Search results for: Spatial Data Analyses

Authors: Sibo Lu, Zhongkai Qian

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This study endeavors to articulate a spectrum of capitalist transformation from a politico-economic perspective, categorizing the development of capitalism into pre-modern, modern, and post-modern stages while examining the transitions between these states. It critically engages with the concepts of pre-modernity, modernity, and post-modernity, typically aligned with cultural studies, to shed light on their objective changes in the politico-economic realm. Post-modernity, in this context, is associated with the transition to high-value-added services and economic growth in ‘developed’ countries amidst globalization, framing a ‘neoliberal’ economic transformation. The paper scrutinizes the neoliberal economic shifts in the latter half of the 20th century as part of the post-modern state, arguing against viewing post-modernity merely as a cultural or subjective interpretative stance. Instead, it is posited as a concrete politico-economic phase marked by the dominance of post-Fordist systems. Through integrating insights from the political economy with continental philosophy, this research provides a nuanced analysis of capitalism's evolution, challenging conventional class analyses under the capitalist system and fostering a broader understanding of socio-economic paradigms.

Keywords: post marxism, critical theory, political economy, capitalism transformation

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Awdhesh Narayan Sharma

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The use of herbal medicines for the cure of various ailments among the tribal population is as old as human origin itself. Most of the tribal populations of Madhya Pradesh inhabit in remote and inaccessible ecological setup. From long back, tribals and forests are interrelated to each other. They use an enormous range of wild plants for their basic needs and medicines. The tribal developed a unique understanding with wild plants, herbs, etc., and earned specialized knowledge of disease pattern and curative therapy-through hard experiences, common sense, trial, and error methods. They have passed this knowledge through traditions, taboos, totems, folklore by words of mouth from generation to generation. Here, an attempt has been made to study the possible aspects of herbal medicine for the cure of Jaundice among the tribal populations of Madhya Pradesh, India, through primary data as well as available secondary data. The data have been collected from the 305 Bharias of Patalkot, Madhya Pradesh, India, and included available secondary source of data by various investigators. It may be concluded that a sizable herbal medicinal plants' wealth exists in Madhya Pradesh, India, which still awaits for scientific exploration. The existing herbal medicines used for the cure of jaundice need an extensive investigation from the pharmaceutical point of view.

Keywords: Bharias, herbal medicine, tribal, Madhya Pradesh

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Authors: Yamba Dabone, Tounwendyam Frédéric Ouedraogo, Pengwendé Justin Kouraogo, Oumarou Sie

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Reliable data transport over the Internet is one of the goals of researchers in the field of computer science. Data such as videos and audio files are becoming increasingly large. As a result, transporting them over the Internet is becoming difficult. Therefore, it has been important to establish a method to locally interconnect autonomous systems (AS) with each other to facilitate traffic exchange. It is in this context that Internet Exchange Points (IXPs) are set up to facilitate local and even regional traffic. They are now the lifeblood of the Internet. Therefore, it is important to think about the factors that can characterize IXPs. However, other more quantifiable characteristics can help determine the quality of an IXP. In addition, these characteristics may allow ISPs to have a clearer view of the exchange node and may also convince other networks to connect to an IXP. To that end, we define five new IXP characteristics: the attraction rate (τₐₜₜᵣ); and the peering rate (τₚₑₑᵣ); the target rate of an IXP (Objₐₜₜ); the number of IXP links (Nₗᵢₙₖ); the resistance rate τₑ𝒻𝒻 and the attraction failure rate (τ𝒻).

Keywords: characteristic, autonomous system, internet service provider, internet exchange point, rate

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Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

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Authors: Y. Atilgan Şengül

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Health information technologies promise higher quality, safer care and much more for both patients and professionals. Despite their promise, they are costly to develop and difficult to implement. On the other hand, user acceptance and usage determine the success of implemented information technology in healthcare. This study provides a model to understand health professionals’ perception and expectation of health information technology. Extensive literature review has been conducted to determine the main factors to be measured. A questionnaire has been designed as a measurement model and submitted to the personnel of an in vitro fertilization clinic. The respondents’ degree of agreement according to five-point Likert scale was 72% for convenient access to data and 69.4% for the importance of data security. There was a significant difference in acceptance of electronic data storage for female respondents. Also, other significant differences between professions were obtained.

