Search results for: heterogeneous data

Authors: H. Khanfari, M. Johari Fard

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Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

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Authors: C. C. Alamanjo, A. O. Adepoju, H. Martin, R. N. Baines

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Peri-urban agriculture in Jos Nigeria serves as a major means of livelihood for both urban and peri-urban poor, and constitutes huge commercial inclination with a target market that has spanned beyond Plateau State. Yet, the sustainability of this sector is threatened by intensive application of urban refuse ash contaminated with heavy metals, as a result of the highly heterogeneous materials used in ash production. Hence, this research aimed to understand the current fertilizer employed by farmers, their perception and acceptability in utilization of household sewage sludge for agricultural purposes and their capacity in mitigating risks associated with such practice. Mixed methods approach was adopted, and data collection tools used include survey questionnaire, focus group discussion with farmers, participants and field observation. The study identified that farmers maintain a complex mixture of organic and chemical fertilizers, with mixture composition that is dependent on fertilizer availability and affordability. Also, farmers have decreased the rate of utilization of urban refuse ash due to labor and increased logistic cost and are keen to utilize household sewage sludge for soil fertility improvement but are mainly constrained by accessibility of this waste product. Nevertheless, farmers near to sewage disposal points have commenced utilization of household sewage sludge for improving soil fertility. Farmers were knowledgeable on composting but find their strategic method of dewatering and sun drying more convenient. Irrigation farmers were not enthusiastic for treatment, as they desired both water and sludge. Secondly, household sewage sludge observed in the field is heterogeneous due to nearness between its disposal point and that of urban refuse, which raises concern for possible cross-contamination of pollutants and also portrays lack of extension guidance as regards to treatment and management of household sewage sludge for agricultural purposes. Hence, farmers concerns need to be addressed, particularly in providing extension advice and establishment of decentralized household sewage sludge collection centers, for continuous availability of liquid and concentrated sludge. Urgent need is also required for the Federal Government of Nigeria to increase commitment towards empowering her subsidiaries for efficient discharge of corporate responsibilities.

Keywords: ash, farmers, household, peri-urban, refuse, sewage, sludge, urban

Procedia PDF Downloads 140

Authors: Ajay Pinjani, Minha Khan, Ayesha Mehkeri, Anum Iftikhar

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There is much research available on the benefits of adopting mother tongue-based multilingual education (MTB MLE) in primary school classrooms, but there is limited guidance available on how to design such programs for low-resource and linguistically diverse contexts. This paper is an effort to bridge the gap between theory and practice by offering a practitioner’s perspective on designing an MTB MLE program for linguistically heterogeneous contexts. The research compounds findings from current academic literature on MTB MLE, the study of global MTB MLE programs, interviews with practitioners, policy-makers, and academics worldwide, and a socio-linguistic survey carried out in parts of Tharparkar, Pakistan, the area selected for envisioned pilot implementation. These findings enabled the creation of ‘guiding principles’ which provide structure for the development of a contextualized and holistic MTB-MLE program. The guiding principles direct the creation of teaching and learning materials, creating effective teaching and learning environment, community engagement, and program evaluation. Additionally, the paper demonstrates the development of a context-specific language ladder framework which outlines the language journey of a child’s education, beginning with the mother tongue/ most familiar language in the early years and then gradually transitioning into other languages. Both the guiding principles and language ladder can be adapted to any multilingual context. Thus, this research provides MTB MLE practitioners with assistance in developing an MTB MLE model, which is best suited for their context.

Keywords: mother tongue based multilingual education, education design, language ladder, language issues, heterogeneous contexts

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Authors: Amir Mohammad Parvini, Amir Masoud Rahimi

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Currently, most parts of the world have shifted from traditional roundabouts to modern roundabouts with respect to the role of roundabouts in reducing accidents, increasing safety, lowering the maintenance costs compared to traffic circles with their improper functional and safety experiences. In this study, field data collected from a current traditional roundabout was analyzed by the software AIMSUN and the obtained numbers were recorded. The modern roundabout was designed by changes in the traditional one, considering the geometric standards listed in regulations. Then, the modern roundabout was analyzed by applying a heterogeneous traffic by a micro-simulation software SIDRA (5.1). The function, capacity, and safety of the roundabout were analyzed assuming the superiority of modern roundabouts and acceptable LOS. The obtained results indicate that the function, capacity, and safety of modern roundabouts are better than traditional ones.

