Search results for: q-rung orthopair fuzzy sets

Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

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Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

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Authors: Louiza C. Duncker, Duarte Gonçalves

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Wildlife crime is a complex problem with many interconnected facets, which are generally responded to in parts or fragments in efforts to “break down” the complexity into manageable components. However, fragmentation increases complexity as coherence and cooperation become diluted. A whole-of-society approach has been developed towards finding a common goal and integrated approach to preventing wildlife crime. As part of this development, research was conducted in rural communities adjacent to conservation areas in South Africa to define and comprehend the challenges faced by them, and to understand their perceptions of wildlife crime. The results of the research showed that the perceptions of community members varied - most were in favor of conservation and of protecting rhinos, only if they derive adequate benefit from it. Regardless of gender, income level, education level, or access to services, conservation was perceived to be good and bad by the same people. Even though people in the communities are poor, a willingness to stop rhino poaching does exist amongst them, but their perception of parks not caring about people triggered an attitude of not being willing to stop, prevent or report poaching. Understanding the nuances, the history, the interests and values of community members, and the drivers behind poaching mind-sets (intrinsic or driven by transnational organized crime) is imperative to create sustainable and resilient communities on multiple levels that make a substantial positive impact on people’s lives, but also conserve wildlife for posterity.

Keywords: community perceptions, conservation, rhino poaching, whole-of-society approach, wildlife crime

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Authors: Akmuhammet Karayev, Hassam Mazhar, Mamdouh Al Harthi

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Polyethylene terephthalate (PET) recycling stands as a pivotal solution in combating plastic pollution and fostering a circular economy. This study addresses the catalytic glycolysis of PET, a key step in its recycling process, using synthesized catalysts. Our focus lies in elucidating the catalytic mechanism, optimizing reaction kinetics, and enhancing reactor design for efficient PET conversion. We synthesized anionic clays tailored for PET glycolysis and comprehensively characterized them using XRD, FT-IR, BET, DSC, and TGA techniques, confirming their suitability as catalysts. Through systematic parametric studies, we optimized reaction conditions to achieve complete PET conversion to bis hydroxy ethylene terephthalate (BHET) with over 75% yield within 2 hours at 200°C, employing a minimal catalyst concentration of 0.5%. These results underscore the catalysts' exceptional efficiency and sustainability, positioning them as frontrunners in catalyzing PET recycling processes. Furthermore, we demonstrated the recyclability of the obtained BHETs by repolymerizing them back to PET without the need for a catalyst. Heating the BHETs in a distillation unit facilitated their conversion back to PET, highlighting the closed-loop potential of our recycling approach. Our work embodies a significant leap in catalytic glycolysis kinetics, driven by sustainable catalysts, offering rapid and high-impact PET conversion while minimizing environmental footprint. This breakthrough not only sets new benchmarks for efficiency in PET recycling but also exemplifies the pivotal role of catalysis and reaction engineering in advancing sustainable materials management.

Keywords: polymer recycling, catalysis, circular economy, glycolysis

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Authors: Adeniyi G. Adeogun, Bolaji F. Sule, Adebayo W. Salami, Michael O. Daramola

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Estimation of water yield and water balance in a river catchment is critical to the sustainable management of water resources at watershed level in any country. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) interfaced with Geographical Information System (GIS) was applied as a tool to predict water balance and water yield of a catchment area in Nigeria. The catchment area, which was 12,992km2, is located upstream Jebba hydropower dam in North central part of Nigeria. In this study, data on the observed flow were collected and compared with simulated flow using SWAT. The correlation between the two data sets was evaluated using statistical measures, such as, Nasch-Sucliffe Efficiency (NSE) and coefficient of determination (R2). The model output shows a good agreement between the observed flow and simulated flow as indicated by NSE and R2, which were greater than 0.7 for both calibration and validation period. A total of 42,733 mm of water was predicted by the calibrated model as the water yield potential of the basin for a simulation period 1985 to 2010. This interesting performance obtained with SWAT model suggests that SWAT model could be a promising tool to predict water balance and water yield in sustainable management of water resources. In addition, SWAT could be applied to other water resources in other basins in Nigeria as a decision support tool for sustainable water management in Nigeria.