Keywords: healthcare, health informatics, medical record system, questionnaire

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Authors: Ehsan Derikvand, Hamid Kaykha, Rooholah Mansoori Yekta, Taleb Javanmard, Mohsen Mehdi Zadeh

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Corrosion and scaling are one of the most complicated and costly problems of drinking water supply. Corrosion has adverse effect on general health and public acceptance of water source and drinking water supply costs. The present study aimed to determine the potentials of corrosion and scaling of potable water supply reservoirs of Ilam city in June 2013 and August 2014 by Langelier Index (LI) and Reynar. The results of experiments and calculations show that the mean index of LSI in the first and second sampling stages is 0.34, 0.2, respectively and the mean index RSI in the first and second stages of sampling is 7.15 and 7.22, respectively. Based on LSI index of reservoirs water in the first phase, none of stations are corrosive and only one station in the second sampling phase has corrosive tendency. According to RSI index, there is no corrosive tendency in two phases. Based on the results, the water of drinking water reservoirs in Ilam city has no corrosion tendency and the analyses and results of Langelier Index (LI) and Ryznar are in relatively good condition.

Keywords: corrosion, scaling, water reservoirs, langelier and ryznar indices, Ilam city

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Authors: Fatemeh Yazdanmehr, Iulian Nistor

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The scope of the current study is the evaluation of the electric field effect on electrostatic desalting mathematical modeling with laboratory data. This research study was focused on developing a model for an existing operation desalting unit of one of the Iranian heavy oil field with a 75 MBPD production capacity. The high temperature of inlet oil to dehydration unit reduces the oil recovery, so the mathematical modeling of desalter operation parameters is very significant. The existing production unit operating data has been used for the accuracy of the mathematical desalting plant model. The inlet oil temperature to desalter was decreased from 110 to 80°C, and the desalted electrical field was increased from 0.75 to 2.5 Kv/cm. The model result shows that the desalter parameter changes meet the water-oil specification and also the oil production and consequently annual income is increased. In addition to that, changing desalter operation conditions reduces environmental footprint because of flare gas reduction. Following to specify the accuracy of selected electrostatic desalter electrical field, laboratory data has been used. Experimental data are used to ensure the effect of electrical field change on desalter. Therefore, the lab test is done on a crude oil sample. The results include the dehydration efficiency in the presence of a demulsifier and under electrical field (0.75 Kv) conditions at various temperatures. Comparing lab experimental and electrostatic desalter mathematical model results shows 1-3 percent acceptable error which confirms the validity of desalter specification and operation conditions changes.

Keywords: desalter, electrical field, demulsification, mathematical modeling, water-oil separation

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Authors: Swati Kishor Zode, Rahul Ambekar

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Data mining is the extraction of fascinating examples on the other hand information from enormous measure of information and choice is made as indicated by the applicable information extracted. As of late, with the dangerous advancement in internet, stockpiling of information and handling procedures, privacy preservation has been one of the major (higher) concerns in data mining. Various techniques and methods have been produced for protection saving data mining. In the situation of Clinical Decision Support System, the choice is to be made on the premise of the data separated from the remote servers by means of Internet to diagnose the patient. In this paper, the fundamental thought is to build the precision of Decision Support System for multiple diseases for different maladies and in addition protect persistent information while correspondence between Clinician side (Client side) also, the Server side. A privacy preserving protocol for clinical decision support network is proposed so that patients information dependably stay scrambled amid diagnose prepare by looking after the accuracy. To enhance the precision of Decision Support System for various malady C5.0 classifiers and to save security, a Homomorphism encryption algorithm Paillier cryptosystem is being utilized.

Keywords: classification, homomorphic encryption, clinical decision support, privacy

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Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar

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In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.

Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques

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Authors: Danni Cheng

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Background: Preclinical and epidemiological studies have reported potential protective effects of low-density lipoprotein cholesterol (LDL-C) lowering drugs on head and neck squamous cell cancer (HNSCC) survival, but the causality was not consistent. Genetic variants associated with LDL-C lowering drug targets can predict the effects of their therapeutic inhibition on disease outcomes. Objective: We aimed to evaluate the causal association of genetically proxied cholesterol-lowering drug targets and circulating lipid traits with cancer survival in HNSCC patients stratified by human papillomavirus (HPV) status using two-sample Mendelian randomization (MR) analyses. Method: Single-nucleotide polymorphisms (SNPs) in gene region of LDL-C lowering drug targets (HMGCR, NPC1L1, CETP, PCSK9, and LDLR) associated with LDL-C levels in genome-wide association study (GWAS) from the Global Lipids Genetics Consortium (GLGC) were used to proxy LDL-C lowering drug action. SNPs proxy circulating lipids (LDL-C, HDL-C, total cholesterol, triglycerides, apoprotein A and apoprotein B) were also derived from the GLGC data. Genetic associations of these SNPs and cancer survivals were derived from 1,120 HPV-positive oropharyngeal squamous cell carcinoma (OPSCC) and 2,570 non-HPV-driven HNSCC patients in VOYAGER program. We estimated the causal associations of LDL-C lowering drugs and circulating lipids with HNSCC survival using the inverse-variance weighted method. Results: Genetically proxied HMGCR inhibition was significantly associated with worse overall survival (OS) in non-HPV-drive HNSCC patients (inverse variance-weighted hazard ratio (HR IVW), 2.64[95%CI,1.28-5.43]; P = 0.01) but better OS in HPV-positive OPSCC patients (HR IVW,0.11[95%CI,0.02-0.56]; P = 0.01). Estimates for NPC1L1 were strongly associated with worse OS in both total HNSCC (HR IVW,4.17[95%CI,1.06-16.36]; P = 0.04) and non-HPV-driven HNSCC patients (HR IVW,7.33[95%CI,1.63-32.97]; P = 0.01). A similar result was found that genetically proxied PSCK9 inhibitors were significantly associated with poor OS in non-HPV-driven HNSCC (HR IVW,1.56[95%CI,1.02 to 2.39]). Conclusion: Genetically proxied long-term HMGCR inhibition was significantly associated with decreased OS in non-HPV-driven HNSCC and increased OS in HPV-positive OPSCC. While genetically proxied NPC1L1 and PCSK9 had associations with worse OS in total and non-HPV-driven HNSCC patients. Further research is needed to understand whether these drugs have consistent associations with head and neck tumor outcomes.

Keywords: Mendelian randomization analysis, head and neck cancer, cancer survival, cholesterol, statin

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Authors: Salah Jellali, Nusiba Suliman, Yassine Charabi, Jamal Al-Sabahi, Ahmed Al Raeesi, Malik Al-Wardy, Mejdi Jeguirim

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Huge amounts of agricultural biomasses are worldwide produced. At the same time, large quantities of phosphorus are annually discharged into water bodies with possible serious effects onto the environment quality. The main objective of this work is to turn a local Omani biomass (date palm fronds wastes: DPFW) into an effective material for phosphorus recovery from aqueous and the reuse of this P-loaded material in agriculture as ecofriendly amendment. For this aim, the raw DPFW were firstly impregnated with 1 M salt separated solutions of CaCl₂, MgCl₂, FeCl₃, AlCl₃, and a mixture of MgCl₂/AlCl₃ for 24 h, and then pyrolyzed under N2 flow at 500 °C for 2 hours by using an adapted tubular furnace (Carbolite, UK). The synthetized biochars were deeply characterized through specific analyses concerning their morphology, structure, texture, and surface chemistry. These analyses included the use of a scanning electron microscope (SEM) coupled with an energy-dispersive X-Ray spectrometer (EDS), X-Ray diffraction (XRD), Fourier Transform Infrared (FTIR), sorption micrometrics, and X-ray Fluorescence (XRF) apparatus. Then, their efficiency in recovering phosphorus was investigated in batch mode for various contact times (1 min to 3 h), aqueous pH values (from 3 to 11), initial phosphorus concentrations (10-100 mg/L), presence of anions (nitrates, sulfates, and chlorides). In a second step, dynamic assays, by using laboratory columns (height of 30 cm and diameter of 3 cm), were performed in order to investigate the recovery of phosphorus by the modified biochar with a mixture of Mg/Al. The effect of the initial P concentration (25-100 mg/L), the bed depth height (3 to 8 g), and the flow rate (10-30 mL/min) was assessed. Experimental results showed that the biochars physico-chemical properties were very dependent on the type of the used modifying salt. The main affected parameters concerned the specific surface area, microporosity area, and the surface chemistry (pH of zero-point charge and available functional groups). These characteristics have significantly affected the phosphorus recovery efficiency from aqueous solutions. Indeed, the P removal efficiency in batch mode varies from about 5 mg/g for the Fe-modified biochar to more than 13 mg/g for the biochar functionalized with Mg/Al layered double hydroxides. Moreover, the P recovery seems to be a time dependent process and significantly affected by the pH of the aqueous media and the presence of foreign anions due to competition phenomenon. The laboratory column study of phosphorus recovery by the biochar functionalized with Mg/Al layered double hydroxides showed that this process is affected by the used phosphorus concentration, the flow rate, and especially the column bed depth height. Indeed, the phosphorus recovered amount increased from about 4.9 to more than 9.3 mg/g used biochar mass of 3 and 8 g, respectively. This work proved that salt-modified palm fronds-derived biochars could be considered as attractive and promising materials for phosphorus recovery from aqueous solutions even under dynamic conditions. The valorization of these P-loaded-modified biochars as eco-friendly amendment for agricultural soils is necessary will promote sustainability and circular economy concepts in the management of both liquid and solid wastes.

