Search results for: urban network space

Authors: Reza Mehrafarin, Nafiseh Mirshekari, Mahila Mehrafarin

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Sistan is one of the ancient regions of Iran, which is located in the east of this country. 1660 ancient sites were identified in the archeological field surveys that we did in this area. Of these, about 900 sites belong to the Bronze Age, which are located in an area of about 3000 square kilometers. The Bronze Age in Iran began at the end of the fourth millennium BC and ended at the beginning of the second millennium BC. During this period, many cities and villages were established in Sistan, that the burnt city (Shahr-e Sokhta) was its most important center, with an area of about 150 hectares and a population of 5,000. In this article, we have tried to identify and introduce the most important features of the Bronze Age of Sistan, especially the burnt city. Another goal of the article is to identify the factors that led to the emergence of the Bronze Age, especially urbanization in Sistan at the end of the fourth millennium BCand then we want to know what factors caused the destruction of Bronze Age civilization and urbanization in Sistan. Studying and evaluating these factors are the most important goals of this article. The research method of this article is field research. As we surveyed all of Sistan with a large number of archaeologists for two years in order to identify its ancient sites and understanding its geographical space. The result of this survey led to the identification of a large number of ancient sites which were formed in three major terraces in Sistan. The most important factor in the emergence of these civilizations, especially the Bronze Age in Sistan, was the Hirmand River. On the other hand, the most important factor in the destruction of the Bronze Age and its cities in Sistan was the Hirmand River.As it was destroyed by the movement of the Hirmand River bed or the long droughts of the Bronze Age of Sistan.

Keywords: archaeological survey, bronze age, sistan, urbanization

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: Elizelle Juaneé Cilliers

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The green hype is becoming stronger within various disciplines, modern practices and academic thinking, enforced by concepts such as eco-health, eco-tourism, eco-cities, and eco-engineering. There is currently also an expanded scientific understanding regarding the value and benefits relating to green infrastructure, for both communities and their host cities, linked to broader sustainability and resilience thinking. The integration and implementation of green infrastructure as part of spatial planning approaches and municipal planning, are, however, more complex, especially in South Africa, inflated by limitations of budgets and human resources, development pressures, inequities in terms of green space availability and political legacies of the past. The prevailing approach to spatial planning is further contributing to complexity, linked to misguided perceptions of the function and value of green infrastructure. As such, green spaces are often considered a luxury, and green infrastructure a costly alternative, resulting in green networks being susceptible to land-use changes and under-prioritized in local authority decision-making. Spatial planning, in this sense, may well be a valuable tool to realise the green agenda, encapsulating various initiatives of sustainability as provided by a range of disciplines. This paper aims to clarify the importance and value of green infrastructure planning as a component of spatial planning approaches, in order to inform and encourage local authorities to embed sustainability thinking into city planning and decision-making approaches. It reflects on the decisive role of land-use management to guide the green agenda and refers to some recent planning initiatives. Lastly, it calls for trans-disciplinary planning approaches to build a case towards green(er) cities.

Keywords: green infrastructure, spatial planning, transdisciplinary, integrative

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Authors: F. A. Olutoge, O.R. Olulope, M. O. Odelola

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This study investigates the strength potentials of groundnut husk ash as partial cement replacement in mortar and also develops a predictive model using Artificial Neural Network. Groundnut husks sourced from Ogbomoso, Nigeria, was sun dried, calcined to ash in a furnace at a controlled temperature of 600⁰ C for a period of 6 hours, and sieved through the 75 microns. The ash was subjected to chemical analysis and setting time test. Fine aggregate (sand) for the mortar was sourced from Ado Ekiti, Nigeria. The cement: GHA constituents were blended in ratios 100:0, 95:5, 90:10, 85:15 and 80:20 %. The sum of SiO₂, Al₂O₃, and Fe₂O₃ content in GHA is 26.98%. The compressive strength for mortars PC, GHA5, GHA10, GHA15, and GHA20 ranged from 6.3-10.2 N/mm² at 7days, 7.5-12.3 N/mm² at 14 days, 9.31-13.7 N/mm² at 28 days, 10.4-16.7 N/mm² at 56days and 13.35- 22.3 N/mm² at 90 days respectively, PC, GHA5 and GHA10 had competitive values up to 28 days, but GHA10 gave the highest values at 56 and 90 days while GHA20 had the lowest values at all ages due to dilution effect. Flexural strengths values at 28 days ranged from 1.08 to 1.87 N/mm² and increased to a range of 1.53-4.10 N/mm² at 90 days. The ANN model gave good prediction for compressive strength of the mortars. This study has shown that groundnut husk ash as partial cement replacement improves the strength properties of mortar.

