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Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in VerilogHDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: Auto-encoder, Behavior model simulation, Digital hardware design, Pre-route simulation, Unsupervised feature learning.

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Authors: Maria Visitacion N. Gumabay, Byron Joseph A. Hallar, Annjeannette Alain D. Galang

Abstract:

This study was intended to provide a more efficient and convenient way for mobile users to enhance their knowledge about ASEAN countries. The researchers evaluated the utility of the developed crossword puzzle application and assessed the general usability of its user interface for its intended purpose and audience of users. The descriptive qualitative research method for the research design and the Mobile-D methodology was employed for the development of the software application output. With a generally favorable reception from its users, the researchers concluded that the iSEA Mobile Based Learning Application can be considered ready for general deployment and use. It was also concluded that additional studies can also be done to make a more complete assessment of the knowledge gained by its users before and after using the application.

Keywords: Mobile learning, e-learning, crossword, ASEAN, iSEA.

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Authors: Nur Razia Mohd Suradi, Hema Subramaniam, Marina Hassan, Siti Fatimah Omar

Abstract:

Knowledge sharing culture contributes to a positive working environment. Currently, there is no platform for the Faculty of Industrial Information Technology (FIIT), Unisel academic staff to share knowledge among them. As it is done manually, the sharing process is through common meeting or by any offline discussions. There is no repository for future retrieval. However, with open source solution the development of knowledge based application may reduce the cost tremendously. In this paper we discuss about the domain on which this knowledge portal is being developed and also the deployment of open source tools such as JOOMLA, PHP programming language and MySQL. This knowledge portal is evidence that open source tools also reliable in developing knowledge based portal. These recommendations will be useful to the open source community to produce more open source products in future.

Keywords: Knowledge management, Portal, ContentManagement, JOOMLA.

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Authors: Mehrdad Nouri Khajavi, Sajjad Ahoui Ghazvin, Ghader Rezazadeh, Mohammad Fathalilou

Abstract:

In this paper static and dynamic response of a varactor of a micro-phase shifter to DC, step DC and AC voltages have been studied. By presenting a mathematical modeling Galerkin-based step by step linearization method (SSLM) and Galerkin-based reduced order model have been used to solve the governing static and dynamic equations, respectively. The calculated static and dynamic pull-in voltages have been validated by previous experimental and theoretical results and a good agreement has been achieved. Then the frequency response and phase diagram of the system has been studied. It has been shown that applying the DC voltage shifts down the phase diagram and frequency response. Also increasing the damping ratio shifts up the phase diagram.

Keywords: MEMS, Phase Shifter, Pull-in Voltage, PhaseDiagram

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Authors: Han Park, JooSeok Song

Abstract:

We propose an enhanced key management scheme based on Key Infection, which is lightweight scheme for tiny sensors. The basic scheme, Key Infection, is perfectly secure against node capture and eavesdropping if initial communications after node deployment is secure. If, however, an attacker can eavesdrop on the initial communications, they can take the session key. We use common neighbors for each node to generate the session key. Each node has own secret key and shares it with its neighbor nodes. Then each node can establish the session key using common neighbors- secret keys and a random number. Our scheme needs only a few communications even if it uses neighbor nodes- information. Without losing the lightness of basic scheme, it improves the resistance against eavesdropping on the initial communications more than 30%.

Keywords: Wireless Sensor Networks, Key Management

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Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

Abstract:

The growing popularity of systems based on Unmanned Aerial Vehicles (UAVs) is highlighting their vulnerability particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signal. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: Visual odometry, autonomous UAV, position measurement, autonomous outdoor flight.

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Authors: Roshafima R. Ali, W. A. Wan Abdul Rahman, Rafiziana M. Kasmani, N. Ibrahim

Abstract:

This current research focused on development of degradable starch based packaging film with enhanced mechanical properties. A series of low density polyethylene (LDPE)/tapioca starch compounds with various tapioca starch contents were prepared by twin screw extrusion with the addition of maleic anhydride grafted polyethylene as compatibilizer. Palm cooking oil was used as processing aid to ease the blown film process, thus, degradable film can be processed via conventional blown film machine. Studies on their characteristics, mechanical properties and biodegradation were carried out by Fourier Transform Infrared (FTIR) spectroscopy and optical properties, tensile test and exposure to fungi environment respectively. The presence of high starch contents had an adverse effect on the tensile properties of LDPE/tapioca starch blends. However, the addition of compatibilizer to the blends improved the interfacial adhesion between the two materials, hence, improved the tensile properties of the films. High content of starch amount also was found to increase the rate of biodegradability of LDPE/tapioca starch films. It can be proved by exposure of the film to fungi environment. A growth of microbes colony can be seen on the surface of LDPE/tapioca starch film indicates that the granular starch present on the surface of the polymer film is attacked by microorganisms, until most of it is assimilated as a carbon source.

