Search results for: surface features

Authors: Pragyan Paramita Das, Vishwas N. Khatri

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By using the lower- and upper- bound finite elements to limit analysis in conjunction with second-order conic programming (SOCP), the effect of seismic forces on the bearing capacity of surface strip footing resting on dense sand underlain by loose sand deposit is explored. The soil is assumed to obey the Mohr-Coulomb’s yield criterion and an associated flow rule. The angle of internal friction (ϕ) of the top and the bottom layer is varied from 42° to 44° and 32° to 34° respectively. The coefficient of seismic acceleration is varied from 0 to 0.3. The variation of bearing capacity with different thickness of top layer for various seismic acceleration coefficients is generated. A comparison will be made with the available solutions from literature wherever applicable.

Keywords: bearing capacity, conic programming, finite elements, seismic forces

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Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Asmau Mukhtar Ahmed, Olga Duran

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Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

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Authors: Dorottya Guban, Irina Borbath, Istvan Bakos, Peter Nemeth, Andras Tompos

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One of the greatest challenges of the implementation of polymer electrolyte membrane fuel cells (PEMFCs) is to find active and durable electrocatalysts. The cell performance is always limited by the oxygen reduction reaction (ORR) on the cathode since it is at least 6 orders of magnitude slower than the hydrogen oxidation on the anode. Therefore high loading of Pt is required. Catalyst corrosion is also more significant on the cathode, especially in case of mobile applications, where rapid changes of loading have to be tolerated. Pt-Sn bulk alloys and SnO2-decorated Pt3Sn nanostructures are among the most studied bimetallic systems for fuel cell applications. Exclusive formation of supported Sn-Pt alloy phases with different Pt/Sn ratios can be achieved by using controlled surface reactions (CSRs) between hydrogen adsorbed on Pt sites and tetraethyl tin. In this contribution our results for commercial and a home-made 20 wt.% Pt/C catalysts modified by tin anchoring via CSRs are presented. The parent Pt/C catalysts were synthesized by modified NaBH4-assisted ethylene-glycol reduction method using ethanol as a solvent, which resulted either in dispersed and highly stable Pt nanoparticles or evenly distributed raspberry-like agglomerates according to the chosen synthesis parameters. The 20 wt.% Pt/C catalysts prepared that way showed improved electrocatalytic performance in the ORR and stability in comparison to the commercial 20 wt.% Pt/C catalysts. Then, in order to obtain Sn-Pt/C catalysts with Pt/Sn= 3 ratio, the Pt/C catalysts were modified with tetraethyl tin (SnEt4) using three and five consecutive tin anchoring periods. According to in situ XPS studies in case of catalysts with highly dispersed Pt nanoparticles, pre-treatment in hydrogen even at 170°C resulted in complete reduction of the ionic tin to Sn0. No evidence of the presence of SnO2 phase was found by means of the XRD and EDS analysis. These results demonstrate that the method of CSRs is a powerful tool to create Pt-Sn bimetallic nanoparticles exclusively, without tin deposition onto the carbon support. On the contrary, the XPS results revealed that the tin-modified catalysts with raspberry-like Pt agglomerates always contained a fraction of non-reducible tin oxide. At the same time, they showed increased activity and long-term stability in the ORR than Pt/C, which was assigned to the presence of SnO2 in close proximity/contact with Pt-Sn alloy phase. It has been demonstrated that the content and dispersion of the fcc Pt3Sn phase within the electrocatalysts can be controlled by tuning the reaction conditions of CSRs. The bimetallic catalysts displayed an outstanding performance in the ORR. The preparation of a highly dispersed 20Pt/C catalyst permits to decrease the Pt content without relevant decline in the electrocatalytic performance of the catalysts.

