Search results for: temporal reasoning

Authors: H. Lee, J. Park

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In this present study, for the first time, we retrieved the Formaldehyde (HCHO) Vertical Column Density (HCHOVCD) using Pandora instruments in Seoul, a megacity in northeast Asia, for the period between 2012 and 2014 and investigated the temporal characteristics of HCHOVCD. HCHO Slant Column Density (HCHOSCD) was obtained using the Differential Optical Absorption Spectroscopy (DOAS) method. HCHOSCD was converted to HCHOVCD using geometric Air Mass Factor (AMFG) as Pandora is the direct-sun measurement. The HCHOVCDs is low at 12:00 Local Time (LT) and is high in the morning (10:00 LT) and late afternoon (16:00 LT) except for winter. The maximum (minimum) values of Pandora HCHOVCD are 2.68×1016 (1.63×10¹⁶), 3.19×10¹⁶ (2.23×10¹⁶), 2.00×10¹⁶ (1.26×10¹⁶), and 1.63×10¹⁶ (0.82×10¹⁶) molecules cm⁻² in spring, summer, autumn, and winter, respectively. In terms of seasonal variations, HCHOVCD was high in summer and low in winter which implies that photo-oxidation plays an important role in HCHO production in Seoul. In comparison with the Ozone Monitoring Instrument (OMI) measurements, the HCHOVCDs from the OMI are lower than those from Pandora. The correlation coefficient (R) between monthly HCHOVCDs values from Pandora and OMI is 0.61, with slop of 0.35. Furthermore, to understand HCHO mixing ratio within Planetary Boundary Layer (PBL) in Seoul, we converted Pandora HCHOVCDs to HCHO mixing ratio in the PBL using several meteorological input data from the Atmospheric InfraRed Sounder (AIRS). Seasonal HCHO mixing ratio in PBL converted from Pandora (OMI) HCHOVCDs are estimated to be 6.57 (5.17), 7.08 (6.68), 7.60 (4.70), and 5.00 (4.76) ppbv in spring, summer, autumn, and winter, respectively.

Keywords: formaldehyde, OMI, Pandora, remote sensing

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Authors: Guoqin Ge, Minhui Huang, Yazhou Zhou

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The growth of the Chengdu-Chongqing urban agglomeration has been designated as a national strategy in China. Analyzing its spatial evolution characteristics is crucial for devising relevant development strategies. This paper enhances the gravitational model by using temporal distance as a factor. It applies this improved model to assess the economic interconnection and concentration level of each geographical unit within the Chengdu-Chongqing urban agglomeration between 2011 and 2019. On this basis, this paper examines the spatial correlation characteristics of economic agglomeration intensity and urban-rural development equalization by employing spatial autocorrelation analysis. The study findings indicate that the spatial integration in the Chengdu-Chongqing urban agglomeration is currently in the "point-axis" development stage. The spatial organization structure is becoming more flattened, and there is a stronger economic connection between the core of the urban agglomeration and the peripheral areas. The integration of the Chengdu-Chongqing urban agglomeration is currently hindered by conflicting interests and institutional heterogeneity between Chengdu and Chongqing. Additionally, the connections between the relatively secondary spatial units are largely loose and weak. The strength and scale of economic ties and the level of urban-rural equilibrium among spatial units within the Chengdu-Chongqing urban agglomeration have increased, but regional imbalances have continued to widen, and such positive and negative changes have been characterized by the spatial and temporal synergistic evolution of the "core-periphery". Ultimately, this paper presents planning ideas for the future integration development of the Chengdu-Chongqing urban agglomeration, drawing from the findings.

