Search results for: dynamic Bayesian networks

Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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Authors: Sanju Vaidya, Aihua Li

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Vulnerability measures and topological indices are crucial in solving various problems such as the stability of the communication networks and development of mathematical models for chemical compounds. In 1947, Harry Wiener introduced a topological index related to molecular branching. Now there are more than 100 topological indices for graphs. For example, Hosoya polynomials (also called Wiener polynomials) were introduced to derive formulas for certain vulnerability measures and topological indices for various graphs. In this paper, we will find a relation between the Hosoya polynomials of any graph and its Mycielskian graph. Additionally, using this we will compute vulnerability measures, closeness and betweenness centrality, and extended Wiener indices. It is fascinating to see how Hosoya polynomials are useful in the two diverse fields, cybersecurity and chemistry.

Keywords: hosoya polynomial, mycielskian graph, graph vulnerability measure, topological index

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Authors: Kiyoumars Roushangar, Saeid Sadaghian

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Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

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Authors: Midhun Xavier

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This paper introduces a method to verify multi-agent systems in industrial control systems using blockchain technology. The proposed solution enables to record and verify each process that occurs while generating a customized product using Ethereum-based smart contracts. Node-Red software agents are developed with the help of semantic web technologies, and these software agents interact with IEC 61499 function blocks to execute the processes. The agent associated with each mechatronic component and its controller can communicate with the blockchain to record various events that occur during each process, and the latter smart contract helps to verify these process orders of the customized product.

Keywords: blockchain, Ethereum, node-red, IEC 61499, multi-agent system, MQTT

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Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn

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In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.

Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter

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Authors: M.Goodarzi, M.Mohammadi, M. Rezaee

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The technical analysis of using solar energy and electricity for water pumping in the Khuzestan province in Iran is investigated. For this purpose, the ecological conditions such as the weather data, air clearness and sunshine hours are analyzed. The nature of groundwater in the region was examined in terms of depth, static and dynamic head, water pumping rate.Three configurations for solar water pumping system were studied in this thesis; AC solar water pumping with storage battery, AC solar water pumping with storage tank and DC direct solar water pumping.

Keywords: technical feasibility, solar energy, photovoltaic systems, photovoltaic water pumping system

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Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

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Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

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Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

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Authors: Marcelo Sanhueza Cartes, Nelson Maureira Carsalade

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This research evaluates the effectiveness of a pallet isolation device for the protection of selective-type industrial storage racks. The device works only in the longitudinal direction of the aisle, and it is made up of a platform installed on the rack beams. At both ends, the platform is connected to the rack structure by means of a spring-damper system working in parallel. A system of wheels is arranged between the isolation platform and the rack beams in order to reduce friction, decoupling of the movement and improve the effectiveness of the device. The latter is evaluated by the reduction of the maximum dynamic responses of basal shear load and story drift in relation to those corresponding to the same rack with the traditional construction system. In the first stage, numerical simulations of industrial storage racks were carried out with and without the pallet isolation device. The numerical results allowed us to identify the archetypes in which it would be more appropriate to carry out experimental tests, thus limiting the number of trials. In the second stage, experimental tests were carried out on a shaking table to a select group of full-scale racks with and without the proposed device. The movement simulated by the shaking table was based on the Mw 8.8 magnitude earthquake of February 27, 2010, in Chile, registered at the San Pedro de la Paz station. The peak ground acceleration (PGA) was scaled in the frequency domain to fit its response spectrum with the design spectrum of NCh433. The experimental setup contemplates the installation of sensors to measure relative displacement and absolute acceleration. The movement of the shaking table with respect to the ground, the inter-story drift of the rack and the pallets with respect to the rack structure were recorded. Accelerometers redundantly measured all of the above in order to corroborate measurements and adequately capture low and high-frequency vibrations, whereas displacement and acceleration sensors are respectively more reliable. The numerical and experimental results allowed us to identify that the pallet isolation period is the variable with the greatest influence on the dynamic responses considered. It was also possible to identify that the proposed device significantly reduces both the basal cut and the maximum inter-story drift by up to one order of magnitude.