Keywords: traditional roundabout, traffic circles, modern roundabout, AIMSUN, SIDRA

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: capacity, carrier aggregation, LTE-Advanced, MIMO (Multiple Input Multiple Output), peak data rate, spectral efficiency

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Authors: D. Mowla, N. Rasti, P. Keshavarz

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Reduction of fossil fuels sources, increasing of pollution gases emission, and global warming effects increase the demand of renewable fuels. One of the main candidates of alternative fuels is biodiesel. Biodiesel limits greenhouse gas effects due to the closed CO₂ cycle. Biodiesel has more biodegradability, lower combustion emissions such as CO, SO_x, HC, PM and lower toxicity than petro diesel. However, biodiesel has high production cost due to high price of plant oils as raw material. So, the utilization of waste cooking oils (WCOs) as feedstock, due to their low price and disposal problems reduce biodiesel production cost. In this study, production of biodiesel by transesterification of methanol and WCO using modified sodic potassic (SP) clinoptilolite zeolite and sodic potassic calcic (SPC) clinoptilolite zeolite as heterogeneous catalysts have been investigated. These natural clinoptilolite zeolites were modified by KOH solution to increase the site activity. The optimum biodiesel yields for SP clinoptilolite and SPC clinoptilolite were 95.8% and 94.8%, respectively. Produced biodiesel were analyzed and compared with petro diesel and ASTM limits. The properties of produced biodiesel confirm well with ASTM limits. The density, kinematic viscosity, cetane index, flash point, cloud point, and pour point of produced biodiesel were all higher than petro diesel but its acid value was lower than petro diesel. Finally, the reusability and regeneration of catalysts were investigated. The results indicated that the spent zeolites cannot be reused directly for the transesterification, but they can be regenerated easily and can obtain high activity.

Keywords: biodiesel, renewable fuel, transesterification, waste cooking oil

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: R. Sivasamy, G. Paulraj, S. Kalaimani, N.Thillaigovindan

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For profitable businesses, queues are double-edged swords and hence the pain of long wait times in a queue often frustrates customers. This paper suggests a technical way of reducing the pain of lines through a Poisson M/M1, M2/2 queueing system operated by two heterogeneous servers with an objective of minimising the mean sojourn time of customers served under the queue discipline ‘First Come First Served with an ‘m’ policy, i.e. FCFS-m policy’. Arrivals to the system form a Poisson process of rate λ and are served by two exponential servers. The service times of successive customers at server ‘j’ are independent and identically distributed (i.i.d.) random variables and each of it is exponentially distributed with rate parameter μj (j=1, 2). The primary condition for implementing the queue discipline ‘FCFS-m policy’ on these service rates μj (j=1, 2) is that either (m+1) µ2 > µ1> m µ2 or (m+1) µ1 > µ2> m µ1 must be satisfied. Further waiting customers prefer the server-1 whenever it becomes available for service, and the server-2 should be installed if and only if the queue length exceeds the value ‘m’ as a threshold. Steady-state results on queue length and waiting time distributions have been obtained. A simple way of tracing the optimal service rate μ*2 of the server-2 is illustrated in a specific numerical exercise to equalize the average queue length cost with that of the service cost. Assuming that the server-1 has to dynamically adjust the service rates as μ1 during the system size is strictly less than T=(m+2) while μ2=0, and as μ1 +μ2 where μ2>0 if the system size is more than or equal to T, corresponding steady state results of M/M1+M2/1 queues have been deduced from those of M/M1,M2/2 queues. To conclude this investigation has a viable application, results of M/M1+M2/1 queues have been used in processing of those waiting messages into a single computer node and to measure the power consumption by the node.