Keywords: compressive strength, groundnut husk ash, mortar, pozzolanic index

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Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: clique, clan, electronic health records, physician collaboration

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Authors: Cassandra Seery

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During the twentieth century, the notion of child rights at the international level began with the League of Nations’ Geneva Declaration of the Rights of the Child 1924, culminating in the development and adoption of the UN Convention on the Rights of the Child (‘the Convention’) in 1989. A key foundation of child rights lies in the development of the ‘best interests of the child’ principle and its subsequent incorporation into domestic legislation across the globe. This principle has become a key concept in child rights protection and has become a widely recognized principle in the protection of child rights. However, despite its status as the primary operating standard in child and family law and its ‘deepening hold in domestic and international instruments’, the meaning of the ‘best interests of the child’ principle has been criticised as open-ended and vague. This paper explores the evolution and development of the principle in the context of parental separation at international law throughout the 21st century and identifies opportunities for the Nation States to further improve legislative responses in associated child protection cases. An extensive review of relevant United Nations documentation (including instruments, resolutions and comments, jurisprudence, reports, guidelines and policies, training materials and so forth) explores: (i) what progress has been made to further develop the principle at the international level with regard to parental separation; and (ii) what developments participating the Nation States should consider as part of future legal and social policy reforms in this space. It will highlight opportunities for improvement and explore the benefit and relevance of international approaches for the Nation States moving forward.

Keywords: international human rights, best interests of the child, legal and social policy, child rights

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Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

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Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

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Authors: Eduwin Eko Franjaya, Andi Gunawan, Wahju Qamara Mugnisjah

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Sustainable agriculture in the form of integrated farming with its LEISA (Low External Input Sustainable Agriculture) concept has brought a positive impact on agriculture development and ambient amelioration. But, most of the small farmers in Indonesia did not know how to put the concept of it and how to combine agricultural commodities on the site effectively and efficiently. This research has an aim to promote integrated farming (agrofisheries, etc) to the farmers by designing the agricultural landscape to become integrated farming landscape as medium of education for the farmers. The method used in this research is closely related with the rule of design in the landscape architecture science. The first step is inventarization for the existing condition on the research site. The second step is analysis. Then, the third step is concept-making that consists of base concept, design concept, and developing concept. The base concept used in this research is sustainable agriculture with LEISA. The concept design is related with activity base on site. The developing concept consists of space concept, circulation, vegetation and commodity, production system, etc. The fourth step as the final step is planning and design. This step produces site plan of integrated farming based on LEISA. The result of this research is site plan of integrated farming with its explanation, including the energy flow of integrated farming system on site and the production calendar of integrated farming commodities for education and agri-tourism opportunity. This research become the right way to promote the integrated farming and also as a medium for the farmers to learn and to develop it.

Keywords: integrated farming, LEISA, planning and design, site plan

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Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das

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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.

Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear

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Authors: Maria M. Giannakou, Athanasios K. Ziliaskopoulos

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Transmission pipelines carrying natural gas are often routed through populated cities, industrial and environmentally sensitive areas. While the need for these networks is unquestionable, there are serious concerns about the risk these lifeline networks pose to the people, to their habitat and to the critical infrastructures, especially in view of natural disasters such as earthquakes. This work presents an Integrated Pipeline Risk Management methodology (IPRM) for assessing the hazard associated with a natural gas pipeline failure due to natural or manmade disasters. IPRM aims to optimize the allocation of the available resources to countermeasures in order to minimize the impacts of pipeline failure to humans, the environment, the infrastructure and the economic activity. A proposed knapsack mathematical programming formulation is introduced that optimally selects the proper mitigation policies based on the estimated cost – benefit ratios. The proposed model is demonstrated with a small numerical example. The vulnerability analysis of these pipelines and the quantification of consequences from such failures can be useful for natural gas industries on deciding which mitigation measures to implement on the existing pipeline networks with the minimum cost in an acceptable level of hazard.