Keywords: pallet isolation system, industrial storage racks, basal shear load, interstory drift.

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Authors: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: D. Touil, L. Ouadah

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An industrial model of cement grinding circuit is proposed on the basis of sampling surveys undertaken in the Meftah cement plant in Algiers, Algeria. The ball mill is described by a series of equal fully mixed stages that incorporates the effect of air sweeping. The kinetic parameters of this material in the energy normalized form obtained using the data of batch dry ball milling are taken into account in developing the present scale-up procedure. The dynamic separator is represented by the air classifier selectivity equation corrected by empirical factors. The model is incorporated in computer program that predict full size distributions and mass flow rates for all streams in a circuit under a particular set of operating conditions.

Keywords: grinding circuit, clinker, cement, modeling, population balance, energy

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Authors: Yang Chen, Lili Fu

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Promoting urban regeneration in existing areas has been elevated to a national strategy in China. In this context, because of the multidimensional sustainable effect through the intensive use of land, mixed-use development has become an important objective for high-quality urban regeneration in the inner city. However, in the long period of time since China's reform and opening up, the "unbalanced phenomenon" of mixed-use development in China's inner cities has been very serious. On the one hand, the excessive focus on certain individual spaces has led to an increase in the level of mixed-use development in some areas, substantially ahead of others, resulting in a growing gap between different parts of the inner city; On the other hand, the excessive focus on a one-dimensional element of the spatial organization of mixed-use development, such as the enhancement of functional mix or spatial capacity, has led to a lagging phenomenon or neglect in the construction of other dimensional elements, such as pedestrian permeability, green environmental quality, social inclusion, etc. This phenomenon is particularly evident in the central area of the inner city, and it clearly runs counter to the need for sustainable development in China's new era. Therefore, a rational qualitative and quantitative analysis of the "unbalanced phenomenon" will help to identify the problem and provide a basis for the formulation of relevant optimization plans in the future. This paper builds a dynamic evaluation method of mixed-use development based on a meta-dimensional model and then uses spatial evolution analysis and spatial consistency analysis with ArcGIS software to reveal the "unbalanced phenomenon " in over the past 40 years of the central city area in Nanjing, a China’s typical city facing regeneration. This study result finds that, compared to the increase in functional mix and capacity, the dimensions of residential space mix, public service facility mix, pedestrian permeability, and greenness in Nanjing's city central area showed different degrees of lagging improvement, and the unbalanced development problems in each part of the city center are different, so the governance and planning plan for future mixed-use development needs to fully address these problems. The research methodology of this paper provides a tool for comprehensive dynamic identification of mixed-use development level’s change, and the results deepen the knowledge of the evolution of mixed-use development patterns in China’s inner cities and provide a reference basis for future regeneration practices.

Keywords: mixed-use development, unbalanced phenomenon, the meta-dimensional model, over the past 40 years of Nanjing, China

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Authors: Nazeef, Suleiman, Umar, Danladi Muhammad, Ja'afar Ali, Zaliha Adamu Umar

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The population dynamics of Auchenoglanis occidentalis from the Dadin-Kowa reservoir were studied. Population dynamic parameters such as growth, mortality and recruitment patterns were analyzed using length frequency data over a 12-month period employing FiSAT II software. Findings revealed that LWR (b - constant) = 2.88, K = 0.72 -yr., L∞ = 40.91 cm and Tmax = 3.57 years and Ɵ’ = 3.14. Mortality indices revealed that natural mortality (M = 1.39), fishing mortality (F = 0.22) and exploitation ratio (E = 0.14), Lc/L∞ = 0.48, Emax = 0.64, while Lopt = 26.4 cm. Uni-modal recruitment peak observed with Lm = 27.3 cm. A restocking program is suitable to ensure its continuous existence as it seems to have a low population.

