfall, infiltration, evaporation and depression storage for sub-catchments were simulated and the runoff from the sub-catchment to collection node was calculated. The simulation results are presented, discussed and compared. The total surface runoff generated by SWMM runoff, Kinematic wave and Time-Area methods are found to be reasonably close, which indicates any of these methods can be used for developing runoff hydrograph of the study area. Laurenson method produces a comparatively less amount of surface runoff, however, it creates highest peak of surface runoff among all which may be suitable for hilly region. Although the Laurenson hydrograph technique is widely acceptable surface runoff routing technique in Queensland (Australia), extensive investigation is recommended with detailed topographic and hydrologic data in order to assess its suitability for use in the case study area.

Keywords: ARI, design storm, IFD, rainfall temporal pattern, routing techniques, surface runoff, XPSTORM

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Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 112

Authors: Frodouard Minani

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Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

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Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Meltem Eryılmaz

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With the emergence of the COVID-19 infection outbreak, the socio-cultural, political, economic, educational systems dynamics of the world have gone through a major change, especially in the educational field, specifically dentistry preclinical education, where the students must have a certain amount of real-time experience in endodontics and other various procedures. The totality of the digital and physical elements that make our five sense organs feel as if we really exist in a virtual world is called virtual reality. Virtual reality, which is very popular today, has started to be used in education. With the inclusion of developing technology in education and training environments, virtual learning platforms have been designed to enrich students' learning experiences. The field of health is also affected by these current developments, and the number of virtual reality applications developed for students studying dentistry is increasing day by day. The most widely used tools of this technology are virtual reality glasses. With virtual reality glasses, you can look any way you want in a world designed in 3D and navigate as you wish. With this project, solutions that will respond to different types of dental practices of students who study dentistry with virtual reality applications are produced. With this application, students who cannot find the opportunity to work with patients in distance education or who want to improve themselves at home have unlimited trial opportunities. Unity 2021, Visual Studio 2019, Cardboard SDK are used in the study.

Keywords: dentistry, intelligent tutoring system, virtual reality, online learning, COVID-19

Procedia PDF Downloads 181

Authors: Jesus Carretero, Mario Vasile, Guillermo Izquierdo, Javier Garcia-Blas

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Currently, there is a so called ‘identity crisis’ in cybersecurity caused by the substantial security, privacy and usability shortcomings encountered in existing systems for identity management. Federated Identity Management (FIM) could be solution for this crisis, as it is a method that facilitates management of identity processes and policies among collaborating entities without enforcing a global consistency, that is difficult to achieve when there are ID legacy systems. To cope with this problem, the Connecting Europe Facility (CEF) initiative proposed in 2014 a federated solution in anticipation of the adoption of the Regulation (EU) N°910/2014, the so-called eIDAS Regulation. At present, a network of eIDAS Nodes is being deployed at European level to allow that every citizen recognized by a member state is to be recognized within the trust network at European level, enabling the consumption of services in other member states that, until now were not allowed, or whose concession was tedious. This is a very ambitious approach, since it tends to enable cross-border authentication of Member States citizens without the need to unify the authentication method (eID Scheme) of the member state in question. However, this federation is currently managed by member states and it is initially applied only to citizens and public organizations. The goal of this paper is to present the results of a European Project, named eID@Cloud, that focuses on the integration of eID in 5 cloud platforms belonging to authentication service providers of different EU Member States to act as Service Providers (SP) for private entities. We propose an initiative based on a private eID Scheme both for natural and legal persons. The methodology followed in the eID@Cloud project is that each Identity Provider (IdP) is subscribed to an eIDAS Node Connector, requesting for authentication, that is subscribed to an eIDAS Node Proxy Service, issuing authentication assertions. To cope with high loads, load balancing is supported in the eIDAS Node. The eID@Cloud project is still going on, but we already have some important outcomes. First, we have deployed the federation identity nodes and tested it from the security and performance point of view. The pilot prototype has shown the feasibility of deploying this kind of systems, ensuring good performance due to the replication of the eIDAS nodes and the load balance mechanism. Second, our solution avoids the propagation of identity data out of the native domain of the user or entity being identified, which avoids problems well known in cybersecurity due to network interception, man in the middle attack, etc. Last, but not least, this system allows to connect any country or collectivity easily, providing incremental development of the network and avoiding difficult political negotiations to agree on a single authentication format (which would be a major stopper).