Keywords: date palm wastes, Mg/Al double-layered hydroxides functionalized biochars, phosphorus, recovery, sustainability, circular economy

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Authors: Anant Sharma, Ashwin Rajan

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Customer experience is measured today based on defining a set of metrics and KPIs, setting up thresholds and defining triggers across those thresholds. While this is an effective way of measuring against a Key Performance Indicator ( referred to as KPI in the rest of the paper ), this approach cannot capture the various nuances that make up the overall customer experience. Customers consume a product or service at various levels, which is not reflected in metrics like Customer Satisfaction or Net Promoter Score, but also across other measurements like recurring revenue, frequency of service usage, e-learning and depth of usage. Here we explore an alternative method of measuring customer experience by flipping the traditional views. Rather than rolling customers up to a metric, we roll up metrics to hierarchies and then measure customer experience. This method allows any team to quantify customer experience across multiple touchpoints in a customer’s journey. We make use of various data sources which contain information for metrics like CXSAT, NPS, Renewals, and depths of service usage collected across a customer lifecycle. This data can be mined systematically to get linkages between different data points like geographies, business groups, products and time. Additional views can be generated by blending synthetic contexts into the data to show trends and top/bottom types of reports. We have created a framework that allows us to measure customer experience using the above logic.

Keywords: analytics, customers experience, BI, business operations, KPIs, metrics

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Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

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Authors: Muhammad Feteha

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The socio-political Middle East scene has radically changed over the last decade, and one major contributor to this change was the Egyptian revolution of 2011. The massive impact of this revolution that originally started as a small protest in the Tahrir square has attracted more scholars to study the public space in Egypt, where it has become a necessity in order to understand and improve the socio-political conditions. The status of public space in Egypt has been deteriorating due to many reasons, including privatization and neglect. This paper studies one of the major problems of the contemporary public space in Cairo, which is the lack of identity. This takes place through a comparative analysis between selected case studies from both medieval and contemporary Cairo. The theoretical framework upon which the analysis is based views public space as a ‘container of social action’ and a ‘product of spatial practice’. Through the ‘deciphering of space’, differences in the socio-political role, symbolism, and identity of public spaces between both eras are shown. The paper aims to extract some lessons from public space in medieval Cairo, which was truly the ‘centerpiece of the public realm’ and a ‘fundamental expressions’ of the unique trans-dynastic architectural identity of Cairo. In addition, it suggests some strategies to revive the Cairene identity of public space instead of constructing new ones to be only ‘utilitarian spaces used for circulation’ and lack any identity.

