Search results for: Radial Basis Network.

Authors: S. Chabbak

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In a widely globalized world, the influence of audiovisual translation on the culture and identity of audiences is unmistakable. However, in the Arab World, there is a noticeable disproportion between this growing influence and the research carried out in the field. As a matter of fact, the voiced-over documentary is one of the most abundantly translated genres in the Arab World that carries lots of ideological elements which are in many cases rendered by manipulation. However, voiced-over documentaries have hardly received any focused attention from researchers in the Arab World. This paper attempts to scrutinize the process of translation of voiced-over documentaries in the Arab World, from French into Arabic in the present case study, by sub-categorizing the ideological items subject to manipulation, identifying the techniques utilized in their translation and exploring the potential extra-linguistic factors that prompt translation agents to opt for manipulative translation. The investigation is based on a corpus of 94 episodes taken from a series entitled 360° GEO Reports, produced by the French German network ARTE in French, and acquired, translated and aired by Al Jazeera Documentary Channel for Arab audiences. The results yielded 124 cases of manipulation in four sub-categories of ideological items, and the use of 10 different oblique procedures in the process of manipulative translation. The study also revealed that manipulation is in most of the instances dictated by the editorial line of the broadcasting channel, in addition to the religious, geopolitical and socio-cultural peculiarities of the target culture.

Keywords: Audiovisual translation, ideological items, manipulation, voiced-over documentaries.

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: Artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization.

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Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: Growth management, land use externalities, land value, spatial panel dynamic.

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Authors: Chun-Der Chen, Yi-Wen Fan, Cheng-Kiang Farn

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In today-s competitive global business environment, the concept of supply chain management (SCM) continues to become increasingly market-oriented, shifting the primary driver of the value chain from supply to demand. Recent recommendations encourage researchers to focus investigations on the supply chain process integration (SCPI) capabilities that integrate a focal firm with its network of suppliers and business customers to create value for it. However, theoretical and empirical researches pertaining to the antecedents and consequences of a focal firm-s SCPI capabilities have been limited and piecemeal. The purpose of this study is to investigate the critical determinants and consequences of a focal firm-s SCPI capabilities. We test our proposed research framework using a sample of 139 sales managers of manufacturing industries in Taiwan, our research findings show that (1) both perceived business customer-s power and focal firm-s market-oriented culture positively influences a focal firm-s SCPI capabilities, and (2) SCPI capabilities positively influence a focal firm-s SCM performance, both operational and strategic benefits. Implications for practitioners and researchers and suggestions for future research are also addressed in this study.

Keywords: Supply chain process integration capabilities, Perceived business customer's power, Market-oriented culture, Supply chain management performance.

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Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu

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In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.

Keywords: Connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control.

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Authors: Souvik Bhattacharyya, Gautam Sanyal

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In recent years, everything is trending toward digitalization and with the rapid development of the Internet technologies, digital media needs to be transmitted conveniently over the network. Attacks, misuse or unauthorized access of information is of great concern today which makes the protection of documents through digital media a priority problem. This urges us to devise new data hiding techniques to protect and secure the data of vital significance. In this respect, steganography often comes to the fore as a tool for hiding information. Steganography is a process that involves hiding a message in an appropriate carrier like image or audio. It is of Greek origin and means "covered or hidden writing". The goal of steganography is covert communication. Here the carrier can be sent to a receiver without any one except the authenticated receiver only knows existence of the information. Considerable amount of work has been carried out by different researchers on steganography. In this work the authors propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by selecting the embedding pixels using some mathematical function and then finds the 8 neighborhood of the each selected pixel and map each bit of the secret message in each of the neighbor pixel coordinate position in a specified manner. Before embedding a checking has been done to find out whether the selected pixel or its neighbor lies at the boundary of the image or not. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Keywords: Cover Image, LSB, Pixel Coordinate Position (PCP), Stego Image.

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Authors: Javed Parvez, Mushtaq Ahmad Peer

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Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Keywords: Bandwidth Reservation, Congestion, DynamicNetwork Topology, End-to-End Delay, Flexible QoS Model forMANET(FQMM), Hidden Terminal, Mobile AdhocNetwork(MANET), Packet Jitter, Queuing, Quality-of-Service(QoS), Relative Bandwidth Service Differentiation(RBSD), Resource ReSerVation Protocol (RSVP).