Keywords: integration, planning strategy, space organization, space evolution, urban agglomeration

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Authors: Guilherme Henrique Gabriel, Lucí Hidalgo Nunes

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An important feature of rainfall regimes is the variability, which is subject to the atmosphere’s general and regional dynamics, geographical position and relief. Despite being inherent to the climate system, it can harshly impact virtually all human activities. In turn, global climate change has the ability to significantly affect smaller-scale rainfall regimes by altering their current variability patterns. In this regard, it is useful to know if regional climates are changing over time and whether it is possible to link these variations to climate change trends observed globally. This study is part of an international project (Metropole-FAPESP, Proc. 2012/51876-0 and Proc. 2015/11035-5) and the objective was to identify and evaluate possible changes in rainfall behavior in the state of São Paulo, southeastern Brazil, using rainfall data from 79 rain gauges for the last forty years. Cluster analysis and gamma distribution parameters were used for evaluating spatial and temporal trends, and the outcomes are presented by means of geographic information systems tools. Results show remarkable changes in rainfall distribution patterns in São Paulo over the years: changes in shape and scale parameters of gamma distribution indicate both an increase in the irregularity of rainfall distribution and the probability of occurrence of extreme events. Additionally, the spatial outcome of cluster analysis along with the gamma distribution parameters suggest that changes occurred simultaneously over the whole area, indicating that they could be related to remote causes beyond the local and regional ones, especially in a current global climate change scenario.

Keywords: climate change, cluster analysis, gamma distribution, rainfall

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Authors: Farshad Badie

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The central focus of this article is on the fact that knowledge is constructed from an interaction between humans’ experiences and over their conceptions of constructed concepts. Logical characterisation of ‘human inductive learning over human’s constructed concepts’ within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. This research connects with the topics ‘human learning’, ‘epistemology’, ‘cognitive modelling’, ‘knowledge representation’ and ‘ontological reasoning’.

Keywords: human concept learning, concept construction, knowledge construction, terminological systems

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Liliana O. Martínez, Juan E. González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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In this work, the use of a collection of mathematical challenges and puzzles aimed at students who are starting in algebra is proposed. The selected challenges and puzzles are intended to arouse students' interest in this area of mathematics, in addition to facilitating the teaching-learning process through challenges such as riddles, crossword puzzles, and board games, all in everyday situations that allow them to build themselves the learning. For this, it is proposed to carry out a "Math Rally: algebra" divided into four sections: mathematical reasoning, a hierarchy of operations, fractions, and algebraic equations.

Keywords: algebra, algebraic challenge, algebraic puzzle, math rally

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Authors: Morteza Khorrami

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The logic as an intellectual infrastructure plays an essential role in the Islamic sciences. Hence, there are a few of the verses of the Holy Quran that their interpretation is not possible due to lack of proper logic. In many verses in the Quran, argument and the respondent has requested from the audience that shows the logic rule is in the Quran. The paper which use a descriptive and analytic method, tries to show the role of logic in understanding of the Quran reasoning methods and display some of Quranic statements with mathematical symbols and point that we can help these symbols for interesting and interpretation and answering to some questions and doubts. In this paper, this problem has been mentioned that the Quran did not use two-valued logic (Aristotelian) in all cases, but the fuzzy logic can also be searched in the Quran.

Keywords: aristotelian logic, fuzzy logic, interpretation, Holy Quran

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Authors: M. Ndaw, G. Mendy, S. Ouya

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Information system risk management helps to reduce or eliminate risk by implementing appropriate controls. In this paper, we propose a quantification model of controls impact on information system risks by automatizing the residual criticality estimation step of FMECA which is based on a inductive reasoning. For this, we defined three equations based on type and maturity of controls. For testing, the values obtained with the model were compared to estimated values given by interlocutors during different working sessions and the result is satisfactory. This model allows an optimal assessment of controls maturity and facilitates risk analysis of information system.

