Search results for: Multiple Factorial Correspondence Analysis

Authors: Rajneesh, Priyanka Singh

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Biomass resources have been one of the main energy sources for mankind since the dawn of civilization. There is a vast scope to convert these energy sources into biogas which is a clean, low carbon technology for efficient management and conversion of fermentable organic wastes into a cheap and versatile fuel and bio/organic manure. Thus, in order to enhance the performance of anaerobic digester, an optimizing analysis of resultant parameters (organic dry matter (oDM) content, methane percentage, and biogas yield) has been done for a plug flow anaerobic digester having mesophilic conditions (20-40°C) with the wet fermentation process. Based on the analysis, correlations for oDM, methane percentage, and biogas yield are derived using multiple regression analysis. A statistical model is developed to correlate the operating variables using the design of experiment approach by selecting central composite design (CCD) of a response surface methodology. Results shown in the paper indicates that as the operating temperature increases the efficiency of digester gets improved provided that the pH and hydraulic retention time (HRT) remains constant. Working in an optimized range of carbon-nitrogen ratio for the plug flow digester, the output parameters show a positive change with the variation of dry matter content (DM).

Keywords: biogas, digester efficiency, design of experiment, plug flow digester

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Authors: Raheleh Khademian, Roghayeh Aminian

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For the study of salinity stress on Vicia villosa and calcium effect for modulation of that, an experiment was conducted under hydroponic condition, and some important morphological and physiological characteristics were evaluated. This experiment was conducted as a factorial based on randomized complete design with three replications. The treatments include salinity stress in three levels (0, 50, and 100 mM NaCl) and calcium in two levels (content in Hoagland solution and double content). The results showed that all morphological and physiological traits include root and shoot length, root and shoot wet and dry weight, leaf area, leaf chlorophyll content, RWC, CMS, and biological yield was significantly different from the control and is affected by the salinity stress severely. But, calcium effect on them was not significant despite of decreasing salinity effect.

Keywords: Vicia villossa, salinity stress, calcium, hydroponic

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Authors: Asma Alzahrani, Elizabeth Stojanovski

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This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, factors influence

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Authors: Saba Harati, Nasrin Arian Parsa

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The current research was an attempt to investigate the effect of resilience on mental health and life satisfaction. In one Cross Sectional research, 287 (173 females and 114 males) students of Tehran University were participated their average age was 23.17 years old (SD=4.9). The instruments used for assessing the research variables included: Cutter and Davidson resilience scale (CD-RISC), the short form of the depression-anxiety-stress scale, and life satisfaction scale. The data analysis was done in the form of structural equation model. The results of Simultaneous Hierarchical Multiple Regression Analysis indicated that there was a significant mediating role of the negative emotions (depression, anxiety, and stress), in the relationship between the family resilience (p < 0.001) and satisfaction with life (p < 0.001). Resilience results in life satisfaction by reducing the emotional problems (or increasing the mental health level). The effect of the resilience variable on life satisfaction was indirect.

Keywords: resilience, negative emotion, mental health, life satisfaction

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Authors: Mukund Ramchandra Mogarekar, Pankaj Kumar, Shraddha Vilas More

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Background: Myocardial infarction (MI) is defined as myocardial cell death due to prolonged ischemia as a consequence of atherosclerosis. TC, low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), Apo B, and lipoprotein(a) was found as atherogenic factors while high-density lipoprotein cholesterol (HDL-C) was anti-atherogenic. Methods and Results: The study group consists of 40, MI subjects and 40 healthy individuals in control group. PON 1 Arylesterase activity (ARE) was measured by using phenylacetate. Phenotyping was done by double substrate method, serum AOPP by using chloramine T and Apo B by Turbidimetric immunoassay. PON 1 ARE activities were significantly lower (p< 0.05) and AOPPs & Apo B were higher in MI subjects (p> 0.05). Trimodal distribution of QQ, QR, and RR phenotypes of study population showed no significant difference among cases and controls (p> 0.05). Univariate binary logistic regression analysis showed independent association of TC, HDL, LDL, AOPP, Apo B, and PON 1 ARE activity with MI and multiple forward binary logistic regression showed PON 1 ARE activity and serum Apo B as an independent predictor of MI. Conclusions: Decrease in PON 1 ARE activity in MI subjects than in controls suggests increased oxidative stress in MI which is reflected by significantly increased AOPP and Apo B. PON1 polymorphism of QQ, QR and RR showed no significant difference in protection against MI. Univariate and multiple binary logistic regression showed PON1 ARE activity and serum Apo B as an independent predictor of MI.

