Search results for: data structure

Authors: S. Mohammadzadehmoghadam, Y. Dong

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In this study, Bombyx mori silk fibroin/gelatin (SF/GT) nanocomposite with different GT ratio (SF/GT 100/0, 90/10 and 70/30) were prepared by electrospinning process and crosslinked with glutaraldehyde (GA) vapor. Properties of crosslinked SF/GT nanocomposites were investigated by scanning electron microscopy (SEM), mechanical test, water uptake capacity (WUC) and porosity. From SEM images, it was found that fiber diameter increased as GT content increased. The results of mechanical test indicated that the SF/GT 70/30 nanocomposites had both the highest Young’s modulus of 342 MPa and the highest tensile strength of about 14 MPa. However, porosity and WUC decreased from 62% and 405% for pristine SF to 47% and 232% for SF/GT 70/30, respectively. This behavior can be related to higher degree of crosslinking as GT ratio increased which altered the structure and physical properties of scaffolds. This study showed that incorporation of GT into SF nanofibers can enhance mechanical properties of resultant nanocomposite, but the GA treatment should be optimized to control and fine-tune other properties to warrant their biomedical application.

Keywords: electrospinning, gelatin, silk fibroin, mechanical properties, nanocomposites

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

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Authors: Soroor Ghaziof, Wei Gao

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Sol-enhanced Zn-Ni-Al2O3 nano-composite coatings were electroplated on mild steel by our newly developed sol-enhanced electroplating method. In this method, transparent Al2O3 sol was added into the acidic Zn-Ni bath to produced Zn-Ni-Al2O3 nano-composite coatings. The chemical composition, microstructure and mechanical properties of the composite and alloy coatings deposited at two different agitation speed were investigated. The structure of all coatings was single γ-Ni5Zn21 phase. The composite coatings possess refined crystals with higher microhardness compared to Zn-Ni alloy coatings. The wear resistance of Zn-Ni coatings was improved significantly by incorporation of alumina nano particles into the coatings. Higher agitation speed provided more uniform coatings with smaller grain sized and slightly higher microhardness. Considering composite coatings, high agitation speeds may facilitate co-deposition of alumina in the coatings.

Keywords: microhardness, sol-enhanced electroplating, wear resistance, Zn-Ni-Al2O3 composite coatings

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Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Janis Matvejs

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Visual representation of a city creates unique perspectives that allow to interpret the urban environment and enable to understand a space that is culturally created and territorially organized. Residential complexes are an essential part of cities and cinema is a specific representation form of these areas. There has been very little research done on exploring how these areas are depicted in the Thai movies. The aim of this research is to interpret the discourse of residential areas of Bangkok throughout the 20th and 21st centuries and to examine essential changes in the residential structure. Specific cinematic formal techniques in relation to the urban image were used. The movie review results were compared with changes in Bangkok’s residential development. Movie analysis displayed that residential areas are frequently used in Thai cinematography and they make up an integral part of the urban visual perception.

Keywords: Bangkok, cinema, residential area, representation, visual perception

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Authors: Yuliang Liu, Thomas Lavallee, Mary Weishaar, Gretchen Fricke, Huaibo Xin

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The longitudinal study was designed to investigate the impacts of the International Training Program in Pedagogy (ITPP) at a midwestern institution in the United States on the visiting scholars from China from 2012-18. The study used the survey research method and involved 48 visiting scholars from Northwest Normal University in China in those eight ITPP cohorts. The results of both quantitative and qualitative data were critically examined and indicated both types of data sources revealed similar findings. It was found that the ITPP has significantly affected all scholars' instruction in China. International implications resulted from the study.