Keywords: anode catalyst, cathode catalyst, controlled surface reactions, oxygen reduction reaction, PtSn/C electrocatalyst

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Authors: M. Shopska, D. Paneva, G. Kadinov, Z. Cherkezova-Zheleva, I. Mitov

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The iron containing materials are used as catalysts in different processes. The chemical methods of their synthesis use toxic and expensive chemicals; sophisticated devices; energy consumption processes that raise their cost. Besides, dangerous waste products are formed. At present time such syntheses are out of date and wasteless technologies are indispensable. The bioinspired technologies are consistent with the ecological requirements. Different microorganisms participate in the biomineralization of the iron and some phytochemicals are involved, too. The methods for biogenic production of iron containing materials are clean, simple, nontoxic, realized at ambient temperature and pressure, cheaper. The biogenic iron materials embrace different iron compounds. Due to their origin these substances are nanosized, amorphous or poorly crystalline, porous and have number of useful properties like SPM, high magnetism, low toxicity, biocompatibility, absorption of microwaves, high surface area/volume ratio, active sites on the surface with unusual coordination that distinguish them from the bulk materials. The biogenic iron materials are applied in the heterogeneous catalysis in different roles - precursor, active component, support, immobilizer. The application of biogenic iron oxide materials gives rise to increased catalytic activity in comparison with those of abiotic origin. In our study we investigated the catalytic behavior of biomasses obtained by cultivation of Leptothrix bacteria in three nutrition media – Adler, Fedorov, and Lieske. The biomass composition was studied by Moessbauer spectroscopy and transmission IRS. Catalytic experiments on CO oxidation were carried out using in situ DRIFTS. Our results showed that: i) the used biomasses contain α-FeOOH, γ-FeOOH, γ-Fe2O3 in different ratios; ii) the biomass formed in Adler medium contains γ-FeOOH as main phase. The CO conversion was about 50% as evaluated by decreased integrated band intensity in the gas mixture spectra during the reaction. The main phase in the spent sample is γ-Fe2O3; iii) the biomass formed in Lieske medium contains α-FeOOH. The CO conversion was about 20%. The main phase in the spent sample is α-Fe2O3; iv) the biomass formed in Fedorov medium contains γ-Fe2O3 as main phase. CO conversion in the test reaction was about 19%. The results showed that the catalytic activity up to 200°C resulted predominantly from α-FeOOH and γ-FeOOH. The catalytic activity at temperatures higher than 200°C was due to the formation of γ-Fe2O3. The oxyhydroxides, which are the principal compounds in the biomass, have low catalytic activity in the used reaction; the maghemite has relatively good catalytic activity; the hematite has activity commensurate with that of the oxyhydroxides. Moreover it can be affirmed that catalytic activity is inherent in maghemite, which is obtained by transformation of the biogenic lepidocrocite, i.e. it has biogenic precursor.

Keywords: nanosized biogenic iron compounds, catalytic behavior in reaction of CO oxidation, in situ DRIFTS, Moessbauer spectroscopy

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Authors: Sue Hershberger Yoder, Jon Yoder

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“The appearance does not hide the essence, it reveals it; it is the essence.”—Jean-Paul Sartre, Being and Nothingness Three decades ago, transarchitect Marcos Novak developed an early form of algorithmic animation he called “liquid architecture.” In that project, digitally floating forms morphed seamlessly in cyberspace without claiming to evolve or improve. Change itself was seen as inevitable. And although some imagistic moments certainly stood out, none was hierarchically privileged over another. That project challenged longstanding assumptions about creativity and artistic genius by posing infinite parametric possibilities as inviting alternatives to traditional notions of stability, originality, and evolution. Through ephemeral processes of printing, milling, and projecting, the exhibition “Liquid Illumination” destabilizes the solid foundations of fashion and architecture. The installation is neither worn nor built in the conventional sense, but—like the sensual art forms of fashion and architecture—it is still radically embodied through the logics and techniques of design. Appearances are everything. Surface pattern and color are no longer understood as minor afterthoughts or vapid carriers of dubious content. Here, they become essential but ever-changing aspects of precisely fabricated images. Fourteen silk “colorways” (a term from the fashion industry) are framed selections from ongoing experiments with intricate pattern and complex color configurations. Whether these images are printed on fabric, milled in foam, or illuminated through projection, they explore and celebrate the untapped potentials of the surficial and superficial. Some components of individual prints appear to float in front of others through stereoscopic superimpositions; some figures appear to melt into others due to subtle changes in hue without corresponding changes in value; and some layers appear to vibrate via moiré effects that emerge from unexpected pattern and color combinations. The liturgical atmosphere of Liquid Illumination is intended to acknowledge that, like the simultaneously sacred and superficial qualities of rose windows and illuminated manuscripts, artistic and religious ideologies are also always malleable. The intellectual provocation of this paper pushes the boundaries of current thinking concerning viable applications for fashion print designs and architectural images—challenging traditional boundaries between fine art and design. The opportunistic installation of digital printing, CNC milling, and video projection mapping in a gallery that is normally reserved for fine art exhibitions raises important questions about cultural/commercial display, mass customization, digital reproduction, and the increasing prominence of surface effects (color, texture, pattern, reflection, saturation, etc.) across a range of artistic practices and design disciplines.