Keywords: advanced oxidation protein product, apolipoprotein B, PON 1 arylesterase activity, myocardial infarction

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Authors: Fiona Lord

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This paper presents research on strengthening urban governance and planning practices for sustainable and regenerative city transformations looking at urban governance in Cambodia as a case study. Transformations to urban sustainability and regeneration require systemic and long-term transformation processes, across multiple levels of society and inclusive of multiple urban actors. This paper presents the emerging findings of a qualitative case study comparing the urban governance and planning practices in two of Cambodia's secondary cities - Battambang and Sihanoukville. The lessons learned have broader implications for how governance and planning can be strengthened to initiate and sustain urban sustainability transformations in other developing country cities of Cambodia and the Southeast Asia region.

Keywords: Cambodia, planning practices, urban governance, urban sustainability transformations

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

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Authors: Anvi Kumar

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This paper explores the attitudes and awareness of multiple generations ranging from Boomers I to GenZ (i.e. from 1954 to 2012) towards mental health issues. A convenient sample of 191 people was gathered in India aged 11-77. 20 people each were considered from 5 generational cohorts, namely- Boomers I, Boomers II, Gen X, Millennials, and Gen Z. The study tool comprised a survey that included demographic questions and the Community Attitude towards Mental Illness (CAMI) scale by Taylor & Dear (1981). Descriptive statistics, ANOVA, and Bonferonni’s post-hoc analysis have been used to perform the analysis. The findings reveal that the level of kindness towards those who struggle with mental health varies through certain age groups. An overall sense of exclusion of those struggling with mental health is prevalent among all age groups. GenZ’s awareness of mental health issues is primarily via social media, as against the rest of the generations seeking it from close relatives and friends. The study’s findings suggest a need to investigate further the quality of mental health knowledge content and its consumption pattern. Understanding the dynamics of information sharing and the potential for biases requires further discovery.

Keywords: attitude, behaviour, mental illness, Gen Z, millennials, Gen Y, multi-generations, generational differences

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Authors: Yichen Lin, Hsiao-Han Chen, Chi-Chen Jan

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Since 1990, the research area of Integrated Marketing Communications (IMC) has been presented from a different perspective. With advances in information technology and the rise of consumer consciousness, businesses are in a competitive environment. There is an urgent need to adopt more profitable and effective integrated marketing strategies to increase core competitiveness. The goal of the company's sustainable management is to increase consumers' willingness to purchase and to maximize profits. This research uses six aspects of IMC, which includes awareness integration, unified image, database integration, customer-based integration, stakeholders-based integration, and evaluation integration to examine the role of marketing strategies in the strengths and weaknesses of the six components of integrated marketing communications, their effectiveness, the most important components and the most important components that need improvement. At the same time, social media such as FaceBook, Instagram, Youtube, Line, or even TikTok have become marketing tools which firms adopt them more and more frequently in the marketing strategy. In the end of 2019, the outbreak of COVID-19 did really affect the global industries. Lockdown policies also accelerated closure of brick-mentor stores worldwide. Online purchases rose dramatically. Hence, the effectiveness of online marketing will be essential to maintain the business. This study uses multiple-case studies to extend the effects of social media and IMC. Moreover, the study would also explore the differences of social media and IMC during COVID-19. Through literature review and multiple-case studies, it is found that using social media combined with IMC did really help companies expand their business and make good connections with stakeholders. One of previous studies also used system theory to explore the interrelationship among Integrated Marketing Communication, collaborative marketing, and global brand building. Even during pandemic, firms could still maintain the operation and connect with their customers more tightly.

Keywords: integration marketing communications, multiple-case studies, social media, system theory

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Authors: Arti Devi, Parthasarthi Choudhury

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Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analysed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on ZDIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.

Keywords: L-moments, ZDIST statistics, serial correlation, Mann Kendall test

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Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

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In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

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Authors: Mohamed Barbary, Mohamed H. Abd El-Azeem

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Maneuvering extended object tracking (M-EOT) using high-resolution inverse synthetic aperture radar (ISAR) observations has been gaining momentum recently. This work presents a new robust implementation of the multiple models (MM) multi-Bernoulli (MB) filter for M-EOT, where the M-EOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, MM-MB-TBD filter

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Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

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Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

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Authors: Kawthar F. Albasri, Abdullah M. AlHudaithi, Dana B. AlTurairi, Abdullaziz S. AlQuraini, Adoub Y. AlDerazi, Reem A. Hubail, Haitham A. Jahrami