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Authors: B. Bahmani Firouzi, T. Niknam, M. Nayeripour

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With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.

Keywords: Distributed Generation, Optimal Operation Management of distribution networks, Ant Colony Optimization(ACO).

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Authors: Bakari M. M. Mwinyiwiwa

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Renewable Energy based microgrids are being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. The technical challenges associated with the operation and controls are immense. Electricity generation by Renewable Energy Sources is of stochastic nature such that there is a demand for regulation of voltage output in order to satisfy the standard loads’ requirements. In a renewable energy based microgrid, the energy sources give stochastically variable magnitude AC or DC voltages. AC voltage regulation of micro and mini sources pose practical challenges as well as unbearable costs. It is therefore practically and economically viable to convert the voltage outputs from stochastic AC and DC voltage sources to constant DC voltage to satisfy various DC loads including inverters which ultimately feed AC loads. This paper presents results obtained from SEPIC converter based DC bus voltage regulator as a case study for renewable energy microgrid application. Real-Time Simulation results show that upon appropriate choice of controller parameters for control of the SEPIC converter, the output DC bus voltage can be kept constant regardless of wide range of voltage variations of the source. This feature is particularly important in the situation that multiple renewable sources are to be integrated to supply a microgrid under main grid integration or isolated modes of operation.

Keywords: DC Voltage Regulator, microgrid, multisource, Renewable Energy, SEPIC Converter.

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: Prospecting, technology forecasting, photovoltaic, urban residences.

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Authors: Mst. Nilufa Sultana, Shatirah Akib, Muhammad Aqeel Ashraf, Mohamed Roseli Zainal Abidin

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Most people today are aware that global climate change is not just a scientific theory but also a fact with worldwide consequences. Global climate change is due to rapid urbanization, industrialization, high population growth and current vulnerability of the climatic condition. Water is becoming scarce as a result of global climate change. To mitigate the problem arising due to global climate change and its drought effect, harvesting rainwater from green roofs, an environmentally-friendly and versatile technology, is becoming one of the best assessment criteria and gaining attention in Malaysia. This paper addresses the sustainability of green roofs and examines the quality of water harvested from green roofs in comparison to rainwater. The factors that affect the quality of such water, taking into account, for example, roofing materials, climatic conditions, the frequency of rainfall frequency and the first flush. A green roof was installed on the Humid Tropic Centre (HTC) is a place of the study on monitoring program for urban Stormwater Management Manual for Malaysia (MSMA), Eco-Hydrological Project in Kuala Lumpur, and the rainwater was harvested and evaluated on the basis of four parameters i.e., conductivity, dissolved oxygen (DO), pH and temperature. These parameters were found to fall between Class I and Class III of the Interim National Water Quality Standards (INWQS) and the Water Quality Index (WQI). Some preliminary treatment such as disinfection and filtration could likely to improve the value of these parameters to class I. This review paper clearly indicates that there is a need for more research to address other microbiological and chemical quality parameters to ensure that the harvested water is suitable for use potable water for domestic purposes. The change in all physical, chemical and microbiological parameters with respect to storage time will be a major focus of future studies in this field.

Keywords: Green roofs, INWQS, MSMA-SME, Rainwater harvesting.

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Authors: J. Hey, D. A. Howey, R. Martinez-Botas, M. Lamperth

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This paper presents the development of a hybrid thermal model for the EVO Electric AFM 140 Axial Flux Permanent Magnet (AFPM) machine as used in hybrid and electric vehicles. The adopted approach is based on a hybrid lumped parameter and finite difference method. The proposed method divides each motor component into regular elements which are connected together in a thermal resistance network representing all the physical connections in all three dimensions. The element shape and size are chosen according to the component geometry to ensure consistency. The fluid domain is lumped into one region with averaged heat transfer parameters connecting it to the solid domain. Some model parameters are obtained from Computation Fluid Dynamic (CFD) simulation and empirical data. The hybrid thermal model is described by a set of coupled linear first order differential equations which is discretised and solved iteratively to obtain the temperature profile. The computation involved is low and thus the model is suitable for transient temperature predictions. The maximum error in temperature prediction is 3.4% and the mean error is consistently lower than the mean error due to uncertainty in measurements. The details of the model development, temperature predictions and suggestions for design improvements are presented in this paper.

