Search results for: indoor mobile network

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.

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Authors: YongXian, JIN

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Introducing survivability into embedded real-time system (ERTS) can improve the survivability power of the system. This paper mainly discusses about the survivability of ERTS. The first is the survivability origin of ERTS. The second is survivability analysis. According to the definition of survivability based on survivability specification and division of the entire survivability analysis process for ERTS, a survivability analysis profile is presented. The quantitative analysis model of this profile is emphasized and illuminated in detail, the quantifying analysis of system was showed helpful to evaluate system survivability more accurate. The third is platform design of survivability analysis. In terms of the profile, the analysis process is encapsulated and assembled into one platform, on which quantification, standardization and simplification of survivability analysis are all achieved. The fourth is survivability design. According to character of ERTS, strengthened design method is selected to realize system survivability design. Through the analysis of embedded mobile video-on-demand system, intrusion tolerant technology is introduced in whole survivability design.

Keywords: ERTS (embedded real-time system), survivability, quantitative analysis, survivability specification, intrusion tolerant

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Authors: Aline Zeitunlian, Ramzi A. Haraty

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Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.

Keywords: Cache consistency, hybrid algorithm, and mobileenvironments

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Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

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The mobile systems are powered by batteries. Reducing the system power consumption is a key to increase its autonomy. It is known that mostly the systems are dealing with time varying signals. Thus, we aim to achieve power efficiency by smartly adapting the system processing activity in accordance with the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting signal driven sampling and processing. In this context, a signal driven filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by analysing the input signal local variations. Thus, it correlates the processing activity with the signal variations. It leads towards a drastic computational gain of the proposed technique compared to the classical one.

Keywords: Level Crossing Sampling, Activity Selection, Adaptive Rate Filtering, Computational Complexity.

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Authors: Thach D. Do, Juhum Kwon, Chang-Joo Moon

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A Ground Control System (GCS), which controls Unmanned Aerial Vehicles (UAVs) and monitors their missionrelated data, is one of the major components of UAVs. In fact, some traditional GCSs were built on an expensive, complicated hardware infrastructure with workstations and PCs. In contrast, a GCS on a portable device – such as an Android phone or tablet – takes advantage of its light-weight hardware and the rich User Interface supported by the Android Operating System. We implemented that kind of GCS and called it Ground System Software (GSS) in this paper. In operation, our GSS communicates with UAVs or other GSS via TCP/IP connection to get mission-related data, visualizes it on the device-s screen, and saves the data in its own database. Our study showed that this kind of system will become a potential instrument in UAV-related systems and this kind of topic will appear in many research studies in the near future.

Keywords: Android Operating System, Ground Control System, Mobile Device, Unmanned Aerial Vehicle.

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Authors: Nermin A. Mohamed, Mohamed F. Madkour

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We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.

Keywords: Adaptive arrays, channel estimation, interferencecancellation, wideband code division multiple access (WCDMA).

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Authors: Yun Won Chung

Abstract:

The energy consumption of home femto base stations (BSs) can be reduced, by turning off the Wi-Fi radio interface when there is no mobile station (MS) under the coverage of the BSs or MSs do not transmit or receive data packet for long time, especially in late night. In the energy-efficient home femto BSs, if MSs have any data packet to transmit and the Wi-Fi radio interface in off state, MSs wake up the Wi-Fi radio interface of home femto BSs by using additional low power radio interface. In this paper, the performance of the energy-efficient home femto BSs from the aspect of energy consumption and cumulative average delay, and show the effect of various parameters on energy consumption and cumulative average delay. From the results, the tradeoff relationship between energy consumption and cumulative average delay is shown and thus, appropriate operation should be needed to balance the tradeoff.

Keywords: energy consumption, power saving, femto base station.

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Authors: Stephen Barnes, Ian Mills, Frances Cleary

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Augmented and Virtual Reality based applications offer many benefits for the heritage and tourism sector. This technology provides a platform to showcase the regions of interest to people without the need for them to be physically present, which has had a positive impact on enticing tourists to visit those locations. However, the technology also provides the opportunity to present historical artefacts in a form that accurately represents their original, intended appearance. Three sites of interest were identified in the Lingaun Valley in South East Ireland wherein virtual representations of site specific artefacts of interest were created via a multidisciplinary team encompassing archaeology, art history, 3D modelling, design and software development. The collated information has been presented to users via an Augmented Reality mobile based application that provides information in an engaging manner that encourages an interest in history as well as visits to the sites in the Lingaun Valley.

Keywords: Augmented Reality, Virtual Heritage, 3D modelling, archaeology, virtual representation.

