Search results for: fuzzy cluster analysis

Authors: Ursachi Andrei

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The Smart Grid Simulator is a computer software based on advanced algorithms which has as the main purpose to lower the energy bill in the most optimized price efficient way as possible for private households, companies or energy providers. It combines the energy provided by a number of solar modules and wind turbines with the consumption of one household or a cluster of nearby households and information regarding weather conditions and energy prices in order to predict the amount of energy that can be produced by renewable energy sources and the amount of energy that will be bought from the distributor for the following day. The user of the system will not only be able to minimize his expenditures on energy fractures, but also he will be informed about his hourly consumption, electricity prices fluctuation and money spent for energy bought as well as how much money he saved each day and since he installed the system. The paper outlines the algorithm that supports the Smart Grid Simulator idea and presents preliminary test results that support the discussion and implementation of the system.

Keywords: smart grid, sustainable energy, applied science, renewable energy sources

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Authors: Pedro B. Antunes, Paulo J. Ramísio

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Road runoff is a linear source of diffuse pollution that can cause significant environmental impacts. During rainfall events, pollutants from both stationary and mobile sources, which have accumulated on the road surface, are dragged through the superficial runoff. Road runoff in coastal zones may present high levels of salinity and chlorides due to the proximity of the sea and transported marine aerosols. Appearing to be correlated to this process, organic matter concentration may also be significant. This study assesses this phenomenon with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included thirty rainfall events, in different weather, traffic and salt deposition conditions in a three years period. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological and traffic parameters were continuously measured. The salt deposition rates (SDR) were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The SDR, variable throughout the year, appears to show a high correlation with wind speed and direction, but mostly with wave propagation, so that it is lower in the summer, in spite of the favorable wind direction in the case study. The distance to the sea, topography, ground obstacles and the platform altitude seems to be also relevant. It was confirmed the high salinity in the runoff, increasing the concentration of the water quality parameters analyzed, with significant amounts of seawater features. In order to estimate the correlations and patterns of different water quality parameters and variables related to weather, road section and salt deposition, the study included exploratory data analysis using different techniques (e.g. Pearson correlation coefficients, Cluster Analysis and Principal Component Analysis), confirming some specific features of the investigated road runoff. Significant correlations among pollutants were observed. Organic matter was highlighted as very dependent of salinity. Indeed, data analysis showed that some important water quality parameters could be divided into two major clusters based on their correlations to salinity (including organic matter associated parameters) and total suspended solids (including some heavy metals). Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed. Based on the results of a monitoring case study, in a coastal zone, it was proven that SDR, associated with the hydrological characteristics of road runoff, can contribute for a better knowledge of the runoff characteristics, and help to estimate the specific nature of the runoff and related water quality parameters.

Keywords: coastal zones, monitoring, road runoff pollution, salt deposition

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: G. Schuh, S. Woelk, D. Schraknepper, A. Such

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The systematic evaluation of manufacturing technologies with regard to the potential for product designing constitutes a major challenge. Until now, conventional evaluation methods primarily consider the costs of manufacturing technologies. Thus, the potential of manufacturing technologies for achieving additional product design features is not completely captured. To compensate this deficit, final evaluations of new technologies are mainly intuitive in practice. Therefore, an additional evaluation dimension is needed which takes the potential of manufacturing technologies for specific realizable product designs into account. In this paper, we present the approach of an evaluation method for selecting manufacturing technologies with regard to their potential for product designing. This research is done within the Fraunhofer innovation cluster »AdaM« (Adaptive Manufacturing) which targets the development of resource efficient and adaptive manufacturing technology processes for complex turbo machinery components.