Keywords: fashion, print design, architecture, projection mapping, image, fabrication

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Authors: Yani Shi, Jiaqi Yan

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A new product is important for companies to extend consumers and manifest competitiveness. New product often involves new features that consumers might not be familiar with while it may also have a competitive advantage to attract consumers compared to established products. However, although most online retailers employ recommendation agents (RA) to influence consumers’ product choice decision, recommended new products are not accepted and chosen as expected. We argue that it might also be caused by providing a new product recommendation in the wrong way at the wrong time. This study seeks to discuss how new product evaluations sourced from third parties could be employed in RAs as evidence of the superiority for the new product and how the new product recommendation could be provided to a consumer at the right time so that it can be accepted and finally chosen during the consumer’s decision-making process. A 2*2 controlled laboratory experiment was conducted to understand the selection of new product recommendation sources and recommendation timing. Human subjects were randomly assigned to one of the four treatments to minimize the effects of individual differences on the results. Participants were told to make purchase choices from our product categories. We find that a new product recommended right after a similar existing product and with the source of the expert review will be more likely to be accepted. Based on this study, both theoretical and practical contributions are provided regarding new product recommendation.

Keywords: new product recommendation, recommendation timing, recommendation source, recommendation agents

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Authors: Zidani Abla

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Lymphoma is a common type of cancer that affects the lymphatic system, including the lymph nodes, spleen and other associated organs. There are two main types of lymphoma: Hodgkin's lymphoma and non-Hodgkin's lymphoma. The epidemiological, clinical and biological features of lymphoma are poorly studied in Algeria. The main objective of our study is to investigate the epidemiological, clinical, paraclinical, etiological, evolutionary and biological characteristics of non-Hodgkin's lymphoma (NHL) in the hematology department of the University Hospital Center (HUC) of Batna. This is a study of 10 patients diagnosed at Batna University Hospital. 70% were male and 30% female (sex ratio M/F= 2.33). Median age was 51.7 years. Pain, especially abdominal pain, was the main reason for consultation. Stage IV predominated (40%), followed by stage III (20%). Abdominal adenopathies (34%) were the most abundant. Secondary hepatic localization was predominant. Large B-cell NHL predominated, accounting for 60% of cases, followed by small B-cell NHL (30%). Serology for hepatitis B and C, and human immunodeficiency virus (HIV) was negative. Biologically, a predominance of hyperleukocytosis, polynuclear neutrophilic leukocytosis, lymphopenia and hypoalbuminemia were present in the majority of cases. In summary, our results remain to be compared with other works for other periods and other regions in order to generalize lymphoma percentages for the entire Algerian population.