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Several studies have found that medical students have a significant prevalence of anxiety. The purpose of this review paper is to carefully evaluate the current research on anxiety among medical students in the MENA region and, as a result, estimate the prevalence of these disturbances. Multiple databases, including the CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, Embase, MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, PsycINFO (Psychological Information Database), Scopus, Web of Science, UpToDate, ClinicalTrials.gov, WHO Global Health Library, EbscoHost, ProQuest, JAMA Network, and ScienceDirect, were searched. The retrieved article reference lists were rigorously searched and rated for quality. A random effects meta-analysis was performed to compute estimates. The current meta-analysis revealed an alarming estimated pooled prevalence of anxiety (K = 46, N = 27023) of 52.5% [95%CI: 43.3%–61.6%]. A total of 62.0% [95% CI 42.9%; 78.0%] of the students (K = 18, N = 16466) suffered from anxiety during the COVID-19 pandemic, while 52.5% [95% CI 43.3%; 61.6%] had anxiety before COVID-19. Based on the GAD-7 measure, a total of 55.7% [95%CI 30.5%; 78.3%] of the students (K = 10, N = 5830) had anxiety, and a total of 54.7% of the students (K = 18, N = 12154) [95%CI 42.8%; 66.0%] had anxiety using the DASS-21 or 42 measure. Anxiety is a common issue among medical students, making it a genuine problem. Further research should be conducted post-COVD 19, with a focus on anxiety prevention and intervention initiatives for medical students.

Keywords: anxiety, medical students, MENA, meta-analysis, prevalence

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Authors: Ira Irawati, Muhammad Rangga Sururi

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The expansion of built-up areas in many cities, particularly, as the consequences of urbanization process, is a common phenomenon in our contemporary world. As happened in many cities in developing world, this horizontal expansion let only a handful size of the area left for green open spaces, creating an extreme unbalance between built-up and green spaces. Combined with the high density and variety of human activities with its transportation modes; a process of urban heat island will occur, resulting in an increase in air temperature. This is one of the indicators of decreasing of the quality of urban microclimate. This paper will explore the effect of several variables of built-up areas and open spaces to the increase of air temperature using multiple linear regression analysis. We selected 11 zones within the radius of 1 km in Inner Bandung city center, and each zones measured within 300 m radius to represent the variety of land use, as well as the composition of buildings and green open spaces. By using a quantitative method which is multiple linear regression analysis, six dependent variables which are a) tree density-x1, b) shade level of tree-x2, c) surface area of buildings’ side which are facing west and east-x3, d) surface area of building side material-x4, e) surface area of pathway material, and f) numbers of motorized vehicles-x6; are calculated to find those influence to the air temperature as an independent variable-y. Finally, the relationship between those variables shows in this equation: y = 30.316 - 3.689 X1 – 6.563 X2 + 0.002 X3 – 2,517E6 X4 + 1.919E-9 X5 + 1.952E-4 X6. It shows that the existence of vegetation has a great impact on lowering temperature. In another way around, built up the area and motorized vehicles would increase the temperature. However, one component of built up area, the surface area of buildings’ sides which are facing west and east, has different result due to the building material is classified in low-middle heat capacity.

Keywords: built-up area, microclimate, vehicles, urban heat island, vegetation

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Mandy Tao Benec

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Propaganda, understood as a ‘deliberate attempt to persuade people to think and behave in a desired way’, contributes to the fabric of mass media discourse as an important component, albeit often under various alternative expressions except ‘propaganda’. When the word ‘propaganda’ does appear in the mainstream media of the West, it is often selectively applied upon undesiring parties such as China, the North Korea, Russia’s Putin, or terrorists, etc.. This attitude reveals an ‘us verse them’ mentality; and a presupposition that propaganda is something only ‘they’ do whilst ‘we’ do not. This phenomenon not only runs in danger of generating political naivety, but also calls for the necessity of re-examining propaganda which will benefit from analysing it in contrasting social and political environments. Therefore, this paper aims to compare how propaganda has been understood and put in practice both in the Anglo-American context and by the Chinese Communist Party (CCP). By revealing the convergence and divergence of the propaganda discourses between China and the West, it will help clarify the misconception and misunderstanding of the term. Historical narrative analysis and critical discourse analysis are the main methodologies. By carefully examining data from academic research on propaganda in both English and Chinese, the landscape of how propaganda is defined throughout different eras is mapped, with special attention paid to analysing the parallelism and/or correspondence between China and the West when applicable. Meanwhile, critically analysing the official documents such as speeches and guidelines for propaganda administration given by top-rank CCP leaders will help reveal that in contrast to the West’s ‘us-them’ mentality, China sees oneself in no difference with the Western democracies when propaganda is concerned. Major findings of this study will identify a series of convergence and divergence between Chinese and Western propaganda discourses, and the relationship between propaganda the ‘signified’ (its essence) and propaganda the ‘signifier’ (the term itself), including (yet not limited to): 1) convergence in China catching up with the West, acknowledging the perceived pejorative connotation of the term 2) divergence in propaganda activities disassociated from the term in the West; and convergence in adopting such practice when China following suit in its external propaganda towards the West 3) convergence in utilising alternative notions to replace ‘propaganda’, first by the West, then imported and incorporated enthusiastically by China into its propaganda discourse 4) divergence between China’s internal and external propaganda and the subsequent differentiation between in which contexts the CCP sees fit to utilise the concept 5) convergence between China and the West in their English language propaganda discourses, whilst simultaneous divergence in their presuppositions: ‘usthem’ by the West and ‘we are the same’ by China. To conclude, this paper will contribute to the study of propaganda and its discourse by analysing how propaganda is understood and utilised in both worlds, and hence to uncover the discourse power struggle between the two, which contributes to the propaganda discourse itself. Hence, to untie the misconception of propaganda.