Keywords: information system, risk, control, FMECA method

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Authors: Mariam Matiashvili

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Argumentation is an integral part of our daily communications - formal or informal. Argumentative reasoning, techniques, and language tools are used both in personal conversations and in the business environment. Verbalization of the opinions requires the use of extraordinary syntactic-pragmatic structural quantities - arguments that add credibility to the statement. The study of argumentative structures allows us to identify the linguistic features that make the text argumentative. Knowing what elements make up an argumentative text in a particular language helps the users of that language improve their skills. Also, natural language processing (NLP) has become especially relevant recently. In this context, one of the main emphases is on the computational processing of argumentative texts, which will enable the automatic recognition and analysis of large volumes of textual data. The research deals with the linguistic analysis of the argumentative structures of Georgian political speeches - particularly the linguistic structure, characteristics, and functions of the parts of the argumentative text - claims, support, and attack statements. The research aims to describe the linguistic cues that give the sentence a judgmental/controversial character and helps to identify reasoning parts of the argumentative text. The empirical data comes from the Georgian Political Corpus, particularly TV debates. Consequently, the texts are of a dialogical nature, representing a discussion between two or more people (most often between a journalist and a politician). The research uses the following approaches to identify and analyze the argumentative structures Lexical Classification & Analysis - Identify lexical items that are relevant in argumentative texts creating process - Creating the lexicon of argumentation (presents groups of words gathered from a semantic point of view); Grammatical Analysis and Classification - means grammatical analysis of the words and phrases identified based on the arguing lexicon. Argumentation Schemas - Describe and identify the Argumentation Schemes that are most likely used in Georgian Political Speeches. As a final step, we analyzed the relations between the above mentioned components. For example, If an identified argument scheme is “Argument from Analogy”, identified lexical items semantically express analogy too, and they are most likely adverbs in Georgian. As a result, we created the lexicon with the words that play a significant role in creating Georgian argumentative structures. Linguistic analysis has shown that verbs play a crucial role in creating argumentative structures.

Keywords: georgian, argumentation schemas, argumentation structures, argumentation lexicon

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Authors: Berhanu Terfa, Nengcheng C.

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The study deals with the analysis of urban expansion and land transformation of Hawass City using remote sensing data and landscape metrics during last three decades (1987–2017). Remote sensing data from Various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used to examine the urban expansion, growth types, and spatial isolation within the urban landscape to develop an understanding the trends of built-up growth in Hawassa City, Ethiopia. Landscape metrics and built-up density were employed to analyze the pattern, process and overall growth status. The area under investigation was divided into concentric circles with a consecutive circle of 1 km incremental radius from the central pixel (Central Business District) for analysis. The result exhibited that the built-up area had increased by 541.32% between 1987 and 2017and an extension growth types (more than 67 %) was observed. The major growth took place in north-west direction followed by north direction in haphazard manner during 1987–1995 period, whereas predominant built-up development was observed in south and southwest direction during 1995–2017 period. Land scape metrics result revealed that the of urban patches density, total edge and edge density increased, while mean nearest neighbors’ distance decreased showing the tendency of sprawl.

Keywords: landscape metrics, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Amit Kumar, Bhupendra Pratap Singh, Manoj Singh, Monika Punia, Krishan Kumar, V. K. Jain

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Ambient concentrations of volatile organic compounds (VOCs) were investigated in order to find out temporal variations and their ozone forming potentials (OFP) at rural site in Delhi National Capital Region during summer 2013. Sampling was performed for continuous five days, to identify the differences in working days and weekend VOCs concentration levels. Sampling and analytical procedure for VOCs were done using National Institute for Occupational Safety and Health (NIOSH) standard method. On each sampling day, VOCs samples were collected for 3-hours in the morning, afternoon and evening. There has been observed a noticeable contrast in the concentration of VOCs levels between working days and weekend. However, most of the VOCs showed diurnal fluctuations with higher concentrations in the morning and evening as compared to afternoon which might be due to change in meteorology. The results showed that mean toluene/benzene and m-/p-xylene/benzene ratios were higher in the afternoon while it was lower during morning and evening. The relative contribution of the VOCs to ozone formation, total propylene equivalent concentrations and OFP were calculated. Toluene was the most contributing organic contaminant to ozone formation as well as ambient VOCs concentrations. Results obtained in current study demonstrate that ozone formation at rural site in Delhi is probably limited by the emissions of VOCs.

