Search results for: K-means cluster analysis

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

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This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: Maryam S. Ghoraishi, John E. Hawk, Thomas Thundat

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Understanding liquid properties in small scale has become important in recent decades as immerging new microelectromechanical systems (MEMS) devices have been widely used for micro pumps, drug delivery, and many other laboratory-on-microchips analysis. Often in microfluidic devices, fluids are transported electrokinetically. Therefore, extensive knowledge of fluid flow, heat transport, electrokinetics and electrochemistry are key to successful lab on a chip design. Among different microfluidic devices, recently developed hollow channel cantilever offers an ideal platform to study different fluid properties simultaneously without drastic decrease in quality factor which normally occurs when traditional cantilevers operate in the liquid phase. Using hollow channel cantilever, we monitor changes in density and viscosity of liquid while simultaneously investigating dielectric properties of alcohol water binary mixtures. Considerable research has been conducted on alcohol-water mixtures since such a mixture is a typical prototype for biomolecules, Micelle formation, and structural stability of proteins (to name a few). Here we show that hollow channel cantilever can be employed to investigate dielectric properties of ethanol/water mixtures in different concentrations. We study dynamic amplitude shifts of hollow channel cantilever oscillation at different concentrations of ethanol/water for different voltages. Our results show how interactions between solute and solvent, and possibly cluster formation, could change dielectric properties and dipole reorientation of the mixture, as well as the resulting force on the hollow cantilever. For comparison, we also examine higher conductivity ionic mixtures of sodium sulfate solution under the same conditions as low conductivity ethanol/water mixtures. We will show the results from systematic investigation of solvent effects on dielectric properties of the binary mixture. We will also address the question of resolution limits in dielectric study of analyte molecules imposed by solvent concentrations.

Keywords: dielectric constant, cantilever sensors, ethanol water mixtures, low frequency

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Authors: A. Sarıkaya, A. Akın

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This study was carried out to investigate effects of Control (C), 18 bud/vine, 23 bud/vine, 28 bud/vine, 18 bud/vine + TKI-Humas (soil), 23 bud/vine + TKI-Humas (soil), 28 bud/vine + TKI-Humas (soil) applications on yield and yield components of Alphonse Lavallee grape cultivar. The results were obtained as the highest cluster weight (302.31 g) with 18 bud/vine application; the highest berry weight (6.31 g) with 23 bud/vine + TKI-Humas (soil) and (6.79 g) with 28 bud/vine + TKI-Humas (soil) applications; the highest maturity index (36.95) with 18 bud/vine + TKI-Humas (soil) application; the highest L* color intensity (33.99) with 18 bud/vine + TKI-Humas (soil); the highest a* color intensity (1.53) with 23 bud/vine + TKI-Humas (soil) application. The effects of applications on grape fresh yield, grape juice yield and b* color intensity values were not found statistically significant.

Keywords: Alphonse Lavallee grape cultivar, crop load, TKI-Humas substances (soil), yield, quality

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Authors: Bayan Alqassem, Israa A. Othman, Mohammed Abu Haija, Fawzi Banat

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The treatment of wastewater from highly toxic pollutants is one of the most challenging issues for humanity. In this study, the advanced oxidation process (AOP) was employed to study the catalytic degradation of phenol using different ferrite catalysts which are CoFe₂O₄, CrFe₂O₄, CuFe₂O₄, MgFe₂O₄, MnFe₂O₄, NiFe₂O₄ and ZnFe₂O₄. The ferrite catalysts were prepared via sol-gel and co-precipitation methods. Different ferrite composites were also prepared either by varying the metal ratios or incorporating chemically reduced graphene oxide in the ferrite cluster. The effect of phosphoric acid treatment on the copper ferrite activity. All of the prepared catalysts were characterized using infrared spectroscopy (IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The ferrites catalytic activities were tested towards phenol degradation using high performance liquid chromatography (HPLC). The experimental results showed that ferrites prepared through sol-gel route were more active than those of the co-precipitation method towards phenol degradation. In both cases, CuFe₂O₄ exhibited the highest degradation of phenol compared to the other ferrites. The photocatalytic properties of the ferrites were also investigated.