Keywords: manufacturing, product design, production, technology assessment, technology management

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Authors: Yasir Ali, Farhatullah

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The present study was conducted to estimate the genetic variability, heritability and genetic advance in six parental lines and their 56 genotypes derived from five introgressed brassica populations on the basis of morphological and biochemical traits. The experiment was laid out in a randomized complete block design with two replications at The University of Agriculture Peshawar-Pakistan during growing season of 2015-2016. The ANOVA of all traits of F5:6 populations showed highly significant differences (P ≤ 0.01) for all morphological and biochemical traits. Among F5:6 populations, the genotype 2(526) was earlier in flowering (108.65 days), and genotype 14(485) was earlier in maturity (170 days). Tallest plants (182.5 cm), largest main raceme (91.5 cm) and maximum number of pods (80.5) on main raceme were recorded for genotype 17(34). Maximum primary branches plant-1(6.2) and longest pods (10.26 cm) were recorded for genotype 15, while genotype 16(171) had more seeds pod⁻¹ (22) and gave maximum yield plant-1 (30.22 g). The maximum 100-seed weight (0.60 g) was observed for genotype 10(506) while high protein content (22.61%) was recorded for genotype 4(99). Maximum oil content (54.08 %) and low linoleic acid (7.07 %) were produced by genotype (12(138) and low glucosinolate (59.01 µMg⁻¹) was recorded for genotype 21(113). The genotype 27(303) having high oleic acid content (51.73 %) and genotype 1(209) gave low erucic acid (35.97 %). Among the F5:6 populations moderate to high heritability observed for all morphological and biochemical traits coupled with high genetic advance. Cluster analysis grouped the 56 F5:6 populations along their parental lines into seven different groups. Each group was different from the other group on the basis of morphological and biochemical traits. Moreover all the F5:6 populations showed sufficient variability. Genotypes 10(506) and 16(171) were superior for high seed yield⁻¹, 100-seeds weight, and seed pod⁻¹ and are recommended for future breeding program.

Keywords: Brassicaceae, biochemical characterization, introgression, morphological characterization

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Authors: Ahmet Diken, Tahsin Karabulut

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The factor which developing countries are in need is capital. Such countries make an effort to increase their income in order to meet their expenses for employment, infrastructure, superstructure investments, education, health and defense. The sole income of the countries is taxes collected from businesses. The businesses should drive profit and return in order to be able to toll. In a world where competition exists, different strategies may be followed by business in developing countries and they must specify their target markets. İn order to minimize cost and maximize profit, SMEs have to concentrate on target markets and select cost oriented strategy. In this study, a theoretical model is suggested that SME firms have to act as cluster between each other, and also must be optimal provider for large scale firms. SMEs’ policy must be supported by public. This relationship can benefit large scale firms to have brand over the world, and this organization increases value added for developing countries.

Keywords: competitiveness, countries, SMEs developing, sustainability

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Authors: Yuan-lin Liu, Ye Li, Tian Xia

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There are some shortcomings in Chinese existing taxi management modes. This paper suggests to establish the third-party comprehensive information management platform and put forward an evaluation model based on credit. Four indicators are used to evaluate the drivers’ credit, they are passengers’ evaluation score, driving behavior evaluation, drivers’ average bad record number, and personal credit score. A weighted clustering method is used to achieve credit level evaluation for taxi drivers. The management of taxi industry is based on the credit level, while the grade of the drivers is accorded to their credit rating. Credit rating determines the cost, income levels, the market access, useful period of license and the level of wage and bonus, as well as violation fine. These methods can make the credit evaluation effective. In conclusion, more credit data will help to set up a more accurate and detailed classification standard library.

Keywords: credit, mobile internet, e-hailing taxi, management mode, weighted cluster

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

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Authors: Jiujie Cai, Fengxia LI, Haibo Wang