Keywords: VOCs, rural, NIOSH, ozone forming potential, propylene equivalent concentration

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

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This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Letizia Maria Drammis, Maria Antonella Brandimonte

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The idea that people use space representations to think about time and number received support from several lines of research. However, how these representations develop in children and then shape space-time and space-number mappings is still a debated issue. In the present study, 40 children (20 pre-schoolers and 20 elementary-school children) performed 4 main tasks, which required the use of more concrete (non-symbolic) or more abstract (symbolic) space-time and space-number associations. In the non-symbolic conditions, children were required to order pictures of everyday-life events occurring in a specific temporal order (Temporal sequences) and of quantities varying in numerosity (Numerical sequences). In the symbolic conditions, they were asked to perform the typical time-to-position and number-to-position tasks by mapping time-related words and numbers onto lines. Results showed that children performed reliably better in the non-symbolic Time conditions than the symbolic Time conditions, independently of age, whereas only pre-schoolers performed worse in the Number-to-position task (symbolic) as compared to the Numerical sequence (non-symbolic) task. In addition, only older children mapped time-related words onto space following the typical left-right orientation, pre-schoolers’ performance being somewhat mixed. In contrast, mapping numbers onto space showed a clear left-right orientation, independently of age. Overall, these results indicate a cross-domain difference in the way younger and older children process time and number, with time-related tasks being more difficult than number-related tasks only when space-time tasks require symbolic representations.

Keywords: space-time associations, space-number associations, orientation, children

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Authors: Noori Shafiqullah

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Millions of people reside downstream of river basins that heavily rely on snowmelt originating from the Hindu Kush (HK) region. Snowmelt plays a critical role as a primary water source in these areas. This study aimed to evaluate snowfall and snowmelt characteristics in the HK region across altitudes ranging from 2019m to 4533m. To achieve this, the study employed a combination of remote sensing techniques and the Snow Model (SM) to analyze the spatial and temporal distribution of Snow Water Equivalent (SWE). By integrating the simulated Snow-cover Area (SCA) with data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the study optimized the Precipitation Gradient (PG), snowfall assessment, and the degree-day factor (DDF) for snowmelt distribution. Ground observed data from various elevations were used to calculate a temperature lapse rate of -7.0 (°C km-1). Consequently, the DDF value was determined as 3 (mm °C-1 d-1) for altitudes below 3000m and 3 to 4 (mm °C-1 d-1) for higher altitudes above 3000m. Moreover, the distribution of precipitation varies with elevation, with the PG being 0.001 (m-1) at lower elevations below 4000m and 0 (m-1) at higher elevations above 4000m. This study successfully utilized the SM to assess SCA and SWE by incorporating the two optimized parameters. The analysis of simulated SCA and MODIS data yielded coefficient determinations of R2, resulting in values of 0.95 and 0.97 for the years 2014-2015, 2015-2016, and 2016-2017, respectively. These results demonstrate that the SM is a valuable tool for managing water resources in mountainous watersheds such as the HK, where data scarcity poses a challenge."

Keywords: improved MODIS, experiment, snow water equivalent, snowmelt

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

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A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: granular computing, granular knowledge, hierarchical structuring, knowledge bases