Keywords: cybersecurity, identity federation, trust, user authentication

Procedia PDF Downloads 145

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Jelili Kunle Adedeji, Toeb Akorede Akinbola

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The problem of vehicle mishap as a result of miscalculation, recklessness, or malfunction of some part in a vehicle is acknowledged to be a global issue. In most of the cases, it results into death or life injuries, all over the world; the issue becomes a nightmare to the stakeholders on how to curb mishaps on our roads due to these endemic factors. Hence this research typically examined the design of a device, specifically for learners that can lead to a society of intelligent vehicles (traffic) without withdrawing the driving authority from them, unlike pre-existing systems. Though ILASS shears a lot of principle with existing advance drivers assistance systems, yet there are two fundamental differences between ILASS system and existing systems. Firstly ILASS is meant to accept continuous input from the throttle at all time such that the devices will not constraint the driving process unnecessarily and ensure a change of speed at any point in time. Secondly, it made use of a variable threshold distance between the host vehicle and front vehicle which can be set by the host driver under the constraint of road maintenance agency, who communicates the minimum possible threshold for a different lane to the host vehicle. The results obtained from the simulation of the ILASS system concluded that ILASS is a good solution to road accidents, particularly road accident which occurs as a result of driving at high speed.

Keywords: front-vehicle, host-speed, threshold-distance, ILASS

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: H. Zormati, J. Chebil, J. Bel Hadj Taher

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The goal of this paper is to present an addressing scheme that allows for assigning a unique IPv6 address to each node in the Internet of Things (IoT) network. This scheme guarantees uniqueness by extracting the clock skew of each communication device and converting it into an IPv6 address. Simulation analysis confirms that the presented scheme provides reductions in terms of energy consumption, communication overhead and response time as compared to four studied addressing schemes Strong DAD, LEADS, SIPA and CLOSA.

Keywords: addressing, IoT, IPv6, network, nodes

Procedia PDF Downloads 267

Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

Procedia PDF Downloads 516

Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

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This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

Procedia PDF Downloads 317

Authors: Houman Tamaddon, Mehrdad Behnia, Masud Behnia

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An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.

Keywords: blood flow, morphometric data, vascular tree, Strahler ordering system

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: Aydin M. Torkabadi, Ehsan Pourjavad

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A decade after the introduction of Lean in Saskatchewan’s public healthcare system, its effectiveness remains a controversial subject among health researchers, workers, managers, and politicians. Therefore, developing a framework to quantitatively assess the Lean achievements is significant. This study investigates the success of initiatives across Saskatchewan health regions by recognizing the Lean healthcare criteria, measuring the success levels, comparing the regions, and identifying the areas for improvements. This study proposes an integrated intelligent computing approach by applying Fuzzy Inference System (FIS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). FIS is used as an efficient approach to assess the Lean healthcare criteria, and TOPSIS is applied for ranking the values in regards to the level of leanness. Due to the innate uncertainty in decision maker judgments on criteria, principals of the fuzzy theory are applied. Finally, FIS-TOPSIS was established as an efficient technique in determining the lean merit in healthcare systems.

Keywords: lean healthcare, intelligent computing, fuzzy inference system, healthcare evaluation, technique for order of preference by similarity to ideal solution, multi-criteria decision making, MCDM

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Authors: Sherif D. El Wakil, John Rice

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The aim of the current work was to employ the finite element method to model a slab, with a small hole across its width, undergoing plastic plane strain deformation. The computational model had, however, to be validated by comparing its results with those obtained experimentally. Since they were in good agreement, the finite element method can therefore be considered a reliable tool that can help gain better understanding of the mechanism of ductile failure in structural members having stress raisers. The finite element software used was ANSYS, and the PLANE183 element was utilized. It is a higher order 2-D, 8-node or 6-node element with quadratic displacement behavior. A bilinear stress-strain relationship was used to define the material properties, with constants similar to those of the material used in the experimental study. The model was run for several tensile loads in order to observe the progression of the plastic deformation region, and the stress concentration factor was determined in each case. The experimental study involved employing the visioplasticity technique, where a circular mesh (each circle was 0.5 mm in diameter, with 0.05 mm line thickness) was initially printed on the side of an aluminum slab having a small hole across its width. Tensile loading was then applied to produce a small increment of plastic deformation. Circles in the plastic region became ellipses, where the directions of the principal strains and stresses coincided with the major and minor axes of the ellipses. Next, we were able to determine the directions of the maximum and minimum shear stresses at the center of each ellipse, and the slip-line field was then constructed. We were then able to determine the stress at any point in the plastic deformation zone, and hence the stress concentration factor. The experimental results were found to be in good agreement with the analytical ones.