Keywords: GIS, modeling, sensitivity analysis, SWAT, water yield, watershed level

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Authors: Benjamin M Dauda, Esther Ibrahim, Sylvester Gadimoh, Asabe Mustapha, Jiyah Mohammed

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Despite diverse optimization techniques on natural hydrophilic fibers, hydrophobic synthetic fibers are still the best oil sorption materials. However, these hydrophobic fibers are not biodegradable, making their disposal problematic. To this end, this work sets out to develop Nonwoven sorbents from epoxy-coated Cotton fibers. As a way of improving the compatibility of the crude oil and reduction of moisture absorption, cotton fibers were coated with epoxy resin by immersion in acetone-thinned epoxy solution. A needle-punching machine was used to convert the fibers into coherent nonwoven sheets. An oil sorption experiment was then carried out. The result indicates that the developed epoxy-modified sorbent has a higher crude oil-sorption capacity compared with those of untreated cotton and commercial polypropylene sorbents. Absorption Curves show that the coated fiber and polypropylene sorbent saturated faster than the uncoated cotton fiber pad. The result also shows that the coated cotton sorbent adsorbed crude faster than the polypropylene sorbent, and the equilibrium exhaustion was also higher. After a simple mechanical squeezing process, the Nonwoven pads could be restored to their original form and repeatedly recycled for oil/water separation. The results indicate that the cotton-coated non-woven pads hold promise for the cleanup of oil spills. Our data suggests that the sorption behaviors of the epoxy-coated Nonwoven pads and their crude oil sorption capacity are relatively stable under various environmental conditions compared to the commercial sheet.

Keywords: oil spill, adsorption, cotton, epoxy, nonwoven

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Authors: Meaghan Bowman

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Microblogging has become increasingly popular for commenting on current events, spreading gossip, and encouraging individualism--which favors its low-context communication channel. These social media (SM) platforms allow users to express opinions while interacting with a wide range of populations. Hashtags allow immediate identification of like-minded individuals worldwide on a vast array of topics. The output of the analytic tool, Linguistic Inquiry and Word Count (LIWC)--a program that associates psychological meaning with the frequency of use of specific words--may suggest the nature of individuals’ internal states and general sentiments. When applied to groupings of SM posts unified by a hashtag, such information can be helpful to community leaders during periods in which the forming of public opinion happens in parallel with the unfolding of political, economic, or social events. This is especially true when outcomes stand to impact the well-being of the group. Here, we applied the online tools, Google Translate and the University of Texas’s LIWC, to a 90-posting sample from a corpus of Colombian Spanish microblogs. On translated disjoint sets, identified by hashtag as being authored by advocates of voting “No,” advocates voting “Yes,” and entities refraining from hashtag use, we observed the value of LIWC’s Tone feature as distinguishing among the categories and the word “peace,” as carrying particular significance, due to its frequency of use in the data.

Keywords: Colombia peace referendum, FARC, hashtags, linguistics, microblogging, social media

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Authors: Jairo Alejandro Fernandez Ortega

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Objective: Regarding effects of training velocity on strength in the functional condition of older adults controversy exists. The purpose of this study was to examine the effects of a twelve-week strength training program (PE) performed at high speed (GAV) versus a traditionally executed program (GBV), on functional performance, maximum strength and muscle power in a group of older adult women. Methodology: 86 women aged between 60-81 years participated voluntarily in the study and were assigned randomly to the GAV (three series at 40% 1RM at maximum speed, with maximum losses of 10% speed) or to the GBV (three series with three sets at 70% of 1RM). Both groups performed three weekly trainings. The maximum strength of upper and lower limbs (1RM), prehensile strength, walking speed, maximum power, mean propulsive velocity (MPV) and functional performance (senior fitness test) were evaluated before and after the PE. Results: Significant improvements were observed (p < 0.05) in all the tests in the two groups after the twelve weeks of training. However, the results of GAV were significantly (P < 0.05) higher than those of the GBV, in the tests of agility and dynamic equilibrium, stationary walking, sitting and standing, walking speed over 4 and 6 meters, MPV and peak power. In the tests of maximum strength and prehensile force, the differences were not significant. Conclusion: Strength training performed at high speeds seems to have a better effect on functional performance and muscle power than strength training performed at low speed.

