Search results for: Smart/Adaptive Antenna

Authors: Andrey A. Chernousov, Ben Y. B. Chan

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The thermal behavior of a large-scale, phase change material (PCM) enhanced building envelope system was studied in regard to the need for pre-fabricated construction in subtropical regions. The proposed large-scale envelope consists of a reinforced aluminum skin, insulation core, phase change material and reinforced gypsum board. The PCM impact on an energy efficiency of an enveloped room was resolved by validation of the EnergyPlus numerical scheme and optimization of a smart material location in the core. The PCM location was optimized by a minimization method of a cooling energy demand. It has been shown that there is good agreement between the test and simulation results. The optimal location of the PCM layer in Hong Kong summer conditions has been then recomputed for core thicknesses of 40, 60 and 80 mm. A non-dimensional value of the optimal PCM location was obtained to be same for all the studied cases and the considered external and internal conditions.

Keywords: Thermal performance, phase change material, energy efficiency, PCM optimization.

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Authors: Li Shoutao, Gordon Lee

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Evolutionary robotics is concerned with the design of intelligent systems with life-like properties by means of simulated evolution. Approaches in evolutionary robotics can be categorized according to the control structures that represent the behavior and the parameters of the controller that undergo adaptation. The basic idea is to automatically synthesize behaviors that enable the robot to perform useful tasks in complex environments. The evolutionary algorithm searches through the space of parameterized controllers that map sensory perceptions to control actions, thus realizing a specific robotic behavior. Further, the evolutionary algorithm maintains and improves a population of candidate behaviors by means of selection, recombination and mutation. A fitness function evaluates the performance of the resulting behavior according to the robot-s task or mission. In this paper, the focus is in the use of genetic algorithms to solve a multi-objective optimization problem representing robot behaviors; in particular, the A-Compander Law is employed in selecting the weight of each objective during the optimization process. Results using an adaptive fitness function show that this approach can efficiently react to complex tasks under variable environments.

Keywords: adaptive fuzzy neural inference, evolutionary tuning

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Authors: Mustafa Sahin, İlkay Yavrucuk

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This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: Adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control.

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Authors: Rawya Rizk, Rehab Abdel-Kader, Rabab Ramadan

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Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.

Keywords: Early packet discard, Fuzzy logic, packet dropping policies, quality-of-service (QoS), TCP over ATM

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Authors: Md. Asraful Haque, Babbar Imam

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Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.

Keywords: Authentication, Graphical Password, Text Password, Information Security, Shoulder-surfing.

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Authors: Hong Son Hoang, Remy Baraille

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This paper addresses the problem of how one can improve the performance of a non-optimal filter. First the theoretical question on dynamical representation for a given time correlated random process is studied. It will be demonstrated that for a wide class of random processes, having a canonical form, there exists a dynamical system equivalent in the sense that its output has the same covariance function. It is shown that the dynamical approach is more effective for simulating and estimating a Markov and non- Markovian random processes, computationally is less demanding, especially with increasing of the dimension of simulated processes. Numerical examples and estimation problems in low dimensional systems are given to illustrate the advantages of the approach. A very useful application of the proposed approach is shown for the problem of state estimation in very high dimensional systems. Here a modified filter for data assimilation in an oceanic numerical model is presented which is proved to be very efficient due to introducing a simple Markovian structure for the output prediction error process and adaptive tuning some parameters of the Markov equation.

Keywords: Statistical simulation, canonical form, dynamical system, Markov and non-Markovian processes, data assimilation.

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Authors: Kazumoto Tanaka, Takayuki Fujino

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Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: Therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image.

