Search results for: global matrix method

Authors: Adesola O. Orimoloye, Edward Gobina

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Membrane separation technology is still considered as an emerging technology in the mining sector and does not yet have the widespread acceptance that it has in other industrial sectors. Underground Coal Gasification (UCG), wherein coal is converted to gas in-situ, is a safer alternative to mining method that retains all pollutants underground making the process environmentally friendly. In-situ combustion of coal for power generation allows access to more of the physical global coal resource than would be included in current economically recoverable reserve estimates. Where mining is no longer taking place, for economic or geological reasons, controlled gasification permits exploitation of the deposit (again a reaction of coal to form a synthesis gas) of coal seams in situ. The oxygen supply stage is one of the most expensive parts of any gasification project but the use of membranes is a potentially attractive approach for producing oxygen-enriched air. In this study, a variety of cost-effective membrane materials that gives an optimal amount of oxygen concentrations in the range of interest was designed and tested at diverse operating conditions. Oxygen-enriched atmosphere improves the combustion temperature but a decline is observed if oxygen concentration exceeds optimum. Experimental result also reveals the preparatory method, apparatus and performance of the fabricated membrane.

Keywords: membranes, oxygen-enrichment, gasification, coal

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Authors: Lin Huo, Xianwei Liu, Jingxiong Zhou

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Recently, due to the existence of semantic gap between image visual features and human concepts, the semantic of image auto-annotation has become an important topic. Firstly, by extract low-level visual features of the image, and the corresponding Hash method, mapping the feature into the corresponding Hash coding, eventually, transformed that into a group of binary string and store it, image auto-annotation by search is a popular method, we can use it to design and implement a method of image semantic auto-annotation. Finally, Through the test based on the Corel image set, and the results show that, this method is effective.

Keywords: image auto-annotation, color correlograms, Hash code, image retrieval

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Authors: Vahid Bairami Rad, Shapoor Norazar, Moslem Talebi Asl

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The fast growing accessibility and capability of emerging technologies have fashioned enormous possibilities of designing, developing and implementing innovative teaching methods in the classroom. Using teaching methods and technology together have a fantastic results, because the global technological scenario has paved the way to new pedagogies in teaching-learning process. At the other side methods by focusing on students and the ways of learning in them, that can demonstrate logical ways of improving student achievement in English as a foreign language in Iran. The sample of study was 90 students of 10th grade of high school located in Ardebil. A pretest-posttest equivalent group designed to compare the achievement of groups. Students divided to 3 group, Control base, computer base, method and technology base. Pretest and post test contain 30 items each from English textbook were developed and administrated, then obtained data were analyzed. The results showed that there was an important difference. The 3rd group performance was better than other groups. On the basis of this result it was obviously counseled that teaching-learning capabilities.

Keywords: method, technology based environment, computer based environment, english as a foreign language, student achievement

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Authors: Emmanuel Iyamuremye, Edouard Singirankabo, Alexis Habineza, Yunvirusaba Nelson

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Temperature is one of the most important climatic factors for crop production. However, severe temperatures cause drought, feverish and cold spells that have various consequences for human life, agriculture, and the environment in general. It is necessary to provide reliable information related to the incidents and the probability of such extreme events occurring. In the 21st century, the world faces a huge number of threats, especially from climate change, due to global warming and environmental degradation. The rise in temperature has a direct effect on the decrease in rainfall. This has an impact on crop growth and development, which in turn decreases crop yield and quality. Countries that are heavily dependent on agriculture use to suffer a lot and need to take preventive steps to overcome these challenges. The main objective of this study is to model the statistical behaviour of extreme maximum temperature values in Rwanda. To achieve such an objective, the daily temperature data spanned the period from January 2000 to December 2017 recorded at nine weather stations collected from the Rwanda Meteorological Agency were used. The two methods, namely the block maxima (BM) method and the Peaks Over Threshold (POT), were applied to model and analyse extreme temperature. Model parameters were estimated, while the extreme temperature return periods and confidence intervals were predicted. The model fit suggests Gumbel and Beta distributions to be the most appropriate models for the annual maximum of daily temperature. The results show that the temperature will continue to increase, as shown by estimated return levels.