Keywords: China, discourse, power, propaganda

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Authors: Ahmet Erdoğan, Şahin Kesici, Mustafa Baloğlu

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Information technologies have lead to changes in the areas of communication, learning, and teaching. Besides offering many opportunities to the learners, these technologies have changed the teaching methods and beliefs of teachers. What the Technological Pedagogical Content Knowledge (TPACK) means to the teachers is considerably important to integrate technology successfully into teaching processes. It is necessary to understand how to plan and apply teacher training programs in order to balance students’ pedagogical and technological knowledge. Because of many inefficient teacher training programs, teachers have difficulties in relating technology, pedagogy and content knowledge each other. While providing an efficient training supported with technology, understanding the three main components (technology, pedagogy and content knowledge) and their relationship are very crucial. The purpose of this study is to determine whether motivational beliefs and self-regulated learning strategies are significant predictors of mathematics teacher candidates' TPACK perceptions. A hundred seventy five Turkish mathematics teachers candidates responded to the Motivated Strategies for Learning Questionnaire (MSLQ) and the Technological Pedagogical And Content Knowledge (TPACK) Scale. Of the group, 129 (73.7%) were women and 46 (26.3%) were men. Participants' ages ranged from 20 to 31 years with a mean of 23.04 years (SD = 2.001). In this study, a multiple linear regression analysis was used. In multiple linear regression analysis, the relationship between the predictor variables, mathematics teacher candidates' motivational beliefs, and self-regulated learning strategies, and the dependent variable, TPACK perceptions, were tested. It was determined that self-efficacy for learning and performance and intrinsic goal orientation are significant predictors of mathematics teacher candidates' TPACK perceptions. Additionally, mathematics teacher candidates' critical thinking, metacognitive self-regulation, organisation, time and study environment management, and help-seeking were found to be significant predictors for their TPACK perceptions.

Keywords: candidate mathematics teachers, motivational beliefs, self-regulated learning strategies, technological and pedagogical knowledge, content knowledge

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Authors: X. Gu, K. L. Blackmore

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The impact factor was introduced to measure the quality of journals. Various impact measures exist from multiple bibliographic databases. In this research, we aim to provide a broader understanding of the relationship between scholarly impact and other characteristics of academic journals. Data used for this research were collected from Ulrich’s Periodicals Directory (Ulrichs), Cabell’s (Cabells), and SCImago Journal & Country Rank (SJR) from 1999 to 2015. A master journal dataset was consolidated via Journal Title and ISSN. We adopted a two-step analysis process to study the quantitative relationships between scholarly impact and other journal characteristics. Firstly, we conducted a correlation analysis over the data attributes, with results indicating that there are no correlations between any of the identified journal characteristics. Secondly, we examined the quantitative relationship between scholarly impact and other characteristics using quartile analysis. The results show interesting patterns, including some expected and others less anticipated. Results show that higher quartile journals publish more in both frequency and quantity, and charge more for subscription cost. Top quartile journals also have the lowest acceptance rates. Non-English journals are more likely to be categorized in lower quartiles, which are more likely to stop publishing than higher quartiles. Future work is suggested, which includes analysis of the relationship between scholars and their publications, based on the quartile ranking of journals in which they publish.