Keywords: cost benefit analysis, knapsack problem, natural gas distribution network, risk management, risk mitigation

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Authors: Giovanni Menichini, Salvatore Giacomo Morano, Gloria Terenzi, Luca Salvatori, Maurizio Orlando

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The “Guidelines for Risk Classification, Safety Assessment, and Structural Health Monitoring of Existing Bridges” were recently approved by the Italian Government to define technical standards for managing the national network of existing bridges. These guidelines provide a framework for risk mitigation and safety assessment of bridges, which are essential elements of the built environment and form the basis for the operation of transport systems. Within the guideline framework, a workflow based on three main points was proposed: (1) risk-based, i.e., based on typical parameters of hazard, vulnerability, and exposure; (2) multi-level, i.e., including six assessment levels of increasing complexity; and (3) multirisk, i.e., assessing structural/foundational, seismic, hydrological, and landslide risks. The paper focuses on applying the Italian Guidelines to specific case studies, aiming to identify the parameters that predominantly influence the determination of the “class of attention”. The significance of each parameter is determined via sensitivity analysis. Additionally, recommendations for enhancing the process of assigning the class of attention are proposed.

Keywords: bridge safety assessment, Italian guidelines implementation, risk classification, structural health monitoring

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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

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

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Authors: Pijush Roy, Vinay Kumar Rai

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The present study highlights the estimation of soil loss and identification of critical area for implementation of best management practice is central to the success of soil conservation programme. The quantification of morphometric and Universal Soil Loss Equation (USLE) factors using remote sensing and GIS for prioritization of micro-watersheds in Asan River catchment, western Doon valley at foothills of Siwalik ranges in the Dehradun districts of Uttarakhand, India. The watershed has classified as a dendritic pattern with sixth order stream. The area is classified into very high, high, moderately high, medium and low susceptibility zones. High to very high erosion zone exists in the urban area and agricultural land. Average annual soil loss of 64 tons/ha/year has been estimated for the watershed. The optimum management practices proposed for micro-watersheds of Asan River basin are; afforestation, contour bunding suitable sites for water harvesting structure as check dam and soil conservation, agronomical measure and bench terrace.

Keywords: erosion susceptibility zones, morphometric characteristics, prioritization, remote sensing and GIS, universal soil loss equation

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Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin

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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.

Keywords: finger movement, neural activity, blind decoding, M1

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Ali Alattabi, Clare Harris, Rafid Alkhaddar, Ali Alzeyadi

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Petroleum refinery wastewater (PRW) can be considered as one of the most significant source of aquatic environmental pollution. It consists of oil and grease along with many other toxic organic pollutants. In recent years, a new technique was implemented using different types of membranes and sequencing batch reactors (SBRs) to treat PRW. SBR is a fill and draw type sludge system which operates in time instead of space. Many researchers have optimised SBRs’ operating conditions to obtain maximum removal of undesired wastewater pollutants. It has gained more importance mainly because of its essential flexibility in cycle time. It can handle shock loads, requires less area for operation and easy to operate. However, bulking sludge or discharging floating or settled sludge during the draw or decant phase with some SBR configurations are still one of the problems of SBR system. The main aim of this study is to develop and innovative design for the SBR optimising the process variables to result is a more robust and efficient process. Several experimental tests will be developed to determine the removal percentages of chemical oxygen demand (COD), Phenol and nitrogen compounds from synthetic PRW. Furthermore, the dissolved oxygen (DO), pH and oxidation-reduction potential (ORP) of the SBR system will be monitored online to ensure a good environment for the microorganisms to biodegrade the organic matter effectively.