Keywords: non Hodgkin's lymphoma, epidemiology, clinic, biology

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Authors: Ali Akbar Zeinali

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Lack of appropriate equivalences for the terms or technical words is the result of ineffective translation guidelines adopted in the translation processes. The increasing number of foreign words and specific terms incorporated into the native language are due to the ongoing development of technology and science. Many problems appear in medical translation when the Persian translators try to employ non-Persian or imported words in medical texts, in which multiple equivalents may be created for one particular word based on the individual preferences of authors and translators in the target language due to lack of standardization. The study attempted to discuss the findings based on the compatibility of the international naming criteria, considering the translation procedures. About 67% of 339 equivalents under this study were grouped as incompatible words while about 33% of them were compatible terms. The similarities and differences were investigated and discussed according to the compatibility status of the equivalents with Sager’s criteria. Such equivalents have been classified into several groups through bi-dimensional descriptions that were different features of translation procedures related to the international naming criteria. In review of the frequency distribution of compatibilities, the equivalents were divided into two categories of compatibles and incompatibles, indicating the effectiveness of the applied translation procedures.

Keywords: linguistics, medical translation, naming, terminology

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Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagallah

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Image enhancement allows the observer to see details in images that may not be immediately observable in the original image. Image enhancement is the transformation or mapping of one image to another. The enhancement of certain features in images is accompanied by undesirable effects. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian scale mixture model and median filter were presented, which accomplishes nonlinearities from scattering a new nonlinear approach for contrast enhancement of bones in bone scan images using both gamma correction and negative transform methods. The usual assumption of a distribution of gamma and Poisson statistics only lead to overestimation of the noise variance in regions of low intensity but to underestimation in regions of high intensity and therefore to non-optional results. The contrast enhancement results were obtained and evaluated using MatLab program in nuclear medicine images of the bones. The optimal number of bins, in particular the number of gray-levels, is chosen automatically using entropy and average distance between the histogram of the original gray-level distribution and the contrast enhancement function’s curve.

Keywords: bone scan, nuclear medicine, Matlab, image processing technique

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Authors: Kathrin Endres, Daniela Greven

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Although chatbots are a widely known and established communication instrument in B2C customer services, B2B industries still hesitate to implement chatbots due to the incertitude of customer acceptance. While many studies examine the chatbot acceptance of B2C consumers, few studies are focusing on the B2B sector, where the customer is represented by a buying center consisting of several stakeholders. This study investigates the challenges of chatbot acceptance in B2B industries compared to challenges of chatbot acceptance from current B2C literature by interviewing experts from German chatbot vendors. The results show many similarities between the customer requirements of B2B customers and B2C consumers. Still, due to several stakeholders involved in the buying center, the features of the chatbot users are more diverse but obfuscated at the same time. Using a factorial survey, this study further examines the customer acceptance of varying situations of B2B chatbot designs based on the chatbot variables transparency, fault tolerance, complexity of products, value of products, as well as transfer to live chat service employees. The findings show that all variables influence the propensity to use the chatbot. The results contribute to a better understanding of how firms in B2B industries can design chatbots to advance their customer service and enhance customer satisfaction.

Keywords: chatbots, technology acceptance, B2B customer service, customer satisfaction

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Authors: Zhang Jianrun, He Tangling

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Superposition wave form automotive exhaust bellows is a new type of bellows, which has the characteristics of large compensation, good vibration isolation performance and long life. It has been paid more and more attention and applications in automotive exhaust pipe system. Aiming at the lack of current design methods of superposition wave form automotive exhaust bellows, this paper proposes a response surface parameter optimization method where the fatigue life and vibration transmissibility of the bellows are set as objectives. The parametric modeling of bellow structure is also adopted to achieve the high efficiency in the design. The approach proposed in this paper provides a new way for the design of superposition wave form automotive exhaust bellows. It embodies good engineering application value.

Keywords: superposition wave form, exhaust bellows, optimization, vibration, fatigue life

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Authors: Sefik Can Karakaya, Ibrahim Demir

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In this study, the relationship between musical preferences and personality traits has been investigated in terms of Spotify audio analysis features. The aim of this paper is to build such a classifier capable of segmenting people into their Myers-Briggs Type Index (MBTI) personality type based on their Spotify playlists. Music takes an important place in the lives of people all over the world and online music streaming platforms make it easier to reach musical contents. In this context, the motivation to build such a classifier is allowing people to gain access to their MBTI personality type and perhaps for more reliably and more quickly. For this purpose, logistic regression and deep neural networks have been selected for classifier and their performances are compared. In conclusion, it has been found that musical preferences differ statistically between personality traits, and evaluated models are able to distinguish personality types based on given musical data structure with over %60 accuracy rate.