Keywords: fish population dynamics, auchenoglanis occidentalis, FISAT II, natural mortality

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Authors: Qinglin Shu

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Based on the analysis of the structural vibration comfort of a domestic bridge, this paper studies the vibration reduction control principle of TMD, the derivation process of design parameter optimization and how to simulate TMD in the finite element software ANSYS. The research shows that, in view of the problem that the comfort level of a bridge exceeds the limit in individual working conditions, the vibration reduction control design of the bridge can effectively reduce the vibration of the structure by using TMD. Calculations show that when the mass ratio of TMD is 0.01, the vibration reduction rate under different working conditions is more than 90%, and the dynamic displacement of the TMD mass block is within 0.01m, indicating that the design of TMD is reasonable and safe.

Keywords: pedestrian bridges, human-induced vibration, comfort, tuned mass dampers

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Authors: J. Y. Heo, H. G. Sung

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Numerical simulations have been performed for assessment of compressibility correction of two-equation turbulence models suitable for large scale separation flows perturbed by pintle strokes. In order to take into account pintle movement, a sliding mesh method was applied. The chamber pressure, mass flow rate, and thrust have been analyzed, and the response lag and sensitivity at the chamber and nozzle were estimated for a movable pintle. The nozzle performance for pintle reciprocating as its insertion and extraction processes, were analyzed to better understand the dynamic performance of the pintle nozzle.

Keywords: pintle, sliding mesh, turbulent model, compressibility correction

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Authors: Ikhlas Ahmed, Jamillah Zamoon

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The human receptor for advanced glycation end product is a plasma membrane receptor with an intrinsically disordered region. The protein consists of three extracellular domains, a single membrane spanning transmembrane domain, and a cytosolic domain which is intrinsically disordered and responsible for signaling. The disordered nature of the cytosolic domain allows it to be dynamic in solution. This receptor self-associates to higher forms. The association is triggered by ligand, metal or by the extracellular domain. Fluorescence spectroscopy technique is used to test the self-association of the different concentrations of the cytosolic domain. This work has concluded that the cytosolic domain of this receptor also self-associates. Moreover, the self-association does not require ligand or metal.

Keywords: fluorescence spectroscopy, hRAGE, IDP, Self-association

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 193

Authors: Suci Lestari Yuana, Shofi Fatihatun Sholihah, Derarika Ensta Jesse

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Textile is one of buyer-driven industry which rely on label trust from the consumers. Most of textile manufacturers produce textile and textile products based on consumer demands. The company’s policy is highly depend on the dynamic evolution of consumers behavior. Recently, ecofriendly has become one of the most important factor of western consumers to purchase the textile and textile product (TPT) from the company. In that sense, companies from developing countries are encouraged to follow western consumers values. Some examples of ecolabel certificate are ISO (International Standard Organisation), Lembaga Ekolabel Indonesia (Indonesian Ecolabel Instution) and Global Ecolabel Network (GEN). The submission of national company to international standard raised a critical question whether this is a reflection towards the legitimation of global norms into national policy or it is actually a practical strategy of the company to gain global consumer. By observing one of the prominent textile company in Indonesia, this research is aimed to discuss what kind of impetus factors that cause a company to use ecolabel and what is the meaning behind it. Whether it comes from normative power or the strategy of the company. This is a qualitative research that choose a company in Sukoharjo, Central Java, Indonesia as a case study in explaining the pratice of ecolabelling by textitle company. Some deep interview is conducted with the company in order to get to know the ecolabelling process. In addition, this research also collected some document which related to company’s ecolabelling process and its impact to company’s value. The finding of the project reflected issues that concerned several issues: (1) role of media as consumer information (2) role of government and non-government actors as normative agency (3) role of company in social responsibility (4) the ecofriendly consciousness as a value of the company. As we know that environmental norms that has been admitted internationally has changed the global industrial process. This environmental norms also pushed the companies around the world, especially the company in Sukoharjo, Central Java, Indonesia to follow the norm. The neglection toward the global norms will remained the company in isolated and unsustained market that will harm the continuity of the company. So, in buyer-driven industry, the characteristic of company-consumer relations has brought a fast dynamic evolution of norms and values. The creation of global norms and values is circulated by passing national territories or identities.