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After years of research, offshore oil and gas development now are shifted to unconventional reservoirs, where multi-stage hydraulic fracturing technology has been widely used. However, the simulation of complex hydraulic fractures in tight reservoirs is faced with geological and engineering difficulties, such as large burial depths, sand-shale interbeds, and complex stress barriers. The objective of this work is to simulate the hydraulic fracture propagation in the tight sandstone matrix of the marine-continental transitional reservoirs, where the Shanxi Formation in Tianhuan syncline of the Dongsheng gas field was used as the research target. The characteristic parameters of the vertical rock samples with rich beddings were clarified through rock mechanics experiments. The influence of rock mechanical parameters, vertical stress difference of pay-zone and bedding layer, and fracturing parameters (such as injection rates, fracturing fluid viscosity, and number of perforation clusters within single stage) on fracture initiation and propagation were investigated. In this paper, a 3-D fracture propagation model was built to investigate the complex fracture propagation morphology by boundary element method, considering the strength of bonding surface between layers, vertical stress difference and fracturing parameters (such as injection rates, fluid volume and viscosity). The research results indicate that on the condition of vertical stress difference (3 MPa), the fracture height can break through and enter the upper interlayer when the thickness of the overlying bedding layer is 6-9 m, considering effect of the weak bonding surface between layers. The fracture propagates within the pay zone when overlying interlayer is greater than 13 m. Difference in fluid volume distribution between clusters could be more than 20% when the stress difference of each cluster in the segment exceeds 2MPa. Fracture cluster in high stress zones cannot initiate when the stress difference in the segment exceeds 5MPa. The simulation results of fracture height are much higher if the effect of weak bonding surface between layers is not involved. By increasing the injection rates, increasing fracturing fluid viscosity, and reducing the number of clusters within single stage can promote the fracture height propagation through layers. Optimizing the perforation position and reducing the number of perforations can promote the uniform expansion of fractures. Typical curves of fracture height estimation were established for the tight sandstone of the Lower Permian Shanxi Formation. The model results have good consistency with micro-seismic monitoring results of hydraulic fracturing in Well 1HF.

Keywords: fracture propagation, boundary element method, fracture height, offshore oil and gas, marine-continental transitional reservoirs, rock mechanics experiment

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Authors: Proud Arunrangsiwed

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The part of “future direction” in the findings of meta-analysis could provide the great direction to conduct the future studies. This study, “The Documentary Analysis of Meta-Analysis Research in Violence of Media” would conclude “future directions” out of 10 meta-analysis papers. The purposes of this research are to find an appropriate research design or an appropriate methodology for the future research related to the topic, “violence of media”. Further research needs to explore by longitudinal and experimental design, and also needs to have a careful consideration about age effects, time spent effects, enjoyment effects, and ordinary lifestyle of each media consumer.

Keywords: aggressive, future direction, meta-analysis, media, violence

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Authors: Mansour Mohammadpour

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Data transformation refers to the modification of any point in a data set by a mathematical function. When applying transformations, the measurement scale of the data is modified. Data transformations are commonly employed to turn data into the appropriate form, which can serve various functions in the quantitative analysis of the data. This study addresses the investigation of the use of data transformations in Data Envelopment Analysis (DEA). Although data transformations are important options for analysis, they do fundamentally alter the nature of the variable, making the interpretation of the results somewhat more complex.

Keywords: data transformation, data envelopment analysis, undesirable data, negative data

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Authors: Nazri Kama, Sufyan Basri, Roslina Ibrahim

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It is important to manage the changes in the software to meet the evolving needs of the customer. Accepting too many changes causes delay in the completion and it incurs additional cost. One type of information that helps to make the decision is through change impact analysis. Current impact analysis approaches assume that all classes in the class artifact are completely developed and the class artifact is used as a source of analysis. However, these assumptions are impractical for impact analysis in the software development phase as some classes in the class artifact are still under development or partially developed that leads to inaccuracy. This paper presents a novel impact analysis approach to be used in the software development phase. The significant achievements of the approach are demonstrated through an extensive experimental validation using three case studies.

Keywords: software development, impact analysis, traceability, static analysis.