Keywords: international training program in pedagogy, visiting scholars, survey research method, International implications

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Authors: Tanja Salary

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This paper discusses a study conducted in a juvenile justice facility regarding medication errors. It includes an introduction to data collected about medication errors in a juvenile justice facility from 2011 - 2019 and explores contributing factors that relate to those errors. The data was obtained from electronic incident records of medication errors that were documented from the years 2011 through 2019. In addition, the presentation reviews both current and historical research of empirical data about patient safety standards and quality care comparing traditional health care facilities to juvenile justice residential facilities and acknowledges a gap in research. The theoretical/conceptual framework for the research study was Bandura and Adams’s self-efficacy theory of behavioral change and Mark Friedman’s results-based accountability theory. Despite the lack of evidence in previous studies addressing medication errors in juvenile justice facilities, this presenter will share information that adds to the body of knowledge, including the potential relationship of medication errors and contributing factors of race and age. Implications for future research include the effect that education and training will have on the communication among juvenile justice staff, including nurses, who administer medications to juveniles to ensure adherence to patient safety standards. There are several opportunities for future research concerning other characteristics about factors that may affect medication administration errors within the residential juvenile justice facility.

Keywords: Juvenile justice, medication errors, juveniles, error reduction strategies

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgiana Duarte

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This study explored early adolescents’ anxious and depressed syndromes in Northeast China. Specifically, the study examined anxious and depressed behaviors and the relationship to education environments. The purpose is to examine how the elements of educational environments and the early adolescents’ behaviors as independent variables influence and possibly predict the early adolescents’ anxious/depressed problems. Achenbach System of Empirically Based Assessment (ASEBA), was the instrument, used in collection of data. A stratified sampling method was utilized to collect data from 2532 participants in seven schools. The results indicated that several background variables influenced anxious/depressed problem. Specifically, age, grade, sports activities and hobbies had a relationship with the anxious/depressed variable.

Keywords: anxious/depressed problems, CBCL, empirically-based assessment, internalizing problems

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Authors: Ramzi Bekri Umer

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Aim: This study attempts to investigate the causes and difficulties with women’s incarceration as well as threat for their reintegration after release from prison with emphasis on the correctional facility of Haramaya city. Method and Methodology: Both quantitative and qualitative research methods were employed in this study; key informant interviews and participant observation were utilized to gather qualitative data, while crosssectional and descriptive research designs were used to gather quantitative data. Findings: This study shows that the women's incarceration was caused by their family histories, genderbased violence, illiteracy, and socioeconomic issues. The principal charges made against the female culprits were theft, vandalism, murder, and moral perversion. A poor quality of life in prison, concerns about family dissolution, emotional instability, financial difficulties, and a lack of spirituality were the main causes of unhappiness for the women behind bars, while social stigma, mistrust, and retaliation fears were the main obstacles to the women's ability to reintegrate into their families and communities. Theoretical Importance: This study involves incarcerated women at correctional center of Haramaya who committed various types of crimes. The local government sectors and non-governmental organization will gain from the study in order to create workable plans to reduce women's criminality and the growing number of female lawbreakers. Local communities and other governmental and nongovernmental partners will be able to support gender equality initiatives that seek to eradicate gender-based violence and discrimination, which worsen the criminality of women. Data Collection and Analysis Procedures: The quantitative and qualitative data were collected prospectively from a sample of 100 women prisoners. Quantitative data were analyzed using descriptive statistics, whereas, thematic analysis, were used for qualitative data. Question Answered: 1. What are the main causes women’s imprisonment in Haramaya city correctional facility. 2. What are the main obstacles of the women's ability to reintegrate into their families and communities after released from incarceration. Conclusion: The study concludes that incarcerated women experience a tremendous impact on their daily life. It highlights the importance of addressing factors such as family backgrounds, gender-based violence, illiteracy and socio-economic problem to decrease the number of women imprisonment. Detention environment, fear for family breakup, financial hardship and deprivation of spiritual life are the major sources of distress among the incarcerated women.