Keywords: ferrite catalyst, ferrite composites, phenol degradation, photocatalysis

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Authors: Austyn Snowden

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Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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Authors: Otgonjargal Damdinbaljir

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Background: Infant feeding practices have a major role in determining the nutritional status of children and are associated with household socioeconomic and demographic factors. In 2010, Mongolia used WHO 2008 edition of Indicators for assessing infant and young child feeding practices for the first time. Objective: To evaluate the feeding status of infants and young children under 2 years old in Mongolia. Materials and Methods: The study was conducted by cluster random sampling. The data on breastfeeding and complementary food supplement of the 350 infants and young children aged 0-23 months in 21 provinces of the 4 economic regions of the country and capital Ulaanbaatar city were collected through questionnaires. The feeding status was analyzed according to the WHO 2008 edition of Indicators for assessing infant and young child feeding practices. Analysis of data: Survey data was analysed using the PASW statistics 18.0 and EPI INFO 2000 software. For calculation of overall measures for the entire survey sample, analyses were stratified by region. Age-specific feeding patterns were described using frequencies, proportions and survival analysis. Logistic regression was done with feeding practice as dependent and socio demographic factors as independent variables. Simple proportions were calculated for each IYCF indicator. The differences in the feeding practices between sexes and age-groups, if any, were noted using chi-square test. Ethics: The Ethics Committee under the auspices of the Ministry of Health approved the study. Results: A total of 350 children aged 0-23 months were investigated. The rate of ever breastfeeding of children aged 0-23 months reached up to 98.2%, while the percentage of early initiation of breastfeeding was only 85.5%. The rates of exclusive breastfeeding under 6 months, continued breastfeeding for 1 year, and continued breastfeeding for 2 years were 71.3%, 74% and 54.6%, respectively. The median time of giving complementary food was the 6th month and the weaning time was the 9th month. The rate of complementary food supplemented from 6th-8th month in time was 80.3%. The rates of minimum dietary diversity, minimum meal frequency, and consumption of iron-rich or iron-fortified foods among children aged 6-23 months were 52.1%, 80.8% (663/813) and 30.1%, respectively. Conclusions: The main problems revealed from the study were inadequate category and frequency of complementary food, and the low rate of consumption of iron-rich or iron-fortified foods were the main issues to be concerned on infant feeding in Mongolia. Our findings have highlighted the need to encourage mothers to enrich their traditional wheat- based complementary foods add more animal source foods and vegetables.

Keywords: complementary feeding, early initiation of breastfeeding, exclusive breastfeeding, minimum meal frequency

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Authors: Kali Prasad Sarma, Nibedita Baul, Jinu Deka

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In the present study, pollution level of polycyclic aromatic hydrocarbon (PAH) in surface soil of historic Tezpur town located in the north bank of the River Brahmaputra were evaluated. In order to determine the seasonal distribution and concentration level of 16 USEPA priority PAHs surface soil samples were collected from 12 different sampling sites with various land use type. The total concentrations of 16 PAHs (∑16 PAHs) varied from 242.68µgkg-1to 7901.89µgkg-1. Concentration of total probable carcinogenic PAH ranged between 7.285µgkg-1 and 479.184 µgkg-1 in different seasons. However, the concentration of BaP, the most carcinogenic PAH, was found in the range of BDL to 50.01 µgkg-1. The composition profiles of PAHs in 3 different seasons were characterized by following two different types of ring: (1) 4-ring PAHs, contributed to highest percentage of total PAHs (43.75%) (2) while in pre- and post- monsoon season 3- ring compounds dominated the PAH profile, contributing 65.58% and 74.41% respectively. A high PAHs concentration with significant seasonality and high abundance of LMWPAHs was observed in Tezpur town. Soil PAHs toxicity was evaluated taking toxic equivalency factors (TEFs), which quantify the carcinogenic potential of other PAHs relative to BaP and estimate benzo[a]pyrene-equivalent concentration (BaPeq). The calculated BaPeq value signifies considerable risk to contact with soil PAHs. We applied cluster analysis and principal component analysis (PCA) with multivariate linear regression (MLR) to apportion sources of polycyclic aromatic hydrocarbons (PAHs) in surface soil of Tezpur town, based on the measured PAH concentrations. The results indicate that petrogenic and pyrogenic sources are the important sources of PAHs. A combination of chemometric and molecular indices were used to identify the sources of PAHs, which could be attributed to vehicle emissions, a mixed source input, natural gas combustion, wood or biomass burning and coal combustion. Source apportionment using absolute principle component scores–multiple linear regression showed that the main sources of PAHs are 22.3% mix sources comprising of diesel and biomass combustion and petroleum spill,13.55% from vehicle emission, 9.15% from diesel and natural gas burning, 38.05% from wood and biomass burning and 16.95% contribute coal combustion. Pyrogenic input was found to dominate source of PAHs origin with more contribution from vehicular exhaust. PAHs have often been found to co-emit with other environmental pollutants like heavy metals due to similar source of origin. A positive correlation was observed between PAH with Cr and Pb (r2 = 0.54 and 0.55 respectively) in monsoon season and PAH with Cd and Pb (r2 = 0.54 and 0.61 respectively) indicating their common source. Strong correlation was observed between PAH and OC during pre- and post- monsoon (r2=0.46 and r2=0.65 respectively) whereas during monsoon season no significant correlation was observed (r2=0.24).