Keywords: Electric vehicle, hybrid thermal model, transient temperature prediction, Axial Flux Permanent Magnet machine.

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Authors: G. S. Ayyappan, M. Raja Raghavan, R. Poonthalir, Kota Srinivas, B. Ramesh Babu

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Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.

Keywords: Best operating point, iLON smart server, motor asset management, LONWORKS, Modbus RTU, motor performance.

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Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, Charnes Cooper & Rhodes (CCR) Model, network data envelopment analysis, Iran electricity power chain.

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Authors: R. Reka, R. S. D. Wahidabanu

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The conventional routing protocol designed for MANET fail to handle dynamic movement and self-starting behavior of the node effectively. Every node in MANET is considered as forward as well receiver node and all of them participate in routing the packet from source to the destination. While the interconnection topology is highly dynamic, the performance of the most of the routing protocol is not encouraging. In this paper, a reliable broadcast approach for MANET is proposed for improving the transmission rate. The MANET is considered with asymmetric characteristics and the properties of the source and destination nodes are different. The non-forwarding node list is generated with a downstream node and they do not participate in the routing. While the forwarding and non-forwarding node is constructed in a conventional way, the number of nodes in non-forwarding list is more and increases the load. In this work, we construct the forwarding and non-forwarding node optimally so that the flooding and broadcasting is reduced to certain extent. The forwarded packet is considered as acknowledgements and the non-forwarding nodes explicitly send the acknowledgements to the source. The performance of the proposed approach is evaluated in NS2 environment. Since the proposed approach reduces the flooding, we have considered functionality of the proposed approach with AODV variants. The effect of network density on the overhead and collision rate is considered for performance evaluation. The performance is compared with the AODV variants found that the proposed approach outperforms all the variants.

Keywords: Flooding, Forwarded Nodes, MANET, Non-forwarding nodes, Routing protocols.

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: Data mining, K-means, road traffic accidents, Waze, Weka.

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Authors: Jong-Moon Chung, Hyung-Weon Cho, Ki-Yong Jin, Min-Hee Cho

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In this paper, we present an analytical framework for the evaluation of the uplink performance of multihop cellular networks based on dynamic time division duplex (TDD). New wireless broadband protocols, such as WiMAX, WiBro, and 3G-LTE apply TDD, and mobile communication protocols under standardization (e.g., IEEE802.16j) are investigating mobile multihop relay (MMR) as a future technology. In this paper a novel MMR TDD scheme is presented, where the dynamic range of the frame is shared to traffic resources of asymmetric nature and multihop relaying. The mobile communication channel interference model comprises of inner and co-channel interference (CCI). The performance analysis focuses on the uplink due to the fact that the effects of dynamic resource allocation show significant performance degradation only in the uplink compared to time division multiple access (TDMA) schemes due to CCI [1-3], where the downlink results to be the same or better.The analysis was based on the signal to interference power ratio (SIR) outage probability of dynamic TDD (D-TDD) and TDMA systems,which are the most widespread mobile communication multi-user control techniques. This paper presents the uplink SIR outage probability with multihop results and shows that the dynamic TDD scheme applying MMR can provide a performance improvement compared to single hop applications if executed properly.

Keywords: Co-Channel Interference, Dynamic TDD, MobileMultihop Reply, Cellular Network, Time Division Multiple Access.

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Authors: Corneliu Sofronie, Roxana Zubcov

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Cognitive Science appeared about 40 years ago, subsequent to the challenge of the Artificial Intelligence, as common territory for several scientific disciplines such as: IT, mathematics, psychology, neurology, philosophy, sociology, and linguistics. The new born science was justified by the complexity of the problems related to the human knowledge on one hand, and on the other by the fact that none of the above mentioned sciences could explain alone the mental phenomena. Based on the data supplied by the experimental sciences such as psychology or neurology, models of the human mind operation are built in the cognition science. These models are implemented in computer programs and/or electronic circuits (specific to the artificial intelligence) – cognitive systems – whose competences and performances are compared to the human ones, leading to the psychology and neurology data reinterpretation, respectively to the construction of new models. During these processes if psychology provides the experimental basis, philosophy and mathematics provides the abstraction level utterly necessary for the intermission of the mentioned sciences. The ongoing general problematic of the cognitive approach provides two important types of approach: the computational one, starting from the idea that the mental phenomenon can be reduced to 1 and 0 type calculus operations, and the connection one that considers the thinking products as being a result of the interaction between all the composing (included) systems. In the field of psychology measurements in the computational register use classical inquiries and psychometrical tests, generally based on calculus methods. Deeming things from both sides that are representing the cognitive science, we can notice a gap in psychological product measurement possibilities, regarded from the connectionist perspective, that requires the unitary understanding of the quality – quantity whole. In such approach measurement by calculus proves to be inefficient. Our researches, deployed for longer than 20 years, lead to the conclusion that measuring by forms properly fits to the connectionism laws and principles.