Keywords: myers-briggs type indicator, music psychology, Spotify, behavioural user profiling, deep neural networks, logistic regression

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Authors: Samson Davoyan, Ashot Davoyan, Ani Khachatryan

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The indexes (Global Competitiveness Index, Economic Freedom Index, Human Development Index, etc.) developed by different international and non-government organizations in time and space express the quantitative and qualitative features of different fields of various reforms implemented in different countries. The main objective of our research is to develop new methodology that we will use to create integral index based on many indexes and that will include many areas of reforms. To achieve our aim we have used econometric methods (regression model for panel data method). The basis of our methodology is the development of the new integral index based on quantitative assessment of the change of two main parameters: the score of the countries by different indexes and the change of the ranks of countries for following two periods of time. As a result of the usage of methods for analyzes we have defined the indexes that are used to create the new integral index and the scales for each of them. Analyzing quantitatively and qualitatively analysis through the integral index for more than 100 countries for 2009-2014, we have defined comparative efficiency that helps to conclude in which directions countries have implemented reforms more effectively compared to others and in which direction reforms have implemented less efficiently.

Keywords: development, rank, reforms, comparative, index, economic, corruption, social, program

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Authors: Nikolaos Reppas, Yilin Gui, Ben Wetenhall, Colin Davie

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Injection of CO2 inside wellbore can induce different kind of loadings that can lead to thermal, hydraulic, and mechanical changes on the surrounding rock. A dual-porosity theoretical constitutive model will be presented for the stability analysis of the wellbore during CO2 injection. An elastoplastic damage response will be considered. A bounding yield surface will be presented considering damage effects on sandstone. The main target of the research paper is to present a theoretical constitutive model that can help industries to safely store CO2 in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elasto-plastic damage Thermo-Hydraulic-Mechanical theoretical model will be validated from existing experimental data for sandstone after simulating some scenarios by using FEM on MATLAB software.

Keywords: carbon capture and storage, rock mechanics, THM effects on rock, constitutive model

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Authors: Asghar Ebrahimzadeh, Sattar Malekian, Mohammad Ali Aazami, Mohammad Bagher Hassanpouraghdam

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Roses are of main ornamental flowers worldwide. Rosa damascena Mill., besides being an ornamental plant, has major pharmaceutical, cosmetic and fragrance applications. Traditional propagation methods of the plant are using suckers, cutting and grafting. In the present experiment, we used the different explants (leaf section, petioles and nodal cutting) for the optimization of this high-valued ornamental from a native clonal plant. Diverse explants were acquired from mature plants during the growing season and were planted on MS medium supplemented with different hormonal combinations. 70% alcohol and sodium hypochloride were utilized for the surface sterilization. For proliferation, BAP and BA (1-5 mg L-1) and NAA (1-2 mg L-1) were tested. The highest proliferation rate was afforded from MS medium supplemented with 1.5 mg L-1 BA and 5 mg L-1 BAP. Callogenesis from leaf samples and petioles was the best with 1/2 MS medium enriched with 1mg L-1 BAP and 4 mg L-1 2,4-D. Rooting was occurred with the highest frequency in a medium containing 0.1 mg L-1 IBA.

Keywords: Rosa damascene, micropropagation, petiole, IBA, BAP

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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Authors: Abolfazl Bezaatpour, Sahar Khatami

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Fe3O4 nanoparticles were prepared by the co-precipitation method and silica was then coated on the magnetic nanoparticles followed by modification with (3-aminopropyl) trimethoxysilane. Then, dioxomolybdenum(VI) Schiff base complex of N,N′-bis(5-chloromethyl-salicylidine)-1,2-phenylenediamine) was immobilized on the surface of magnetic nanoparticles as a heterogeneous catalyst. The catalyst was identified by scanning electron microscopy (SEM) and vibrating sample magnetometer (VSM), X-ray diffraction, IR spectroscopy, diffuse reflectance spectra and atomic absorption spectroscopy techniques. The catalyst shows excellent catalytic activity in epoxidation of olefins using tert-butylhydroperoxide in 1,2-dichloroethane. In this report, the supported complex exhibited 100% selectivity for epoxidation with 100% conversion for cyclooctene. Nanocatalyst can be easily recovered by a magnetic field and reused for subsequent reactions for at least 5 times with less deterioration in catalytic activity.