Keywords: finite element method to model a slab, slab undergoing plastic deformation, stress distribution around a circular hole, visioplasticity

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

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Authors: Ziani Zakarya, Mahdad Moustafa Yassine

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Greenhouse farming has greatly contributed to the development of modern agriculture by optimizing crops, especially market gardening, ornamental horticulture, and recently, fruit species ... Greenhouse cultivation has enabled farmers to produce fruits and vegetables out of season while guaranteeing them a good production, and therefore a considerable gain throughout the year. However, this mode of production has shown its limits, especially in extreme conditions, such as the continental steppe climate and the Saharan climate, which are characterized by significant thermal amplitudes and strong winds, making it impossible to use conventional greenhouses for several months, of the year. In Algeria and precisely in the highlands, the use of greenhouses by farmers is very rare or occasional, especially in spring, because the limiting factors mentioned above are frequent there, causing significant damage to the plant product and to the environment. infrastructure. The same observation is observed in the Saharan regions but with less frequencies. Certainly, the use of controlled multi-chapel greenhouses would solve the problem, but at what cost? These hi-tech infrastructures are very expensive to purchase but also to maintain, so few farmers have the financial means to obtain them. In addition, the existence of intelligent and less expensive polymer films, whose properties could control greenhouse production parameters, in particular, the temperature parameter, maybe a judicious solution for the development of new generations of greenhouses that can be used in extreme conditions and normal.

Keywords: greenhouse, polymer film, modern agriculture, optimizing crops

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Authors: Nobuyuki Takemoto, Ai Koyanagi, Masanori Yasuda, Hiroshi Yamamoto

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Background: Fluorescence imaging (FI) is one of the methods to identify sentinel lymph nodes (SLNs). However, the procedure is technically complicated and requires procedural skills, as SLN biopsy must be conducted in dim light conditions. As an improved version of this method, we introduced a combined method (Combined mixed dye and fluorescence; CMF) consisting of indigo carmine blue dye and FI. The direct visualization of SLNs under shadowless surgical light conditions is facilitated by the addition of the blue dye. We compared the SLN detection rates of CMF with that of the indocyanine green (ICG) dye method (ICG-D). Methods: A total of 202 patients with stage ≤ IIA breast cancer who underwent breast conservative therapy with separate incision from January 2004 to February 2017 were reviewed. Details of the two methods are as follows: (1) ICG-D: 2ml of ICG (10mg) was used and the green-stained SLNs were resected via a 3-4cm axillary incision; (2) CMF: A combination of 1ml of ICG (5mg) and 1-3ml of indigo carmine (4-12mg) was used. Using Photodynamic Eye (PDE), a 1.5-2 cm incision was made near the point of disappearance of the fluorescence and SLNs with intermediate color of blue and green were resected. Results: There were 92 ICG-D and 110 CMF cases. CMF resulted in a significantly higher detection rate than ICG-D (96.4% vs. 83.7%; p=0.003). This difference was particularly notable in those aged ≥ 60 years (98.3% vs. 74.3%) and individuals with BMI ≥ 25kg/m2 (90.3% vs. 58.3%). Conclusion: CMF is an effective method to identify SLNs which is safe, efficient, and cost-effective. Furthermore, radiation exposure can be avoided, and it can be performed in institutes without nuclear medicine facilities. CMF achieves a high SLN identification rate, and most of this procedure is feasible under shadowless surgical light conditions. CMF can reliably perform SLN biopsy even in those aged ≥ 60 years and individuals with BMI ≥ 25 kg/m2.

