Search results for: Supply chain performance

Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: Correlation filter, long-term tracking, random fern, real-time tracking.

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM2.5, fugitive, emission inventory.

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Authors: H. Golchoobian, M. H. Taheri, S. Saedodin, A. Sarafraz

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This paper investigates the possibility of using three systems of organic Rankine auxiliary power generation, ejector refrigeration and absorption to recover energy from a diesel car. The analysis is done for both urban and suburban driving modes that vary from 60 to 120 km/h. Various refrigerants have also been used for organic Rankine and Ejector refrigeration cycles. The capacity was evaluated by Organic Rankine Cycle (ORC) system in both urban and suburban conditions for cyclopentane and ammonia as refrigerants. Also, for these two driving plans, produced cooling by absorption refrigeration system under variable ambient temperature conditions and in ejector refrigeration system for R123, R134a and R141b refrigerants were investigated.

Keywords: Absorption system, diesel engine, ejector refrigeration, energy recovery, organic Rankine cycle.

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Authors: W. Maddison

Abstract:

This paper describes an Action Research project which was undertaken to inform professional practice in order to develop a newly created Centre for Student Success in the specific context of transnational medical and nursing education in the Middle East. The objectives were to enhance the academic performance, persistence, integration and personal and professional development of a multinational study body, in particular in relation to pre-clinical medical students, and to establish a comfortable, friendly and student-driven environment within an Irish medical university recently established in Bahrain. The outcomes of the project resulted in the development of a specific student success ‘signature’ for this particular transnational higher education context.

Keywords: Global-Local, pre-clinical medical students, student success, transnational higher education, Middle East.

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: Cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization.

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Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar

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Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.

Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis

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Authors: Gyoutae Park, Woosuk Kim, Sangguk Ahn, Seungmo Kim, Minjun Kim, Jinhan Lee, Youngdo Jo, Jongsam Moon, Hiesik Kim

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In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries.

Keywords: Gas leakage detector, inspection instrument, extracting numerals, concentration.

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Authors: M. Umabharathi, S. Vijayabaskar

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Evolutionary Fuzzy PID Speed Controller for Permanent Magnet Synchronous Motor (PMSM) is developed to achieve the Speed control of PMSM in Closed Loop operation and to deal with the existence of transients. Consider a Fuzzy PID control design problem, based on common control Engineering Knowledge. If the transient error is big, that Good transient performance can be obtained by increasing the P and I gains and decreasing the D gains. To autotune the control parameters of the Fuzzy PID controller, the Evolutionary Algorithms (EA) are developed. EA based Fuzzy PID controller provides better speed control and guarantees the closed loop stability. The Evolutionary Fuzzy PID controller can be implemented in real time Applications without any concern about instabilities that leads to system failure or damage.

Keywords: Evolutionary Algorithm (EA), Fuzzy system, Genetic Algorithm (GA), Membership, Permanent Magnet Synchronous Motor (PMSM).

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Authors: Peter Burggräf, Moritz Krunke, Hanno Voet

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Due to shortening product and technology lifecycles, many companies use standardization approaches in product development and factory planning to reduce costs and time to market. Unlike large companies, where modular systems are already widely used, small and medium-sized companies often show a much lower degree of standardization due to lower scale effects and missing capacities for the development of these standards. To overcome these challenges, the development of industry sector specific standards in cooperations or by third parties is an interesting approach. This paper analyzes which branches that are mainly dominated by small or medium-sized companies might be especially interesting for the development of factory standards using the example of the German industry. For this, a key performance indicator based approach was developed that will be presented in detail with its specific results for the German industry structure.

Keywords: Factory planning, factory standards, industry sector specific standardization, production planning.

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Authors: Li Long, Thomas Ortlepp

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The transport properties of carriers in polycrystalline silicon film affect the performance of polycrystalline silicon-based devices. They depend strongly on the grain structure, grain boundary trap properties and doping concentration, which in turn are determined by the film deposition and processing conditions. Based on the properties of charge carriers, phonons, grain boundaries and their interactions, the thermoelectric properties of polycrystalline silicon are analyzed with the relaxation time approximation of the Boltzmann transport equation. With this approach, thermal conductivity, electrical conductivity and Seebeck coefficient as a function of grain size, trap properties and doping concentration can be determined. Experiment on heavily doped polycrystalline silicon is carried out and measurement results are compared with the model.

Keywords: Conductivity, polycrystalline silicon, relaxation time approximation, Seebeck coefficient, thermoelectric property.