Keywords: climate change, global warming, extreme value theory, rwanda, temperature, generalised extreme value distribution, generalised pareto distribution

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Authors: Chun-Yuan Chen, Ming-Chang Li, Xiu-Hui Wen, Yi-Ching Tu

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The objective of this study explores GPS (Global Positioning System) applied to trace construction vehicles such as trucks or cranes, help to pattern the earth-dumping stations of traffic construction in Taiwan. Traffic construction in this research is defined as the engineering of high-speed railways, expressways, and which that distance more than kilometers. Audit the location and check the compliance with regulations of earth-dumping stations is one of important tasks in Taiwan EPA. Basically, the earth-dumping station was known as one source of particulate matter from air pollution during construction process. Due to GPS data can be analyzed quickly and be used conveniently, this study tried to find out dumping stations by modeling vehicles tracks from GPS data during work cycle of construction. The GPS data updated from 13 vehicles related to an expressway construction in central Taiwan. The GPS footprints were retrieved to Keyhole Markup Language (KML) files so that can pattern the tracks of trucks by computer applications, the data was collected about eight months- from Feb. to Oct. in 2017. The results of GPS footprints identified dumping station and outlined the areas of earthwork had been passed to the Taiwan EPA for on-site inspection. Taiwan EPA had issued advice comments to the agency which was in charge of the construction to prevent the air pollution. According to the result of this study compared to the commonly methods in inspecting environment by manual collection, the GPS with KML patterning and modeling method can consumes less time. On the other hand, through monitoring the GPS data from construction vehicles could be useful for administration to development and implementation of strategies in environmental management.

Keywords: automatic management, earth-dumping station, environmental management, Global Positioning System (GPS), particulate matter, traffic construction

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Authors: Gregory E. Ofili

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Introduction and Objective: Climate change and a global economy mean farmers must adapt and gain access to affordable and reliable automation technologies. Key barriers include a lack of transportation, electricity, and internet service, coupled with costly enabling technologies and limited local subject matter expertise. Methodology/Approach: Resourcefulness is essential to mechanization on a farm. This runs contrary to the tech industry practice of planned obsolescence and disposal. One solution is plug-and-play hardware that allows farmer to assemble, repair, program, and service their own fleet of industrial machines. To that end, we developed a method of manufacturing low-cost utility robots, transport vehicles, and solar/wind energy harvesting systems, all running on an open-source Robot Operating System (ROS). We demonstrate this technology by fabricating a utility robot and an all-terrain (4X4) utility vehicle. Constructed of aluminum trusses and weighing just 40 pounds, yet capable of transporting 200 pounds of cargo, on sale for less than $2,000. Conclusions & Policy Implications: Electricity, internet, and automation are essential for productivity and competitiveness. With planned obsolescence, the priorities of technology suppliers are not aligned with the farmer’s realities. This patent-pending method of manufacturing low-cost industrial robots and electric vehicles has met its objective. To create low-cost machines, the farmer can assemble, program, and repair with basic hand tools.

Keywords: automation, robotics, utility robot, small-hold farm, robot operating system