Keywords: power training, resistance exercise, aging, strength, physical performance, high-velocity, resistance training

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Authors: Adnan Ahmad, Yusri Kamin, Asnol Dahar Minghat, Mohd. Khir Nordin, Dayana Farzeha, Ahmad Nabil

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The purpose of this study is to identify the teaching method practices of the practical work subject in Vocational Secondary School. This study examined the practice of Vocational Teaching Method in Automotive Practical Work. The quantitative method used the sets of the questionnaire. 283 students and 63 teachers involved from ten VSS involved in this research. Research finding showed in conducting the introduction session teachers prefer used the demonstration method and questioning technique. While in deliver the content of practical task, teachers applied group monitoring and problem-solving approach. To conclude the task of automotive practical work, teachers choose re-explain and report writing to make sure students really understand all the process of teaching. VTM-APW also involved the competency-based concept to embed in the model. Derived from factors investigated, research produced the combination of elements in teaching skills and vocational skills which could be used as the best teaching method in automotive practical work for school level. As conclusion this study has concluded that the VTM-APW model is able to apply in teaching to make an improvement with current practices in Vocational Secondary School. Hence, teachers are suggested to use this method to enhance student's knowledge in Automotive and teachers will deliver skills to the current and future workforce relevant with the required competency skilled in workplace.

Keywords: vocational teaching method, practical task, teacher preferences, student preferences

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

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PERMATApintar^® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar^® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar^® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar^® biology curriculum.

Keywords: academic performances, biology, gender differences, gifted students,

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Authors: Hafsat Iyabo Sa'adu

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A salient feature of the Nigerian Tax Law is the right of the taxpayer to demand for a refund where excess tax is paid. Section 23 of the Federal Inland Revenue Service (Establishment) Act, 2007 vests Federal Inland Revenue Services with the power to make tax refund as well as set guidelines and requirements for refund process from time to time. In addition, Section 61 of the Federal Inland Revenue Service (Establishment) Act, 2007, empowers the Federal Inland Revenue Services to issue information circular to acquaint stakeholders with the policy on the refund process. A Circular was issued to that effect to correct the position that until after the annual audit of the Service before such excess can be paid to the claimant/taxpayer. But it is amazing that such circular issuance does not feature under the states’ laws. Hence, there is an inconsistencies in the tax paying system in Nigeria. This study, therefore, sets an objective, to examine the trending concept of tax refund in Nigeria. In order to achieve this set objective, a doctrinal study went under way, wherein both federal and states laws were consulted including journals and textbooks. At the end of the research, it was revealed that the law should be specific as to the time frame within which to make the refund. It further revealed that it is essential to put up a legal framework for the tax system to recognize excess payment as debt due from the state. This would provide a foundational framework for the relationship between taxpayers and Federal Inland Revenue Service as well as promote effective tax administration in all the states of the federation. Several Recommendations were made especially relating to legislative passage of ‘’Refund Circular Bill at the states levels’ pursuant to the Federal Inland Revenue Service (Establishment) Act, 2007.

Keywords: claim, Nigeria, refund, right

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: Dainius Genys, Vylius Leonavicius, Ricardas Krikstolaitis

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Energy security problems in Lithuania are analyzed on a regular basis; however, there is no comprehensive research on the very issue of the concept of public energy security. There is a lack of attention not only to social determinants of perception of energy security, but also a lack of a deeper analysis of the public opinion. This article aims to research the Lithuanian public perception of energy security. Complex tasks were set during the sociological study. Survey questionnaire consisted of different sets of questions: view of energy security (risk perception, political orientation, and energy security; comprehensiveness and energy security); view of energy risks and threats (perception of energy safety factors; individual dependence and burden; disobedience and risk); view of the activity of responsible institutions (energy policy assessment; confidence in institutions and energy security), demographic issues. In this article, we will focus on two aspects: a) We will analyze public opinion on the most important aspects of energy security and social factors influencing them; The hypothesis is made that public perception of energy security is related to value orientations: b) We will analyze how public opinion on energy policy executed by the government and confidence in the government are intertwined with the concept of energy security. Data of the survey, conducted on May 10-19 and June 7-17, 2013, when Seimas and the government consisted of the coalition dominated by Social Democrats with Labor, Order and Justice Parties and the Electoral Action of Poles, were used in this article. It is important to note that the survey was conducted prior to Russia’s occupation of the Crimea.