Keywords: polycyclic aromatic hydrocarbon, Tezpur town, chemometric analysis, ecological risk assessment, pollution

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Authors: Pingping Lin, Xudong Luo

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Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: application, natural language processing, online comments, sentiment analysis

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Authors: Mohamad Saleh Sangin Ostadi, Esmail Safari, Somayeh Akbari, Kaveh Qaderi Bagajan

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The aim of this study is to compare abused and normal male students in Tehran guidance schools with emphasis on the co-dependency of their mothers. The method of this study is based on survey method and comparison (Ex-Post Facto). The method of sampling is also multi-stage cluster. Accordingly, we did sampling from secondary schools of education and training in Tehran, including 12 schools with levels of first, second and third. Each of the schools represents the three – high, medium and low- economic and social conditions. In the following, three classes from every school and 20 students from each class were randomly selected. By (CTQ) abused and normal students were separated that 670 children were recognized as normal and 50 children as abused. Then, 50 children were randomly selected from normal group and compared with abused group. Using Spanned-Fischer Co-dependency Scale, we compared mothers of abused and normal students. The results showed that mothers of the abused children have higher co- dependency average comparing to the mothers of the normal children.

Keywords: co-dependency, child abuse, abused children, parental psychological health

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Authors: Rejab Hajlaoui, Tarek Moulahi, Hervé Guyennet

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In a highway scenario, the vehicle speed can exceed 120 kmph. Therefore, any vehicle can enter or leave the network within a very short time. This mobility adversely affects the network connectivity and decreases the life time of all established links. To ensure an effective stability in vehicular ad hoc networks with minimum broadcasting storm, we have developed a weighted algorithm based on the k-medoids clustering algorithm (WKCA). Indeed, the number of clusters and the initial cluster heads will not be selected randomly as usual, but considering the available transmission range and the environment size. Then, to ensure optimal assignment of nodes to clusters in both k-medoids phases, the combined weight of any node will be computed according to additional metrics including direction, relative speed and proximity. Empirical results prove that in addition to the convergence speed that characterizes the k-medoids algorithm, our proposed model performs well both AODV-Clustering and OLSR-Clustering protocols under different densities and velocities in term of end-to-end delay, packet delivery ratio, and throughput.

Keywords: communication, clustering algorithm, k-medoids, sensor, vehicular ad hoc network

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Authors: Lei Qin

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As shared accommodation has become one of the most important market developments in the tourism industry, numerous contributions have emerged on travelers’ motivations to choose shared accommodation. A debated question, however, resides in the heterogeneity of travelers based on motivations. This paper aims to reconcile opposing perspectives by comparing motivation segmentation at two distinct phases of innovation adoption of this new hospitality option: (i) before the first travel – potential users showing interest (n=420) and (ii) after the first travel – users (n=420). Interestingly, we find that travelers (including pre-and-post adopters) have a stronger agreement in experiential motivations than practical motivations. However, the heterogeneity of motivations among travelers is significantly higher in users, increasing from two to six clusters, which means travelers cluster into more and distinct motivation groups after adoption. Rather than invalidating specific assumptions used in the literature in terms of motivation heterogeneity, this paper reconciles opposing findings by putting them along with one another in the process of innovation adoption. A subsequent tourists’ segmentation based on motivations were conducted according to their innovation adoption stages.