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Authors: Ngoc Dang Khoa Nguyen, Imran Ali

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The cloud customer relationship management (CRM) has emerged as an innovative tool to augment the customer satisfaction and performance of banking systems. Cloud CRM allows to collect, analyze and utilize customer-associated information and update the systems, thereby offer superior customer service. Cloud technologies have invaluable potential to ensure innovative customer experiences, successful collaboration, enhanced speed to marketplace and IT effectiveness. As such, many leading banks have been attracted towards adoption of such innovative and customer-driver solutions to revolutionize their existing business models. Chief Information Officers (CIOs) are already implemented or in the process of implementation of cloud CRM. However, many organizations are still reluctant to take such initiative due to the lack of information on the factors influencing its implementation. This paper, therefore, aims to delve into the strategies, benefits and challenges intertwined in the implementation of cloud CRM in banking sector and provide reliable solutions.

Keywords: Banking sector, cloud computing, cloud CRM, strategy.

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Authors: F. May Liou, Y. C. Edwin Tang

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This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.

Keywords: Bank failure, CAMEL, competitive disadvantage, resource configuration.

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Authors: S Hariharan, K Chaitanya, P Muthuchidambaranathan

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The IEEE 802.22 working group aims to drive the Digital Video Broadcasting-Terrestrial (DVB-T) bands for data communication to the rural area without interfering the TV broadcast. In this paper, we arrive at a closed-form expression for average detection probability of Fusion center (FC) with multiple antenna over the κ − μ fading channel model. We consider a centralized cooperative multiple antenna network for reporting. The DVB-T samples forwarded by the secondary user (SU) were combined using Maximum ratio combiner at FC, an energy detection is performed to make the decision. The fading effects of the channel degrades the detection probability of the FC, a generalized independent and identically distributed (IID) κ − μ and an additive white Gaussian noise (AWGN) channel is considered for reporting and sensing respectively. The proposed system performance is verified through simulation results.

Keywords: IEEE 802.22, Cooperative spectrum sensing, Multiple antenna, κ − μ .

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Authors: Selvakuma Kumaresh, Man Young Kim

Abstract:

Combustion phenomenon will be accomplished effectively by the development of low emission combustor. One of the significant factors influencing the entire Combustion process is the mixing between a swirling angular jet (Primary Air) and the non-swirling inner jet (fuel). To study this fundamental flow, the chamber had to be designed in such a manner that the combustion process to sustain itself in a continuous manner and the temperature of the products is sufficiently below the maximum working temperature in the turbine. This study is used to develop the effective combustion with low unburned combustion products by adopting the concept of high swirl flow and motility of holes in the secondary chamber. The proper selection of a swirler is needed to reduce emission which can be concluded from the emission of Nox and CO2. The capture of CO2 is necessary to mitigate CO2 emissions from natural gas. Thus the suppression of unburned gases is a meaningful objective for the development of high performance combustor without affecting turbine blade temperature.

Keywords: Combustion, Emission, Can-type Combustion Chamber, CFD, Motility of Holes, Swirl Flow.

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Authors: Aline F. Marcon, Eduardo F. da Silva, Marina Bouzon

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The impact of lean management on environmental sustainability is the research line that receives the most attention from academicians. Therefore, the social dimension of sustainable development has so far received less attention. This paper aims to evaluate the impact of intra-plant lean manufacturing practices on social sustainability indicators extracted from the Global Reporting Initiative (GRI) parameters. The method is two-phased, including MCDM approach to uncover the most relevant practices regarding social performance and Interpretive Structural Modeling (ISM) method to reveal the structural relationship among lean practices. Professionals from the academic and industrial fields answered the questionnaires. From the results of this paper, it is possible to verify that practices such as “Safety Improvement Programs”, “Total Quality Management” and “Cross-functional Workforce” are the ones which have the most positive influence on the set of GRI social indicators.

Keywords: Indicators, ISM, lean, social, sustainability.

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Authors: Mingyu Xie, Mietek Brdys

Abstract:

The paper develops a Non-Linear Model Predictive Control (NMPC) of water quality in Drinking Water Distribution Systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: Model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives.

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Authors: Saroj Kumar Sarangi, M. C. Ray

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This paper deals with the analysis of active constrained layer damping (ACLD) of doubly curved laminated composite shells using active fiber composite (AFC) materials. The constraining layer of the ACLD treatment has been considered to be made of the AFC materials. A three dimensional energy based finite element model of the smart doubly curved laminated composite shell integrated with a patch of such ACLD treatment has been developed to demonstrate the performance of the patch on enhancing the damping characteristics of the doubly curved laminated composite shells. Particular emphasis has been placed on studying the effect of variation of piezoelectric fiber orientation angle in the constraining AFC layer on the control authority of the ACLD patch.

Keywords: Active constrained layer damping, Active fibercomposites, Finite element modeling, First order shear deformationtheory.