Keywords: Ethiopia, women prisoner, incarceration, reintegration

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Authors: Santiago Quesada-García, María Lozano-Gómez, Pablo Valero-Flores

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The recent digital revolution, together with modern technologies, is changing the environment and the way people interact with inhabited space. However, in society, the elderly are a very broad and varied group that presents serious difficulties in understanding these modern technologies. Outpatients with cognitive disabilities, such as those suffering from Alzheimer's disease (AD), are distinguished within this cluster. This population group is in constant growth, and they have specific requirements for their inhabited space. According to architecture, which is one of the health humanities, environments are designed to promote well-being and improve the quality of life for all. Buildings, as well as the tools and technologies integrated into them, must be accessible, inclusive, and foster health. In this new digital paradigm, artificial intelligence (AI) appears as an innovative resource to help this population group improve their autonomy and quality of life. Some experiences and solutions, such as those that interact with users through chatbots and voicebots, show the potential of AI in its practical application. In the design of healthy spaces, the integration of AI in architecture will allow the living environment to become a kind of 'exo-brain' that can make up for certain cognitive deficiencies in this population. The objective of this paper is to address, from the discipline of neuroarchitecture, how modern technologies can be integrated into everyday environments and be an accessible resource for people with cognitive disabilities. For this, the methodology has a mixed structure. On the one hand, from an empirical point of view, the research carries out a review of the existing literature about the applications of AI to build space, following the critical review foundations. As a unconventional architectural research, an experimental analysis is proposed based on people with AD as a resource of data to study how the environment in which they live influences their regular activities. The results presented in this communication are part of the progress achieved in the competitive R&D&I project ALZARQ (PID2020-115790RB-I00). These outcomes are aimed at the specific needs of people with cognitive disabilities, especially those with AD, since, due to the comfort and wellness that the solutions entail, they can also be extrapolated to the whole society. As a provisional conclusion, it can be stated that, in the immediate future, AI will be an essential element in the design and construction of healthy new environments. The discipline of architecture has the compositional resources to, through this emerging technology, build an 'exo-brain' capable of becoming a personal assistant for the inhabitants, with whom to interact proactively and contribute to their general well-being. The main objective of this work is to show how this is possible.

Keywords: Alzheimer’s disease, artificial intelligence, healthy architecture, neuroarchitecture, architectural design

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Authors: Belloui Bouzid

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In this paper, broadband design of erbium doped fiber amplifier (EDFA) is demonstrated and proved experimentally. High and broad gain is covered in C and L bands. The used technique combines, in one configuration, two double passes with split band structure for the amplification of two traveled signals one for the C band and the other for L band. This new topology is to investigate the trends of high gain and wide amplification at different status of pumping power, input wavelength, and input signal power. The presented paper is to explore the performance of EDFA gain using what it can be called double pass double branch wide band amplification configuration. The obtained results show high gain and wide broadening range of 44.24 dB and 80 nm amplification respectively.

Keywords: erbium doped fiber amplifier, erbium doped fiber laser, optical amplification, fiber laser

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Authors: Biswaranjan D. Mohapatra, Ipsha Hota, Swarna P. Mantry, Nibedita Behera, Kumar S. K. Varadwaj