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Authors: Ammar Elyas babiker, M.Nordin B. Zakaria, Hassan Yosif, Samir B. Ibrahim

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Variable channel conditions in underwater networks, and variable distances between sensors due to water current, leads to variable bit error rate (BER). This variability in BER has great effects on energy efficiency of error correction techniques used. In this paper an efficient energy adaptive hybrid error correction technique (AHECT) is proposed. AHECT adaptively changes error technique from pure retransmission (ARQ) in a low BER case to a hybrid technique with variable encoding rates (ARQ & FEC) in a high BER cases. An adaptation algorithm depends on a precalculated packet acceptance rate (PAR) look-up table, current BER, packet size and error correction technique used is proposed. Based on this adaptation algorithm a periodically 3-bit feedback is added to the acknowledgment packet to state which error correction technique is suitable for the current channel conditions and distance. Comparative studies were done between this technique and other techniques, and the results show that AHECT is more energy efficient and has high probability of success than all those techniques.

Keywords: Underwater communication, wireless sensornetworks, error correction technique, energy efficiency

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: Automobile suspension, MATLAB, control system, PID, PSO.

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Authors: S. Sowmyayani, P. Arockia Jansi Rani

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This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.

Keywords: Block Distortion Measure, Block Matching Algorithms, H.264/AVC, Motion estimation, Search patterns, Shot cut detection.

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Authors: Abdullah A. Al Orainy

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Small cell backhaul solutions need to be cost-effective, scalable, and easy to install. This paper presents an overview of small cell backhaul technologies. Wireless solutions including TV white space, satellite, sub-6 GHz radio wave, microwave and mmWave with their backhaul characteristics are discussed. Recent research on issues like beamforming, backhaul architecture, precoding and large antenna arrays, and energy efficiency for dense small cell backhaul with mmWave communications is reviewed. Recent trials of 5G technologies are summarized.

Keywords: Backhaul, Small Cells, Wireless, 5G.

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Authors: S. Areerachakul

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Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Melvin A. Ballera

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Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: Youcef Bekakra, Djilani Ben attous

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In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.

Keywords: Induction motor drive, field oriented control, model reference adaptive system (MRAS), particle swarm optimization (PSO).

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30d B SNR as a reference for voice activity.

Keywords: Atomic Decomposition, Gabor, Gammatone, Matching Pursuit, Voice Activity Detection.

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Authors: Kaznah Alshammari, Thomas Beach, Yacine Rezgui

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Technological advances in the construction sector are helping to make smart cities a reality by means of Cyber-Physical Systems (CPS). CPS integrate information and the physical world through the use of Information Communication Technologies (ICT). An increasingly common goal in the built environment is to integrate Building Information Models (BIM) with Internet of Things (IoT) and sensor technologies using CPS. Future advances could see the adoption of digital twins, creating new opportunities for CPS using monitoring, simulation and optimisation technologies. However, researchers often fail to fully consider the security implications. To date, it is not widely possible to assimilate BIM data and cybersecurity concepts and, therefore, security has thus far been overlooked. This paper reviews the empirical literature concerning IoT applications in the built environment and discusses real-world applications of the IoT intended to enhance construction practices, people’s lives and bolster cybersecurity. Specifically, this research addresses two research questions: (a) How suitable are the current IoT and CPS security stacks to address the cybersecurity threats facing digital twins in the context of smart buildings and districts? and (b) What are the current obstacles to tackling cybersecurity threats to the built environment CPS? To answer these questions, this paper reviews the current state-of-the-art research concerning digital twins in the built environment, the IoT, BIM, urban cities and cybersecurity. The results of the findings of this study confirmed the importance of using digital twins in both IoT and BIM. Also, eight reference zones across Europe have gained special recognition for their contributions to the advancement of IoT science. Therefore, this paper evaluates the use of digital twins in CPS to arrive at recommendations for expanding BIM specifications to facilitate IoT compliance, bolster cybersecurity and integrate digital twin and city standards in the smart cities of the future.

Keywords: BIM, cybersecurity, digital twins, IoT, urban cities.