Keywords: petroleum refinery wastewater, sequencing batch reactor, hydraulic retention time, Phenol, COD, mixed liquor suspended solids (MLSS)

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Authors: R. Granger-Ellis, R. B. Speaker, Jr., P. J. Austin

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This research study examined more than 340 gifted and talented students enrolled in various gifted and talented programs in a large southeastern United States metropolitan area (creative arts, urban charters, suburban public schools) for socio-affective psychological development and whether a particular curriculum encouraged developmental growth. This study focused on students receiving distinctive gifted and talented curricula (creative arts, arts-integrated, and academic acceleration) and analyzed for (1) socio-affective development levels and (2) whether a particular curriculum encouraged developmental growth. Research questions guiding the study: (1) How do academically and artistically gifted 10th and 11th grade students perform on psychological scales of social and emotional intelligence? (2) Do adolescents receiving distinctive gifted and talented curriculum differ in their socio-affective developmental profiles? Students’ performances on psychometric scales were compared over time and by curriculum type. Over the first semester of the academic year, participants took pre- and post-tests assessing socio-affective intelligence (BarOn EQ-I: YV). Differences in growth on these psychological scales (individuals and programs) were examined. Program artifacts provided insight for curriculum correlation.

Keywords: gifted and talented curriculum, social and emotional development, moral development, socio-affective curriculum

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Authors: Satyasen Panda, Urmila Bhanja

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In this paper, we have presented and analyzed three-dimensional (3-D) matrices of wavelength/time/space code for optical code division multiple access (OCDMA) networks with NAND subtraction detection technique. The 3-D codes are constructed by integrating a two-dimensional modified quadratic congruence (MQC) code with one-dimensional modified prime (MP) code. The respective encoders and decoders were designed using fiber Bragg gratings and optical delay lines to minimize the bit error rate (BER). The performance analysis of the 3D-OCDMA system is based on measurement of signal to noise ratio (SNR), BER and eye diagram for a different number of simultaneous users. Also, in the analysis, various types of noises and multiple access interference (MAI) effects were considered. The results obtained with NAND detection technique were compared with those obtained with OR and AND subtraction techniques. The comparison results proved that the NAND detection technique with 3-D MQC\MP code can accommodate more number of simultaneous users for longer distances of fiber with minimum BER as compared to OR and AND subtraction techniques. The received optical power is also measured at various levels of BER to analyze the effect of attenuation.

Keywords: Cross Correlation (CC), Three dimensional Optical Code Division Multiple Access (3-D OCDMA), Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA), Multiple Access Interference (MAI), Phase Induced Intensity Noise (PIIN), Three Dimensional Modified Quadratic Congruence/Modified Prime (3-D MQC/MP) code

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Authors: Bakr Gomaa, Hana Awad

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A stuffy room is one of the indicators of poor indoor air quality. Through working in an educational building in Alexandria, it is noticed that one of the rooms is smelly. A field study is conducted in a private university building in Alexandria to achieve indoor sustainable educational environment. Additionally, the indoor air quality is empirically assessed, and thermal comfort is identified in educational buildings, in studio halls specifically during lecture hours. The current research uses qualitative and quantitative methods in the form of literature review, investigation and test measurements. At a similar time that the teachers and students fill in a questionnaire regarding the concept of indoor climate, thermal comfort variables are determined. The indoor thermal conditions of the studio are assessed through three variables including Fanger’s comfort indicators (calculated using PMV, predicted mean vote and PPD, predicted percentage of dissatisfied people), the actual people clothing and metabolic rate. Actual measurements of air quality are obtained in a case study in an architectural building. Results have proved that indoor climatic conditions as air flow and temperature are inconvenient to inhabitants. Regarding questionnaire results, occupants appear to be uncomfortable in both seasons, with result percentages out of the acceptable range. Finally, further researches will center on how to preserve thermal comfort in school buildings since it has a vital influence on the student’s knowledge.