Keywords: two heterogeneous servers, M/M1, M2/2 queue, service cost and queue length cost, M/M1+M2/1 queue

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Authors: Fidelis Chigondo

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This study focuses on investigating the effectiveness of watermelon rind in phenol removal from aqueous solution. The effects of various parameters (pH, initial phenol concentration, biosorbent dosage and contact time) on phenol adsorption were investigated. The pH of 2, initial phenol concentration of 40 ppm, the biosorbent dosage of 0.6 g and contact time of 6 h also deduced to be the optimum conditions for the adsorption process. The maximum phenol removal under optimized conditions was 85%. The sorption data fitted to the Freundlich isotherm with a regression coefficient of 0.9824. The kinetics was best described by the intraparticle diffusion model and Elovich Equation with regression coefficients of 1 and 0.8461 respectively showing that the reaction is chemisorption on a heterogeneous surface and the intraparticle diffusion rate only is the rate determining step. The study revealed that watermelon rind has a potential of removing phenol from industrial wastewaters.

Keywords: biosorption, phenol, biosorbent, watermelon rind

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

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Authors: Xiaoping Su, Gabriel G. Malouf

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Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

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Authors: M. Bevilacqua, F. E. Ciarapica, G. Marcucci

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Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

Keywords: supply chain resilience, resilience definition, supply chain resilience triangle

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Padmini S. Navalgund, Manasi Naik, Ujwala Patil

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Road hump is a semi-cylindrical elevation on the road made across specific locations of the road. The vehicle needs to maneuver the hump by reducing the speed to avoid car damage and pass over the road hump safely. Road Humps on road surfaces, if identified in advance, help to maintain the security and stability of vehicles, especially in adverse visibility conditions, viz. night scenarios. We have proposed a deep learning architecture adaptation by implementing the MISH activation function and developing a new classification loss function called "Effective Focal Loss" for Indian road humps detection in adverse light scenarios. We captured images comprising of marked and unmarked road humps from two different types of cameras across South India to build a heterogeneous dataset. A heterogeneous dataset enabled the algorithm to train and improve the accuracy of detection. The images were pre-processed, annotated for two classes viz, marked hump and unmarked hump. The dataset from these images was used to train the single-stage object detection algorithm. We utilised an algorithm to synthetically generate reduced visible road humps scenarios. We observed that our proposed framework effectively detected the marked and unmarked hump in the images in clear and ad-verse light environments. This architectural adaptation sets up an option for early detection of Indian road humps in reduced visibility conditions, thereby enhancing the autonomous driving technology to handle a wider range of real-world scenarios.

Keywords: Indian road hump, reduced visibility condition, low light condition, adverse light condition, marked hump, unmarked hump, YOLOv9

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Sabrina Tabassum

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Using Census Data for Housing and Population of Australia 2001, 2006, 2011, and 2016, this paper shows the existence of wage differences between natives and immigrants in Australia. Addressing the heterogeneous nature of immigrants, this study group the immigrants in three broad categories- migrants from English speaking countries and migrants from India and China. Migrants from English speaking countries and India earn more than the natives per week, whereas migrants from China earn far less than the natives per week. Oaxaca decomposition suggests that major part of this differential is unexplained. Using the occupational segregation concept and Brown decomposition, this study indicates that migrants from India and China would have been earned more than the natives if they had the same occupation distribution as natives due to their individual characteristics. Within occupation, wage differences are more prominent than inter-occupation wage differences for immigrants from China and India.