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Authors: Karun K. Karki

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Globalization has intensified the transnational movement of people, mainly from the Global South to the Global North. In this context of transnationalism, migration is framed within the national interests required for economic prosperity. More specifically, the competition for the ‘best and the brightest of highly educated immigrants from around the world can be perceived as evidence that countries in the North are competing in the knowledge-based global economy. Canada is not an exception. Since the early 1970s, Canada has successfully admitted, on average, 200,000 to 280,000 immigrants annually for permanent residency, primarily for economic development, family reunification and humanitarian affairs. Among these three components, economic class immigrants are the highest priority in its immigration policy. Although Canada admits highly qualified immigrant professionals with the expectation of easily integrating them, many highly skilled immigrants are marginalized in the labour market due to a myriad of layered structural and institutional barriers that prevent them from working in the professions for which they were trained in their country of origin. More than 67% of highly skilled immigrants are more likely to be in jobs for which they are formally overqualified. The deteriorating employment situation of highly educated immigrants, particularly the immigrants of racialized groups, needs analytical scrutiny of the immigration policy of Canada. In this paper, author examine how the historical legacy of colonialism still continues in Canada’s immigration policymaking and how this legacy has impacted developing countries in the global South. Author argue that the Canadian immigration policy is based on the notion of exploiting/dominating smaller countries and immigrants from these countries. Such colonial policies have systematically ‘Othered’ immigrants based on their race, ethnicity, gender, culture, and linguistic characteristics. Recommendations are made to revisit contemporary immigration and settlement policies to effectively integrate immigrants into Canadian society.

Keywords: colonialism, Canadian immigration policy, racialized immigrants, skilled immigrants

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Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Anton A. Larenkov, Alesya Ya Maruk

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In the present study, highly effective iTLC single strip method for the determination of radiochemical purity (RCP) of ⁶⁸Ga-BCA-peptides was developed (with no double-developing, changing of eluents or other additional manipulation). In this method iTLC-SG strips and commonly used eluent TFA_aq. (3-5 % (v/v)) are used. The method allows determining each of the key radiochemical forms of ⁶⁸Ga (colloidal, bound, ionic) separately with the peaks separation being no less than 4 σ. Rf = 0.0-0.1 for ⁶⁸Ga-colloid; Rf = 0.5-0.6 for ⁶⁸Ga-BCA-peptides; Rf = 0.9-1.0 for ionic ⁶⁸Ga. The method is simple and fast: For developing length of 75 mm only 4-6 min is required (versus 18-20 min for pharmacopoeial method). The method has been tested on various compounds (including ⁶⁸Ga-DOTA-TOC, ⁶⁸Ga-DOTA-TATE, ⁶⁸Ga-NODAGA-RGD₂ etc.). The cross-validation work for every specific form of ⁶⁸Ga showed good correlation between method developed and control (pharmacopoeial) methods. The method can become convenient and much more informative replacement for pharmacopoeial methods, including HPLC.

Keywords: DOTA-TATE, 68Ga, quality control, radiochemical purity, radiopharmaceuticals, TLC

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Authors: Palwinder Singh, Munish Sandhir, Tejinder Singh

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The ordinary differential equations (ODE) represent a natural framework for mathematical modeling of many real-life situations in the field of engineering, control systems, physics, chemistry and astronomy etc. Such type of differential equations can be solved by analytical methods or by numerical methods. If the solution is calculated using analytical methods, it is done through calculus theories, and thus requires a longer time to solve. In this paper, we compare the numerical accuracy of the solutions given by the three main types of one-step initial value solvers: Taylor’s Series Method, Euler’s Method and Runge-Kutta Fourth Order Method (RK4). The comparison of accuracy is obtained through comparing the solutions of ordinary differential equation given by these three methods. Furthermore, to verify the accuracy; we compare these numerical solutions with the exact solutions.

Keywords: Ordinary differential equations (ODE), Taylor’s Series Method, Euler’s Method, Runge-Kutta Fourth Order Method

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Authors: Mai Nguyen-Phuong-Mai