Keywords: dioxomolybdenum (VI), epoxidation, nanocatalysis, nanoparticles, Schiff base

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Manoj Kumar Gupta, Jayashree Bijwe

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Additives in lubricating oils are the focus of research attention since the further reduction in friction and wear properties of oils would lead to the further saving of tribo-materials and energy apart from improving their efficiency. Remarkable tribo-performance enhancement is reported in the literature due to addition of particles of solid lubricants in lubricating oils; especially that of nano-sizes. In the present work graphite nano-particles (NPs) in various amounts (1, 2, 3 and 4 wt. %) were used to explore the possible anti-wear (AW) performance enhancement in Group III oil. Polyisobutylene succinimide (PIBSI- 1 wt. %) was used as a dispersant for dispersing these NPs and to enhance the stability of these nano-suspensions. It was observed that PIBSI inclusion enhanced the stability of oil almost by eight times. NPs in all amounts enhanced the AW performance of oil considerably. The optimum amount was three wt. %, which led to the highest enhancement under all loads. The extent of benefits, however, were dependent on load. At the lowest (392 N) and highest loads (784 N), the benefits were not profound. At moderate load (588 N), highest improvement (around 60 %) was recorded. The SEM and AFM studies were done on the worn ball surfaces to reveal the detailed features of films transferred and proved useful to correlate the wear performance of oils.

Keywords: dispersant, graphite, nano-lubricant, anti-wear additive

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Authors: Synthia Atas Sari, Engkos Achmad Kuncoro, Haryadi Sarjono

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The purpose of this paper is to examine the impact of reward system which is determined by government over the work of Board of Commissioners in implementing good corporate governance in Indonesian state-owned enterprises. To do so, this study analyses the adequacy of the remuneration, the job attractiveness, and the board commitment and dedication with the remuneration system. Qualitative method used to examine the significant features and challenges to the government policy over the remuneration determination for the board of commissioners to their roles. Data are gathered through semi-structure in-depth interview to the 21 participants over 10 Indonesian stated-owned enterprises and written documents. Findings in this study indicate that government policies over the remuneration system is not effective to increase the performance of board of commissioners in implementing good corporate governance in Indonesian state-owned enterprises due to unattractiveness of the remuneration amount, demotivate active members, and conflict interest over members of the remuneration committee.

Keywords: reward system, board of commissioners, state-owned enterprises, good corporate governance

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Authors: Raj Kishore Swain, Kamdev Sethy, Sumanta Kumar Mishra