Keywords: academic journal, acceptance rate, impact factor, journal characteristics

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Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: T. Yamaguchi, M. Watanabe, M. Sasajima, C. Yuan, S. Maruyama, T. B. Ibrahim, H. Tomita

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This paper deals with nonlinear vibration analysis using finite element method for frame structures consisting of elastic and viscoelastic damping layers supported by multiple nonlinear concentrated springs with hysteresis damping. The frame is supported by four nonlinear concentrated springs near the four corners. The restoring forces of the springs have cubic non-linearity and linear component of the nonlinear springs has complex quantity to represent linear hysteresis damping. The damping layer of the frame structures has complex modulus of elasticity. Further, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled differential equations using normal coordinate corresponding to linear natural modes. Comparing shares of strain energy of the elastic frame, the damping layer and the springs, we evaluate the influences of the damping couplings on the linear and nonlinear impact responses. We also investigate influences of damping changed by stiffness of the elastic frame on the nonlinear coupling in the damped impact responses.

Keywords: dynamic response, nonlinear impact response, finite element analysis, numerical analysis

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Authors: Tunjo Perič, Marin Fatović

Abstract:

In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology is tested on the example of flour purchase for a bakery with two decision makers.

Keywords: cooperative game theory, multiple objective linear programming, revised weighting method, vendor selection

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Authors: Davut Disci

Abstract:

Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance- Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling(SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: education, mobile behavior, mobile learning, technology, Turkey

Procedia PDF Downloads 421

Authors: Davut Disci

Abstract:

Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance-Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore, these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling (SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: learning technology, instructional technology, mobile learning, technology

Procedia PDF Downloads 452

Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

Abstract:

This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

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Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Devendra Kr Tayal, Vrinda Gupta, Aastha Bansal, Khushi Singh, Sristi Sharma, Hunny Gaur

Abstract:

In today's world, suicide is a serious problem. In order to save lives, early suicide attempt detection and prevention should be addressed. A good number of at-risk people utilize social media platforms to talk about their issues or find knowledge on related chores. Twitter and Reddit are two of the most common platforms that are used for expressing oneself. Extensive research has already been done in this field. Through supervised classification techniques like Nave Bayes, Bernoulli Nave Bayes, and Multiple Layer Perceptron on a Reddit dataset, we demonstrate the early recognition of suicidal ideation. We also performed comparative analysis on these approaches and used accuracy, recall score, F1 score, and precision score for analysis.

Keywords: machine learning, suicide ideation detection, supervised classification, natural language processing

Procedia PDF Downloads 90

Authors: Katja Siefken, Astrid Junge

Abstract:

Background: Research indicates that physical activity (PA) protects us from developing mental disorders. The knowledge regarding optimal domain, intensity, type, context, and amount of PA promotion for the prevention of mental disorders is sparse and incoherent. The objective of this study is to determine the relationship between PA domains and mental well-being, and whether associations vary by domain, amount, context, intensity, and type of PA. Methods: 310 individuals (age: 25 yrs., SD 7; 73% female) completed a questionnaire on personal patterns of their PA behaviour (IPQA) and their mental health (Centre of Epidemiologic Studies Depression Scale (CES-D), Generalized Anxiety Disorder (GAD-7) scale, the subjective physical well-being (FEW-16)). Linear and multiple regression were used for analysis. Findings: Individuals who met the PA recommendation (N=269) reported higher scores on subjective physical well-being than those who did not meet the PA recommendations (N=41). Whilst vigorous intensity PA predicts subjective well-being (β = .122, p = .028), it also correlates with depression. The more vigorously physically active a person is, the higher the depression score (β = .127, p = .026). The strongest impact of PA on mental well-being can be seen in the transport domain. A positive linear correlation on subjective physical well-being (β =.175, p = .002), and a negative linear correlation for anxiety (β =-.142, p = .011) and depression (β = -.164, p = .004) was found. Multiple regression analysis indicates similar results: Time spent in active transport on the bicycle significantly lowers anxiety and depression scores and enhances subjective physical well-being. The more time a participant spends using the bicycle for transport, the lower the depression (β = -.143, p = .013) and anxiety scores (β = -.111,p = .050). Conclusions: Meeting the PA recommendations enhances subjective physical well-being. Active transport has a substantial impact on mental well-being. Findings have implications for policymakers, employers, public health experts and civil society. A stronger focus on the promotion and protection of health through active transport is recommended. Inter-sectoral exchange, outside the health sector, is required. Health systems must engage other sectors in adopting policies that maximize possible health gains.

Keywords: active transport, mental well-being, health promotion, psychological disorders

Procedia PDF Downloads 321