Keywords: complementary methodology, connection approach, networks without scaling, quantum psychology.

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Authors: Saule Mussabekova

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Recent advances in genetics have allowed increasing acutely the capacities of the formation of reliable evidence in conducting forensic examinations. Thus, traces of biological origin are important sources of information about a crime. Currently, around the world, sexual offenses have increased, and among them are those in which the criminals use various detergents to remove traces of their crime. A feature of modern synthetic detergents is the presence of biological additives - enzymes. Enzymes purposefully destroy stains of biological origin. To study the nature and extent of the impact of modern washing powders on saliva stains on the physical evidence, specially prepared test specimens of different types of tissues to which saliva was applied have been examined. Materials and Methods: Washing machines of famous manufacturers of household appliances have been used with different production characteristics and advertised brands of washing powder for test washing. Over 3,500 experimental samples were tested. After washing, the traces of saliva were identified using modern research methods of forensic medicine. Results: The influence was tested and the dependence of the use of different washing programs, types of washing machines and washing powders in the process of establishing saliva trace and identify of the stains on the physical evidence while washing was revealed. The results of experimental and practical expert studies have shown that in most cases it is not possible to draw the conclusions in the identification of saliva traces on physical evidence after washing. This is a consequence of the effect of biological additives and other additional factors on traces of saliva during washing. Conclusions: On the basis of the results of the study, the feasibility of saliva traces of the stains on physical evidence after washing is established. The use of modern molecular genetic methods makes it possible to partially solve the problems arising in the study of unlaundered evidence. Additional study of physical evidence after washing facilitates detection and investigation of sexual offenses against women and children.

Keywords: Saliva research, modern synthetic detergents, laundry detergents, forensic medicine.

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Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: Roughness progression, empirical model, pavement performance, heavy duty pavement.

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Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

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Growing human population has placed increased demands on water supplies and spurred a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP, an IAEA sponsored program. DE-TOP has capabilities to analyze power generation systems coupled to desalination plants through various steam extraction positions, taking into consideration the isolation loop between the nuclear and the thermal desalination facilities (i.e., for radiological isolation).

Keywords: APR1400, Cogeneration, Desalination, DE-TOP, IAEA, MED, MED-TVC, MSF, RO.

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Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

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We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: Air pollution, dispersion, emissions, line sources, road traffic, urban transport.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

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Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows drawing conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stageby- stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: M. Umar Farooq, T. Ahmad Afridi, M. Zia-Ul-Islam Arsalan, U. Hussain Haider, S. Ullah

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Cancer, a leading fatal disease worldwide, can be treated with various techniques including radiation therapy. It involves the use of ionizing radiation to target cancer cells. On basis of source placement, radiation therapy is of two types i.e., Brachytherapy and External Beam Radiotherapy (EBRT). EBRT has evolved from 2-D conventional therapy to 3-D Conformal radiotherapy (3D-CRT) and then Intensity-Modulated Radiotherapy (IMRT). IMRT improves dose conformity and sparing of organs at risk. Volumetric Modulated Arc Therapy (VMAT) is a modern technique that uses treatment delivery in arcs with rotation of the gantry. In this report, a dosimetry comparison was performed between IMRT and VMAT. This study was conducted in the Radiotherapy Department of the Institute of Nuclear Medicine and Oncology Lahore (INMOL). Ten patients with Prostate Carcinoma were selected for this study to compare the methods. Simulation of these patients was done with help of a CT Simulator. All target volumes and organs were delineated by the oncologists. Then suitable fields/arcs were applied which cover volumes effectively. This was followed by the optimization of plans for both techniques for every patient. Finally, a comparison of evaluating parameters e.g., Conformity Index (CI), Volume Coverage, Homogeneity Index (HI), Organ Doses, and MUs (Monitor Units) was performed. We obtained better results of target conformity indices from VMAT (CI = 1.16) than IMRT (CI = 1.24). VMAT was better in organ sparing too. Also, VMAT shows fewer MUs (733 MUs) as compared to IMRT (2149 MUs). From this study, it is concluded that VMAT is a better treatment technique than IMRT. This technique will enhance treatment efficiency as it takes less time in obtaining the required results. Also, a very less scatter dose will be delivered to the patient.