Keywords: sentinel lymph node biopsy, identification rate, indocyanine green (ICG), indigocarmine, fluorescence

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Authors: Keunhong Chae, Seokho Yoon

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Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

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Authors: Festus Okotie

Abstract:

Nigeria is the giant of Africa with great and diverse transport potentials yet to be fully tapped into and explored.it is the most populated nation in Africa with nearly 200 million people, the sixth largest oil producer overall and largest oil producer in Africa with proven oil and gas reserves of 37 billion barrels and 192 trillion cubic feet, over 300 square kilometers of arable land and significant deposits of largely untapped minerals. A world bank indicator which measures trading across border ranked Nigeria at 183 out of 185 countries in 2017 and although different governments in the past made efforts through different interventions such as 2007 ports reforms led by Ngozi Okonjo-Iweala, a former minister of Finance and world bank managing director also attempted to resolve some of the challenges such as infrastructure shortcomings, policy and regulatory inconsistencies, overlapping functions and duplicated roles among the different MDA’S. It is one of the fundamental structures smart nations and cities are using to improve the living conditions of its citizens and achieving sustainability. Examples of some of its benefits includes tracking high pedestrian areas, traffic patterns, railway stations, planning and scheduling bus times, it also enhances interoperability, creates alerts of transport situation and has swift capacity to share information among the different platforms and transport modes. It also offers a comprehensive approach to risk management, putting emergency procedures and response capabilities in place, identifying dangers, including vandalism or violence, fare evasion, and medical emergencies. The Nigerian transport system is urgently in need of modern infrastructures such as ITS. Smart city transport technology helps cities to function productively, while improving services for businesses and lives of is citizens. This technology has the ability to improve travel across traditional modes of transport, such as cars and buses, with immediate benefits for city dwellers and also helps in managing transport systems such as dangerous weather conditions, heavy traffic, and unsafe speeds which can result in accidents and loss of lives. Intelligent transportation systems help in traffic control such as permitting traffic lights to react to changing traffic patterns, instead of working on a fixed schedule in traffic. Intelligent transportation systems is very important in Nigeria’s transportation sector and so would require trained personnel to drive its efficiency to greater height because the purpose of introducing it is to add value and at the same time reduce motor vehicle miles and traffic congestion which is a major challenge around Tin can island and Apapa Port, a major transportation hub in Nigeria. The need for the federal government, state governments, houses of assembly to organise a national transportation workshop to begin the process of addressing the challenges in our nation’s transport sector is highly expedient and so bills that will facilitate the implementation of policies to promote intelligent transportation systems needs to be sponsored because of its potentials to create thousands of jobs for our citizens, provide farmers with better access to cities and a better living condition for Nigerians.

Keywords: intelligent, transport, system, Nigeria

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

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Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

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Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

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Authors: Oyekan Kolawole Jamiu

Abstract:

The right to life is a moral principle based on the belief that a human being has the right to life and, in particular, should not be unjustly killed by another human being. However, the most worrisome security challenge in Nigeria which has cut short the lives of innocent Nigerians is the activities of the dreaded terrorist group known as Boko Haram (which means Western Education is a sin). Between 2004 till date, over 15000 people have been gruesomely murdered by this terrorist group. However, despite the facts that suspected terrorists are arrested and paraded almost on a daily basis, cases of terrorism in our courts in Nigeria today have not been expeditiously dealt with by the judiciary. This paper examines the concept of right to life. The right to life is an inherent right for each and every person. From his or her birth; the individual is considered a living being that must be protected. The right to life connotes also right to live and grow in a healthy environment where there is appropriate health care, qualitative education and adequate security of lives and property. The paper also examines the fight against terrorism and the duty of the government to protect right to life of every individual even in the midst of the fight against terrorism. The paper further reviews the Terrorism Act 2011(as amended) and the clogs in the wheel of prosecution of suspected terrorists. The paper concludes that since terrorism is a new security challenge, to prevent conflict of interest, only one security agency should be trained and saddled with the responsibility of prosecuting suspected terrorist, Law should be enacted to compel intelligent gathering and sharing of information among security agencies and in addition, a special court should be established to deal expeditiously with cases of terrorism in Nigeria.

Keywords: terrorism, intelligent gathering, right to life, prosecution

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