Keywords: architectural identity, Cairene public space, Islamic architectural history, production of space

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Authors: Asadollah Bahrami

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In the present study, spectral radiative entropy generation is analyzed in a furnace filled with a mixture of H₂O, CO₂ and soot at radiative equilibrium. For the angular and spatial discretization of the radiative transfer equation and radiative entropy generation equations, the discrete ordinates method and the finite volume method are used, respectively. Spectral radiative properties are obtained using the correlated-k (CK) non-gray model with updated parameters based on the HITEMP2010 high-resolution database. In order to evaluate the effects of the location of the heat source, boundary condition and wall emissivity on radiative entropy generation, five cases are considered with different conditions. The spectral and total radiative entropy generation in the system are calculated for all cases and the effects of mentioned parameters on radiative entropy generation are attentively analyzed and finally, the optimum condition is especially presented. The most important results can be stated as follows: Results demonstrate that the wall emissivity has a considerable effect on the radiative entropy generation. Also, irreversible radiative transfer at the wall with lower temperatures is the main source of radiative entropy generation in the furnaces. In addition, the effect of the location of the heat source on total radiative entropy generation is less than other factors. Eventually, it can be said that characterizing the effective parameters of radiative entropy generation provides an approach to minimizing the radiative entropy generation and enhancing the furnace's performance practicality.

Keywords: spectral radiative entropy generation, non-gray medium, correlated k(CK) model, heat source

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Authors: Juan Li, Hui Tian, Min Wang

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In China, under the considerable pressure of 'Gaokao' –the highly competitive college entrance examination, high school teachers and parents often worry that doing physical activity would take away the students’ precious study time and may have a negative impact on the academic grades. There was a tendency to achieve high academic scores at the cost of physical exercise. Therefore, the purpose of this study was to examine the relationship between the physical fitness and academic achievement of Chinese high school students. The participants were 968 grade one (N=457) and grade two students (N=511) with an average age of 16 years from three high schools of different levels in Beijing, China. 479 were boys, and 489 were girls. One of the schools is a top high school in China, another is a key high school in Beijing, and the other is an ordinary high school. All analyses were weighted using SAS 9.4 to ensure the representatives of the sample. The weights were based on 12 strata of schools, sex, and grades. Physical fitness data were collected using the scores of the National Physical Fitness Test, which is an annual official test administered by the Ministry of Education in China. It includes 50m run, sits and reach test, standing long jump, 1000m run (for boys), 800m run (for girls), pull-ups for 1 minute (for boys), and bent-knee sit-ups for 1 minute (for girls). The test is an overall evaluation of the students’ physical health on the major indexes of strength, endurance, flexibility, and cardiorespiratory function. Academic scores were obtained from the three schools with the students’ consent. The statistical analysis was conducted with SPSS 24. Independent-Samples T-test was used to examine the gender group differences. Spearman’s Rho bivariate correlation was adopted to test for associations between physical test results and academic performance. Statistical significance was set at p<.05. The study found that girls obtained higher fitness scores than boys (p=.000). The girls’ physical fitness test scores were positively associated with the total academic grades (rs=.103, p=.029), English (rs=.096, p=.042), physics (rs=.202, p=.000) and chemistry scores (rs=.131, p=.009). No significant relationship was observed in boys. Cardiorespiratory fitness had a positive association with physics (rs=.196, p=.000) and biology scores (rs=.168, p=.023) in girls, and with English score in boys (rs=.104, p=.029). A possible explanation for the greater association between physical fitness and academic achievement in girls rather than boys was that girls showed stronger motivation in achieving high scores in whether academic tests or fitness tests. More driven by the test results, girls probably tended to invest more time and energy in training for the fitness test. Higher fitness levels were associated with an academic benefit among girls generally in Chinese high schools. Therefore, physical fitness needs to be given greater emphasis among Chinese adolescents and gender differences need to be taken into consideration.

Keywords: physical fitness; adolescents; academic achievement; high school

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Authors: Jamilatuzzahro, Rezzy Eko Caraka

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The yield curve is the plot of the yield to maturity of zero-coupon bonds against maturity. In practice, the yield curve is not observed but must be extracted from observed bond prices for a set of (usually) incomplete maturities. There exist many methodologies and theory to analyze of yield curve. We use two methods (the Nelson-Siegel Method, the Svensson Method, and the SVR method) in order to construct and compare our zero-coupon yield curves. The objectives of this research were: (i) to study the adequacy of NSS model and SVR to Indonesian government bonds data, (ii) to choose the best optimization or estimation method for NSS model and SVR. To obtain that objective, this research was done by the following steps: data preparation, cleaning or filtering data, modeling, and model evaluation.