Keywords: motivation, pre-and-post adoption, shared accommodation, segmentation

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Authors: Pantip Kayee

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17α-ethinylestradiol (EE2) is a recalcitrant micropollutant which is found in small amounts in municipal wastewater. But these small amounts still adversely affect for the reproductive function of aquatic organisms. Evidence in the past suggested that full-scale WWTPs equipped with nitrification process enhanced the removal of EE2 in the municipal wastewater. EE2 has been proven to be able to be transformed by ammonia oxidizing bacteria (AOB) via co-metabolism. This research aims to clarify the EE2 degradation pattern by different consortium of ammonia oxidizing microorganism (AOM) including AOA (ammonia oxidizing archaea) and investigate contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM. The result showed that AOA or AOB of N. oligotropha cluster in enriched nitrifying activated sludge (NAS) from 2mM and 5mM, commonly found in municipal WWTPs, could degrade EE2 in wastewater via co-metabolism. Moreover, the investigation of the contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM demonstrated that the new synthesized AMO enzyme may perform ammonia oxidation rather than the existing AMO enzyme or the existing AMO enzyme may has a small amount to oxidize ammonia.

Keywords: 17α-ethinylestradiol, nitrification, ammonia oxidizing bacteria, ammonia oxidizing archaea

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Authors: Amr A. El Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, fuel, security and capital in many countries, particularly Saudi Arabia. Identification of animal breeds has progressed rapidly during the last decade. Advanced molecular techniques are playing a significant role in breeding or strain protection laws. On the other hand, fingerprinting of some molecular markers related to some productive traits in farm animals represents most important studies to our knowledge, which aim to conserve these local genetic resources, and to the genetic improvement of such local breeds by selective programs depending on gene markers. Milk records were taken two days in each week from female camels of Majahem, Safara, Wathaha, and Hamara breeds, respectively from different private farms in northern Jeddah, Riyadh and Alwagh governorates and average weekly yields were calculated. DNA sequencing for CSN2 gene was used for evaluating the genetic variations and calculating the genetic distance values among four Saudi camel populations which are Hamra(R), Safra(Y), Wadha(W) and Majaheim(M). In addition, this marker was analyzed for reconstructing the Neighbor joining tree among evaluating camel breeds. In respect to milk yield during winter season, result indicated that average weekly milk yield of Safara camel breed (30.05 Kg/week) is significantly (p < 0.05) lower than the other 3 breeds which ranged from 39.68 for Hamara to 42.42 Kg/week for Majahem, while there are not significant differences between these three breeds. The Neighbor Joining analysis that re-constructed based on DNA variations showed that samples are clustered into two unique clades. The first clade includes Y (from Y4 to Y18) and M (from M1, to M9). On the other hand, the second cluster is including all R (from R1 to R6) and W (from W1 to W6). The genetic distance values were equal 0.0068 (between the groups M&Y and R&W) and equal 0 (within each group).

Keywords: milk yield, beta-casein precursor (CSN2), Saudi camel, molecular markers

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Authors: Pallavi Roe

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Violent crime is a significant public safety concern in urban areas across the United States, and Washington, DC, is no exception. This research discusses the prevalence and types of crime, particularly violent crime, in Washington, DC, along with the factors contributing to the high rate of violent crime in the city, including poverty, inequality, access to guns, and racial disparities. The organizations working towards ensuring safety in neighborhoods are also listed. The proposal to perform spatial and temporal analysis on violent crime and the use of guns in crime analysis is presented to identify patterns and trends to inform evidence-based interventions to reduce violent crime and improve public safety in Washington, DC. The stakeholders for crime analysis are also discussed, including law enforcement agencies, prosecutors, judges, policymakers, and the public. The anticipated result of the spatial and temporal analysis is to provide stakeholders with valuable information to make informed decisions about preventing and responding to violent crimes.

Keywords: crime analysis, spatial analysis, temporal analysis, violent crime

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Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

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An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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Authors: Milad Keshvardoost, Amir Khanlari, Nader Khalesi

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Background: Any firm in the pharmaceutical industry requires efficient and effective management information systems (MIS) to support managerial functions. Purpose: The aim of this study is to investigate the impact of Task-Technology Fit on user effectiveness, efficiency, and creativity in Iranian pharmaceutical companies. Methodology: 345 reliable and validate questionnaires were distributed among selected samples, through the cluster method, to Information system users of eight leading Iranian pharmaceutical companies, based on the likert scale. The proposed model of the article is based on a model with Task technology fit, on user performance with the definition of efficiency, effectiveness, and creativity through mediation effects of perceived usefulness and ease of use. Results: This study confirmed that TTF with definitions of adequacy and compatibility has positive impacts on user performance Conclusion: We concluded that pharmaceutical users of IS, utilizing a system with a precise and intense observation of users' demands, may make facilitation for them to design an exclusive IS framework.