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Authors: Houshang Taghizadeh, Gholamreza Soltani Fesghandis

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Nowadays, without the awareness of consumer behavior and correct understanding of it, it is not possible for organizations to take appropriate measures to meet the consumer needs and demands. The aim of this paper is the identification and prioritization of the factors affecting the consumer behavior based on the product value. The population of the study includes all the consumers of furniture producing firms in East Azarbaijan province, Iran. The research sample includes 93 people selected by the sampling formula in unlimited population. The data collection instrument was a questionnaire, the validity of which was confirmed through face validity and the reliability of which was determined, using Cronbach's alpha coefficient. The Kolmogorov-Smironov test was used to test data normality, the t-test for identification of factors affecting the product value, and Friedman test for prioritizing the factors. The results show that quality, satisfaction, styling, price, finishing operation, performance, safety, worth, shape, use, and excellence are placed from 1 to 11 priorities, respectively.

Keywords: Consumer Behavior, Consumer Satisfaction, Product, Value

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Authors: G.A.C.P. Ganegoda, D.M.A. Samaranayake, L.S. Bandara, K.A.D.N.K. Wimalawarne

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With the popularity of the multi-core and many-core architectures there is a great requirement for software frameworks which can support parallel programming methodologies. In this paper we introduce an Eclipse toolkit, JConqurr which is easy to use and provides robust support for flexible parallel progrmaming. JConqurr is a multi-core and many-core programming toolkit for Java which is capable of providing support for common parallel programming patterns which include task, data, divide and conquer and pipeline parallelism. The toolkit uses an annotation and a directive mechanism to convert the sequential code into parallel code. In addition to that we have proposed a novel mechanism to achieve the parallelism using graphical processing units (GPU). Experiments with common parallelizable algorithms have shown that our toolkit can be easily and efficiently used to convert sequential code to parallel code and significant performance gains can be achieved.

Keywords: Multi-core, parallel programming patterns, GPU, Java, Eclipse plugin, toolkit,

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Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

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This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: Model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging.

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Authors: Anam Rafique, Syed Sohail Ahmed

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One of the essential components of much of DSP application is noise cancellation. Changes in real time signals are quite rapid and swift. In noise cancellation, a reference signal which is an approximation of noise signal (that corrupts the original information signal) is obtained and then subtracted from the noise bearing signal to obtain a noise free signal. This approximation of noise signal is obtained through adaptive filters which are self adjusting. As the changes in real time signals are abrupt, this needs adaptive algorithm that converges fast and is stable. Least mean square (LMS) and normalized LMS (NLMS) are two widely used algorithms because of their plainness in calculations and implementation. But their convergence rates are small. Adaptive averaging filters (AFA) are also used because they have high convergence, but they are less stable. This paper provides the comparative study of LMS and Normalized NLMS, AFA and new enhanced average adaptive (Average NLMS-ANLMS) filters for noise cancelling application using speech signals.

Keywords: AFA, ANLMS, LMS, NLMS.

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Authors: Balsam Mustafa, Safaai Deris

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Requirements are critical to system validation as they guide all subsequent stages of systems development. Inadequately specified requirements generate systems that require major revisions or cause system failure entirely. Use Cases have become the main vehicle for requirements capture in many current Object Oriented (OO) development methodologies, and a means for developers to communicate with different stakeholders. In this paper we present the results of a laboratory experiment that explored whether different types of use case format are equally effective in facilitating high knowledge user-s understanding. Results showed that the provision of diagrams along with the textual use case descriptions significantly improved user comprehension of system requirements in both familiar and unfamiliar application domains. However, when comparing groups that received models of textual description accompanied with diagrams of different level of details (simple and detailed) we found no significant difference in performance.

Keywords: Prior knowledge, requirement specification, usecase format, user understanding.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

Abstract:

Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Roslina Ibrahim, Azizah Jaafar

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Educational games (EG) seem to have lots of potential due to digital games popularity and preferences of our younger generations of learners. However, most studies focus on game design and its effectiveness while little has been known about the factors that can affect users to accept or to reject EG for their learning. User acceptance research try to understand the determinants of information systems (IS) adoption among users by investigating both systems factors and users factors. Upon the lack of knowledge on acceptance factors for educational games, we seek to understand the issue. This study proposed a model of acceptance factors based on Unified Theory of Acceptance and Use of Technology (UTAUT). We use original model (performance expectancy, effort expectancy and social influence) together with two new determinants (learning opportunities and enjoyment). We will also investigate the effect of gender and gaming experience that moderate the proposed factors.