Keywords: support vector regression, Nelson-Siegel-Svensson, yield curve, Indonesian government

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Authors: Fuad A. A. Trayek, Tunku Badariah Tunku Ahmad, Mohamad Sahari Nordin, Mohammed AM Dwikat

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This paper reports on the results of an exploratory factor analysis procedure applied on the e-learning readiness data obtained from a survey of four hundred and seventy-nine (N = 479) teachers from secondary schools in Nablus, Palestine. The data were drawn from a 23-item Likert questionnaire measuring e-learning readiness based on Chapnick's conception of the construct. Principal axis factoring (PAF) with Promax rotation applied on the data extracted four distinct factors supporting four of Chapnick's e-learning readiness dimensions, namely technological readiness, psychological readiness, infrastructure readiness and equipment readiness. Together these four dimensions explained 56% of the variance. These findings provide further support for the construct validity of the items and for the existence of these four factors that measure e-learning readiness.

Keywords: e-learning, e-learning readiness, technological readiness, psychological readiness, principal axis factoring

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Authors: Kusmartono, Siti Chuzaemi, Hartutik dan Mashudi

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Two studies were conducted involving an in vitro (Expt 1) and in vivo (Expt 2) measurements. Expt 1. aimed to evaluate effects of adding CT extracts on gas production and efficiency of microbial protein synthesis (EMPS), Expt 2 aimed to evaluate effects of supplementing shrub/tree leaves as CT source on feed consumption, digestibility, N retention, body weight gain and dressing percentage of growing sheep fed on elephant grass (EG) as a basal diet.Ten shrub and tree leaves used as CT sources were wild sunflower (Tithonia diversifolia), mulberry (Morus macroura), cassava (Manihot utilissima), avicienna (Avicennia marina), calliandra (Calliandra calothyrsus), sesbania (Sesbania grandiflora), acacia (acacia vilosa), glyricidia (Glyricidia sepium), jackfruit (Artocarpus heterophyllus), moringa (Moringa oleifera). The treatments applied in Expt 1 were: T1=Elephant grass (60%)+concentrate (40%); T2 = T1 + CT (3% DM); T3= T2 + PEG; T4 = T1 + CT (3.5% DM); T5 = T4 + PEG; T6 = T1 + CT (4% DM) and T7 = T6 + PEG. Data obtained were analysed using Randomized Block Design. Statistical analyses showed that treatments significanty affected (P<0.05) total gas production and EMPS. The lowest values of total gas production (45.9 ml/500 mg DM) and highest value of EMPS (64.6 g/kg BOTR) were observed in the treatment T4 (3.5% CT from cassava leave extract). Based on this result it was concluded that this treatment was the best and was chosen for further investigation using in vivo method. The treatmets applied for in vivo trial were: T1 = EG (60%) + concentrate (40%); T2 = T1 + dried cassava leave (equivalent to 3.5% CT); T3 = T2 + PEG. 18 growing sheep aging of 8-9 months and weighing of 23.67kg ± 1.23 were used in Expt 2. Results of in vivo study showed that treatments significanty affected (P<0.05) nutrients intake and digestibility (DM, OM and CP). N retention for sheep receiving treatment T2 were significantly higher (P<0.05; 15.6 g/d) than T1 (9.1 g/d) and T3 (8.53 g/d). Similar results were obtained for daily weight gain where T2 were the highest (62.79 g/d), followed by T1 (51.9 g/d) and T3 (52.85 g/d). Dressing percentage of T2 was the highest (51.54%) followed by T1 (49.61%) and T3 (49.32%). It can be concluded that adding adding dried cassava leaves did not reduce palatability due to CT, but rather increased OM digestibility and hence feed consumption was improved. N retention was increased due to the action of CT in the cassava leaves and this may have explained a higher input of N into duodenum which was further led to higer daily weight gain and dressing percentage.