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This paper incorporates insight from various models, studies and disciplines to construct a framework called the Inverted Pyramid Model. It is argued that such a framework has several advantages: (1) it reduces the shortcomings of the problem-focused approach that dominates the mainstream theories of cross-cultural management. With contributing insight from neuroscience, it suggests that training in business cross-cultural awareness should start with potential synergy emerged from differences instead of the traditional approach that focuses on the liability of foreigners and negative consequences of cultural distance. (2) The framework supports a dynamic and holistic way of analyzing cultural diversity by analyzing four major cultural units (global, national, organizational and group culture). (3) The framework emphasizes the role of individuals –an aspect of culture that is often ignored or regarded as a non-issue in the traditional approach. It is based on the notion that people don’t do business with a country, but work (in)directly with a unique person. And it is at this individual level that culture is made, personally, dynamically, and contextually. Insight from neuroscience provides significant evidence that a person can develop a multicultural mind, confirm and contradict, follow and reshape a culture, even when (s)he was previously an outsider to this culture. With this insight, the paper proposes a revision of the old adage (Think global – Act local) and change it into Think global – Plan local – Act individual.

Keywords: static–dynamic paradigm, cultural diversity, multicultural mind, neuroscience

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Authors: Ralf Gliniorz, Carolin Petzoldt, Andreas Ehrlich, Sandra Gelbrich, Lothar Kroll

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The building envelope is integral part of buildings, and renewable resources have a key role in energy consumption. So our aim was the development and implementation of a free forming facade system, consisting of fibre-reinforced polymer, which is built up of commercial biobased resin systems and natural fibre reinforcement. The field of application is aimed in modern architecture, like the office block 'Fachagentur Nachwachsende Rohstoffe e.V.' with its oak wood recyclate facade. The build-up of our elements is a classically sandwich-structured composite: face sheets as fibre-reinforced composite using polymer matrix, here a biobased epoxy, and natural fibres. The biobased core consists of stuck cardboard structure (BC-flute). Each element is manufactured from two shells in a counterpart, via hand lay-up laminate. These natural fibre skins and cardboard core have adhered 'wet-on-wet'. As a result, you get the effect of translucent face sheets with matrix illumination. Each created pixel can be controlled in RGB-colours and form together a screen at buildings. A 10 x 5 m² area 'NFP-BIO' with 25 elements is planned as a reference object in Chemnitz. The resolution is about 100 x 50 pixels. Specials are also the efficient technology of production and the possibility to extensively 3D-formed elements for buildings, replacing customary facade systems, which can give out information or advertising.

Keywords: biobased facade, cardboard core, natural fibre skins, sandwich element

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Robert Long, Hiroaki Watanabe

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This longitudinal study examines the grammatical errors of Japanese university students’ dialogues with a native speaker over an academic year. The L2 interactions of 15 Japanese speakers were taken from the JUSFC2018 corpus (April/May 2018) and the JUSFC2019 corpus (January/February). The corpora were based on a self-introduction monologue and a three-question dialogue; however, this study examines the grammatical accuracy found in the dialogues. Research questions focused on a possible significant difference in grammatical accuracy from the first interview session in 2018 and the second one the following year, specifically regarding errors in clauses per 100 words, global errors and local errors, and with specific errors related to parts of speech. The investigation also focused on which forms showed the least improvement or had worsened? Descriptive statistics showed that error-free clauses/errors per 100 words decreased slightly while clauses with errors/100 words increased by one clause. Global errors showed a significant decline, while local errors increased from 97 to 158 errors. For errors related to parts of speech, a t-test confirmed there was a significant difference between the two speech corpora with more error frequency occurring in the 2019 corpus. This data highlights the difficulty in having students self-edit themselves.

Keywords: clause analysis, global vs. local errors, grammatical accuracy, L2 output, longitudinal study

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Authors: Mukesh Lal Das, Muthukumar Muthuchamy