Keywords: energy security, public opinion, risk, energy threat, energy security policy

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Ali Essam El Shazly

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The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

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Comprehensive water management considers economic, environmental, technical and social sustainability of water resources for future generations. Integrated water management implies cooperative approach and involves all stakeholders and also introduces issues to managers and decision makers. Solving these issues needs integrated and system approach according to the recognition of actors or key persons in necessary to apply cooperative management of water resources. Therefore, social network analysis can be used to demonstrate the most effective actors for environmental base decisions. The linkage of diverse sets of actors and knowledge systems across management levels and institutional boundaries often poses one of the greatest challenges in adaptive water management. Bridging stakeholder can facilitate interactions among actors in management settings by lowering the transaction costs of collaboration. This research examines how network connections between group members affect in co- management. Cohesive network structures allow groups to more effectively achieve their goals and objectives Strong; centralized leadership is a better predictor of working group success in achieving goals and objectives. Finally, geometric position of each actor was illustrated in the network. The results of the research based on between centrality index have a key and bridging actor in recognition of cooperative management of water resources in Darbandsar village and also will help managers and planners of water in the case of recognition to organization and implementation of sustainable management of water resources and water security.

Keywords: co-management, water management, social network, bridging stakeholder, darbandsar village

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Authors: Taramani Yadav, Gajender Kumar, R.K. Yadav, H.S. Jat

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Soil Salinity and irrigation water salinity is critical threat to enhance agricultural food production to full fill the demand of billion plus people worldwide. Salt affected soils covers 6.73 Mha in India and ~1000 Mha area around the world. Irrigation scheduling of saline water is the way to ensure food security in salt affected areas. Research experiment was conducted at ICAR-Central Soil Salinity Research Institute, Experimental Farm, Nain, Haryana, India with 36 treatment combinations in double split plot design. Three sets of treatments consisted of (i) three regimes of irrigation viz., 60, 80 and 100% (I1, I2 and I3, respectively) of crop ETc (crop evapotranspiration at identified respective stages) in main plot; (ii) four levels of irrigation water salinity (sub plot treatments) viz., 2, 4, 8 and 12 dS m-1 (iii) applications of two PBRs along with control (without PBRs) i.e. salicylic acid (G1; 1 mM) and thiourea (G2; 500 ppm) as sub-sub plot treatments. Grain yield of wheat (Triticum aestivum) was increased with less amount of high salt loaded irrigation water at the same level of salinity (2 dS m-1), the trend was I3>I2>I1 at 2 dS m-1 with 8.10 and 17.07% increase at 80 and 100% ETc, respectively compared to 60% ETc. But contrary results were obtained by increasing amount of irrigation water at same level of highest salinity (12 dS m-1) showing following trend; I1>I2>I3 at 12 dS m-1 with 9.35 and 12.26% increase at 80 and 60% ETc compared to 100% ETc. Enhancement in grain yield of wheat (Triticum aestivum) is not need to increase amount of irrigation water under saline condition, with salty irrigation water less amount of irrigation water gave the maximum wheat (Triticum aestivum) grain yield.