Keywords: Degradable polymer, starch based biofilms, blown film extrusion, green food packaging.

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Authors: M. Tria, M. Benidir, E. Chaumette

Abstract:

In Secondary Surveillance Radar (SSR) systems, it is more difficult to locate and recognise aircrafts in the neighbourhood of civil airports since aerial traffic becomes greater. Here, we propose to apply a recent Blind Source Separation (BSS) algorithm based on Time-Frequency Analysis, in order to separate messages sent by different aircrafts and falling in the same radar beam in reception. The above source separation method involves joint-diagonalization of a set of smoothed version of spatial Wigner-Ville distributions. The technique makes use of the difference in the t-f signatures of the nonstationary sources to be separated. Consequently, as the SSR sources emit different messages at different frequencies, the above fitted to this new application. We applied the technique in simulation to separate SSR replies. Results are provided at the end of the paper.

Keywords: Blind Source Separation, Time-Frequency Analysis, Secondary Radar

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Authors: Ying Huang, Zhiliang Wang, An Ping

Abstract:

With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.

Keywords: computer vision, gaze tracking, human-computer interaction.

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Authors: Fernando Pérez, Humberto Sossa, Rigoberto Martínez, Daniel Lorias, Arturo Minor

Abstract:

This paper presents a system for tracking the movement of laparoscopic instruments which is based on an orthogonal system of webcams and video image processing. The movements are captured with two webcams placed orthogonally inside of the physical trainer. On the image, the instruments were detected by using color markers placed on the distal tip of each instrument. The 3D position of the tip of the instrument within the work space was obtained by linear triangulation method. Preliminary results showed linearity and repeatability in the motion tracking with a resolution of 0.616 mm in each axis; the accuracy of the system showed a 3D instrument positioning error of 1.009 ± 0.101 mm. This tool is a portable and low-cost alternative to traditional tracking devices and a trustable method for the objective evaluation of the surgeon’s surgical skills.

Keywords: Laparoscopic Surgery, Orthogonal Vision, Tracking Instruments, Triangulation.

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Authors: L. Ramirez, E. Guillén, J. Sánchez

Abstract:

Some of the main goals about telecare such as monitoring, treatment, telediagnostic are deployed with the integration of applications with specific appliances. In order to achieve a coherent model to integrate software, hardware, and healthcare systems, different telehealth models with Internet of Things (IoT), cloud computing, artificial intelligence, etc. have been implemented, and their advantages are still under analysis. In this paper, we propose an integrated model based on IoT architecture and cloud computing telehealth center. Analytics module is presented as a solution to control an ideal diagnostic about some diseases. Specific features are then compared with the recently deployed conventional models in telemedicine. The main advantage of this model is the availability of controlling the security and privacy about patient information and the optimization on processing and acquiring clinical parameters according to technical characteristics.

Keywords: Analytics, telemedicine, internet of things, cloud computing.

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Authors: Ali Shariq Imran, M. Younus Javed, Naveed Sarfraz Khattak

Abstract:

This paper presents a novel method for data hiding based on neighborhood pixels information to calculate the number of bits that can be used for substitution and modified Least Significant Bits technique for data embedding. The modified solution is independent of the nature of the data to be hidden and gives correct results along with un-noticeable image degradation. The technique, to find the number of bits that can be used for data hiding, uses the green component of the image as it is less sensitive to human eye and thus it is totally impossible for human eye to predict whether the image is encrypted or not. The application further encrypts the data using a custom designed algorithm before embedding bits into image for further security. The overall process consists of three main modules namely embedding, encryption and extraction cm.

Keywords: Data hiding, image processing, information security, stagonography.

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Authors: Jing Hang Choo, Soon Nyean Cheong, Yee Lien Lee, Sze Hou Teh

Abstract:

The advancement of smartphones, wireless networking and Near Field Communication (NFC) technology have opened up a new approach to indoor navigation. Although NFC technology has been used to support electronic commerce, access control, and ticketing, there is a lack of research work on building NFC-based indoor navigation system for smartphone users. This paper presents an indoor interactive navigation system (named I2Navi) based on NFC technology for users to navigate within a building with ease using their smartphones. The I2Navi system has been implemented at the Faculty of Engineering (FOE), Multimedia University (MMU) to enable students, parents, visitors who own NFC-enabled Android smartphones to navigate themselves within the faculty. An evaluation is carried out and the results show positive response to the proposed indoor navigation system using NFC and smartphone technologies.

Keywords: Near Field Communication, indoor navigation system, smartphones.

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Authors: V. Rashtchi, R. Aghmasheh

Abstract:

Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.