Keywords: in vitro gas production, sheep, shrub and tree leaves, condensed tannin

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Authors: Jongbae Lee, Seongsoo Lee

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Modern sensors often embed small-size digital controller for sensor control, value calibration, and signal processing. These sensors require digital data communication with host microprocessors, but conventional digital communication protocols are too heavy for price reduction. SAE J2716 SENT (single edge nibble transmission) protocol transmits direct digital waveforms instead of complicated analog modulated signals. In this paper, a SENT interface is designed in Verilog HDL (hardware description language) and implemented in FPGA (field-programmable gate array) evaluation board. The designed SENT interface consists of frame encoder/decoder, configuration register, tick period generator, CRC (cyclic redundancy code) generator/checker, and TX/RX (transmission/reception) buffer. Frame encoder/decoder is implemented as a finite state machine, and it controls whole SENT interface. Configuration register contains various parameters such as operation mode, tick length, CRC option, pause pulse option, and number of nibble data. Tick period generator generates tick signals from input clock. CRC generator/checker generates or checks CRC in the SENT data frame. TX/RX buffer stores transmission/received data. The designed SENT interface can send or receives digital data in 25~65 kbps at 3 us tick. Synthesized in 0.18 um fabrication technologies, it is implemented about 2,500 gates.

Keywords: digital sensor interface, SAE J2716, SENT, verilog HDL

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Authors: Rafat Alwazna

Abstract:

Translation teaching is a particular activity that includes translators and interpreters training either inside or outside institutionalised settings, such as universities. It can also serve as a means of teaching other fields, such as foreign languages. Translation teaching began in the twentieth century. Teachers of translation hold the responsibilities of educating students, developing their translation competence and training them to be professional translators. The activity of translation teaching involves various tasks, including curriculum design, course delivery, material writing as well as application and implementation. The present paper addresses translation teaching during COVID-19 outbreak, seeking to find out the challenges encountered by translation teachers in online translation teaching and the discoveries/solutions arrived at to resolve them. The paper makes use of a comprehensive questionnaire, containing closed-ended and open-ended questions to elicit both quantitative as well as qualitative data from about sixty translation teachers who have been teaching translation at BA and MA levels during COVID-19 outbreak. The data shows that about 40% of the participants evaluate their online translation teaching experience during COVID-19 outbreak as enjoyable and exhilarating. On the contrary, no participant has evaluated his/her online translation teaching experience as being not good, nor has any participant evaluated his/her online translation teaching experience as being terrible. The data also presents that about 23.33% of the participants evaluate their online translation teaching experience as very good, and the same percentage applies to those who evaluate their online translation teaching experience as good to some extent. Moreover, the data indicates that around 13.33% of the participants evaluate their online translation teaching experience as good. The data also demonstrates that the majority of the participants have encountered obstacles in online translation teaching and have concurrently proposed solutions to resolve them.

Keywords: online translation teaching, electronic learning platform, COVID-19 outbreak, challenges, solutions

Procedia PDF Downloads 223

Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

Abstract:

High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch

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Authors: I. Mukherjee, J. Ghose, T. Chakraborty, S. Chaudhury, R. Majumder

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India is the second most populated nation in the world. With the Indian population hitting the 1.26 billion mark in the year 2014, there has been an unprecedented rise in power and energy requirements throughout the nation. This mammoth demand for energy, both at the industrial as well as at the domestic household level, as well as the increase in the usage of automobiles has led to a corresponding increase in the total tonnage of fuels being burnt every year. This, in turn, has led to an increase in the concentration of atmospheric pollutants over the years with enhanced particulate concentrations being reported for different parts of the country. Considering the adverseness of the particulates, the paper analyses the role of the particulates on the air quality of four major congested cities of the country namely, Kolkata (22034’ N, 88024’ E), Delhi (28038’N , 77012’ E), Bangalore (12058’ N , 77038’E) and Mumbai (18.9750° N, 72.8258° E) over a period of four years from 2006-2009. The fractional contribution of the finer fractions to the coarser one has been considered in the study in addition to the relative occurrences of the particulate fractions with respect to the other gaseous pollutants such as sulphur dioxide (SO2) and nitrogen oxides (NOX).

