Search results for: multicriteria decision analysis.

Authors: Avelino Mondlane, Karin Hansson, Oliver Popov, Xavier Muianga

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This paper discusses the role and importance of Information and Communication Technologies (ICT) and social Networking (SN) in the process of decision making for Flood Risk and Knowledge Management Strategies. We use Mozambique Red Cross (CVM) as the case study and further more we address scenarios for flood risk management strategies, using earlier warning and social networking and we argue that a sustainable desirable stage of life can be achieved by developing scenario strategic planning based on backcasting.

Keywords: ICT, KM, scenario planning, backcasting and flood risk management.

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Authors: Ricardo C. Silva, Luiza A. P. Cantao, Akebo Yamakami

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Based on the fuzzy set theory this work develops two adaptations of iterative methods that solve mathematical programming problems with uncertainties in the objective function and in the set of constraints. The first one uses the approach proposed by Zimmermann to fuzzy linear programming problems as a basis and the second one obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. We outline similarities between the two iterative methods studied. Selected examples from the literature are presented to validate the efficiency of the methods addressed.

Keywords: Fuzzy Theory, Nonlinear Optimization, Fuzzy Mathematics Programming.

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Authors: Naoki Yamamoto, Jun Murakami, Chiharu Okuma, Yutaro Shigeto, Satoko Saito, Takashi Izumi, Nozomi Hayashida

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Multi-dimensional principal component analysis (PCA) is the extension of the PCA, which is used widely as the dimensionality reduction technique in multivariate data analysis, to handle multi-dimensional data. To calculate the PCA the singular value decomposition (SVD) is commonly employed by the reason of its numerical stability. The multi-dimensional PCA can be calculated by using the higher-order SVD (HOSVD), which is proposed by Lathauwer et al., similarly with the case of ordinary PCA. In this paper, we apply the multi-dimensional PCA to the multi-dimensional medical data including the functional independence measure (FIM) score, and describe the results of experimental analysis.

Keywords: multi-dimensional principal component analysis, higher-order SVD (HOSVD), functional independence measure (FIM), medical data, tensor decomposition

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Authors: Yiannis Smirlis, Dimitris K. Despotis

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This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.

Keywords: Data envelopment analysis, Greek universities, operating expenditures, ordinal data.

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Authors: P. Bhramara, V. D. Rao, K. V. Sharma , T. K. K. Reddy

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In designing of condensers, the prediction of pressure drop is as important as the prediction of heat transfer coefficient. Modeling of two phase flow, particularly liquid – vapor flow under diabatic conditions inside a horizontal tube using CFD analysis is difficult with the available two phase models in FLUENT due to continuously changing flow patterns. In the present analysis, CFD analysis of two phase flow of refrigerants inside a horizontal tube of inner diameter, 0.0085 m and 1.2 m length is carried out using homogeneous model under adiabatic conditions. The refrigerants considered are R22, R134a and R407C. The analysis is performed at different saturation temperatures and at different flow rates to evaluate the local frictional pressure drop. Using Homogeneous model, average properties are obtained for each of the refrigerants that is considered as single phase pseudo fluid. The so obtained pressure drop data is compared with the separated flow models available in literature.

Keywords: Adiabatic conditions, CFD analysis, Homogeneousmodel and Liquid – Vapor flow.

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Authors: Matheus Borges Carneiro, Fabiane Letícia Lizarelli, José Carlos de Toledo

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The evolution of quality management by companies was strongly enabled by, among others, ISO 9001 certification, which is considered a crucial requirement for several customers. Likewise, performance measurement provides useful insights for companies to identify the reflection of their decision-making process on their improvement. One of the most used performance measurement models is the balanced scorecard (BSC), which uses four perspectives to address a firm’s performance: financial, internal process, customer satisfaction, and learning and growth. Since ISO 9001 certified firms are likely to measure their performance through BSC approach, it is important to verify whether the certificate influences the firm performance or not. Therefore, this paper aims to verify the impact of ISO 9001:2015 on Brazilian firms’ performance based on the BSC perspective. Hence, nine certified companies located in the Southeast region of Brazil were studied through a multiple case study approach. Within this study, it was possible to identify the positive impact of ISO 9001 on firms’ overall performance, and four Critical Success Factors (CSFs) were identified as relevant on the linkage among ISO 9001 and firms’ performance: employee involvement, top management, process management, and customer focus. Due to the COVID-19 pandemic, the number of interviews was limited to the quality manager specialist, and the sample was limited since several companies were closed during the period of the study. This study presents an in-depth analysis of how the relationship between ISO 9001 certification and firms’ performance in a developing country is.

Keywords: Balanced scorecard, Brazilian firms’ performance, critical success factors, ISO 9001 certification, performance measurement.