Keywords: broken bar, PSO, fault detection, SCIM

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Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

Abstract:

Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

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Authors: Maria Istvanova

Abstract:

The purpose of the comparative study of the affricate consonants in Chinese and Slovak is to increase the awareness of the main distinguishing features between these two languages taking into consideration this particular group of consonants. We determine the main difficulties of the Slovak learners in the process of acquiring correct pronunciation of affricate initial consonants in Chinese based on the understanding of the distinguishing features of Chinese and Slovak affricates in combination with the experimental measuring of voice onset time (VOT) values. The software tool Praat is used for the analysis of the recorded language samples. The language samples contain recordings of a Chinese native speaker and Slovak students of Chinese with different language proficiency levels. Based on the results of the analysis in Praat, we identify erroneous pronunciation and provide clarification of its cause.

Keywords: Chinese, comparative study, initial consonants, pronunciation, Slovak

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Authors: Ghassan A. Abed, Akbal O. Salman, Bayan M. Sabbar

Abstract:

Transmission Control Protocol (TCP) among the wired and wireless networks, it still has a practical problem; where the congestion control mechanism does not permit the data stream to get complete bandwidth over the existing network links. To solve this problem, many TCP protocols have been introduced with high speed performance. Therefore, an enhanced congestion window (cwnd) for the congestion control mechanism is proposed in this article to improve the performance of TCP by increasing the number of cycles of the new window to improve the transmitted packet number. The proposed algorithm used a new mechanism based on the available bandwidth of the connection to detect the capacity of network path in order to improve the regular clocking of congestion avoidance mechanism. The work in this paper based on using Network Simulator 2 (NS-2) to simulate the proposed algorithm.

Keywords: TCP, cwnd, Congestion Control, NS-2.

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: Brain Computer Interface (BCI), Electroencephalogram (EEG), EEGLab, BCILab, Emotiv, Emotions, Interval features, Spectral features, Artificial Neural Network, Control applications.

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Authors: Sangjun Park, Sangbae Jeong, Moonsung Han, Minsoo hahn

Abstract:

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. The algorithm detects the DOAs of multiple sources using the inverse of the eigenvalue-weighted eigen spectra. To apply the algorithm to target signal detection for GSC-based beamforming, we utilize its spectral response for the target DOA in noisy conditions. For evaluation of the algorithm, the performance of the proposed target signal detection method is compared with that of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics(ROC) curves.

Keywords: Beamforming, direction of arrival, multiple signal classification, target signal detection.

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Authors: Hong-Bing Wang, Zhi-Hua Fan, Chun-Dong She

Abstract:

Open Agent System platform based on High Level Architecture is firstly proposed to support the application involving heterogeneous agents. The basic idea is to develop different wrappers for different agent systems, which are wrapped as federates to join a federation. The platform is based on High Level Architecture and the advantages for this open standard are naturally inherited, such as system interoperability and reuse. Especially, the federal architecture allows different federates to be heterogeneous so as to support the integration of different agent systems. Furthermore, both implicit communication and explicit communication between agents can be supported. Then, as the wrapper RTI_JADE an example, the components are discussed. Finally, the performance of RTI_JADE is analyzed. The results show that RTI_JADE works very efficiently.

Keywords: Open Agent System, High Level Architecture, Heterogeneous Agents, Wrapper.

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Authors: Sana Ktata, Kaïs Ouni, Noureddine Ellouze

Abstract:

Electrocardiogram (ECG) data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. A wavelet ECG data codec based on the Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm is proposed in this paper. The SPIHT algorithm has achieved notable success in still image coding. We modified the algorithm for the one-dimensional (1-D) case and applied it to compression of ECG data. By this compression method, small percent root mean square difference (PRD) and high compression ratio with low implementation complexity are achieved. Experiments on selected records from the MIT-BIH arrhythmia database revealed that the proposed codec is significantly more efficient in compression and in computation than previously proposed ECG compression schemes. Compression ratios of up to 48:1 for ECG signals lead to acceptable results for visual inspection.

Keywords: Discrete Wavelet Transform, ECG compression, SPIHT.

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Authors: E. Jomehzadeh, A.R. Saidi

Abstract:

In the present article, nonlinear vibration analysis of single layer graphene sheets is presented and the effect of small length scale is investigated. Using the Hamilton's principle, the three coupled nonlinear equations of motion are obtained based on the von Karman geometrical model and Eringen theory of nonlocal continuum. The solutions of Free nonlinear vibration, based on a one term mode shape, are found for both simply supported and clamped graphene sheets. A complete analysis of graphene sheets with movable as well as immovable in-plane conditions is also carried out. The results obtained herein are compared with those available in the literature for classical isotropic rectangular plates and excellent agreement is seen. Also, the nonlinear effects are presented as functions of geometric properties and small scale parameter.