Keywords: ecolabeling, waste management, CSR, normative power

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Authors: Tzu-Ting Hu, Jung-Der Wang, Ming-Yeng Lin, Jin-Luh Chen, Perng-Jy Tsai

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The vinyl chloride monomer (VCM) has been classified as group 1 (human) carcinogen by the IARC. Workers exposed to VCM are known associated with the development of the liver cancer and hence might cause economical and health losses. Particularly, for those work for the petrochemical industry have been seriously concerned in the environmental and occupational health field. Considering assessing workers’ health risks and their resultant economical and health losses requires the establishment of long-term VCM exposure data for any similar exposure group (SEG) of interest, the development of suitable technologies has become an urgent and important issue. In the present study, VCM exposures for petrochemical industry workers were determined firstly based on the database of the 'Workplace Environmental Monitoring Information Systems (WEMIS)' provided by Taiwan OSHA. Considering the existence of miss data, the reconstruction of historical exposure techniques were then used for completing the long-term exposure data for SEGs with routine operations. For SEGs with non-routine operations, exposure modeling techniques, together with their time/activity records, were adopted for determining their long-term exposure concentrations. The Bayesian decision analysis (BDA) was adopted for conducting exposure and health risk assessments for any given SEG in the petrochemical industry. The resultant excessive cancer risk was then used to determine the corresponding loss of quality-adjusted life expectancy (QALE). Results show that low average concentrations can be found for SEGs with routine operations (e.g., VCM rectification 0.0973 ppm, polymerization 0.306 ppm, reaction tank 0.33 ppm, VCM recovery 1.4 ppm, control room 0.14 ppm, VCM storage tanks 0.095 ppm and wastewater treatment 0.390 ppm), and the above values were much lower than that of the permissible exposure limit (PEL; 3 ppm) of VCM promulgated in Taiwan. For non-routine workers, though their high exposure concentrations, their low exposure time and frequencies result in low corresponding health risks. Through the consideration of exposure assessment results, health risk assessment results, and QALE results simultaneously, it is concluded that the proposed method was useful for prioritizing SEGs for conducting exposure abatement measurements. Particularly, the obtained QALE results further indicate the importance of reducing workers’ VCM exposures, though their exposures were low as in comparison with the PEL and the acceptable health risk.

Keywords: exposure assessment, health risk assessment, petrochemical industry, quality-adjusted life years, vinyl chloride monomer

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Authors: Reza Sirjani, Nobosse Tafem Bolan

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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

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Authors: F. Rahmani, F. Razaghian, A. R. Kashaninia

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This article proposes a new method for application in communication circuit systems that increase efficiency, PAE, output power and gain in the circuit. The proposed method is based on a combination of switching class-E and class-J and has been termed class-EJ. This method was investigated using both theory and simulation to confirm ~72% PAE and output power of > 39 dBm. The combination and design of the proposed power amplifier accrues gain of over 15dB in the 2.9 to 3.5 GHz frequency bandwidth. This circuit was designed using MOSFET and high power transistors. The load- and source-pull method achieved the best input and output networks using lumped elements. The proposed technique was investigated for fundamental and second harmonics having desirable amplitudes for the output signal.

Keywords: power amplifier (PA), high power, class-J and class-E, high efficiency

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Latif Adnane, Benaatou Wafa, Pla Vicent

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Handover is of great significance to achieve seamless connectivity in wireless networks. This paper gives an impression of the main factors which are being affected by the soft and the hard handovers techniques. To know and understand the handover process in The Universal Mobile Telecommunications System (UMTS) network, different statistics are calculated. This paper focuses on the quality of service (QoS) of soft and hard handover in UMTS network, which includes the analysis of received power, signal to noise radio, throughput, delay traffic, traffic received, delay, total transmit load, end to end delay and upload response time using OPNET simulator.