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Climate change Adaptation strategy (AS) is a scientific approach to dealing with the impacts of climate change (CC). Efforts are being made to contain the global emission of greenhouse gas within threshold limits, thereby limiting the rise of global temperature to an optimal level. Global Climate change is a spontaneous process; therefore, reversing the damage would take decades. The climate change adaptation strategy recommended by various stakeholders could be a key to resilience for biodiversity. The Indian Government has constituted the panel to synthesize the climate change action report at the federal and state levels. This review scavenged the published literature on the Western Ghats hotspots. And highlight the adaptation strategy recommended by diverse scientific actors to conserve biodiversity. It also reviews the grey literature adopted by state and federal governments and its effectiveness in mitigating the impacts on biodiversity. We have narrowed the scope of interest to the state action report by 6 Indian states such as Gujarat, Maharashtra, Goa, Karnataka, Kerala and Tamil Nadu, which host Western Ghats global biodiversity hotspot. Western Ghats(WGs) act as the water tower to the peninsular part of India, and its extensive watershed caters to the water demand of the Industry sector, Agriculture and urban community. Conservation of WGs is the key to the prosperity of Peninsular India. The global scientific community suggested more than 600+ Climate change adaptation strategies for the policymakers, stakeholders, and other state actors to take proactive actions. The preliminary analysis of the federal and the state action plan on climate change in the wake of CC indicate inadequacy in motion as per recommended scientific adaptation strategies. Tamil Nadu and Kerala state constitute nine effective adaptation strategies out of the 40+ recommended for Western Ghats conservation. And other four states' adaptation strategies are deficient, confusing and vague. Western Ghats' resilience capacity will soon or might have reached its threshold, and the frequency of severe drought and flash floods might upsurge manifold in the decades to come. The lack of a clear roadmap to climate change adaptation strategies in the federal and state action stirred us to identify the gap and address it by offering a holistic approach to WGs biodiversity conservation.

Keywords: adaptation strategy, biodiversity conservation, climate change, resilience, Western Ghats

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Authors: Nadia E. Christiana, Azzahra A. N. Ginting, Ardhito Nurcahya, Havisa P. Novira

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One of the quickest ways to do a short trip in urban areas is by walking, either individually, in couple or groups. Walkability nowadays becomes one of the parameters to measure the quality of an urban neighborhood. As a Central Business District and public transport transit hub, Dukuh Atas area becomes one of the highest numbers of commuters that pass by the area and interchange between transportation modes daily. Thus, as a public transport hub, a lot of investment should be focused to speed up the development of the area that would support urban transit activity between transportation modes, one of them is revitalizing pedestrian walkways. The purpose of this research is to formulate the visual design concept of 'Walkable City' based on the results of the observation and a series of rankings. To achieve this objective, it is necessary to accomplish several stages of the research that consists of (1) Identifying the system of pedestrian paths in Dukuh Atas area using descriptive qualitative method (2) Analyzing the sidewalk walkability rate according to the perception and the walkability satisfaction rate using the characteristics of pedestrians and non-pedestrians in Dukuh Atas area by using Global Walkability Index analysis and Multicriteria Satisfaction Analysis (3) Analyzing the factors that determine the integration of pedestrian walkways in Dukuh Atas area using descriptive qualitative method. The results achieved in this study is that the walkability level of Dukuh Atas corridor area is 44.45 where the value is included in the classification of 25-49, which is a bit of facility that can be reached by foot. Furthermore, based on the questionnaire, satisfaction rate of pedestrian walkway in Dukuh Atas area reached a number of 64%. It is concluded that commuters have not been fully satisfied with the condition of the sidewalk. Besides, the factors that influence the integration in Dukuh Atas area have been reasonable as it is supported by the utilization of land and modes such as KRL, Busway, and MRT. From the results of all analyzes conducted, the visual design and the application of the concept of walkable city along the pathway pedestrian corridor of Dukuh Atas area are formulated. Achievement of the results of this study amounted to 80% which needs to be done further review of the results of the analysis. The work of this research is expected to be a recommendation or input for the government in the development of pedestrian paths in maximizing the use of public transportation modes.

Keywords: design, global walkability index, mass rapid transit, walkable city

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Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song

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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.

Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera

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Authors: Johannes Keil, Eric Mischorr, Veit Würfel, Jan Condé-Wolter, Alexander Liebsch, Maik Gude

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In the aviation sector wastewater pipes are subjected to many different mechanical and medial loads. Worst-case scenarios include high-velocity impacts resulting from the introduction of foreign objects into the system. The industry is seeking to reduce the weight of these pipes, which are currently manufactured from titanium. A promising alternative is the use of fiber-reinforced polymers (FRP), specifically carbon fiber (CF) reinforced polyaryletherketone (PAEK) laminates. This study employs an experimental methodology to investigate the impact resistance of CF/PAEK laminates, with a particular focus on three configurations: crimp, non-crimp, and interleaved matrix rich films in cross-ply laminates. High-velocity impacts were performed using a gas gun resulting in three-dimensional damage patterns. Afterwards the damage behavior was qualitatively and quantitatively analyzed using ultrasonic scans and computed tomography (CT). Samples with an interleaved matrix-rich film led to a reduction of the damage area by around 40% compared to the non-interleaved, non-crimp samples, while the crimp architecture resulted in a reduction of more than 60%. Therefore, these findings contribute to understanding the influence of laminate architecture on impact resistance, paving the way for more efficient materials in aviation applications.

Keywords: fracture toughness, high-velocity-impact, textile architecture, thermoplastic composites

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Authors: Francky Fouedjio

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Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

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Authors: Kuo-Cheng Liu

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In the perceptual image coding, the objective is to shape the coding distortion such that the amplitude of distortion does not exceed the error visibility threshold, or to remove perceptually redundant signals from the image. While most researches focus on color image coding, the perceptual-based quantizer developed for luminance signals are always directly applied to chrominance signals such that the color image compression methods are inefficient. In this paper, the internal generative mechanism is integrated into the design of a color image compression method. The internal generative mechanism working model based on the structure-based spatial masking is used to assess the subjective distortion visibility thresholds that are visually consistent to human eyes better. The estimation method of structure-based distortion visibility thresholds for color components is further presented in a locally adaptive way to design quantization process in the wavelet color image compression scheme. Since the lowest subband coefficient matrix of images in the wavelet domain preserves the local property of images in the spatial domain, the error visibility threshold inherent in each coefficient of the lowest subband for each color component is estimated by using the proposed spatial error visibility threshold assessment. The threshold inherent in each coefficient of other subbands for each color component is then estimated in a local adaptive fashion based on the distortion energy allocation. By considering that the error visibility thresholds are estimated using predicting and reconstructed signals of the color image, the coding scheme incorporated with locally adaptive perceptual color quantizer does not require side information. Experimental results show that the entropies of three color components obtained by using proposed IGM-based color image compression scheme are lower than that obtained by using the existing color image compression method at perceptually lossless visual quality.

Keywords: internal generative mechanism, structure-based spatial masking, visibility threshold, wavelet domain

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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Authors: Benjamin Goldsmith, Felix Heisel

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The building industry must reduce its emissions in order to meet 2030 neutrality targets, and modular and/or offsite construction is seen as an alternative to conventional construction methods which could help achieve this goal. Modular construction has previously been shown to be less wasteful and has a lower global warming potential (GWP). While many studies have been conducted investigating the life cycle impacts of modular and conventional construction, few studies have compared different types of modular assembly and construction in order to determine which offer the greatest environmental benefits over their whole life cycle. This study seeks to investigate three different modular construction types -infill frame, core, and podium- in order to determine environmental impacts such as GWP as well as circularity indicators. The study will focus on the emissions of the production, construction, and end-of-life phases. The circularity of the various approaches will be taken into consideration in order to acknowledge the potential benefits of the ability to reuse and/or reclaim materials, products, and assemblies. The study will conduct hypothetical case studies for the three different modular construction types, and in doing so, control the parameters of location, climate, program, and client. By looking in-depth at the GWP of the beginning and end phases of various simulated modular buildings, it will be possible to make suggestions on which type of construction has the lowest global warming potential.