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Authors: Swati Arun

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The present paper argues that Balance of Power (BOP) needs to conjugate with certain contingencies like geography. It is evident that sea powers (‘insular’ for better clarity) are not balanced (if at all) in the same way as land powers. Its apparent that artificial insularity that the US has achieved reduces the chances of balancing (constant) and helps it maintain preponderance (variable). But how precise is this approach in assessing the dynamics between China’s rise and reaction of other powers and US. The ‘evolved’ theory can be validated by putting China and US in the equation. Systemic Relation between the nations was explained through the Balance of Power theory much before the systems theory was propounded. The BOP is the crux of functionality of ‘power relation’ dynamics which has played its role in the most astounding ways leading to situations of war and peace. Whimsical; but true that, the BOP has remained a complicated and indefinable concepts since Hans. Morganthau to Kenneth Waltz. A challenge of the BOP, however remains; “ that it has too many meanings”. In the recent times it has become evident that the myriad of expectations generated by BOP has not met the practicality of the current world politics. It is for this reason; the BoP has been replaced by Preponderance Theory (PT) to explain prevailing power situation. PT does provide an empirical reasoning for the success of this theory but fails in a abstract logical reasoning required for making a theory universal. Unipolarity clarifies the current system as one where balance of power has become redundant. It seems to reach beyond the contours of BoP, where a superpower does what it must to remain one. The centrality of this arguments pivots around - an exception, every time BOP fails to operate, preponderance of power emerges. PT does not sit well with the primary logic of a theory because it works on an exception. The evolution of such a pattern and system where BOP fails and preponderance emerges is absent. The puzzle here is- if BOP really has become redundant or it needs polishing. The international power structure changed from multipolar to bipolar to unipolar. BOP was looked at to provide inevitable logic behind such changes and answer the dilemma we see today- why US is unchecked, unbalanced? But why was Britain unchecked in 19th century and why China was unbalanced in 13th century? It is the insularity of the state that makes BOP reproduce “imbalance of power”, going a level up from off-shore balancer. This luxury of a state to maintain imbalance in the region of competition or threat is the causal relation between BOP’s and geography. America has applied imbalancing- meaning disequilibrium (in its favor) to maintain the regional balance so that over time the weaker does not get stronger and pose a competition. It could do that due to the significant parity present between the US and the rest.

Keywords: balance of power, china, preponderance of power, US

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Authors: Dipo Dunsin, Mohamed C. Ghanem, Karim Ouazzane

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Digital investigators often have a hard time spotting evidence in digital information. It has become hard to determine which source of proof relates to a specific investigation. A growing concern is that the various processes, technology, and specific procedures used in the digital investigation are not keeping up with criminal developments. Therefore, criminals are taking advantage of these weaknesses to commit further crimes. In digital forensics investigations, artificial intelligence is invaluable in identifying crime. It has been observed that an algorithm based on artificial intelligence (AI) is highly effective in detecting risks, preventing criminal activity, and forecasting illegal activity. Providing objective data and conducting an assessment is the goal of digital forensics and digital investigation, which will assist in developing a plausible theory that can be presented as evidence in court. Researchers and other authorities have used the available data as evidence in court to convict a person. This research paper aims at developing a multiagent framework for digital investigations using specific intelligent software agents (ISA). The agents communicate to address particular tasks jointly and keep the same objectives in mind during each task. The rules and knowledge contained within each agent are dependent on the investigation type. A criminal investigation is classified quickly and efficiently using the case-based reasoning (CBR) technique. The MADIK is implemented using the Java Agent Development Framework and implemented using Eclipse, Postgres repository, and a rule engine for agent reasoning. The proposed framework was tested using the Lone Wolf image files and datasets. Experiments were conducted using various sets of ISA and VMs. There was a significant reduction in the time taken for the Hash Set Agent to execute. As a result of loading the agents, 5 percent of the time was lost, as the File Path Agent prescribed deleting 1,510, while the Timeline Agent found multiple executable files. In comparison, the integrity check carried out on the Lone Wolf image file using a digital forensic tool kit took approximately 48 minutes (2,880 ms), whereas the MADIK framework accomplished this in 16 minutes (960 ms). The framework is integrated with Python, allowing for further integration of other digital forensic tools, such as AccessData Forensic Toolkit (FTK), Wireshark, Volatility, and Scapy.