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Designing highly active and low-cost oxygen evolution (2H₂O → 4H⁺ + 4e⁻ + O₂) electrocatalyst is one of the most active areas of advanced energy research. Some precious metal-based electrocatalysts, such as IrO₂ and RuO₂, have shown excellent performance for oxygen evolution reaction (OER); however, they suffer from high-cost and low abundance which limits their applications. Recently, layered double hydroxides (LDHs), composed of layers of divalent and trivalent transition metal cations coordinated to hydroxide anions, have gathered attention as an alternative OER catalyst. However, LDHs are insulators and coupled with carbon materials for the electrocatalytic applications. Graphene covalently doped with nitrogen has been demonstrated to be an excellent electrocatalyst for energy conversion technologies such as; oxygen reduction reaction (ORR), oxygen evolution reaction (OER) & hydrogen evolution reaction (HER). However, they operate at high overpotentials, significantly above the thermodynamic standard potentials. Recently, we reported remarkably enhanced catalytic activity of benzoate or 1-pyrenebutyrate functionalized N-doped graphene towards the ORR in alkaline medium. The molecular and heteroatom co-doping on graphene is expected to tune the electronic structure of graphene. Therefore, an innovative catalyst architecture, in which LDHs are anchored on aromatic acid functionalized ‘N’ doped graphene may presumably boost the OER activity to a new benchmark. Herein, we report fabrication of Co₂Fe-LDH on aromatic acid (AA) functionalized ‘N’ doped reduced graphene oxide (NG) and studied their OER activities in alkaline medium. In the first step, a novel polyol method is applied for synthesis of AA functionalized NG, which is well dispersed in aqueous medium. In the second step, Co₂Fe LDH were grown on AA functionalized NG by co-precipitation method. The hybrid samples are abbreviated as Co₂Fe LDH/AA-NG, where AA is either Benzoic acid or 1, 3-Benzene dicarboxylic acid (BDA) or 1, 3, 5 Benzene tricarboxylic acid (BTA). The crystal structure and morphology of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). These studies confirmed the growth of layered single phase LDH. The electrocatalytic OER activity of these hybrid materials was investigated by rotating disc electrode (RDE) technique on a glassy carbon electrode. The linear sweep voltammetry (LSV) on these catalyst samples were taken at 1600rpm. We observed significant OER performance enhancement in terms of onset potential and current density on Co₂Fe LDH/BTA-NG hybrid, indicating the synergic effect. This exploration of molecular functionalization effect in doped graphene and LDH system may provide an excellent platform for innovative design of OER catalysts.

Keywords: π-π functionalization, layered double hydroxide, oxygen evolution reaction, reduced graphene oxide

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Authors: Shahram Nanekarania, Majid Goodarzia

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Calpastatin and callipyge have been known as one of the candidate genes in meat quality and quantity. Calpastatin gene has been located to chromosome 5 of sheep and callipyge gene has been localized in the telomeric region on ovine chromosome 18. The objective of this study was identification of calpastatin and callipyge genes polymorphism and analysis of genotype structure in population of Lori sheep kept in Iran. Blood samples were taken from 120 Lori sheep breed and genomic DNA was extracted by salting out method. Polymorphism was identified using the PCR-RFLP technique. The PCR products were digested with MspI and FaqI restriction enzymes for calpastatin gene and callipyge gene, respectively. In this population, three patterns were observed and AA, AB, BB genotype have been identified with the 0.32, 0.63, 0.05 frequencies for calpastatin gene. The results obtained for the callipyge gene revealed that only the wild-type allele A was observed, indicating that only genotype AA was present in the population under consideration.

Keywords: polymorphism, calpastatin, callipyge, PCR-RFLP, Lori sheep

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Authors: Caroline E. Mendes, Alberto C. Badino

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Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while  was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching  of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.

Keywords: bubble column, internal loop airlift, gas hold-up, kLa

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Authors: Yuan Xu, Xun Liang, Meina Zhang

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The rise and attenuation of the public opinion broadcast of an emergent accident, in the social network, has a close relationship with the dynamic development of its subevents cluster. In this article, we take Tianjin Port explosion's subevents as an example to research the dynamic propagation discipline of Internet public opinion in a sudden accident, and analyze the overall structure of dynamic propagation to propose four different routes for subevents clusters propagation. We also generate network diagrams for the dynamic public opinion propagation, analyze each propagation type specifically. Based on this, suggestions on the supervision and guidance of Internet public opinion broadcast can be made.