Keywords: modular construction, offsite construction, life cycle analysis, global warming potential, environmental impact, circular economy

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Authors: J. Shiue, I. H. Chen, S. W. Y. Chiu, Y. L. Wang

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In this work, we present a nondestructive method to characterize bacteria in a TEM system. Unlike the conventional TEM specimen preparation method, which needs to thin the specimen in a destructive way, or spread the samples on a tiny millimeter sized carbon grid, our method is easy to operate without the need of sample pretreatment. With a specially designed transparent chip that allows the electron beam to pass through, and a custom made chip holder to fit into a standard TEM sample holder, the bacteria specimen can be easily prepared on the chip without any pretreatment, and then be observed under TEM. The centimeter-sized chip is covered with Au nanoparticles in the surface as the markers which allow the bacteria to be observed easily on the chip. We demonstrate the success of our method by using E. coli as an example, and show that high-resolution TEM images of E. coli can be obtained with the method presented. Some E. coli morphology characteristics imaged using this method are also presented.

Keywords: bacteria, chip, nanoparticles, TEM

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Maria Jose Granero Paris, Ana Isabel Jimenez Zarco, Agustin Pablo Alvarez Herranz

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In the industrial sector the collaboration along the supply chain is key especially in order to develop product, production methods or process innovations. The access to resources and knowledge not being available inside the company, the achievement of cost competitive solutions, the reduction of the time required to innovate are some of the benefits linked with the collaboration with suppliers. The big industrial manufacturers have a long tradition to collaborate with their suppliers to develop new products in the developed countries. Since they have increased their global supply chains and global sourcing activities, the objective of the research is to analyse if the same best practices, way of working, experiences, information technology tools, governance methodologies are applied when collaborating with suppliers in the developed world or in developing countries. Most of the current research focuses to analyse the Supply Chain Collaboration in the developed countries and in recent years the number of publications related to the Supply Chain Collaboration in developing countries has increased, but there is still a lack of research comparing both and analysing the similarities, differences and key success factors among the Supply Chain Collaboration practices in developed and developing countries. With this gap in mind, the research under preparation will focus on the following goals: -Identify the most important elements required for a successful supply chain collaboration in the developed and developing countries. -Set up the optimal governance framework to manage the supply chain collaboration in the developed and developing countries. -Define some recommendations about required improvements in the current supply chain collaboration business relationship practices in place. Following the case methodology we will analyze the way manufacturers and suppliers collaborate in the development of new products, production methods or process innovations and in the set up of new global supply chains in two industries with different level of technology intensity and collaboration history being the automotive and aerospace industries.

Keywords: global supply chain networks, Supply Chain Collaboration, supply chain governance, supply chain performance

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Authors: S. Madhu, V. V. Subba Rao

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In the implementation of carbon nanotube reinforced polymer matrix composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using Classical Laminate Plate Theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.

Keywords: carbon nanotube, micromechanics, composite plate, multi-scale analysis, classical laminate plate theory

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Authors: Nana Kwasi Amoateng

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The paper uses secondary information to investigate some longstanding limitations in International Relations (IR) theory. Specifically, the analysis highlights IR theory through the lens of J. C. Sharman’s brilliant concept of outside-in state-building logic in which some states, particularly those in Africa, have relied mainly on foreign resources to address local threats. The key findings are that IR theory has been largely understood from the perspective of an inside-out state-building logic, whereby Western and other advanced states have heavily relied on local resources to address foreign threats. In this vein, IR theorists, including Critical Theorists, have not been able to fully grasp African states and states elsewhere that have generally relied on an outside-in logic of state-building. The paper helps to fill a major gap in IR theory, which has mainly addressed criticisms of being Euro- or Western-centric or failing to include the unique experiences of states and other actors in the Global South by developing critical theories such as post-colonial theory and neo-colonialism. Although this has helped to understand some experiences of actors in the Global South, the fundamental difference between state-building in the West and the Global South, particularly Africa, has not been adequately explored to fully comprehend why, despite the works of Critical Theorists, IR theory still fails to capture many political and socioeconomic realities in Africa and elsewhere.