Keywords: Irrigation, Salinity, Wheat, Yield

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Authors: Feiying Wu

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Chatbots are computer programs that attempt to engage a human in a dialogue, which originated in the 1960s with MIT's Eliza. However, they have become widespread more recently as advances in language technology have produced chatbots with increasing linguistic quality and sophistication, leading to their potential to serve as a tool for Computer-Assisted Language Learning(CALL). The aim of this article is to assess the feasibility of using two chatbots, Mitsuku and CleverBot, as pedagogical tools for learning English as a second language by stimulating L2 learners with distinct English proficiencies. Speaking of the input of stimulated learners, they are measured by AntWordProfiler to match the user's expected vocabulary proficiency. Totally, there are four chat sessions as each chatbot will converse with both beginners and advanced learners. For evaluation, it focuses on chatbots' responses from a linguistic standpoint, encompassing vocabulary and sentence levels. The vocabulary level is determined by the vocabulary range and the reaction to misspelled words. Grammatical accuracy and responsiveness to poorly formed sentences are assessed for the sentence level. In addition, the assessment of this essay sets 25% lexical and grammatical incorrect input to determine chatbots' corrective ability towards different linguistic forms. Based on statistical evidence and illustration of examples, despite the small sample size, neither Mitsuku nor CleverBot is ideal as educational tools based on their performance through word range, grammatical accuracy, topic range, and corrective feedback for incorrect words and sentences, but rather as a conversational tool for beginners of L2 English.

Keywords: chatbots, CALL, L2, corrective feedback

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Huazhen Lin, Ruihua Xu, Zhibin Jiang

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In this real-world case, timetabling the LRT network as a whole is rather challenging for the operator: they are supposed to create a timetable to avoid various route conflicts manually while satisfying a given interval and the number of rolling stocks, but the outcome is not satisfying. Therefore, the operator adopts a computerised timetabling tool, the Train Plan Maker (TPM), to cope with this problem. However, with various constraints in the dual-line network, it is still difficult to find an adequate pairing of turnback time, interval and rolling stocks’ number, which requires extra manual intervention. Aiming at current problems, a one-off model for timetabling is presented in this paper to simplify the procedure of timetabling. Before the timetabling procedure starts, this paper presents how the dual-line system with a ring and several branches is turned into a simpler structure. Then, a non-linear programming model is presented in two stages. In the first stage, the model sets a series of constraints aiming to calculate a proper timing for coordinating two lines by adjusting the turnback time at termini. Then, based on the result of the first stage, the model introduces a series of inequality constraints to avoid various route conflicts. With this model, an analysis is conducted to reveal the relation between the ratio of trains in different directions and the possible minimum interval, observing that the more imbalance the ratio is, the less possible to provide frequent service under such strict constraints.

Keywords: light rail transit (LRT), non-linear programming, railway timetabling, timetable coordination

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Authors: Arwa Alzughaibi

Abstract:

Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Dušan Bojović, Wei Huang, Zdravko Stojanović, Jovan Ilić

Abstract:

In an era of ever-growing electricity generation from renewable energy sources, namely wind and solar, a need for reliable energy storage and intensive balancing of the electric power system gains significance. For decades, pump storage hydroelectric power plants have proven to be an important asset regarding the storage of generated electricity. However, with the increasing overall share of wind and solar in electric systems at large, the importance of electric grid stability keeps growing. A large pump storage project, the Bistrica Pump Storage Plant (PSP), is currently under development in Serbia. The Bistrica PSP will be designed as a 600+ MW power plant, which is envisaged as a significant contributor to the Serbian power grid stability as more and more renewable energy sources are implemented over time. PSP Bistrica is seen as a strategically important project on the green agenda path of the Electric Power Industry of Serbia as a necessary pre-condition for the safe implementation of other renewable energy sources. The importance of such a plant would also play an important role in reducing the electricity production from coal, i.e., thermoelectric power plants. During the project’s development, various techniques and technologies are evaluated for the purpose of determining the optimum (the most profitable) solution. Over the course of this paper, these technologies – such as frequency-regulated pump turbines and ternary sets will be presented, with a detailed explanation of their possible application within the Bistrica PSP project and their relative advantages/disadvantages in this particular case.