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Authors: Nilay K. Doshi

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A theoretical probe describing the excited energy states of the electron density surrounding a nanoparticle (NP) is presented. An electromagnetic (EM) wave interacts with a NP much smaller than the incident wavelength. The plasmon that oscillates locally around the NP comprises of excited conduction electrons. The system is based on the Jellium model of a cluster of metal atoms. Hohenberg-Kohn (HK) equations and the variational Kohn-Sham (SK) scheme have been used to obtain the NP electron density in the ground state. Furthermore, a time-dependent density functional (TDDFT) theory is used to treat the excited states in a density functional theory (DFT) framework. The non-interacting fermionic kinetic energy is shown to be a functional of the electron density. The time dependent potential is written as the sum of the nucleic potential and the incoming EM field. This view of the quantum oscillation of the electron density is a part of the localized surface plasmon resonance.

Keywords: electron density, energy, electromagnetic, DFT, TDDFT, plasmon, resonance

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Authors: Mustafa İlhan Akbaş, Özlem Garibay, Ivan Garibay

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The economic entities in innovation ecosystems form various industry clusters, in which they compete and cooperate to survive and grow. Within a successful and stable industry cluster, the entities acquire different roles that complement each other in the system. The universities and research centers have been accepted to have a critical role in these systems for the creation and development of innovations. However, the real effect of research institutions on regional economic growth is difficult to assess. In this paper, we present our approach for the identification of the impact of research activities on the regional entrepreneurship for a specific high-tech industry: optics and photonics. The optics and photonics has been defined as an enabling industry, which combines the high-tech photonics technology with the developing optics industry. The recent literature suggests that the growth of optics and photonics firms depends on three important factors: the embedded regional specializations in the labor market, the research and development infrastructure, and a dynamic small firm network capable of absorbing new technologies, products and processes. Therefore, the role of each factor and the dynamics among them must be understood to identify the requirements of the entrepreneurship activities in optics and photonics industry. There are three main contributions of our approach. The recent studies show that the innovation in optics and photonics industry is mostly located around metropolitan areas. There are also studies mentioning the importance of research center locations and universities in the regional development of optics and photonics industry. These studies are mostly limited with the number of patents received within a short period of time or some limited survey results. Therefore the first contribution of our approach is conducting a comprehensive analysis for the state and recent history of the photonics and optics research in the US. For this purpose, both the research centers specialized in optics and photonics and the related research groups in various departments of institutions (e.g. Electrical Engineering, Materials Science) are identified and a geographical study of their locations is presented. The second contribution of the paper is the analysis of regional entrepreneurship activities in optics and photonics in recent years. We use the membership data of the International Society for Optics and Photonics (SPIE) and the regional photonics clusters to identify the optics and photonics companies in the US. Then the profiles and activities of these companies are gathered by extracting and integrating the related data from the National Establishment Time Series (NETS) database, ES-202 database and the data sets from the regional photonics clusters. The number of start-ups, their employee numbers and sales are some examples of the extracted data for the industry. Our third contribution is the utilization of collected data to investigate the impact of research institutions on the regional optics and photonics industry growth and entrepreneurship. In this analysis, the regional and periodical conditions of the overall market are taken into consideration while discovering and quantifying the statistical correlations.

Keywords: entrepreneurship, industrial clusters, optics, photonics, emerging industries, research centers

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Authors: Jiawei Li

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How cooperation emerges and persists in a population of selfish agents is a fundamental question in evolutionary game theory. Our research shows that Collective Strategies with Master-Slave Mechanism (CSMSM) defeat Tit-for-Tat and other well-known strategies in spatial iterated prisoner’s dilemma. A CSMSM identifies kin members by means of a handshaking mechanism. If the opponent is identified as non-kin, a CSMSM will always defect. Once two CSMSMs meet, they play master and slave roles. A mater defects and a slave cooperates in order to maximize the master’s payoff. CSMSM outperforms non-collective strategies in spatial IPD even if there is only a small cluster of CSMSMs in the population. The existence and performance of CSMSM in spatial iterated prisoner’s dilemma suggests that cooperation first appears and persists in a group of collective agents.

Keywords: Evolutionary game theory, spatial prisoners dilemma, collective strategy, master-slave mechanism

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Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

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Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

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Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin

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A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.

Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP

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Authors: Dalia Antiniene, Rosita Lekaviciene

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The qualitative methodology based study is designed to reveal a connection between emotional intelligence (EI) and locus of control (LC) within the population of Lithuanian youth. In the context of emotional problems, the locus of control reflects how one estimates the causes of his/her emotions: internals (internal locus of control) associate their emotions with their manner of thinking, whereas externals (external locus of control) consider emotions to be evoked by external circumstances. On the other hand, there is little empirical data about this connection, and the results in disposition are often contradictory. In the conducted study 1430 young people, aged 17 to 27, from various regions of Lithuania were surveyed. The subjects were selected by quota sampling, maintaining natural proportions of the general Lithuanian youth population. To assess emotional intelligence the EI-DARL test (i.e. self-report questionnaire consisting of 75 items) was implemented. The emotional intelligence test, created applying exploratory factor analysis, reveals four main dimensions of EI: understanding of one’s own emotions, regulation of one’s own emotions, understanding other’s emotions, and regulation of other’s emotions (subscale reliability coefficients fluctuate between 0,84 and 0,91). An original 16-item internality/externality scale was used to examine the locus of control (internal consistency of the Externality subscale - 0,75; Internality subscale - 0,65). The study has determined that the youth understands and regulates other people’s emotions better than their own. Using the K-mean cluster analysis method, it was established that there are three groups of subjects according to their EI level – people with low, medium and high EI. After comparing means of subjects’ favorability of statements on the Internality/Externality scale, a predominance of internal locus of control in the young population was established. The multiple regression models has shown that a rather strong statistically significant correlation exists between total EI, EI subscales and LC. People who tend to attribute responsibility for the outcome of their actions to their own abilities and efforts have higher EI and, conversely, the tendency to attribute responsibility to external forces is related more with lower EI. While pursuing their goals, young people with high internality have a predisposition to analyze perceived emotions and, therefore, gain emotional experience: they learn to control their natural reactions and to act adequately in a situation at hand. Thus the study unfolds, that a person’s locus of control and emotional intelligence are related phenomena and allows us to draw a conclusion, that a person’s internality/externality is a reliable predictor of total EI and its components.

Keywords: emotional intelligence, externality, internality, locus of control

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Authors: Hamed Saremi

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study identified indicators of brand equity based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: anfis, dematel, brand, cosmetic product, brand value

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Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour

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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning

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Authors: Naci Büyükkaracığan

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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

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Authors: T. Padma, Jayashree S. Pillai

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Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.

Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis

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Authors: Magdalena Suárez-Ortega, M. Fe. Sánchez-García

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This paper focuses on the analysis of the motivations that lead people to undertake and consolidate their business. It is addressed from the framework of planned behavior theory, which recognizes the importance of the social environment and cultural values, both in the decision to undertake business and in business consolidation. Similarly, it is also based on theories of career development, which emphasize the importance of career management competencies and their connections to other vital aspects of people, including their roles within their families and other personal activities. This connects directly with the impact of entrepreneurship on the career and the professional-personal project of each individual. This study is part of the project titled Career Design and Talent Management (Ministry of Economy and Competitiveness of Spain, State Plan 2013-2016 Excellence Ref. EDU2013-45704-P). The aim of the study is to identify and describe entrepreneurial competencies and motivational profiles in a sample of 248 Spanish entrepreneurs, considering the consolidated profile and the profile in transition (n = 248).In order to obtain the information, the Questionnaire of Motivation and conditioners of the entrepreneurial career (MCEC) has been applied. This consists of 67 items and includes four scales (E1-Conflicts in conciliation, E2-Satisfaction in the career path, E3-Motivations to undertake, E4-Guidance Needs). Cluster analysis (mixed method, combining k-means clustering with a hierarchical method) was carried out, characterizing the groups profiles according to the categorical variables (chi square, p = 0.05), and the quantitative variables (ANOVA). The results have allowed us to characterize three motivational profiles relevant to the motivation, the degree of conciliation between personal and professional life, and the degree of conflict in conciliation, levels of career satisfaction and orientation needs (in the entrepreneurial project and life-career). The first profile is formed by extrinsically motivated entrepreneurs, professionally satisfied and without conflict of vital roles. The second profile acts with intrinsic motivation and also associated with family models, and although it shows satisfaction with their professional career, it finds a high conflict in their family and professional life. The third is composed of entrepreneurs with high extrinsic motivation, professional dissatisfaction and at the same time, feel the conflict in their professional life by the effect of personal roles. Ultimately, the analysis has allowed us to line the kinds of entrepreneurs to different levels of motivation, satisfaction, needs and articulation in professional and personal life, showing characterizations associated with the use of time for leisure, and the care of the family. Associations related to gender, age, activity sector, environment (rural, urban, virtual), and the use of time for domestic tasks are not identified. The model obtained and its implications for the design of training actions and orientation to entrepreneurs is also discussed.