Keywords: educational games, games acceptance, user acceptance model, UTAUT

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Authors: Wanting Zeng, Hsunling Bai

Abstract:

Silica was extracted from agriculture waste rice husk ash (RHA) and was used as the silica source for synthesis of RMCM-48 and RSBA-16. An alkali fusion process was utilized to separate silicate supernatant and the sediment effectively. The CTAB/Si and F127/Si molar ratio was employed to control the structure properties of the obtained RMCM-48 and RSBA-16 materials. The N2 adsorption-desorption results showed the micro-mesoporous RSBA-16 possessed high specific surface areas (662-1001 m2/g). All the obtained RSBA-16 materials were applied as the adsorbents for acetone adsorption. And the breakthrough tests clearly revealed that the RSBA-16(0.004) materials could achieve the highest acetone adsorption capacity of 181 mg/g under 1000 ppmv acetone vapor concentration at 25oC, which was also superior to ZSM-5 (71mg/g) and MCM-41 (157mg/g) under same test conditions. This can help to reduce the solid waste and the high adsorption performance of the obtained materials could consider as potential adsorbents for acetone adsorption.

Keywords: Acetone, adsorption, micro-mesoporous material, rice husk ash (RHA), RSBA-16.

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Authors: C. Chanapromma, T. Worachak, P. Silapan

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This paper presents positive and negative full-wave rectifier. The proposed structure is based on OTA using commercially available ICs (LT1228). The features of the proposed circuit are that: it can rectify and amplify voltage signal with controllable output magnitude via input bias current: the output voltage is free from temperature variation. The circuit description merely consists of 1 single ended and 3 fully differential OTAs. The performance of the proposed circuit are investigated though PSpice. They show that the proposed circuit can function as positive/negative full-wave rectifier, where the voltage input wide-dynamic range from -5V to 5V. Furthermore, the output voltage is slightly dependent on the temperature variations.

Keywords: Full-wave rectifier, Positive/negative, OTA, Electronically controllable, Wide-dynamic range

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Authors: Madina Hamiane, Amina Khunji

Abstract:

Detecting changes in multiple images of the same scene has recently seen increased interest due to the many contemporary applications including smart security systems, smart homes, remote sensing, surveillance, medical diagnosis, weather forecasting, speed and distance measurement, post-disaster forensics and much more. These applications differ in the scale, nature, and speed of change. This paper presents an application of image processing techniques to implement a real-time change detection system. Change is identified by comparing the RGB representation of two consecutive frames captured in real-time. The detection threshold can be controlled to account for various luminance levels. The comparison result is passed through a filter before decision making to reduce false positives, especially at lower luminance conditions. The system is implemented with a MATLAB Graphical User interface with several controls to manage its operation and performance.

Keywords: Image change detection, Image processing, image filtering, thresholding, B/W quantization.

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Authors: T. T. Lu, H.Y. Liao, M .F. Chen

Abstract:

Recently, malware attacks have become more serious over the Internet by e-mail, denial of service (DoS) or distributed denial of service (DDoS). The Botnets have become a significant part of the Internet malware attacks. The traditional botnets include three parts – botmaster, command and control (C&C) servers and bots. The C&C servers receive commands from botmaster and control the distributions of computers remotely. Bots use DNS to find the positions of C&C server. In this paper, we propose an advanced hybrid peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0 technology to hide the instructions from botmaster into social sites, which are regarded as C&C servers. Servent bots are regarded as sub-C&C servers to get the instructions from social sites. The AHP2P botnet 2.0 can evaluate the performance of servent bots, reduce DNS traffics from bots to C&C servers, and achieve harder detection bots actions than IRC-based botnets over the Internet.

Keywords: Peer-to-peer, Botnets, Botnet 2.0, Hybridpeer-to-peer

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Authors: Shrinivas P. Mahajan, Aarti C. Kshirsagar

Abstract:

Wireless communication technology is rapidly changing with recent developments in portable devices and communication protocols. This has generated demand for more advanced and compact antenna structures and therefore, proposed work focuses on Meander Line Antenna (MLA) design. Here, Pentaband MLA is designed on a FR4 substrate (85 mm x 40 mm) with dielectric constant (ϵr) 4.4, loss tangent (tan ) 0.018 and height 1.6 mm with coplanar feed and open stub structure. It can be operated in LTE (0.670 GHz-0.696 GHz) GPS (1.564 GHz-1.579 GHz), WCDMA (1.920 GHz-2.135 GHz), LTE UL frequency band 23 (2-2.020 GHz) and 5G (3.10 GHz-3.550 GHz) application bands. Also, it gives good performance in terms of Return Loss (RL) which is < -10 dB, impedance bandwidth with maximum Bandwidth (BW) up to 0.21 GHz and realized gains with maximum gain up to 3.28 dBi. Antenna is simulated with open stub and without open stub structures to see the effect on impedance BW coverage. In addition to this, it is checked with human hand and head phantoms to assure that it falls within specified Specific Absorption Rate (SAR) limits.

Keywords: Coplanar feed, L shaped ground, MLA, phantom, SAR, stub.

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Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic

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In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.

Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.

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