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Authors: Maruto Masserie Sardadi, Mohd Shafry bin Mohd Rahim, Zahabidin Jupri, Daut bin Daman

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The latest Geographic Information System (GIS) technology makes it possible to administer the spatial components of daily “business object," in the corporate database, and apply suitable geographic analysis efficiently in a desktop-focused application. We can use wireless internet technology for transfer process in spatial data from server to client or vice versa. However, the problem in wireless Internet is system bottlenecks that can make the process of transferring data not efficient. The reason is large amount of spatial data. Optimization in the process of transferring and retrieving data, however, is an essential issue that must be considered. Appropriate decision to choose between R-tree and Quadtree spatial data indexing method can optimize the process. With the rapid proliferation of these databases in the past decade, extensive research has been conducted on the design of efficient data structures to enable fast spatial searching. Commercial database vendors like Oracle have also started implementing these spatial indexing to cater to the large and diverse GIS. This paper focuses on the decisions to choose R-tree and quadtree spatial indexing using Oracle spatial database in mobile GIS application. From our research condition, the result of using Quadtree and R-tree spatial data indexing method in one single spatial database can save the time until 42.5%.

Keywords: Indexing, Mobile GIS, MapViewer, Oracle SpatialDatabase.

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Authors: Antonios Maniatis

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The present paper focuses on human rights to the water and to the energy and has a scope to promote the legal status on sustainable construction. The right to water constitutes a typical example of 3G fundamental rights, like the right to enjoyment of energy, particularly of electricity, whilst the right to energy efficiency is a right of fourth generation. Both rights to water and energy are examined through their consecration in the framework of the above-mentioned generations. It results that not only decision-makers but also citizens should fight for the further consecration and adequate use of these crucial rights, having to do with the urgent problem of climate change and the sustainable development. The time for the principle of water and energy “rule of law” has come.

Keywords: Climate change law, energy (en + ergon) efficiency, fundamental rights, prosumer, water.

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Authors: Xing Jiankuan, Qin Zheng, Zhang Jinxue

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Decentralized Tuple Space (DTS) implements tuple space model among a series of decentralized hosts and provides the logical global shared tuple repository. Replication has been introduced to promote performance problem incurred by remote tuple access. In this paper, we propose a replication approach of DTS allowing replication policies self-adapting. The accesses from users or other nodes are monitored and collected to contribute the decision making. The replication policy may be changed if the better performance is expected. The experiments show that this approach suitably adjusts the replication policies, which brings negligible overhead.

Keywords: Decentralization, Replication Management, SelfAdaption, Tuple Space.

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Authors: Hyeondal Jeong, Yoonjung Baek

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This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: Positive psychological capital, satisfaction, commitment, OCB, creativity, meta-analysis.

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Authors: J. R. Wang, S. W. Chen, Y. Chiang, W. S. Hsu, J. H. Yang, Y. S. Tseng, C. Shih

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In this research, the HABIT analysis methodology was established for Maanshan nuclear power plant (NPP). The Final Safety Analysis Report (FSAR), reports, and other data were used in this study. To evaluate the control room habitability under the CO₂ storage burst, the HABIT methodology was used to perform this analysis. The HABIT result was below the R.G. 1.78 failure criteria. This indicates that Maanshan NPP habitability can be maintained. Additionally, the sensitivity study of the parameters (wind speed, atmospheric stability classification, air temperature, and control room intake flow rate) was also performed in this research.

Keywords: PWR, HABIT, habitability, Maanshan.

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Authors: Dimitrios J. Dimitriou

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Considering a worldwide tendency, air transports are growing very fast and many changes have taken place in planning, management and decision making process. Given the complexity of airport operation, the best use of existing capacity is the key driver of efficiency and productivity. This paper deals with the evaluation framework for the ground access at airports, by using a set of mode choice indicators providing key messages towards airport’s ground access performance. The application presents results for a sample of 12 European airports, illustrating recommendations to define policy and improve service for the air transport access chain.

Keywords: Air transport chain, airport ground access, airport access performance, airport policy.

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Authors: Mohammed H. Nafie, Ahmed F. Shalash

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With the advent of DSL services, high data rates are now available over phone lines, yet higher rates are in demand. In this paper, we optimize the transmit filters that can be used over wireline channels. Results showing the bit error rates when optimized filters are used, and with a decision feedback equalizer (DFE) employed in the receiver, are given. We then show that significantly higher throughput can be achieved by modeling the channel as a multiple input multiple output (MIMO) channel. A receiver that employs a MIMO-DFE that deals jointly with several users is proposed and shown to provide significant improvement over the conventional DFE.

Keywords: DFE, MIMO Channels, Receiver Architectures, Transmit Filters.

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Authors: Srikanth L., Neelima Satyam D.