Keywords: motivation, entrepreneurial career, guidance needs, life-work balance, job satisfaction, assessment

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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The purpose of this study is to investigate whether friendship in social media can be an important factor in recommender system through social scientific analysis of friendship in popular social media such as Facebook and Twitter. For this purpose, this study analyzes data on friendship in real social media using component analysis and clique analysis among sub-group analysis in social network analysis. In this study, we propose an algorithm to reflect the results of sub-group analysis on the recommender system. The key to this algorithm is to ensure that recommendations from users in friendships are more likely to be reflected in recommendations from users. As a result of this study, outcomes of various subgroup analyzes were derived, and it was confirmed that the results were different from the results of the existing recommender system. Therefore, it is considered that the results of the subgroup analysis affect the recommendation performance of the system. Future research will attempt to generalize the results of the research through further analysis of various social data.

Keywords: sub-group analysis, social media, social network analysis, recommender systems

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Mauro Cristeche

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This paper approaches the intervention of the American State in the social arena and the modeling of the rights system from the Argentinian experience, by observing the characteristics of its federal budgetary system, the evolution of social public spending and welfare programs in recent years, labor and poverty statistics, and the changes on the labor market structure. The analysis seeks to combine different methodologies and sources: in-depth interviews with specialists, analysis of theoretical and mass-media material, and statistical sources. Among the results, it could be mentioned that the tendency to state interventionism (what has been called ‘nationalization of social life’) is quite evident in the United States, and manifests itself in multiple forms. The bibliography consulted, and the experts interviewed pointed out this increase of the state presence in historical terms (beyond short-term setbacks) in terms of increase of public spending, fiscal pressure, public employment, protective and control mechanisms, the extension of welfare policies to the poor sectors, etc. In fact, despite the significant differences between both countries, the United States and Argentina have common patterns of behavior in terms of the aforementioned phenomena. On the other hand, dissimilarities are also important. Some of them are determined by each country's own political history. The influence of political parties on the economic model seems more decisive in the United States than in Argentina, where the tendency to state interventionism is more stable. The centrality of health spending is evident in America, while in Argentina that discussion is more concentrated in the social security system and public education. The biggest problem of the labor market in the United States is the disqualification as a consequence of the technological development while in Argentina it is a result of its weakness. Another big difference is the huge American public spending on Defense. Then, the more federal character of the American State is also a factor of differential analysis against a centralized Argentine state. American public employment (around 10%) is comparatively quite lower than the Argentinian (around 18%). The social statistics show differences, but inequality and poverty have been growing as a trend in the last decades in both countries. According to public rates, poverty represents 14% in The United States and 33% in Argentina. American public spending is important (welfare spending and total public spending represent around 12% and 34% of GDP, respectively), but a bit lower than Latin-American or European average). In both cases, the tendency to underemployment and disqualification unemployment does not assume a serious gravity. Probably one of the most important aspects of the analysis is that private initiative and public intervention are much more intertwined in the United States, which makes state intervention more ‘fuzzy’, while in Argentina the difference is clearer. Finally, the power of its accumulation of capital and, more specifically, of the industrial and services sectors in the United States, which continues to be the engine of the economy, express great differences with Argentina, supported by its agro-industrial power and its public sector.