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Selenium is an essential trace element for the chicken with a variety of biological functions like growth, fertility, immune system, hormone metabolism, and antioxidant defense systems. Selenium deficiency in chicken causes exudative diathesis, pancreatic dystrophy and nutritional muscle dystrophy of the gizzard, heart and skeletal muscle. Additionally, insufficient immunity, lowering of production ability, decreased feathering of chickens and increased embryo mortality may occur due to selenium deficiency. Nano elemental selenium, which is bright red, highly stable, soluble and of nano meter size in the redox state of zero, has high bioavailability and low toxicity due to the greater surface area, high surface activity, high catalytic efficiency and strong adsorbing ability. To assess the effect of dietary nano-Se on performance and expression of gene in Vencobb broiler birds in comparison to its inorganic form (sodium selenite), four hundred fifty day-old Vencobb broiler chicks were randomly distributed into 9 dietary treatment groups with two replicates with 25 chicks per replicate. The dietary treatments were: T1 (Control group): Basal diet; T2: Basal diet with 0.3 ppm of inorganic Se; T3: Basal diet with 0.01875 ppm of nano-Se; T4: Basal diet with 0.0375 ppm of nano-Se; T5: Basal diet with 0.075 ppm of nano-Se, T6: Basal diet with 0.15 ppm of nano-Se, T7: Basal diet with 0.3 ppm of nano-Se, T8: Basal diet with 0.60 ppm of nano-Se, T9: Basal diet with 1.20 ppm of nano-Se. Nano selenium was synthesized by mixing sodium selenite with reduced glutathione and bovine serum albumin. The experiment was carried out in two phases: starter phase (0-3 wks), finisher phase (4-5 wk) in deep litter system. The body weight at the 5th week was best observed in T4. The best feed conversion ratio at the end of 5th week was observed in T4. Erythrocytic catalase, glutathione peroxidase and superoxide dismutase activity were significantly (P < 0.05) higher in all the nano selenium treated groups at 5th week. The antibody titers (log2) against Ranikhet diseases vaccine immunization of 5th-week broiler birds were significantly higher (P < 0.05) in the treatments T4 to T7. The selenium levels in liver, breast, kidney, brain, and gizzard were significantly (P < 0.05) increased with increasing dietary nano-Se indicating higher bioavailability of nano-Se compared to inorganic Se. The real time polymer chain reaction analysis showed an increase in the expression of antioxidative gene in T4 and T7 group. Therefore, it is concluded that supplementation of nano-selenium at 0.0375 ppm over and above the basal level can improve the body weight, antioxidant enzyme activity, Se bioavailability and expression of the antioxidative gene in broiler birds.

Keywords: chicken, growth, immunity, nano selenium

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Authors: Wang Zhaoming, Shao Shegang, Chen Xiaorong, Qi Yanan, Tian Lei, Wang Jian

Abstract:

This study conducts a comparative analysis of the spectral curves of asphalt pavements at various aging stages to improve road information extraction from high-resolution remote sensing imagery. By examining the distinguishing capabilities and spectral characteristics, the research aims to establish a pavement information extraction methodology based on China's high-resolution satellite images. The process begins by analyzing the spectral features of asphalt pavements to construct a spectral assessment model suitable for evaluating pavement health. This model is then tested at a national highway traffic testing site in China, validating its effectiveness in distinguishing different pavement aging levels. The study's findings demonstrate that the proposed model can accurately assess road health, offering a valuable tool for road maintenance planning and infrastructure management.

Keywords: spectral analysis, asphalt pavement aging, high-resolution remote sensing, pavement health assessment

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Authors: Andriy Magula

Abstract:

With the help of a special algorithm being the principle of multilevel periodicity, the periodic change of properties at the nuclear level of chemical elements was discovered and the variant for the periodic system of isotopes was presented. The periodic change in the properties of isotopes, as well as the vertical symmetry of subgroups, was checked for consistency in accordance with the following ten types of experimental data: mass ratio of fission fragments; quadrupole moment values; magnetic moment; lifetime of radioactive isotopes; neutron scattering; thermal neutron radiative capture cross-sections (n, γ); α-particle yield cross-sections (n, α); isotope abundance on Earth, in the Solar system and other stellar systems; features of ore formation and stellar evolution. For all ten cases, the correspondences for the proposed periodic structure of the nucleus were obtained. The system was formed in the usual 2D table, similar to the periodic system of elements, and the mass series of isotopes was divided into 8 periods and 4 types of ‘nuclear’ orbitals: sn, dn, pn, fn. The origin of ‘magic’ numbers as a set of filled charge shells of the nucleus was explained. Due to the isotope system, the periodic structure is shown at a new level of the universe, and the prospects of its practical use are opened up.