Keywords: educational buildings, Indoor air quality, productivity, thermal comfort

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Carlos Alberto Ríos-Reyes, Efraín Casadiego-Quintero

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We propose a generalized workflow for mineralogy investigation of unconventional reservoirs using multi-scale imaging and pore-scale analyses. This workflow can be used for the integral evaluation of these resources. The Cretaceous La Luna Formation´s mudstones in the Middle Magdalena Valley Basin (Colombia) inherently show a heterogeneous pore system with organic and inorganic pores. For this reason, it is necessary to carry out the integration of high resolution 2D images of mapping by conventional petrography, scanning electron microscopy and quantitative evaluation of minerals by scanning electron microscopy to describe their organic and inorganic porosity to understand the transport mechanism through pores. The analyzed rocks show several pore types, including interparticle pores, organoporosity, intraparticle pores, intraparticle pores, and microchannels and/or microfractures. The existence of interconnected pores in pore system of these rocks promotes effective pathways for primary gas migration and storage space for residual hydrocarbons in mudstones, which is very useful in this type of gas reservoirs. It is crucial to understand not only the porous system of these rocks and their mineralogy but also to project the gas flow in order to design the appropriate strategies for the stimulation of unconventional reservoirs. Keywords: mudstones; La Luna Formation; gas storage; migration; hydrocarbon.

Keywords: mudstones, La luna formation, gas storage, migration, hydrocarbon

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Authors: Tingkai Zhao, Jingtian Hu, Xiarong Peng, Wenbo Yang, Tiehu Li

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Homogeneous amorphous carbon nanotube (ACNT) networks have been synthesized using floating catalyst chemical vapor deposition method on a three-dimensional (3D) graphene aerogel (GA)/BaFe₁₂O₁₉ nanorod (BNR) composite which prepared by a self-propagating combustion process. The as-synthesized ACNT/GA/BNR composite which has 3D network structures could be directly used as a good absorber in the electromagnetic wave absorbent materials. The experimental results indicated that the maximum absorbing peak of ACNT/GA/BNR composite with a thickness of 2 mm was -18.35 dB at 10.64 GHz in the frequency range of 2-18 GHz. The bandwidth of the reflectivity below -10 dB is 3.32 GHz. The 3D graphene aerogel structures which composed of dense interlined tubes and amorphous structure of ACNTs bearing quantities of dihedral angles could consume the incident waves through multiple reflection and scattering inside the 3D web structures. The interlinked ACNTs have both the virtues of amorphous CNTs (multiple reflections inside the wall) and crystalline CNTs (high conductivity), consuming the electromagnetic wave as resistance heat. ACNT/GA/BNR composite has a good electromagnetic wave absorbing performance.

Keywords: amorphous carbon nanotubes, graphene aerogel, barium ferrite nanorod, electromagnetic wave absorption

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Authors: Keivan Jmahidi, Afshin Zahedi

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To evaluate neurotoxic effects of ACR on hypothalamus of rat, amino-cupric silver staining technique of de Olmos and electron microscopic examination were conducted. For this purpose 60 adult male Wistar rats (± 250 g) were selected. Randomly assigned groups of rats (10 rats per exposure group, as A, B, C, D, E) were exposed to 0.5, 5, 50, 100 and 500 mg/kg per day×11days i.p. respectively. The remaining 10 rats were housed in group F as control group. Control rats received daily i.p. injections of 0.9% saline (3ml/kg). As indices of developing neurotoxicity, daily weight gain, gait scores and landing hindlimb foot splay (LHF) were determined. After 11 days, two rats for silver stain, and two rats for EM, were randomly selected, dissected and proper samples were collected from hypothalamus. Rats in groups D and E died within 1-2 hours due to sever toxemia. In histopathological studies no argyrophilic neurons or processes were observed in stained sections obtained from hypothalamus of rats belong to groups A, B and F, while moderate to severe argyrophilic changes were observed in different nuclei and regions of stained sections obtained from hypothalamus of rats belong to group C. In ultrastructural studies some variations in the myelin sheet of injured axons including decompactation, interlaminar space formation, disruption of the laminar sheet, accumulation of neurofilaments, vacculation and clumping inside the axolem, and finaly complete disappearance of laminar sheet were observed.