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Authors: Robert L. Burdett, Bayan Bevrani

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: Capacity analysis, capacity expansion, railways.

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Authors: Meng-Jou Chien, Jheng-Cheng Chen, Chang-Hsiung Tsai

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Let max_ζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.

Keywords: Interconnection network, Augmented cube, Induced subgraph, Bisection width.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry

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Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.

Keywords: Effective band inference based power control algorithm (EBIA), Power Selection MRMC Unification Protocol (PMMUP), MRMC State unification Variable Prediction (MRSUP), Wireless Mesh Networks (WMNs).

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Authors: D. Woradechjumroen, H. Li, Y. Yu

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Supermarkets are the most electricity-intensive type of commercial buildings. The unsuitable indoor environment of a supermarket provided by abnormal HVAC operations incurs waste energy consumption in refrigeration systems. This current study briefly describes significantly solid backgrounds and proposes easyto- use analysis terminology for investigating the impact of HVAC operations on refrigeration power consumption using the field-test data obtained from building automation system (BAS). With solid backgrounds and prior knowledge, expected energy interactions between HVAC and refrigeration systems are proposed through Pearson’s correlation analysis (R value) by considering correlations between equipment power consumption and dominantly independent variables (driving force conditions).The R value can be conveniently utilized to evaluate how strong relations between equipment operations and driving force parameters are. The calculated R values obtained from field data are compared to expected ranges of R values computed by energy interaction methodology. The comparisons can separate the operational conditions of equipment into faulty and normal conditions. This analysis can simply investigate the condition of equipment operations or building sensors because equipment could be abnormal conditions due to routine operations or faulty commissioning processes in field tests. With systematically solid and easy-to-use backgrounds of interactions provided in the present article, the procedures can be utilized as a tool to evaluate the proper commissioning and routine operations of HVAC and refrigeration systems to detect simple faults (e.g. sensors and driving force environment of refrigeration systems and equipment set-point) and optimize power consumption in supermarket buildings. Moreover, the analysis will be used to further study the FDD research for supermarkets in future.

Keywords: Energy interaction, HVAC, R-value, Supermarket buildings.

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Authors: Randhir Singh Baghel

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In this study, the fundamental ideas guiding the dynamic area of machine learning—where models thrive and algorithms change over time—are rooted in an innate mathematical link. This study explores the fundamental ideas that drive the development of intelligent systems, providing light on the mutually beneficial link between mathematics and machine learning.

Keywords: Machine Learning, deep learning, Neural Network, optimization.

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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, wireless sensor networks.

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Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: Heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry.

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant.

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: Authentication, key-session, security, wireless sensors.

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Authors: Gulzar A. Khuwaja, Mohammad S. Laghari

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capability to reliably distinguish between an authorized person and an imposter. Signature verification systems can be categorized as offline (static) and online (dynamic). This paper presents a neural network based recognition of offline handwritten signatures system that is trained with low-resolution scanned signature images.

Keywords: Pattern Recognition, Computer Vision, AdaptiveClassification, Handwritten Signature Recognition.

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: Almost strictly positive real, doubly-fed induction generator, simple adaptive control, subsynchronous oscillations, wind turbine.

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: Primary health care, developing countries, policy health planning, settlement strategy.

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Authors: D. Reich, R. Stark

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To provide reliable and valid findings when evaluating innovative in-car devices in the automotive context highly realistic driving environments are recommended. Nowadays, in-car devices are mostly evaluated due to driving simulator studies followed by real car driving experiments. Driving simulators are characterized by high internal validity, but weak regarding ecological validity. Real car driving experiments are ecologically valid, but difficult to standardize, more time-robbing and costly. One economizing suggestion is to implement more immersive driving environments when applying driving simulator studies. This paper presents research comparing non-immersive standard PC conditions with mobile and highly immersive Oculus Rift conditions while performing the Lane Change Task (LCT). Subjective data with twenty participants show advantages regarding presence and immersion experience when performing the LCT with the Oculus Rift, but affect adversely cognitive workload and simulator sickness, compared to non-immersive PC condition.

Keywords: LCT, immersion, oculus rift, presence, situation awareness.

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Authors: Ming-Hua Fu

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No negative control nor control to prevent microbes from escaping was set when the S-shaped flask experiments were performed by Pasteur. Microscope was not used to observe the media in the flasks. Louis Pasteur’s S-shaped flask experiment was re-examined by using U-shaped flasks, modified S-shaped flasks and microscope. A mixture of microbes was isolated from the room air, from which one rod-shaped Bacillus species with proposed name Bacillus gaso-mobilis sp nov and one grape-shaped Staphylococcus species with proposed name of Staphylococcus gaso-mobilis sp nov were identified. Their penicillin and ampicillin resistant strains containing plasmids were isolated. These bacteria could change color, produce odor and automatically move in the air. They did not form colonies on solid media. They had a high suspension capacity in liquid media. Their light absorbance peaked at the wave length of 320 nm.  It was concluded that there were flaws with Louis Pasteur’s S-shaped flask experiments. 