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The transmission line towers are one of the important life line structures in the distribution of power from the source to the various places for several purposes. The predominant external loads which act on these towers are wind and earthquake loads. In this present study tower is analyzed using Indian Standards IS: 875:1987(Wind Load), IS: 802:1995(Structural steel), IS:1893:2002 (Earthquake) and dynamic analysis of tower has been performed considering ground motion of 2001 Bhuj Earthquake (India). The dynamic analysis was performed considering a tower system consisting two towers spaced 800m apart and 35m height each. This analysis has been performed using numerical time stepping finite difference method which is central difference method were employed by a developed MATLAB program to get the normalized ground motion parameters includes acceleration, frequency, velocity which are important in designing the tower. The tower is analyzed using response spectrum analysis.

Keywords: Response Spectra, Dynamic Analysis, Central Difference Method, Transmission Tower.

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Authors: Iveta Řepková

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The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: Data Envelopment Analysis, efficiency, Slovak banking sector, window analysis.

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: Behavior of winds, wind power, fuzzy logic, sustainable development.

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Authors: Zhang Yan, Yu Bin

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Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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Authors: Wenbin Zhang, Hantian Wu, Jian Tang

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An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.

Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.

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Authors: Jeffrey L. Duffany

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An optimal solution for a large number of constraint satisfaction problems can be found using the technique of substitution and elimination of variables analogous to the technique that is used to solve systems of equations. A decision function f(A)=max(A2) is used to determine which variables to eliminate. The algorithm can be expressed in six lines and is remarkable in both its simplicity and its ability to find an optimal solution. However it is inefficient in that it needs to square the updated A matrix after each variable elimination. To overcome this inefficiency the algorithm is analyzed and it is shown that the A matrix only needs to be squared once at the first step of the algorithm and then incrementally updated for subsequent steps, resulting in significant improvement and an algorithm complexity of O(n3).

Keywords: Algorithm, complexity, constraint, np-complete.

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Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

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The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: Input-Output Analysis, Monetary Input-Output Model, Manufacturing Process, Laptop Computer.

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Authors: Jeeeun Kim, Sungjoo Lee

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This research proposes a methodology for patent-citation-based technology input-output analysis by applying the patent information to input-output analysis developed for the dependencies among different industries. For this analysis, a technology relationship matrix and its components, as well as input and technology inducement coefficients, are constructed using patent information. Then, a technology inducement coefficient is calculated by normalizing the degree of citation from certain IPCs to the different IPCs (International patent classification) or to the same IPCs. Finally, we construct a Dependency Structure Matrix (DSM) based on the technology inducement coefficient to suggest a useful application for this methodology.

Keywords: Technology spillover effect, technology relationship, IO table, technology inducement coefficients, patent analysis, patent citation.

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Authors: R. Hosseingholizadeh

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This article presents a method for elections between the members of a group that is founded by fuzzy logic. Linguistic variables are objects for decision on election cards and deduction is based on t-norms and s-norms. In this election-s method election cards are questionnaire. The questionnaires are comprised of some questions with some choices. The choices are words from natural language. Presented method is accompanied by center of gravity (COG) defuzzification added up to a computer program by MATLAB. Finally the method is illustrated by solving two examples; choose a head for a research group-s members and a representative for students.

Keywords: fuzzy election, fuzzy electoral card, fuzzy inference, questionnaire.

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Authors: Mevlüt Burak Dalmış, Kemal Yaman

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In this study, flutter characteristics of cantilever rectangular plate structure under incompressible flow regime are investigated by comparing the results of commercial flutter analysis program ZAERO^© with wind tunnel tests conducted in Ankara Wind Tunnel (ART). A rectangular polycarbonate (PC) plate, 5x125x1000 mm in dimensions, is used for both numerical and experimental investigations. Analysis and test results are very compatible with each other. A comparison between two different solution methods (g and k-method) of ZAERO^© is also done. It is seen that, k-method gives closer result than the other one. However, g-method results are on conservative side and it is better to use conservative results namely g-method results. Even if the modal analysis results are used for the flutter analysis for this simple structure, a modal test should be conducted in order to validate the modal analysis results to have accurate flutter analysis results for more complicated structures.

Keywords: Flutter, plate, subsonic flow, wind tunnel.