Keywords: Australia, labour, migration, wage

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Authors: Carolin Schulze

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Characterized by a positive interdependence of learners, cooperative learning (CL) is one possibility of successfully dealing with the increasing heterogeneity of students. Various positive effects of CL on the mental, physical and social health of students have already been documented. However, this structure is still rarely used in physical education (PE). Moreover, there is a lack of information about factors that determine the successful implementation of CL in PE. Therefore, the objective of the current study was to find out factors that determine the successful implementation of CL in PE using a digital questionnaire that was conducted from November to December 2022. In addition to socio-demographic data (age, gender, teaching experience, and education level), frequency of using CL, implementation strategies (theory-led, student-centred), and positive and negative effects of CL were measured. Furthermore, teachers were asked to rate the success of implementation on a 6-point rating scale (1-very successful to 6-not successful at all). For statistical analysis, multiple linear regression was performed, setting the success of implementation as the dependent variable. A total of 224 teachers (mean age=44.81±10.60 years; 58% male) took part in the current study. Overall, 39% of participants stated that they never use CL in their PE classes. Main reasons against the implementations of CL in PE were no time for preparation (74%) or for implementation (61%) and high heterogeneity of students (55%). When using CL, most of the reported difficulties are related to uncertainties about the correct procedure (54%) and the heterogeneous performance of students (54%). The most frequently mentioned positive effect was increased motivation of students (42%) followed by an improvement of psychological abilities (e.g. self-esteem, self-concept; 36%) and improved class cohesion (31%). Reported negative effects were unpredictability (29%), restlessness (24%), confusion (24%), and conflicts between students (17%). The successful use of CL is related to a theory-based preparation (e.g., heterogeneous formation of groups, use of rules and rituals) and a flexible implementation tailored to the needs and conditions of students (e.g., the possibility of individual work, omission of CL phases). Compared to teachers who solely implemented CL theory-led or student-adapted, teachers who switched from theory-led preparation to student-centred implementation of CL reported more successful implementation (t=5.312; p<.001). Neither frequency of using CL in PE nor the gender, age, the teaching experience, or the education level of the teacher showed a significant connection with the successful use of CL. Corresponding to the results of the current study, it is advisable that teachers gather enough knowledge about CL during their education and to point out the need to adapt the learning structure according to the diversity of their students. In order to analyse implementation strategies of teachers more deeply, qualitative methods and guided interviews with teachers are needed.

Keywords: diversity, educational technology, physical education, teaching styles

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Authors: Oleg Oborin

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This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: H. Parveen Begam, M. A. Maluk Mohamed

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Mobile Grid Computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using different types of electronic portable devices. In a grid environment the security issues are like authentication, authorization, message protection and delegation handled by GSI (Grid Security Infrastructure). Proving better security between mobile devices and grid infrastructure is a major issue, because of the open nature of wireless networks, heterogeneous and distributed environments. In a mobile grid environment, the individual computing devices may be resource-limited in isolation, as an aggregated sum, they have the potential to play a vital role within the mobile grid environment. Some adaptive methodology or solution is needed to solve the issues like authentication of a base station, security of information flowing between a mobile user and a base station, prevention of attacks within a base station, hand-over of authentication information, communication cost of establishing a session key between mobile user and base station, computing complexity of achieving authenticity and security. The sharing of resources of the devices can be achieved only through the trusted relationships between the mobile hosts (MHs). Before accessing the grid service, the mobile devices should be proven authentic. This paper proposes the dynamic certificate based mutual authentication protocol between two mobile hosts in a mobile grid environment. The certificate generation process is done by CA (Certificate Authority) for all the authenticated MHs. Security (because of validity period of the certificate) and dynamicity (transmission time) can be achieved through the secure service certificates. Authentication protocol is built on communication services to provide cryptographically secured mechanisms for verifying the identity of users and resources.

Keywords: mobile grid computing, certificate authority (CA), SSL/TLS protocol, secured service certificates

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Wenlong Liu, Ru Zhang, Wangjie Li, Shenghui Sang

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The boom of smart cities in the age of population aging has caused concerns about the subjective well-being of the elderly. By employing the data from China Health and Retirement Longitudinal Study (CHARLS) 2015, this study uses an ordinary least square to analyze the influence of smart city development on the subjective well-being of the elderly in China. The results of this study suggest that smart cities will improve the life satisfaction of the elderly but reduce their happiness of them. In terms of the moderating effect, social capital negatively moderates the impact of the smart city on the subjective well-being of the elderly. Combined with the results of heterogeneous analysis, it is found that smart city has a stronger impact on the subjective well-being of the elderly with lower levels of personal social capital. To sum up, in the context of the country's vigorous promotion of smart city development, society and families should actively help the elderly to improve their social capital level, enhance the subjective well-being of the elderly, and alleviate the negative effects of smart city development, thereby improving the quality of life of the elderly.