Keywords: network dynamic transmission modes, emergent subevents clusters, Tianjin Port explosion, public opinion supervision

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Wesley A. Saltarelli, Nicolas R. Finkler, Adriana C. P. Miwa, Maria C. Calijuri, Davi G. F. Cunha

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The metabolism of the streams is an indicator of ecosystem disturbance due to the influences of the catchment on the structure of the water bodies. The study of the respiration and photosynthesis allows the estimation of energy fluxes through the food webs and the analysis of the autotrophic and heterotrophic processes. We aimed at evaluating the metabolism in streams located in the Brazilian savannah, Cerrado (Sao Carlos, SP), by determining and modeling the daily changes of dissolved oxygen (DO) in the water during one year. Three water bodies with minimal anthropogenic interference in their surroundings were selected, Espraiado (ES), Broa (BR) and Canchim (CA). Every two months, water temperature, pH and conductivity are measured with a multiparameter probe. Nitrogen and phosphorus forms are determined according to standard methods. Also, canopy cover percentages are estimated in situ with a spherical densitometer. Stream flows are quantified through the conservative tracer (NaCl) method. For the metabolism study, DO (PME-MiniDOT) and light (Odyssey Photosynthetic Active Radiation) sensors log data for at least three consecutive days every ten minutes. The reaeration coefficient (k2) is estimated through the method of the tracer gas (SF6). Finally, we model the variations in DO concentrations and calculate the rates of gross and net primary production (GPP and NPP) and respiration based on the one station method described in the literature. Three sampling were carried out in October and December 2015 and February 2016 (the next will be in April, June and August 2016). The results from the first two periods are already available. The mean water temperatures in the streams were 20.0 +/- 0.8C (Oct) and 20.7 +/- 0.5C (Dec). In general, electrical conductivity values were low (ES: 20.5 +/- 3.5uS/cm; BR 5.5 +/- 0.7uS/cm; CA 33 +/- 1.4 uS/cm). The mean pH values were 5.0 (BR), 5.7 (ES) and 6.4 (CA). The mean concentrations of total phosphorus were 8.0ug/L (BR), 66.6ug/L (ES) and 51.5ug/L (CA), whereas soluble reactive phosphorus concentrations were always below 21.0ug/L. The BR stream had the lowest concentration of total nitrogen (0.55mg/L) as compared to CA (0.77mg/L) and ES (1.57mg/L). The average discharges were 8.8 +/- 6L/s (ES), 11.4 +/- 3L/s and CA 2.4 +/- 0.5L/s. The average percentages of canopy cover were 72% (ES), 75% (BR) and 79% (CA). Significant daily changes were observed in the DO concentrations, reflecting predominantly heterotrophic conditions (respiration exceeded the gross primary production, with negative net primary production). The GPP varied from 0-0.4g/m2.d (in Oct and Dec) and the R varied from 0.9-22.7g/m2.d (Oct) and from 0.9-7g/m2.d (Dec). The predominance of heterotrophic conditions suggests increased vulnerability of the ecosystems to artificial inputs of organic matter that would demand oxygen. The investigation of the metabolism in the pristine streams can help defining natural reference conditions of trophic state.

Keywords: low-order streams, metabolism, net primary production, trophic state

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Authors: Masood Sattari

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Using fuel cell technology to generate electricity for large commercial and industrial sites is a growing segment in the fuel cell industry. The installation of these systems involves design, permitting, procurement of long-lead electrical equipment, and construction involving multiple utilities. The installation of each fuel cell system requires the same amount of coordination as the construction of a new structure requiring a foundation, gas, water, and electricity. Each of these components provide variables that can delay and possibly eliminate a new project. As the manufacturing process and efficiency of fuel cell systems improves, so must the installation methods to prevent a ‘bottle-neck’ in the installation phase of the deployment. Installation methodologies to install the systems vary among companies and this paper will examine the methodologies, describe the benefits and drawbacks for each, and provide guideline for the industry to improve overall installation efficiency.