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Authors: S. M. Amin Hosseini, Oriol Pons, Carmen Mendoza Arroyo, Albert de la Fuente

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In the aftermath of a natural disaster, the major challenge most cities and societies face, regardless of their diverse level of prosperity, is to provide temporary housing (TH) for the displaced population (DP). However, the features of TH, which have been applied in previous recovery programs, greatly varied from case to case. This situation demonstrates that providing temporary accommodation for DP in a short period time and usually in great numbers is complicated in terms of satisfying all the beneficiaries’ needs, regardless of the societies’ welfare levels. Furthermore, when previously used strategies are applied to different areas, the chosen strategies are most likely destined to fail, unless the strategies are context and culturally based. Therefore, as the population of disaster-prone cities are increasing, decision-makers need a platform to help to determine all the factors, which caused the outcomes of the prior programs. To this end, this paper aims to assess the problems, requirements, limitations, potential responses, chosen strategies, and their outcomes, in order to determine the main elements that have influenced the TH process. In this regard, and in order to determine a customizable strategy, this study analyses the TH programs of five different cases as: Marmara earthquake, 1999; Bam earthquake, 2003; Aceh earthquake and tsunami, 2004; Hurricane Katrina, 2005; and, L’Aquila earthquake, 2009. The research results demonstrate that the main vertexes of TH are: (1) local characteristics, including local potential and affected population features, (2) TH properties, which needs to be considered in four phases: planning, provision/construction, operation, and second life, and (3) natural hazards impacts, which embraces intensity and type. Accordingly, this study offers decision-makers the opportunity to discover the main vertexes, their subsets, interactions, and the relation between strategies and outcomes based on the local conditions of each case. Consequently, authorities may acquire the capability to design a customizable method in the face of complicated post-disaster housing in the wake of future natural disasters.

Keywords: Post-disaster temporary accommodation, urban resilience, natural disaster, local characteristic.

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision making has not been far-fetched. Proper classification of these textual information in a given context has also been very difficult. As a result, a systematic review was conducted from previous literature on sentiment classification and AI-based techniques. The study was done in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that could correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy using the knowledge gain from the evaluation of different artificial intelligence techniques reviewed. The study evaluated over 250 articles from digital sources like ACM digital library, Google Scholar, and IEEE Xplore; and whittled down the number of research to 52 articles. Findings revealed that deep learning approaches such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformer (BERT), and Long Short-Term Memory (LSTM) outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also required to develop a robust sentiment classifier. Results also revealed that data can be obtained from places like Twitter, movie reviews, Kaggle, Stanford Sentiment Treebank (SST), and SemEval Task4 based on the required domain. The hybrid deep learning techniques like CNN+LSTM, CNN+ Gated Recurrent Unit (GRU), CNN+BERT outperformed single deep learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of development simplicity and AI-based library functionalities. Finally, the study recommended the findings obtained for building robust sentiment classifier in the future.

Keywords: Artificial Intelligence, Natural Language Processing, Sentiment Analysis, Social Network, Text.

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Authors: Moustafa Osman Mohammed

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This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: Air dispersion model, landfill management, spatial analysis, environmental impact and risk assessment.

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Authors: Eric Filiol

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This paper presents a formalisation of the different existing code mutation techniques (polymorphism and metamorphism) by means of formal grammars. While very few theoretical results are known about the detection complexity of viral mutation techniques, we exhaustively address this critical issue by considering the Chomsky classification of formal grammars. This enables us to determine which family of code mutation techniques are likely to be detected or on the contrary are bound to remain undetected. As an illustration we then present, on a formal basis, a proof-of-concept metamorphic mutation engine denoted PB MOT, whose detection has been proven to be undecidable.

Keywords: Polymorphism, Metamorphism, Formal Grammars, Formal Languages, Language Decision, Code Mutation, Word Problem

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Zeinab Ghasemi, S. Amirhassan Monadjemi, Abbas Vafaei

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This paper presents a comparative analysis of a new unsupervised PCA-based technique for steel plates texture segmentation towards defect detection. The proposed scheme called Variance Based Component Analysis or VBCA employs PCA for feature extraction, applies a feature reduction algorithm based on variance of eigenpictures and classifies the pixels as defective and normal. While the classic PCA uses a clusterer like Kmeans for pixel clustering, VBCA employs thresholding and some post processing operations to label pixels as defective and normal. The experimental results show that proposed algorithm called VBCA is 12.46% more accurate and 78.85% faster than the classic PCA.

Keywords: Principal Component Analysis; Variance Based Component Analysis; Defect Detection; Texture Segmentation.

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Authors: Vitalice K. Oduol

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The paper considers a single-server queue with fixedsize batch Poisson arrivals and exponential service times, a model that is useful for a buffer that accepts messages arriving as fixed size batches of packets and releases them one packet at time. Transient performance measures for queues have long been recognized as being complementary to the steady-state analysis. The focus of the paper is on the use of the functions that arise in the analysis of the transient behaviour of the queuing system. The paper exploits practical modelling to obtain a solution to the integral equation encountered in the analysis. Results obtained indicate that under heavy load conditions, there is significant disparity in the statistics between the transient and steady state values.

Keywords: batch arrivals, modelling, single-server queue, time-varying probabilities, transient analysis.

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