Keywords: the elderly, smart city, social capital, subjective well-being

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Authors: Dhiraj Neupane

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Decentralized policy and practices have largely concentrated on the transformation of decision-making authorities from central to local institutions (or people) in the developing world. Such policy and practices always aimed for the equitable and efficient management of resources in the line of poverty reduction. The transformation of forest decision-making autonomy has also glorified as the best forest management alternatives to maximize the forest benefits and improve the livelihood of local people living nearby the forests. However, social heterogeneity and poor decision-making capacity of local institutions (or people) pose a nexus while managing the resources and sharing the forest benefits among the user households despite the policy objectives. The situation is severe in the lowland of Nepal, where forest resources have higher economic potential and user households have heterogeneous socio-economic conditions. The study discovered that utilizing the power of decision-making autonomy, user households were putting low values of timber considering the equitable access of timber to all user households as it is the most valuable product of community forest. Being the society is heterogeneous by socio-economic conditions, households of better economic conditions were always taking higher amount of forest benefits. The low valuation of timber has negative consequences on equitable benefit sharing and poor support to livelihood improvement of user households. Moreover, low valuation has possibility to increase the local demands of timber and increase the human pressure on forests.

Keywords: decentralized forest policy, Nepal, poverty, social heterogeneity, Terai

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Authors: Pil Seong Park

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Homemade HPC clusters are widely used in many small labs, because they are easy to build and cost-effective. Even though incremental growth is an advantage of clusters, it results in heterogeneous systems anyhow. Instead of adding new nodes to the cluster, we can extend clusters to include some other Internet servers working independently on the same LAN, so that we can make use of their idle times, especially during the night. However extension across a firewall raises some security problems with NFS. In this paper, we propose a method to solve such a problem using SSH tunneling, and suggest a modified structure of the cluster that implements it.

Keywords: extension of HPC clusters, security, NFS, SSH tunneling

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Authors: Atefeh Abedini, Fatemeh Razavi, Mihan Pourabdollah Toutkaboni, Hossein Mehravaran, Arda Kiani

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In countries with the highest prevalence of tuberculosis, such as Iran, the differentiation of malignant tumors from non-malignant is very important. In this study, which was conducted for the first time among the Iranian population, the utility of the ultrasonographic morphological characteristics in patients undergoing EBUS was used to distinguish the non-malignant versus malignant lymph nodes. The morphological characteristics of lymph nodes, which consist of size, shape, vascular pattern, echogenicity, margin, coagulation necrosis sign, calcification, and central hilar structure, were obtained during Endobronchial Ultrasound-Guided Trans-Bronchial Needle Aspiration and were compared with the final pathology results. During this study period, a total of 253 lymph nodes were evaluated in 93 cases. Round shape, non-hilar vascular pattern, heterogeneous echogenicity, hyperechogenicity, distinct margin, and the presence of necrosis sign were significantly higher in malignant nodes. On the other hand, the presence of calcification and also central hilar structure were significantly higher in the benign nodes (p-value ˂ 0.05). Multivariate logistic regression showed that size>1 cm, heterogeneous echogenicity, hyperechogenicity, the presence of necrosis signs and, the absence of central hilar structure are independent predictive factors for malignancy. The accuracy of each of the aforementioned factors is 42.29 %, 71.54 %, 71.90 %, 73.51 %, and 65.61 %, respectively. Of 74 malignant lymph nodes, 100% had at least one of these independent factors. According to our results, the morphological characteristics of lymph nodes based on Endobronchial Ultrasound-Guided Trans-Bronchial Needle Aspiration can play a role in the prediction of malignancy.

Keywords: EBUS-TBNA, malignancy, nodal characteristics, pathology

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Adrian Lo

Abstract:

Since the beginning of modern architecture, ideas of free plan and transparency have proliferated well into current trends of building design, from houses to highrise office buildings. The movement’s notion of a spatially homogeneous, open, and limitless ‘free plan’ stands opposite to the spatially heterogeneous ‘separation of rooms’ defined by load-bearing walls, which in turn triggered new notions of transparency achieved by vast expanses of glazed walls. Similarly, transparency was also dichotomized as something that was physical or optical, as well as something conceptual, akin to spatial organization. As opposed to merely accepting the duality and possible incompatibility of these dichotomies, this paper seeks to ask how can space be both literally and phenomenally transparent, as well as display both homogeneous and heterogeneous qualities? This paper explores this potential destabilization or blurring of spatial phenomena by dissecting the transparent layers and volumes of a series of selected case studies to investigate how different architects have devised strategies of spatial ambivalence, ambiguity, and interpenetration. Projects by Peter Eisenman, Sou Fujimoto, and SANAA will be discussed and analyzed to show how the superimposition of geometries and spaces achieve different conditions of layering, transparency, and interstitiality. Their particular buildings will be explored to reveal various innovative kinds of spatial interpenetration produced through the articulate relations of the elements of architecture, which challenge conventional perceptions of interior and exterior whereby visual homogeneity blurs with spatial heterogeneity. The results show how spatial conceptions such as interpenetration and transparency have the ability to subvert not only inside-outside dialectics but could also produce multiple degrees of interiority within complex and indeterminate spatial dimensions in constant flux as well as present alternative forms of social interaction.