Keywords: acrylamide (ACR), amino-cupric silver staining technique of de Olmos, argyrophilia, hypothalamic neuropathy

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Authors: Mehdi Damaliamiri, Firouzeh Akbari

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Teaching literature to children at an early age is of great importance, and there have been different methods to facilitate learning literature. Based on the law, all children going to school in Iran should learn the Persian language and literature. This has been concomitant with two different levels of learning related to urban or rural bilingualism. For bilingual children living in the villages, learning literature and a new language (Persian) turns into a big challenge as it is done based on the translation the teacher does while in the city, it is easier as the confrontation of children with the Persian language is more. Over recent years, to change the trend of learning Persian by children speaking another language, the TV and radio programs have been considered to be effective, but the scores of the students in Persian language national exams show that these programs have not been so effective for the bilingual students living in the villages. To identify the determinants of weak learning of Persian by bilingual children, two different regions were chosen, Turkish-speaking and Kurdish-speaking communities, to compare their learning of Persian at the first and second levels of elementary school. The criteria of learning was based on the syllabification of Persian words, word order in the sentence, and compound sentences. Students were taught in Persian how to recognize syllabification without letting them translate the words in their own languages and were asked to produce simple sentences in Persian in response to situational questions. Teaching methods, language relatedness with Persian, and exposure to social media programs, especially TV and radio, were the factors that were considered to affect the potential of children in learning Persian.

Keywords: bilingualism, persian, education, Literature

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Authors: Mahmoud Fouad, Mervat Badr, Marwa Ibrahim

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Micro-grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. Renewable power sources such as wind, solar and hydro offer high potential of benign power for future micro-grid systems. Micro-Grid (MG) is basically a low voltage (LV) or medium voltage (MV) distribution network which consists of a number of called distributed generators (DG’s); micro-sources such as photovoltaic array, fuel cell, wind turbine etc. energy storage systems and loads; operating as a single controllable system, that could be operated in both grid-connected and islanded mode. The capacity of the DG’s is sufficient to support all; or most, of the load connected to the micro-grid. This paper presents a micro-grid system based on wind and solar power sources and addresses issues related to operation, control, and stability of the system. Using Matlab/Simulink, the system is modeled and simulated to identify the relevant technical issues involved in the operation of a micro-grid system based on renewable power generation units.

Keywords: micro-grid system, photovoltaic, wind turbine, energy storage, distributed generation, modeling

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Peter J. Glinos

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The Alternative Education Resource Organization (AERO), one of the largest international hubs for alternative educators led by Jerry Mintz, has had a major impact on the global alternative education movement. The organization’s publications, like the AERO-Gramme Newsletter and its successor, the Education Revolution Magazine, allowed members across the globe to discuss issues, share support, and submit writings on policies and reforms. Stored on AERO's online digital archive, this work uses these publications from 1989 to 2011 to investigate the network's entanglements with America, Canada, Russia, Ukraine, Israel, Palestine, Japan, India, and Guatemala. Inspired by Reinhart Koselleck, this historical analysis will trace AERO’s entanglements within the United States, Japan, and Russia, contextualizing each of these multiple temporalities within the history of each nation’s education system, the developments within AERO, and the global geo-political climate at the time of AERO’s expansion. To help remedy the lack of attention paid by global historians to the role state organizations play supporting global networks, as noted in What is Global History? by Sebastian Conrad, this work will focus on the relationship between AERO and state actors.

Keywords: global history, history of education, neoliberalism, transnational history, alternative education

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Authors: Evan Hajani, Ataur Rahman, Khaled Haddad

Abstract:

Climate change will affect the hydrological cycle in many different ways such as increase in evaporation and rainfalls. There have been growing interests among researchers to identify the nature of trends in historical rainfall data in many different parts of the world. This paper examines the trends in annual maximum rainfall data from 30 stations in New South Wales, Australia by using two non-parametric tests, Mann-Kendall (MK) and Spearman’s Rho (SR). Rainfall data were analyzed for fifteen different durations ranging from 6 min to 3 days. It is found that the sub-hourly durations (6, 12, 18, 24, 30, and 48 minutes) show statistically significant positive (upward) trends whereas longer duration (sub-daily and daily) events generally show a statistically significant negative (downward) trend. It is also found that the MK test and SR test provide notably different results for some rainfall event durations considered in this study. Since shorter duration sub-hourly rainfall events show positive trends at many stations, the design rainfall data based on stationary frequency analysis for these durations need to be adjusted to account for the impact of climate change. These shorter durations are more relevant to many urban development projects based on smaller catchments having a much shorter response time.

Keywords: climate change, Mann-Kendall test, Spearman’s Rho test, trends, design rainfall

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Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

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With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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