Keywords: construction, installation, methodology, procurement

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Authors: Sarchil H. Qader, Andrew Harfoot, Mathias Kuepie, Sabrina Juran, Attila Lazar, Andrew J. Tatem

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The need for high-quality, reliable, and timely population data, including demographic information, to support the achievement of the sustainable development goals (SDGs) in all countries was recognized by the United Nations' 2030 Agenda for sustainable development. However, many low and middle-income countries lack reliable and recent census data. To achieve reliable and accurate census and survey outputs, up-to-date census enumeration areas and digital national sampling frames are critical. Census enumeration areas (EAs) are the smallest geographic units for collection, disseminating, and analyzing census data and are often used as a national sampling frame to serve various socio-economic surveys. Even for countries that are wealthy and stable, creating and updating EAs is a difficult yet crucial step in preparing for a national census. Such a process is commonly done manually, either by digitizing small geographic units on high-resolution satellite imagery or walking the boundaries of units, both of which are extremely expensive. We have developed a user-friendly tool that could be employed to generate draft EA boundaries automatically. The tool is based on high-resolution gridded population and settlement datasets, GPS household locations, building footprints and uses publicly available natural, man-made and administrative boundaries. Initial outputs were produced in Burkina Faso, Paraguay, Somalia, Togo, Niger, Guinea, and Zimbabwe. The results indicate that the EAs are in line with international standards, including boundaries that are easily identifiable and follow ground features, have no overlaps, are compact and free of pockets and disjoints, and the boundaries are nested within administrative boundaries.

Keywords: enumeration areas, national sampling frame, gridded population data, preEA tool

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Lotfi Hedi Khezami, Mohamed Ben Rabha, N. Sboui, Mounir Gaidi, B. Bessais

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Metal-nano particle-assisted Chemical Etching is an extraordinary developed wet etching method of producing uniform semiconductor nano structure (nano wires) from patterned metallic film on crystalline silicon surface. The metal films facilitate the etching in HF and H2O2 solution and produce silicon nanowires (SiNWs). Creation of different SiNWs morphologies by changing the etching time and its effects on optical and opto electronic properties was investigated. Combination effect of formed SiNWs and stain etching treatment in acid (HF/HNO3/H2O) solution on the surface morphology of Si wafers as well as on the optical and opto electronic properties are presented in this paper.

Keywords: stain etching, porous silicon, silicon nanowires, reflectivity, lifetime, solar cells

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Authors: Majdah Alnefaie

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The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

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Authors: Angela U. Makolo, Temitayo A. Olagunju

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The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained using high throughput experimental procedures. However, these high throughput methods are known to produce very high rates of false positive and negative interactions. In order to construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed. A weighted interaction graph of the Saccharomyces cerevisiae (Baker’s Yeast) organism using the proteins as the nodes and interactions between them as edges was constructed. The weights were obtained using Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model. A pathway was formalized as a simple path in the interaction network from a starting protein and an ending protein of interest. We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. cerevisiae.

Keywords: Bayesian networks, protein interaction networks, Saccharomyces cerevisiae, signalling pathways

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Authors: Basit Shahzad, Abdullatif M. Abdullatif

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Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

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Authors: Bin Liu

Abstract:

Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

Procedia PDF Downloads 145

Authors: Adrian Rifqi, Febe Napitupulu, Erdi Hermawan, Edwin Putra, Yang Leprilian

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This article focuses on the implementation of the production improvement process of the Indonesian land certificate product that printed in Perum Peruri as the state-owned enterprises. Based on the data obtained, there are several complaints from customers of the 2019 land certificate production. The complaints become a negative value to loyal customers of Perum Peruri. Almost all the complaints are referring to ‘defective printouts and the difference between products in packaging and packaging labels both in terms of type and quantity’. To overcome this problem, we intend to make an improvement to the production process that focuses on complaints ‘there is a difference between products in packaging with packaging labels’. Improvements in the land certificate production process are relying on the technology of the scales and QR code on the packaging label. In addition, using the QR code on the packaging label will facilitate the process of tracking product data. With this method, we hope to reduce the error rate between products in packaging with the packaging label both in terms of quantity, type, and product number on the land certificate and error rate of sending land certificates, which will be sent to many places to 0%. With this solution, we also hope to get precise data and real-time reports on the production of land certificates in the near future, so track and trace implementation can be done as the solution of the land certificate production.