Keywords: handover, UMTS, mobility, simulation, OPNET modeler

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Authors: Dora Triki, Irena Vida, Claude Obadia

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Social networks such as e-Forums or dating sites often face the reluctance of key members to participate. Relying on the conation theory, this study investigates this phenomenon and proposes solutions to mitigate the issue. We show that highly experienced e-Forum members refuse to share business information in a peer to peer information exchange forums. However, forums managers can mitigate this behavior by developing a sentiment of belongingness to the network. Furthermore, by selecting only elite forum participants with ample experience, they can reduce the reluctance of key information providers to engage in information exchange. Our hypotheses are tested with PLS structural equations modeling using survey data from members of a French e-Forum dedicated to the exchange of business information about exporting.

Keywords: conation, e-Forum, information exchange, members participation

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Authors: Margarida Franca

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The influence of the ‘cultural turn’ movement and the consequent deconstruction of scientific thought allowed geography and other social sciences to open or deepen their studies based on the analysis of multiple identities, on singularities, on what is particular or what marks the difference between individuals. In the context of postmodernity, the geography of religion has gained a favorable scientific, thematic and methodological focus for the qualitative and subjective interpretation of various religious identities, sacred places, territories of belonging, religious communities, among others. In the context of ‘late modernity’ or ‘net modernity’, sacred places and the definition of a network of sacred territories allow believers to attain the ‘ontological security’. The integration on a religious group or a local community, particularly a religious community, allows human beings to achieve a sense of belonging, familiarity or solidarity and to overcome, in part, some of the risks or fears that society has discovered. The importance of sacred places comes not only from their inherent characteristics (eg transcendent, mystical and mythical, respect, intimacy and abnegation), but also from the possibility of adding and integrating members of the same community, creating bonds of belonging, reference and individual and collective memory. In addition, the formation of different networks of sacred places, with multiple scales and dimensions, allows the human being to identify and structure his times and spaces of daily life. Thus, each individual, due to his unique identity and life and religious paths, creates his own network of sacred places. The territorial expression of religious identity allows to draw a variable and unique geography of sacred places. Through the case study of the practicing Catholic population in the diocese of Coimbra (Portugal), the aim is to study the territorial expression of the religious identity of the different local communities of this city. Through a survey of six parishes in the city, we sought to identify which factors, qualitative or not, define the different territorial expressions on a local, national and international scale, with emphasis on the socioeconomic profile of the population, the religious path of the believers, the religious group they belong to and the external interferences, religious or not. The analysis of these factors allows us to categorize the communities of the city of Coimbra and, for each typology or category, to identify the specific elements that unite the believers to the sacred places, the networks and religious territories that structure the religious practice and experience and also the non-representational landscape that unifies and creates memory. We conclude that an apparently homogeneous group, the Catholic community, incorporates multitemporalities and multiterritorialities that are necessary to understand the history and geography of a whole country and of the Catholic communities in particular.

Keywords: geography of religion, sacred places, territoriality, Catholic Church

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Authors: Akwesi Assensoh-Kodua

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Online Social Networks (OSN) has come and gone, yet the explosion of business activities on such platforms continuous to surge high, giving advantage to the bold entrepreneurs. It is therefore a practical requirement that practitioners and researchers understand the key determinants of costumers’ online social network business activities and continuance intention. An exploratory literature research to examine OSN continuous intention of business participants on OSN revealed that the practice of doing business on social network has come to stay and the following factors are the likely drivers for this new business model: perceived trust, perceived ease of use, confirmation, habit, social norm, perceived behavioural control, expected benefit, and satisfaction are the most probable factors that can lead to online social network (OSN) continuance intention.

Keywords: online social network, continuance intention, business continuance

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

Procedia PDF Downloads 86