Keywords: artificial intelligence, computer science, criminal investigation, digital forensics

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Thomas LaRocca

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This study explores the development of a public-school music teacher’s professional identity within three domains: as an educator in the profession at large, as a music teacher in a school, and as a professional musician. An autoethnographic method is employed by calling upon undergraduate student teaching reflections, graduate writing assignments and presentations, cover letters for employment, professional correspondence, and reflective memos. These artifacts provide a reference for phenomenological insights into the values, hopes, and criticisms within each domain over time –all of which provide a window into the overall ontological perspective of one’s professional life at different moments in their career. While the topic of music teacher identity has been examined using autoethnographical methods before, by accessing materials over the course of ten years, the study is able to investigate the ‘how’ of identity development in a temporal context; from undergraduate student to established professional. Additionally, while the field offers a considerable amount of work surrounding the child and adolescent identity development, there are unmined opportunities to examine identity development in the adult years, especially surrounding adult professional life. Employing a postpositivist approach with social constructionism as a backdrop, this study examines adult identity formation and the contradictions, resonances, and priorities within each domain, between each domain, and perceived expectations of the professional community. What is revealed is a journey of self-improvement motivated by failure and success, marked by negotiation and sacrifice; as each domain competes for mental and temporal resources, identity is viewed as not just who one is, but also as what one leaves behind. These insights offer a window into the ontology of identity of a music educator and may provide considerations for differentiating professional development based on what stage educators are at in their careers.

Keywords: identity, longitudinal autoethnography, music teacher education, music teacher ontology

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Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Yildirim Ortaoglan

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The attempt to make thought school-like by fitting it into various frameworks with the institutionalization of it is almost simultaneous with philosophy itself. What once sprouted in the “academia” of old has institutionalized under the enlightenment's light, becoming the fundamental space reflecting the spirit of its age. However, the shift from the thinking temple where truth's knowledge was sought to functional spaces where power/power relations are constructed indicates a significant rupture in the meaning of school. Therefore, a genealogical inquiry into the meaning of the school can provide us with a path toward understanding how it should be approached in contemporary times. From this perspective, it is essential to highlight how power/power relations operate in the school in terms of disciplinary practices, temporal management, and spatial organization to construct a distinct subjectivation. Recognizing that the changing and evolving nature of education is related to the structure of space can be understood by revealing how disciplinary power and bio-power, two fundamental aspects of genealogical research, operate. In disciplinary power, the relationship of the subject with discipline, temporal management, and space is about improvement and normalization, while in biopower, it manifests in maximizing utility, increasing free time, and constructing spaces that seem more vital. These indicators not only facilitate the formation of students as a subjectivation but also enable the condition of the possibility of power/power relations. Because power is not applied to subjects but used by them for passage, and behind this lies the idea that the individual is already one of the components of power. As one of the components of power, in terms of subjectivation type, the student is one of the primary targets of power relations. Therefore, conducting a genealogical inquiry of the student as a type of subjectivation and the school as its living area from the philosophical foundations of education may offer a new opportunity for thinking about the contemporary crisis of thought. Within the framework of this possibility, our investigation will consider which aspects of the school and the student, brought together for educational purposes, can be thought of within and beyond power/power relations.

Keywords: power, education, space, school, student, discipline

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Authors: Nasser Salah Eldin Mohammed Salih Shebka

Abstract:

Current problematic issues in AI fields are mainly due to those of knowledge representation conceptual theories, which in turn reflected on the entire scope of cognitive sciences. Knowledge representation methods and tools are driven from theoretical concepts regarding human scientific perception of the conception, nature, and process of knowledge acquisition, knowledge engineering and knowledge generation. And although, these theoretical conceptions were themselves driven from the study of the human knowledge representation process and related theories; some essential factors were overlooked or underestimated, thus causing critical methodological deficiencies in the conceptual theories of human knowledge and knowledge representation conceptions. The evaluation criteria of human cumulative knowledge from the perspectives of nature and theoretical aspects of knowledge representation conceptions are affected greatly by the very materialistic nature of cognitive sciences. This nature caused what we define as methodological deficiencies in the nature of theoretical aspects of knowledge representation concepts in AI. These methodological deficiencies are not confined to applications of knowledge representation theories throughout AI fields, but also exceeds to cover the scientific nature of cognitive sciences. The methodological deficiencies we investigated in our work are: - The Segregation between cognitive abilities in knowledge driven models.- Insufficiency of the two-value logic used to represent knowledge particularly on machine language level in relation to the problematic issues of semantics and meaning theories. - Deficient consideration of the parameters of (existence) and (time) in the structure of knowledge. The latter requires that we present a more detailed introduction of the manner in which the meanings of Existence and Time are to be considered in the structure of knowledge. This doesn’t imply that it’s easy to apply in structures of knowledge representation systems, but outlining a deficiency caused by the absence of such essential parameters, can be considered as an attempt to redefine knowledge representation conceptual approaches, or if proven impossible; constructs a perspective on the possibility of simulating human cognition on machines. Furthermore, a redirection of the aforementioned expressions is required in order to formulate the exact meaning under discussion. This redirection of meaning alters the role of Existence and time factors to the Frame Work Environment of knowledge structure; and therefore; knowledge representation conceptual theories. Findings of our work indicate the necessity to differentiate between two comparative concepts when addressing the relation between existence and time parameters, and between that of the structure of human knowledge. The topics presented throughout the paper can also be viewed as an evaluation criterion to determine AI’s capability to achieve its ultimate objectives. Ultimately, we argue some of the implications of our findings that suggests that; although scientific progress may have not reached its peak, or that human scientific evolution has reached a point where it’s not possible to discover evolutionary facts about the human Brain and detailed descriptions of how it represents knowledge, but it simply implies that; unless these methodological deficiencies are properly addressed; the future of AI’s qualitative progress remains questionable.

Keywords: cognitive sciences, knowledge representation, ontological reasoning, temporal logic

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Authors: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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Authors: Savita, Anurag Sharma, Harsukhpreet Singh

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Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

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Authors: Masoud Irannezhad, Sirpa Rasmus, Saghar Ahmadian, Deliang Chen, Bjorn Klove

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Variability and changes in thermal conditions play a crucial role in functioning of human society, particularly over cold climate regions like Finland. Accordingly, the frost-free season (FFS) parameters in terms of start (FFSS), end (FFSE) and length (FFSL) have substantial effects not only on natural environment (e.g. flora and fauna), but also on human requirements (e.g. agriculture, forestry and energy generation). Applying the 0°C threshold of minimum temperature (Tmin), the FFS was defined as the period between the last spring frost as FFSS and the first fall frost as FFSE. For this study, gridded (10 x 10 km2) daily minimum temperature datasets throughout Finland during 1961-2011 was used to investigate recent spatio-temporal variations and trends in frost-free season (FFS) parameters and their relationships with the well-known large-scale climate teleconnections (CTs). The FFS in Finland naturally increases from north (~60 days) to south (~190 days), in association with earlier FFSS (~24 April) and later FFSE (~30 October). Statistically significant (p<0.05) trends in FFSL were all positive (increasing) ranged between 0 and 13.5 (days/decade) and mainly observed in the east, upper west, centre and upper north of Finland. Such lengthening trends in FFS were attributable to both earlier FFSS and later FFSE mostly over central and upper northern Finland, while only to later FFSE in eastern and upper western parts. Variations in both FFSL and FFSS were significantly associated with the Polar (POL) pattern over northern Finland, while with the East Atlantic (EA) pattern over eastern and upper western areas. However, the POL and Scandinavia (SCA) patterns were most influential CTs for FFSE variability over northern Finland.