Keywords: land certificates, QR code, track and trace, packaging

Procedia PDF Downloads 146

Authors: Scott McCutcheon, Karen Schreder

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Higher education is facing a new reality. Student connection with coursework, instructor, and peers competes with online gaming, screen time, and instant gratification. Pedagogical methods that align student connection and critical thinking in a content-rich environment are important in supporting student learning, a sense of community, and emotional health. This mixed methods study focuses on exploring how the use of educational escape rooms (EERs) can support student learning and learning retention while fostering engagement with each other, the instructor, and the coursework. EERs are content-specific, cooperative, team-based learning activities designed to be completed within a short segment of a typical class. Data for the study was collected over three semesters and includes results from the implementation of EERs in science-based and liberal studies courses taught by different instructors. Twenty-seven students were surveyed regarding their learning experiences with this pedagogy, and interviews with four student volunteers were conducted to add depth to the survey data. A key finding from this research indicates that students felt more connected to each other and the course content after participating in the escape room activity. Additional findings point to increased engagement and comprehension of the class material. Data indicates that the use of an EER pedagogy supports student engagement, well-being, subject comprehension, and student-student and student-instructor connection.

Keywords: gamification, innovative pedagogy, student engagement, student emotional well being

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Authors: Amanda Madden

Abstract:

The purpose of this research was to identify students understanding of well-being and perceptions of the effective components of school-based well-being programs they have participated in during their time in secondary school. With one in four adolescents suffering from some form of mental health disorder, which has the potential to directly impact their academic ability, schools have moved towards a more holistic approach to education, resulting in the growth of school-based well-being programs. There is limited research on the effectiveness of school-based well-being programs, with fewer studies examining students’ perspectives on their well-being. A mixed-method design was utilized, framed by a social constructivist methodology. Quantitative data was collected through a researcher-developed self-report survey, and qualitative data were collected through one-on-one interviews and a semi-structured focus group undertaken with Year 12 students from three independent co-educational schools in Western Australia. Preliminary findings indicate that participants have experienced a minimal impact, either positively or negatively, on their well-being from school-based well-being programs. The data detailed that adolescents consider happiness, positive attitude, good physical health, balance, emotional fulfillment and confidence components of well-being. The findings also highlighted sports, positive family relationships, positive friendships, and pets positively enhanced well-being. This research suggests that researchers and educational leaders should consider students’ understanding of well-being in the development of school-based well-being assessments and interventions. Students are the recipients of school-based well-being programs and are best placed to inform what they will and will not respond to in the determination of appropriate well-being content.

Keywords: wellbeing, school based wellbeing, adolescents, wellbeing interventions

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Authors: Jongho Park, Jinwoong Choi, Sungnam Hong, Seung-Kyung Kye, Sun-Kyu Park

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Recently, to cope with the rapidly changing construction trend because of aging infrastructures, modular bridge technology has been studied actively. Modular bridge is easily constructed by assembling standardized precast structure members in the field. It will be possible to construct rapidly and reduce construction cost efficiently. However, the shape examination of the transverse connection of T-type girder newly developed between the segmented modules is not performed. Therefore, the investigation of the connection shape is needed. In this study, shape of the modular T-girder bridge transverse connection was analyzed by finite element model that was verified in study which was verification of model for transverse connection using Abaqus. Connection angle was chosen as the parameter. The result of analyses showed that optimal value of angle is 130 degree.

Keywords: modular bridge, optimal transverse shape, parameter, FEM

Procedia PDF Downloads 638

Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

Abstract:

Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

Procedia PDF Downloads 141