Keywords: hydraulic turbines, pumped storage, renewable energy, competing technologies

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Authors: Muskan Jain, Baiju Gopal

Abstract:

Objectives: Intimacy in interpersonal relationships is integral to psychological health and everyday wellbeing; the focus is on intimacy, which can be described as feelings of closeness, connection, and belonging within relationships, which is influenced by an individual's gender identity as well as life experiences. The study aims to explore the experiences of intimacy of the non-binary gender; this marginalized community has increased risks of developing the imposter phenomenon. The study explores the influence of IP on the development and sustenance of intimacy in relationships. Methods: The present study accumulates detailed narratives from 10 non-binary young adults ages 18 to 25 in metropolitan cities of India. Thematic analysis was used for the data analysis. Results: Seven major themes have emerged revolving around internalized criticism and self-depreciating behavior, which causes distance between partners. The four themes that result in the internalization of criticism are lack of social stability, invalidation by social units, adverse life experiences, and estrangement due to gender identity. Three themes that encapsulate major difficulties in relationships are limited self-disclosure, inhibition of physical needs, and fear of taking space. The findings have been critically compared and contrasted with the existing body of literature in the domain, which sets the agenda for further inquiry. Conclusion: It is important for future studies to capture the experiences of non-binary genders in India to provide better therapeutic support in order to assist them in forming meaningful and authentic relationships, thus increasing overall wellbeing.

Keywords: imposter phenomenon, intimacy, internalized criticism, marginalized community

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Authors: Shima Dehghan

Abstract:

Aim: imbalance between antioxidant defensive system and increasing production of free radicals caused oxidative stress that can be rolled in cellular damage and occurring some of diseases such as diabetes. The aim of current study was to investigate the effect of eight weeks aerobic training on peroxidant and antioxidants indicators in women with type2 diabetes. Methodology: thirty two inactive women with type 2 diabetes were randomly assigned into four groups: 1. control, 2. Aerobic training, 3. Purslane seed and 4. Aerobic training + Purslane seed groups. Subjects were asked to accomplish eight weeks aerobic training (50 min aerobic exercise, 3 days/week, for to achieve 65-75% maximum of heart rate). Also, subjects in certain groups received purslane seeds for eight weeks. Blood samples were obtained in two sets (one session and after 8 weeks). Data was analyzed using one way ANOVA. A significant difference was accepted at p < 0/05 level. Results: After eight weeks of aerobic training with purslane seeds supplementation, malon dyaldehyde (MDA) concentration in training group were significantly decreased (p < 0/000), but A difference significant was not found in control group. Superoxide dismutase (SOD) and catalase (CAT) concentrations in training group were significantly increased (p < 0/000), while difference significant wasnot found in control group. Conclusion: The finding of the current study indicates that disciplined aerobic training with purslane seeds supplementation can be caused improvement in peroxidant/antioxidant balance in women with type2 diabetes.

Keywords: aerobic training, purslane seed, peroxidant/antioxidant balance, diabetes2

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Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

Abstract:

This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

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Authors: Veronika Zivicova, Petr Broz, Zdenek Fik, Alzbeta Mifkova, Jan Plzak, Zdenek Cada, Herbert Kaltner, Jana Fialova Kucerova, Hans-Joachim Gabius, Karel Smetana Jr.

Abstract:

The possibility to determine genome-wide expression profiles of cells and tissues opens a new level of analysis in the quest to define dysregulation in malignancy and thus identify new tumor markers. Toward this long-term aim, we here address two issues on this level for head and neck cancer specimen: i) defining profiles in different regions, i.e. the tumor, the transition zone and normal control and ii) comparing complete data sets for seven individual patients. Special focus in the flanking immunohistochemical part is given to adhesion/growth-regulatory galectins that upregulate chemo- and cytokine expression in an NF-κB-dependent manner, to these regulators and to markers of differentiation, i.e. keratins. The detailed listing of up- and down-regulations, also available in printed form (1), not only served to unveil new candidates for testing as marker but also let the impact of the tumor in the transition zone become apparent. The extent of interindividual variation raises a strong cautionary note on assuming uniformity of regulatory events, to be noted when considering therapeutic implications. Thus, a combination of test targets (and a network analysis for galectins and their downstream effectors) is (are) advised prior to reaching conclusions on further perspectives.

Keywords: galectins, genome scale sequencing, squamous cell carcinoma, transition zone

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Authors: G. Shahzadi, A. Soulaimani

Abstract:

This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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