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Authors: T. S. Myers, J. Trevathan

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Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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Authors: Mohamed K. Watfa

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Like any sentient organism, a smart environment relies first and foremost on sensory data captured from the real world. The sensory data come from sensor nodes of different modalities deployed on different locations forming a Wireless Sensor Network (WSN). Embedding smart sensors in humans has been a research challenge due to the limitations imposed by these sensors from computational capabilities to limited power. In this paper, we first propose a practical WSN application that will enable blind people to see what their neighboring partners can see. The challenge is that the actual mapping between the input images to brain pattern is too complex and not well understood. We also study the connectivity problem in 3D/2D wireless sensor networks and propose distributed efficient algorithms to accomplish the required connectivity of the system. We provide a new connectivity algorithm CDCA to connect disconnected parts of a network using cooperative diversity. Through simulations, we analyze the connectivity gains and energy savings provided by this novel form of cooperative diversity in WSNs.

Keywords: Wireless Sensor Networks, Pervasive Computing, Eye Vision Application, 3D Connectivity, Clusters, Energy Efficient, Cooperative diversity.

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

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Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: Kjersti Engan, Thor Ole Gulsrud, Karl Fredrik Fretheim, Barbro Furebotten Iversen, Liv Eriksen

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Clusters of microcalcifications in mammograms are an important sign of breast cancer. This paper presents a complete Computer Aided Detection (CAD) scheme for automatic detection of clustered microcalcifications in digital mammograms. The proposed system, MammoScan μCaD, consists of three main steps. Firstly all potential microcalcifications are detected using a a method for feature extraction, VarMet, and adaptive thresholding. This will also give a number of false detections. The goal of the second step, Classifier level 1, is to remove everything but microcalcifications. The last step, Classifier level 2, uses learned dictionaries and sparse representations as a texture classification technique to distinguish single, benign microcalcifications from clustered microcalcifications, in addition to remove some remaining false detections. The system is trained and tested on true digital data from Stavanger University Hospital, and the results are evaluated by radiologists. The overall results are promising, with a sensitivity > 90 % and a low false detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).

Keywords: mammogram, microcalcifications, detection, CAD, MammoScan μCaD, VarMet, dictionary learning, texture, FTCM, classification, adaptive thresholding

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Authors: Ahmed Al-Adaileh, Souheil Khaddaj

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Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.

Keywords: Smart energy management systems, internet of things, wireless mesh networks, microservices, cloud computing, big data.

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Authors: Nan-Chyuan Tsai, Din-Chang Chen, Rong-Mao Lee, Bai-Lu Wang

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This paper presents how the real-time chatter prevention can be realized by feedback of acoustic cutting signal, and the efficacy of the proposed adaptive spindle speed tuning algorithm is verified by intensive experimental simulations. A pair of microphones, perpendicular to each other, is used to acquire the acoustic cutting signal resulting from milling chatter. A real-time feedback control loop is constructed for spindle speed compensation so that the milling process can be ensured to be within the stability zone of stability lobe diagram. Acoustic Chatter Signal Index (ACSI) and Spindle Speed Compensation Strategy (SSCS) are proposed to quantify the acoustic signal and actively tune the spindle speed respectively. By converting the acoustic feedback signal into ACSI, an appropriate Spindle Speed Compensation Rate (SSCR) can be determined by SSCS based on real-time chatter level or ACSI. Accordingly, the compensation command, referred to as Added-On Voltage (AOV), is applied to increase/decrease the spindle motor speed. By inspection on the precision and quality of the workpiece surface after milling, the efficacy of the real-time chatter prevention strategy via acoustic signal feedback is further assured.

Keywords: Chatter compensation, Stability lobes, Non-invasivemeasurement.

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Authors: P. V. Pramila, V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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Authors: H. Bonakdari, I. Ebtehaj

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The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: Adaptive neuro-fuzzy inference system, ANFIS, artificial neural network, ANN, bridge pier, scour depth, nonlinear regression, NLR.

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: Air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF.

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Authors: M. Ramadan, B. Salah

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This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: Lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping.