Keywords: Bacteria, gaso-mobile, re-examine, S-shaped flasks.

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Authors: O. S. Ebrahim, K. O. Shawky, M. O. Ebrahim, P. K. Jain

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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). Changing the connection of the stator windings from delta to star at no load can achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: Artificial Neural Network, ANN, Energy Saving Mode, ESM, Induction Motor, IM, star/delta switch, supervisory control, fluid transportation, reliability, power quality.

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.

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Authors: Jito Vanualailai, Bibhya Sharma

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Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.

Keywords: Attractive-repulsive swarm model, individual-based swarm model, Lagrangian swarm model, Lyapunov stability, Lyapunov-like function, practical stability, unicycle.

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Authors: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: Embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems.

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Authors: Salem Alajmi, Bader Altaweel

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Kuwait, like many parts of the world, has started facing the dangerous growth of electrical and electronic waste. This growth has been noted in last two decades, emerging with the development of mobile phones, computers, TVs, as well as other electronic devices and electrical equipment. Kuwait is already among the highest global producers of electronic waste (e-waste) in kg per capita. Furthermore, Kuwait is among the global countries that set high-level future targets in renewable energy projects. Accumulation of this electronic waste, as well as accelerated renewable energy projects, will lead to the increase of future threats to the country. In this research, factors that lead to the increase the e-waste in Kuwait are presented. Also, the current situations of dealing with e-waste in the country as well as the associated challenges are examined. The impact of renewable energy projects on future e-waste accumulation is considered. Moreover, this research proposes the best strategies and practices toward successfully dealing with the waste of electronic devices and renewable energy technologies.

Keywords: E-waste, landfill, environmental management, valuable metals, hazardous materials.

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Authors: Yoshitaka Fujiwara, Jun-ichirou Fukushima, Yasunari Maeda

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Keys to high-quality face-to-face education are ensuring flexibility in the way lectures are given, and providing care and responsiveness to learners. This paper describes a face-to-face education support system that is designed to raise the satisfaction of learners and reduce the workload on instructors. This system consists of a lecture adaptation assistance part, which assists instructors in adapting teaching content and strategy, and a Q&A assistance part, which provides learners with answers to their questions. The core component of the former part is a “learning achievement map", which is composed of a Bayesian network (BN). From learners- performance in exercises on relevant past lectures, the lecture adaptation assistance part obtains information required to adapt appropriately the presentation of the next lecture. The core component of the Q&A assistance part is a case base, which accumulates cases consisting of questions expected from learners and answers to them. The Q&A assistance part is a case-based search system equipped with a search index which performs probabilistic inference. A prototype face-to-face education support system has been built, which is intended for the teaching of Java programming, and this approach was evaluated using this system. The expected degree of understanding of each learner for a future lecture was derived from his or her performance in exercises on past lectures, and this expected degree of understanding was used to select one of three adaptation levels. A model for determining the adaptation level most suitable for the individual learner has been identified. An experimental case base was built to examine the search performance of the Q&A assistance part, and it was found that the rate of successfully finding an appropriate case was 56%.

Keywords: Bayesian network, face-to-face education, lecture adaptation, Q&A assistance.

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Authors: S.M. Bahri, F.T. Bendimerad

Abstract:

We propose a downlink multiple-input multipleoutput (MIMO) multi-carrier code division multiple access (MCCDMA) system with adaptive beamforming algorithm for smart antennas. The algorithm used in this paper is based on the Least Mean Square (LMS), with pilot channel estimation (PCE) and the zero forcing equalizer (ZFE) in the receiver, requiring reference signal and no knowledge channel. MC-CDMA is studied in a multiple antenna context in order to efficiently exploit robustness against multipath effects and multi-user flexibility of MC-CDMA and channel diversity offered by MIMO systems for radio mobile channels. Computer simulations, considering multi-path Rayleigh Fading Channel, interference inter symbol and interference are presented to verify the performance. Simulation results show that the scheme achieves good performance in a multi-user system.

Keywords: Adaptive Beamforming, LMS Algorithm, MCCDMA, MIMO System, Smart Antenna.

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Authors: A. El Harraj, N. Raissouni

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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