Keywords: Small scale, Nonlinear vibration, Graphene sheet, Nonlocal continuum

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Authors: Tuhin Subhra Sarkar, Subir Das

Abstract:

Several research works have been done in recent times utilizing grayscale image for the measurement of many physical phenomena. In this present paper, we have designed an embedded based inclination sensor utilizing the grayscale image with a resolution of 0.3º. The sensor module consists of a circular shaped metal disc, laminated with grayscale image and an optical transreceiver. The sensor principle is based on temporal changes in light intensity by the movement of grayscale image with the inclination of the target surface and the variation of light intensity has been detected in terms of voltage by the signal processing circuit (SPC).The output of SPC is fed to a microcontroller program to display the inclination angel digitally. The experimental results are shown a satisfactory performance of the sensor in a small inclination measuring range of -40º to + 40º with a sensitivity of 62 mV/°.

Keywords: Grayscale image, Inclination Sensor, Microcontroller Program, Signal Processing Circuit.

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Authors: Ming Cong, Yinghua Wu, Dong Liu, Haiying Wen, Junfa Yu

Abstract:

In order to improve control performance and eliminate steady, a coupling compensation for 6-DOF parallel robot is presented. Taking dynamic load Tank Simulator as the research object, this paper analyzes the coupling of 6-DOC parallel robot considering the degree of freedom of the 6-DOF parallel manipulator. The coupling angle and coupling velocity are derived based on inverse kinematics model. It uses the mechanism-model combined method which takes practical moving track that considering the performance of motion controller and motor as its input to make the study. Experimental results show that the coupling compensation improves motion stability as well as accuracy. Besides, it decreases the dither amplitude of dynamic load Tank Simulator.

Keywords: coupling compensation, screw theory, parallel robot, mechanism-model combined motion

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

Abstract:

The biodegradable family of polymers polyhydroxyalkanoates is an interesting substitute for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: Circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization.

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Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: Cellular automata, neural cellular automata, deep learning, classification.

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Authors: Zeynep Turhan

Abstract:

This review emphasizes the effectiveness of men’s participation in preventing domestic violence, and whether nonviolent (NV) boys’ and men’s perceptions of intimate partner violence (IPV) prevention programs affect their involvement. The main goals of this assessment were to investigate (1) how NV men engaged in anti-violence prevention programs that empower women, (2) what were the possible perceptions of NV men involved in prevention programs (3) how to identify effective approaches and strategies that encouraged NV men to become involved in prevention programs. This critical review also included the overview of prevention programs such as: The Mentors in Violence Prevention Programs (MVP), The White Ribbon Campaign (WRC), and Domestic Violence Prevention Enhancement and Leadership through Alliances (DELTA). The review suggested that (1) the expanding prevention programs need to reach more macro settings such as work place, faith-based and other community based organizations, and (2) territory prevention programs should expand through addressing the long-term effects of violence.

Keywords: Engagement, intimate partner violence, non-violent men, prevention programs.

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Authors: M. Khakbazan, S. L. Scott, H. C. Block, C. D. Robins, W. P. McCaughey

Abstract:

A ten-year grazing study was conducted at the Agriculture and Agri-Food Canada Brandon Research Centre in Manitoba to study the effect of alfalfa inclusion and fertilizer (N, P, K, and S) addition on economics and efficiency of non-renewable energy use in meadow brome grass-based pasture systems for beef production. Fertilizing grass-only or alfalfa-grass pastures to full soil test recommendations improved pasture productivity, but did not improve profitability compared to unfertilized pastures. Fertilizing grass-only pastures resulted in the highest net loss of any pasture management strategy in this study. Adding alfalfa at the time of seeding, with no added fertilizer, was economically the best pasture improvement strategy in this study. Because of moisture limitations, adding commercial fertilizer to full soil test recommendations is probably not economically justifiable in most years, especially with the rising cost of fertilizer. Improving grass-only pastures by adding fertilizer and/or alfalfa required additional non-renewable energy inputs; however, the additional energy required for unfertilized alfalfa-grass pastures was minimal compared to the fertilized pastures. Of the four pasture management strategies, adding alfalfa to grass pastures without adding fertilizer had the highest efficiency of energy use. Based on energy use and economic performance, the unfertilized alfalfa-grass pasture was the most efficient and sustainable pasture system.

Keywords: Alfalfa, grass, fertilizer, pasture systems, economics, energy.

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Authors: A.Goel, M. Agrawal, P. Gupta Poddar

Abstract:

Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.

Keywords: Orthogonal frequency division multiplexing (OFDM), Peak-to-average power ratio (PAPR), Selected mapping (SLM), Side information (SI)

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.

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