Keywords: state intervention, welfare policies, labor market, system of rights, United States of America

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Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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Authors: Jehan Fahim M. Alsulami

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Academic research about sentiment analysis in sentiment analysis has obtained significant advancement over recent years and is flourishing from the collection of knowledge provided by various academic disciplines. In the current study, the status and development trend of the field of sentiment analysis in social networks is evaluated through a bibliometric analysis of academic publications. In particular, the distributions of publications and citations, the distribution of subject, predominant journals, authors, countries are analyzed. The collaboration degree is applied to measure scientific connections from different aspects. Moreover, the keyword co-occurrence analysis is used to find out the major research topics and their evolutions throughout the time span. The area of sentiment analysis in social networks has gained growing attention in academia, with computer science and engineering as the top main research subjects. China and the USA provide the most to the area development. Authors prefer to collaborate more with those within the same nation. Among the research topics, newly risen topics such as COVID-19, customer satisfaction are discovered.

Keywords: bibliometric analysis, sentiment analysis, social networks, social media

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Authors: H. Emari, Z. Emari

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The main objective of this research was to determine the dimensions of service quality in the banking industry of Iran. For this purpose, the study empirically examined the European perspective suggesting that service quality consists of three dimensions, technical, functional and image. This research is an applied research and its strategy is casual strategy. A standard questionnaire was used for collecting the data. 287 customers of Melli Bank of Northwest were selected through cluster sampling and were studied. The results from a banking service sample revealed that the overall service quality is influenced more by a consumer’s perception of technical quality than functional quality. Accordingly, the Gronroos model is a more appropriate representation of service quality than the American perspective with its limited concentration on the dimension of functional quality in the banking industry of Iran. So, knowing the key dimensions of the quality of services in this industry and planning for their improvement can increase the satisfaction of customers and productivity of this industry.

Keywords: technical quality, functional quality, banking, image, mediating role

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

Abstract:

This study investigates consumer behavior in the notebook computer market by integrating social media sentiment analysis with expert evaluations. The rapid evolution of the notebook industry has intensified competition among manufacturers, necessitating a deeper understanding of consumer priorities. Social media platforms, particularly Twitter, have become valuable sources for capturing real-time user feedback. In this research, sentiment analysis was performed on Twitter data gathered in the last two years, focusing on seven major notebook brands. The PyABSA framework was utilized to extract sentiments associated with various notebook components, including performance, design, battery life, and price. Expert evaluations, conducted using fuzzy logic, were incorporated to assess the impact of these sentiments on purchase behavior. To provide actionable insights, the TOPSIS method was employed to prioritize notebook features based on a combination of consumer sentiments and expert opinions. The findings consistently highlight price, display quality, and core performance components, such as RAM and CPU, as top priorities across brands. However, lower-priority features, such as webcams and cooling fans, present opportunities for manufacturers to innovate and differentiate their products. The analysis also reveals subtle but significant brand-specific variations, offering targeted insights for marketing and product development strategies. For example, Lenovo's strong performance in display quality points to a competitive edge, while Microsoft's lower ranking in battery life indicates a potential area for R&D investment. This hybrid methodology demonstrates the value of combining big data analytics with expert evaluations, offering a comprehensive framework for understanding consumer behavior in the notebook market. The study emphasizes the importance of aligning product development and marketing strategies with evolving consumer preferences, ensuring competitiveness in a dynamic market. It also underscores the potential for innovation in seemingly less important features, providing companies with opportunities to create unique selling points. By bridging the gap between consumer expectations and product offerings, this research equips manufacturers with the tools needed to remain agile in responding to market trends and enhancing customer satisfaction.

Keywords: consumer behavior, customer preferences, laptop industry, notebook computers, social media analytics, TOPSIS

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