Keywords: 2-D Conventional Radiotherapy, 3-D Conformal Radiotherapy, Intensity Modulated Radiotherapy, Prostate Carcinoma, Radiotherapy, Volumetric Modulated Arc Therapy.

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: Classifier ensemble, breast cancer survivability, data mining, SEER.

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Yosia Mulumba, Klaus Schmidt

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Financial Inclusion is considered a key pillar for development in most countries around the world. Access to affordable financial services in a country’s economy can be a driver to overcome poverty and reduce income inequalities, and thus increase economic growth. Nevertheless, the number of financially excluded populations in developing countries continues to be very high. This paper explores the role of Financial Technology (Fintech) as a key driver for achieving financial inclusion in developing countries post the COVID-19 pandemic with an emphasis on four East African countries: Kenya, Tanzania, Uganda, and Rwanda. The research paper is inspired by the positive disruption caused by the pandemic, which has compelled societies in East Africa to adapt and embrace the use of financial technology innovations, specifically Mobile Money Services (MMS), to access financial services. MMS has been further migrated and integrated with other financial technology innovations such as Mobile Banking, Micro Savings, and Loans, and Insurance, to mention but a few. These innovations have been adopted across key sectors such as commerce, health care, or agriculture. The research paper will highlight the Mobile Network Operators (MNOs) that are behind MMS, along with numerous innovative products and services being offered to the customers. It will also highlight the regulatory framework under which these innovations are being governed to ensure the safety of the customers' funds.

Keywords: Financial inclusion, financial technology, regulatory framework, mobile money services.

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Authors: Helene Eller

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The aim of non-profit organizations (NPO) is to provide services and goods for its clientele, with profit being a minor objective. By having this definition as the basic purpose of doing business, it is obvious that the goal of an organisation is to serve several bottom lines and not only the financial one. This approach is underpinned by the non-distribution constraint which means that NPO are allowed to make profits to a certain extent, but not to distribute them. The advantage is that there are no single shareholders who might have an interest in the prosperity of the organisation: there is no pie to divide. The gained profits remain within the organisation and will be reinvested in purposeful projects. Good governance is mandatory to support the aim of NPOs. Looking for a measure of good governance the principals of corporate governance (CG) will come in mind. The purpose of CG is direction and control, and in the field of NPO, CG is enlarged to consider the relationship to all important stakeholders who have an impact on the organisation. The recognition of more relevant parties than the shareholder is the link to corporate social responsibility (CSR). It supports a broader view of the bottom line: It is no longer enough to know how profits are used but rather how they are made. Besides, CSR addresses the responsibility of organisations for their impact on society. When transferring the concept of CSR to the non-profit area it will become obvious that CSR with its distinctive features will match the aims of NPOs. As a consequence, NPOs who apply CG apply also CSR to a certain extent. The research is designed as a comprehensive theoretical and empirical analysis. First, the investigation focuses on the theoretical basis of both concepts. Second, the similarities and differences are outlined and as a result the interconnection of both concepts will show up. The contribution of this research is manifold: The interconnection of both concepts when applied to NPOs has not got any attention in science yet. CSR and governance as integrated concept provides a lot of advantages for NPOs compared to for-profit organisations which are in a steady justification to show the impact they might have on the society. NPOs, however, integrate economic and social aspects as starting point. For NPOs CG is not a mere concept of compliance but rather an enhanced concept integrating a lot of aspects of CSR. There is no “either-nor” between the concepts for NPOs.

Keywords: Business ethics, corporate governance, corporate social responsibility, non-profit organisations, stakeholder theory.

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Authors: C. Ardil

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This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.

Keywords: Facility Location Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, Preference Programming, Location Selection, WSM, TOPSIS, VIKOR

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Authors: Matías Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, most roads in rural areas are dirt road. They require frequent maintenance since they are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the maintenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: Dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision.

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