Keywords: periodic system, isotope, period, subgroup, “nuclear” orbital, nuclear reaction

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Authors: Man-Ching Yu

Abstract:

In Chinese music, pentatonic collection is central in constituting all the harmonic and melodic elements; most of the traditional Chinese musicians particularly emphasize the importance of the smoothness between pentatonic collections when one collection modulates to another collection, articulating the roles of the pentatonic common tones. On the contrary, in post-tonal Chinese music the central features of the pentatonic modulations tend to reflect a larger number of semitonal relationships with a lesser number of common tones. This paper offers an analytical account of the transformations between pentatonic collections that arise in post-tonal Chinese music by adopting the methodology of the Tonnetz, in particular, Dual Interval Space (DIS), to elaborate and reexamine pentatonicism by focusing on the transformations between pentatonic elements, especially semitonal motion and common tones. In the essay, various pentatonic passages will be analyzed by means of DIS for highlighting the transformation of the collections. It will be shown that the pentatonic collections that are in semitonal, third, and augmented fourth relationships exhibit the maximum number of semitonal shifts.

Keywords: tonnetz, pentatonicism, post-tonal Chinese music, dual interval space, transformation

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Authors: J. Andrade-Garda, A. Anguera, J. Ares-Casal, M. Hidalgo-Lorenzo, J.-A. Lara, D. Lizcano, S. Suárez-Garaboa

Abstract:

In the current constantly changing economic context, collaborative networks allow partners to undertake projects that would not be possible if attempted by them individually. These projects usually involve the performance of a group of tasks (named roles) that have to be distributed among the partners. Thus, an allocation/matching problem arises that will be referred to as Role-Partner Allocation problem. In real life this situation is addressed by negotiation between partners in order to reach ad hoc agreements. Besides taking a long time and being hard work, both historical evidence and economic analysis show that such approach is not recommended. Instead, the allocation process should be automated by means of a centralized matching scheme. However, as a preliminary step to start the search for such a matching mechanism (or even the development of a new one), the problem and its core components must be specified. To this end, this paper establishes (i) the definition of the problem and its constraints, (ii) the key features of the involved elements (i.e., roles and partners); and (iii) how to create preference lists both for roles and partners. Only this way it will be possible to conduct subsequent methodological research on the solution method.     

Keywords: collaborative network, matching, partner, preference list, role

Procedia PDF Downloads 235

Authors: Torchane Lazhar

Abstract:

In this work, our task consists in optimizing the nitriding treatment at low-temperature of the steel 32CrMoV13 by the way of the mixtures of ammonia gas, nitrogen and hydrogen to improve the mechanical properties of the surface (good wear resistance, friction and corrosion), and of the diffusion layer of the nitrogen (good resistance to fatigue and good tenacity with heart). By limiting our work to the pure iron and to the alloys iron-chromium and iron-chrome-carbon, we have studied the various parameters which manage the nitriding: flow rate and composition of the gaseous phase, the interaction chromium-nitrogen and chromium-carbon by the help of experiments of nitriding realized in the laboratory by thermogravimetry. The acquired knowledge have been applied by the mastery of the growth of the combination layer on the diffusion layer in the case of the industrial steel 32CrMoV13.

Keywords: diffusion of nitrogen, gaseous nitriding, layer growth kinetic, steel

Procedia PDF Downloads 412

Authors: Zi Zhu

Abstract:

The last decade has witnessed increasing urban environmental uprisings in China, as thousands of citizens swarmed into streets to express their deep concerns about the environmental threat and public health through various collective actions. The prevalent western approaches to collective actions, which usually treat urban riots and social movements as distinct phenomenon, have plagued an adequate analysis of the urban environmental uprisings in China. The increasing urban environmental contention can neither be categorized into riots nor social movements, as they carry the features of both: at first sight, they are spontaneous, disorganized and disruptive with an absence of observable mobilization process; however, unlike riots in the west, these collective actions conveyed explicit demand in a mostly non-destructive way rather than a pure expression of frustration. This article proposes a different approach to urban environmental uprisings in China which concerns the diminishing boundaries between riots and social movements and points to the underlying structural causes to the unique forms of urban environmental contention. Taking the urban anti-PX protests as examples, this article analyzes the societal and political structural environment faced by the Chinese environmental protesters and its influence on the origin and development of their contention.

Keywords: urban environmental uprisings, China, anti-PX protests, opportunity structure

Procedia PDF Downloads 289