Keywords: air quality, particulates, yearly variation, relative occurrence, SO2, NOX

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Authors: Muhammad Usman Akram

Abstract:

This research work based on GNSS-Aided Photogrammetry for Digital Mapping. It focuses on topographic survey of an area or site which is to be used in future Planning & development (P&D) or can be used for further, examination, exploration, research and inspection. Survey and Mapping in hard-to-access and hazardous areas are very difficult by using traditional techniques and methodologies; as well it is time consuming, labor intensive and has less precision with limited data. In comparison with the advance techniques it is saving with less manpower and provides more precise output with a wide variety of multiple data sets. In this experimentation, Aerial Photogrammetry technique is used where an UAV flies over an area and captures geocoded images and makes a Three-Dimensional Model (3-D Model), UAV operates on a user specified path or area with various parameters; Flight altitude, Ground sampling distance (GSD), Image overlapping, Camera angle etc. For ground controlling, a network of points on the ground would be observed as a Ground Control point (GCP) using Differential Global Positioning System (DGPS) in PPK or RTK mode. Furthermore, that raw data collected by UAV and DGPS will be processed in various Digital image processing programs and Computer Aided Design software. From which as an output we obtain Points Dense Cloud, Digital Elevation Model (DEM) and Ortho-photo. The imagery is converted into geospatial data by digitizing over Ortho-photo, DEM is further converted into Digital Terrain Model (DTM) for contour generation or digital surface. As a result, we get Digital Map of area to be surveyed. In conclusion, we compared processed data with exact measurements taken on site. The error will be accepted if the amount of error is not breached from survey accuracy limits set by concerned institutions.

Keywords: photogrammetry, post processing kinematics, real time kinematics, manual data inquiry

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Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Kyung-Suk Choi, Hyung-Joon Kim

Abstract:

Modular structural systems are constructed using a method that they are assembled with prefabricated unit modular frames on-site. This provides a benefit that can significantly reduce building construction time. Their structural design is usually carried out under the assumption that the load-carrying mechanism is similar to that of a traditional steel moment-resisting system. However, both systems are different in terms of beam-column connection details which may strongly influence the lateral structural behavior. Specially, the presence of access holes in a beam-column joint of a unit modular frame could cause undesirable failure during strong earthquakes. Therefore, this study carried out finite element analyses (FEM) of unit modular frames to investigate the cyclic behavior of beam-column joints with the structural influence of access holes. Analysis results show that the unit modular frames present stable cyclic response with large deformation capacities, and their joints are classified into semi-rigid connections.

Keywords: unit modular frame, steel moment connection, nonlinear analytical model, moment-rotation relation

Procedia PDF Downloads 619

Authors: Waleed Baloch

Abstract:

This paper investigates the problems and challenges in social-economic research in the case study of the province of Sindh after the COVID-19 pandemic; the pandemic has significantly impacted various aspects of society and the economy, necessitating a thorough examination of the resulting implications. The study also investigates potential strategies and solutions to mitigate these challenges, ensuring the continuation of robust social and economic research in the region. Through an in-depth analysis of data and interviews with key stakeholders, the study reveals several significant findings. Firstly, researchers encountered difficulties in accessing primary data due to disruptions caused by the pandemic, leading to limitations in the scope and accuracy of their studies. Secondly, the study highlights the challenges faced in conducting fieldwork, such as restrictions on travel and face-to-face interactions, which impacted the ability to gather reliable data. Lastly, the research identifies the need for innovative research methodologies and digital tools to adapt to the new research landscape brought about by the pandemic. The study concludes by proposing recommendations to address these challenges, including utilizing remote data collection methods, leveraging digital technologies for data analysis, and establishing collaborations among researchers to overcome resource constraints. By addressing these issues, researchers in the social economic field can effectively navigate the post-COVID-19 research landscape, facilitating a deeper understanding of the socioeconomic impacts and facilitating evidence-based policy interventions.

Keywords: social economic, sociology, developing economies, COVID-19

Procedia PDF Downloads 63

Authors: T. A. Khan, A. B. Khan, M. Babar, T. A. Taj, Imran Ijaz Imran

Abstract:

Smart Meter is a key element in the evolving concept of Smart Grid, which plays an important role in interaction between the consumer and the supplier. In general, the smart meter is an intelligent digital energy meter that measures the consumption of electrical energy and provides other additional services as compared to the conventional energy meters. One of the important element that makes a meter smart and different is its communication module. Smart meters usually have two way and real-time communication between the consumer and the supplier through which its transfer data and information. In this paper, Ultra Wide Band (UWB) is recommended as communication platform because of its high data-rate and presents the physical layer, which could be easily incorporated in existing Smart Meters. The physical layer is simulated in MATLAB Simulink and the results are provided.

Keywords: Ultra Wide Band (UWB), Smart Meter, MATLAB, transfer data

Procedia PDF Downloads 516