Keywords: interpenetration, literal and phenomenal transparency, spatial heterogeneity, visual homogeneity

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Authors: N. F. F. Ebecken, G. C. Pereira

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Although networks provide a powerful approach to the study of a wide variety of ecological systems, their formulation usually does not include various types of interactions, interactions that vary in space and time, and interconnected systems such as networks. The emerging field of 'multilayer networks' provides a natural framework for extending ecological systems analysis to include these multiple layers of complexity as it specifically allows for differentiation and modeling of intralayer and interlayer connectivity. The structure provides a set of concepts and tools that can be adapted and applied to the ecology, facilitating research in high dimensionality, heterogeneous systems in nature. Here, ecological multilayer networks are formally defined based on a review of prior and related approaches, illustrates their application and potential with existing data analyzes, and discusses limitations, challenges, and future applications. The integration of multilayer network theory into ecology offers a largely untapped potential to further address ecological complexity, to finally provide new theoretical and empirical insights into the architecture and dynamics of ecological systems.

Keywords: ecological networks, multilayered networks, sea ecology, Brazilian Coastal Area

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

Abstract:

This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: Worawanna Panyakotkaew, Falan Srisuriyachai

Abstract:

Cyclic steam injection (CSI) is a thermal recovery technique performed by injecting periodically heated steam into heavy oil reservoir. Oil viscosity is substantially reduced by means of heat transferred from steam. Together with gas pressurization, oil recovery is greatly improved. Nevertheless, prediction of effectiveness of the process is difficult when reservoir contains degree of heterogeneity. Therefore, study of heterogeneity together with interest reservoir properties must be evaluated prior to field implementation. In this study, thermal reservoir simulation program is utilized. Reservoir model is firstly constructed as multi-layered with coarsening upward sequence. The highest permeability is located on top layer with descending of permeability values in lower layers. Steam is injected from two wells located diagonally in quarter five-spot pattern. Heavy oil is produced by adjusting operating parameters including soaking period and steam quality. After selecting the best conditions for both parameters yielding the highest oil recovery, effects of degree of heterogeneity (represented by Lorenz coefficient), vertical permeability and permeability sequence are evaluated. Surprisingly, simulation results show that reservoir heterogeneity yields benefits on CSI technique. Increasing of reservoir heterogeneity impoverishes permeability distribution. High permeability contrast results in steam intruding in upper layers. Once temperature is cool down during back flow period, condense water percolates downward, resulting in high oil saturation on top layers. Gas saturation appears on top after while, causing better propagation of steam in the following cycle due to high compressibility of gas. Large steam chamber therefore covers most of the area in upper zone. Oil recovery reaches approximately 60% which is of about 20% higher than case of heterogeneous reservoir. Vertical permeability exhibits benefits on CSI. Expansion of steam chamber occurs within shorter time from upper to lower zone. For fining upward permeability sequence where permeability values are reversed from the previous case, steam does not override to top layers due to low permeability. Propagation of steam chamber occurs in middle of reservoir where permeability is high enough. Rate of oil recovery is slower compared to coarsening upward case due to lower permeability at the location where propagation of steam chamber occurs. Even CSI technique produces oil quite slowly in early cycles, once steam chamber is formed deep in the reservoir, heat is delivered to formation quickly in latter cycles. Since reservoir heterogeneity is unavoidable, a thorough understanding of its effect must be considered. This study shows that CSI technique might be one of the compatible solutions for highly heterogeneous reservoir. This competitive technique also shows benefit in terms of heat consumption as steam is injected periodically.

Keywords: cyclic steam injection, heterogeneity, reservoir simulation, thermal recovery

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