Keywords: international relations theory, outside-in state-building logic, inside-out state-building logic, Africa

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Authors: Giancarlo La Marca, Engy Shokry, Fabio Villanelli

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Epilepsy is one of the most common neurological disorders, with an estimated prevalence of 50 million people worldwide. Twenty five percent of the epilepsy population is represented in children under the age of 15 years. For antiepileptic drugs (AED), there is a poor correlation between plasma concentration and dose especially in children. This was attributed to greater pharmacokinetic variability than adults. Hence, therapeutic drug monitoring (TDM) is recommended in controlling toxicity while drug exposure is maintained. Carbamazepine (CBZ) is a first-line AED and the drug of first choice in trigeminal neuralgia. CBZ is metabolised in the liver into carbamazepine-10,11-epoxide (CBZE), its major metabolite which is equipotent. This develops the need for an assay able to monitor the levels of both CBZ and CBZE. The aim of the present study was to develop and validate a LC-MS/MS method for simultaneous quantification of CBZ and CBZE in dried blood spots (DBS). DBS technique overcomes many logistical problems, ethical issues and technical challenges faced by classical plasma sampling. LC-MS/MS has been regarded as superior technique over immunoassays and HPLC/UV methods owing to its better specificity and sensitivity, lack of interference or matrix effects. Our method combines advantages of DBS technique and LC-MS/MS in clinical practice. The extraction process was done using methanol-water-formic acid (80:20:0.1, v/v/v). The chromatographic elution was achieved by using a linear gradient with a mobile phase consisting of acetonitrile-water-0.1% formic acid at a flow rate of 0.50 mL/min. The method was linear over the range 1-40 mg/L and 0.25-20 mg/L for CBZ and CBZE respectively. The limit of quantification was 1.00 mg/L and 0.25 mg/L for CBZ and CBZE, respectively. Intra-day and inter-day assay precisions were found to be less than 6.5% and 11.8%. An evaluation of DBS technique was performed, including effect of extraction solvent, spot homogeneity and stability in DBS. Results from a comparison with the plasma assay are also presented. The novelty of the present work lies in being the first to quantify CBZ and its metabolite from only one 3.2 mm DBS disc finger-prick sample (3.3-3.4 µl blood) by LC-MS/MS in a 10 min. chromatographic run.

Keywords: carbamazepine, carbamazepine-10, 11-epoxide, dried blood spots, LC-MS/MS, therapeutic drug monitoring

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Authors: Ratna Kuswardani

Abstract:

This paper aims to study the impact of recent Global Financial Crisis (GFC) on 6 selected emerging Asian economies (Indonesia, Malaysia, Thailand, Philippines, Singapore, and South Korea). We first figure out the contagion of GFC from the US and Europe to the selected emerging Asian countries by studying the tail dependence of market stock returns between those countries. We apply the concept of Extreme Value Theory (EVT) to model the dependence between multiple returns series of variables under examination. We explore the factors causing the contagion between the regions. We find dependencies between markets that are influenced by their size, especially for large markets in emerging Asian countries that tend to have a higher dependency to the market in the more advanced country such as the U.S. and some countries in Europe. The results also suggest that the dependencies between market returns and bank stock returns in the same region tend to be higher than dependencies between these returns across two different regions. We extend our analysis by studying the impact of GFC on the systemic in the banking system. We also find that larger institution has more dependencies with the market stock, suggesting that larger size bank can cause disruption in the market. Further, the higher probability of extreme loss can be seen during the crisis period, which is shown by the non-linear dependency between the pre-crisis and the post-crisis period. Finally, our analysis suggests that systemic risk appears in the domestic banking systems in emerging Asia, as shown by the extreme dependencies within banks in the system. Overall, our results provide caution to policy makers and investors alike on the possible contagion of the impact of global financial crisis across different markets.

Keywords: contagion, extreme value theory, global financial crisis, systemic risk

Procedia PDF Downloads 149