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Authors: A. Hol

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Electronic mediums such as websites, feeds, blogs and social media sites are on a daily basis influencing our decision making, are improving our productivity and are shaping futures of many consumers and service/product providers. This research identifies that both customers and business providers heavily rely on smart phone applications. Based on this, mobile applications available on iTunes store were studied. It was identified that fruit and vegetable related applications used by consumers can broadly be categorized into purchase applications, diaries, tracking health applications, trip farm location and cooking applications. On the other hand, applications used by farmers can broadly be classified as: weather tracking, pests / fertilizer applications and general social media applications such as Facebook. To blur this farmer-consumer application divide, our research utilizes Context Specific eTransformation Framework and based on it identifies characteristic future consumer-farmer applications will need to have so that the current divide can be narrowed and consequently better farmerconsumer supply chain link established.

Keywords: Smart Phone Applications, SME, Farmers, Consumer, Fruit and Vegetable, Technology, Business Innovation.

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Authors: Darshana Thomas, Edward Wilkie, James Irvine

Abstract:

The Internet of things (IoT) is currently a highly researched topic, especially within the context of the smart home. These are small sensors that are capable of gathering data and transmitting it to a server. The majority of smart home products use protocols such as ZigBee or Bluetooth Low Energy (BLE). As these small sensors are increasing in number, the need to implement these with much more capable and ubiquitous transmission technology is necessary. The high power consumption is the reason that holds these small sensors back from using other protocols such as the most ubiquitous form of communication, WiFi. Comparing the power consumption of existing transmission technologies to one with WiFi inbuilt, would provide a better understanding for choosing between these technologies. We have developed a small IoT device with WiFi capability and proven that it is much more efficient than the first protocol, 433 MHz. We extend our work in this paper and compare WiFi power consumption with the other most widely used protocol BLE. The experimental results in this paper would conclude whether the developed prototype is capable in terms of power consumption to replace the existing protocol BLE with WiFi.

Keywords: Bluetooth, internet of things, power consumption, WiFi.

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Authors: Joseph V. M. Halim, Hesham El-Badawy, Hadia M. El-Hennawy

Abstract:

In this paper, an adaptive polarized Multiple-Input Multiple-Output (MIMO) Multicarrier Spread Spectrum Code Division Multiple Access (MC-SS-CDMA) system is designed for downlink mobile communications. The proposed system will be examined in Frequency Division Duplex (FDD) mode for both macro urban and suburban environments. For the same transmission bandwidth, a performance comparison between both nonoverlapped and orthogonal Frequency Division Multiplexing (FDM) schemes will be presented. Also, the proposed system will be compared with both the closed loop vertical MIMO MC-SS-CDMA system and the synchronous vertical STBC-MIMO MC-SS-CDMA system. As will be shown, the proposed system introduces a significant performance gain as well as reducing the spatial dimensions of the MIMO system and simplifying the receiver implementation. The effect of the polarization diversity characteristics on the BER performance will be discussed. Also, the impact of excluding the cross-polarization MCSS- CDMA blocks in the base station will be investigated. In addition, the system performance will be evaluated under different Feedback Information (FBI) rates for slowly-varying channels. Finally, a performance comparison for vehicular and pedestrian environments will be presented

Keywords: Closed loop technique, MC-SS-CDMA, Polarized MIMO systems, Transmit diversity.

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Authors: Zongjie Du, Shulin Sui, Panpan Xu

Abstract:

Energy consumption of a hotel can be a hot topic in smart city; it is difficult to evaluate the contribution of impact factors to energy consumption of a hotel. Therefore, grasping the key impact factors has great effect on the energy saving management of a hotel. Based on the SPIRTPAT model, we establish the identity with the impact factors of occupancy rate, unit area of revenue, temperature factor, unit revenue of energy consumption. In this paper, we use the LMDI (Logarithmic Mean Divisia Index) to decompose the impact factors of energy consumption of hotel from Jan. to Dec. in 2001. The results indicate that the occupancy rate and unit area of revenue are the main factors that can increase unit area of energy consumption, and the unit revenue of energy consumption is the main factor to restrain the growth of unit area of energy consumption. When the energy consumption of hotel can appear abnormal, the hotel manager can carry out energy saving management and control according to the contribution value of impact factors.

Keywords: Smart city, SPIRTPAT model, LMDI, saving management and control.

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