Keywords: climate teleconnections, Finland, frost-free season, trend analysis

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Authors: R. Mellah, R. Toumi

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This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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Authors: M. A. Hernández-Ceballos, E. G. San Miguel, C. Galán, J. P. Bolívar

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The evolution of 7Be and 210Pb activity concentrations in surface air along the Guadalquivir valley (southern Iberian Peninsula) is presented in this study. Samples collected for 48 h, every fifteen days, from September 2012 to November 2013 at two sampling sites (Huelva city in the mouth and Cordoba city in the middle (located 250 km far away)), are used to 1) analysing the spatial variability and 2) understanding the influence of wind conditions on 7Be and 210Pb. Similar average concentrations were registered along the valley. The mean 7Be activity concentration was 4.46 ± 0.21 mBq/m3 at Huelva and 4.33 ± 0.20 mBq/m3 at Cordoba, although registering higher maximum and minimum values at Cordoba (9.44 mBq/m3 and 1.80 mBq/m3) than at Huelva (7.95 mBq/m3 and 1.04 mBq/m3). No significant differences were observed in the 210Pb mean activity concentrations between Cordoba (0.40 ± 0.04 mBq/m3) and Huelva (0.35 ± 0.04 mBq/m3), although the maximum (1.10 mBq/m3 and 0.87 mBq/m3) and minimum (0.02 mBq/m3 and 0.04 mBq/m3) values were recorded in Cordoba. Although similar average concentrations were obtained in both sites, the temporal evolution of both natural radionuclides presents differences between them. The meteorological analysis of two sampling periods, in which large differences on 7Be and 210Pb concentrations are observed, indicates the different impact of surface and upper wind dynamics. The analysis reveals the different impact of the two sea-land breeze patterns usually observed along the valley (pure and non-pure) and the corresponding air masses at higher layers associated with each one. The pure, with short development (around 30 km inland) and increasing accumulation process, favours high concentrations of both radionuclides in Huelva (coastal site), while the non-pure, with winds sweeping the valley until arrive to Cordoba (250 km far away), causes high activity values at this site. These results reveal the impact of mesoscale conditions on these two natural radionuclides, and the importance of these circulations on its spatial and temporal variability.

Keywords: 7Be, 210Pb, air masses, mesoscale process

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Authors: Qiuyue Peng, Vladimir Zachar

Abstract:

The application of adipose-derived stromal/stem cells (ASCs) in regenerative medicine is gaining more awareness due to their advanced translational potential and abundant source preparations. However, ASC-based translation has been confounded by high subpopulation heterogeneity, causing ambiguity about its precise therapeutic value. Some phenotypes defined by a unique combination of positive and negative surface markers have been found beneficial to the required roles. Therefore, the immunophenotypic repertoires of cultured ASCs and temporal changes of distinct subsets were investigated in this study. ASCs from three donors undergoing cosmetic liposuction were cultured in standard culturing methods, and the co-expression patterns based on the combination of selected markers at passages 1, 4, and 8 were analyzed by multi-chromatic flow cytometry. The results showed that the level of heterogeneity of subpopulations of ASCs became lower by in vitro expansion. After a few passages, most of the CD166⁺/CD274⁺/CD271⁺ based subpopulations converged to CD166 single positive cells. Meanwhile, these CD29⁺CD201⁺ double-positive cells, in combination with CD36/Stro-1 expression or without, feathered only the major epitopes and maintained prevailing throughout the whole process. This study suggested that, upon in vitro expansion, the phenotype repertoire of ASCs redistributed and stabilized in a way that cells co-expressing exclusively the strong markers remained dominant. These preliminary findings provide a general overview of the distribution of heterogeneous subsets residents within human ASCs during expansion in vitro. It is a critical step to fully characterize ASCs before clinical application, although the biological effects of heterogeneous subpopulations still need to be clarified.

Keywords: adipose-derived stromal/stem cells, heterogeneity, immunophenotype, subpopulations

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