Keywords: information systems, user performance, pharmaceuticals, task technology fit

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Muhammad Waseem Akram

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The current study attempts to analyze the impact of business constraints on the growth potential and performance of Small and Medium Enterprises (SMEs) in the electrical industry of Pakistan. Primary data have been utilized for the study collected from the electrical industry cluster in Sargodha, Pakistan. OLS regression is used to assess the impact of business constraints on the performance of SMEs by controlling the effect of Technology Level, Innovations, and Firm Size. To associate business constraints with the growth potential of SMEs, the study utilized Tetrachoric Correlation and Logistic Regression. Findings reveal that all the business constraints negatively affect the performance of SMEs in the electrical industry except Political Instability. Results of Tetrachoric Correlation show that all the business constraints are negatively correlated with the growth potential of SMEs. Logistic Regression results show that Energy Constraint, Inflation and Price Instability, and Bad Business Practices, all three business constraints cause to reduce the probability of income growth in sample SMEs.

Keywords: SMEs, business constraints, performance, growth potential

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

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Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

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Authors: D. I. Yani, S. Isaramalai, C. Kritpracha

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Adherence to health behaviors is essential to achieve successful TB treatment. This study aimed to examine the effect of a family-based DOTS support program on adherence to health behaviors in patients with pulmonary TB. Sixty TB patients and their families were selected using cluster randomization of community health centers. The subjects were assigned into a control group, who received the routine care, and an experimental group, who received both routine care and care from the family-based DOTS support program. Paired t-test and the independent t-test were applied. The total score of adherence to health behaviors in the experimental group was significantly higher after receiving care from the family-based DOTS support program than the pretest score (t = -10.34, p < .001). Suggestions were made to expand the application of this program in various contexts and to extend knowledge for nursing practices and research.

Keywords: self-care deficit nursing theory, family-based DOTS program, pulmonary tuberculosis, adherence, health behaviors

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: Jin-Woo Park, Sung-Soo Lee, Nong-Moon Hwang

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The generation of charged nanoparticles in the gas phase during the Chemical Vapor Deposition (CVD) process has been frequently reported with their subsequent deposition into films and nanostructures in many systems such as carbon, silicon and zinc oxide. The microstructure evolution of films and nanostructures is closely related with the size distribution of charged nanoparticles. To confirm the generation of charged nanoparticles during GaN, the generation of GaN charged nanoparticles was examined in an atmospheric pressure CVD process using a Differential Mobility Analyser (DMA) combined with a Faraday Cup Electrometer (FCE). It was confirmed that GaN charged nanoparticles were generated under the condition where GaN nanostructures were synthesized on the bare and Au-coated Si substrates. In addition, the deposition behaviour depends strongly on the charge transfer rate of metal substrates. On the metal substrates of a lower CTR such as Mo, the deposition rate of GaN was much lower than on those of a higher CTR such as Fe. GaN nanowires tend to grow on the substrates of a lower CTR whereas GaN thin films tend to be deposited on the substrates of a higher CTR.

Keywords: chemical vapour deposition, charged cluster model, generation of charged nanoparticles, deposition behaviour, nanostructures, gan, charged transfer rate

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

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Authors: Lydia Wahid, Mona F. Ahmed, Nevin Darwish

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The vehicle routing problem (VRP) consists of a group of customers that needs to be served. Each customer has a certain demand of goods. A central depot having a fleet of vehicles is responsible for supplying the customers with their demands. The problem is composed of two subproblems: The first subproblem is an assignment problem where the number of vehicles that will be used as well as the customers assigned to each vehicle are determined. The second subproblem is the routing problem in which for each vehicle having a number of customers assigned to it, the order of visits of the customers is determined. Optimal number of vehicles, as well as optimal total distance, should be achieved. In this paper, an approach for solving the first subproblem (the assignment problem) is presented. In the approach, a clustering algorithm is proposed for finding the optimal number of vehicles by grouping the customers into clusters where each cluster is visited by one vehicle. Finding the optimal number of clusters is NP-hard. This work presents a polynomial time clustering algorithm for finding the optimal number of clusters and solving the assignment problem.

Keywords: vehicle routing problems, clustering algorithms, Clarke and Wright Saving Method, agglomerative hierarchical clustering

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