Search results for: spatial and temporal data

Authors: Marius Zemp

Abstract:

Evidentials indicate how the speaker obtained the information conveyed in a statement. Detailed diachronic-functional accounts of evidential contrasts found in the Greater Himalayan Region (GHR) reveal that contrasting evidentials are not only defined against each other but also that most of them once had different aspecto-temporal (TA) values which must have aligned when their contrast was conventionalized. Based on these accounts, the present paper sheds light on hitherto unidentified mechanisms of grammatical change. The main insights of the present study were facilitated by ‘functional reconstruction’, which (i) revolves around morphemes which appear to be used in divergent ways within a language and/or across different related languages, (ii) persistently devises hypotheses as to how these functional divergences may have developed, and (iii) retains those hypotheses which most plausibly and economically account for the data. Based on the dense and detailed grammatical literature on the Tibetic language family, the author of this study is able to reconstruct the initial steps by which its evidentiality systems developed: By the time Proto-Tibetan started to be spread across much of Central Asia in the 7th century CE, verbal concatenations with and without a connective -s had become common. As typical for resultative constructions around the globe, Proto-Tibetan *V-s-’dug ‘was there, having undergone V’ (employing the simple past of ’dug ‘stay, be there’) allowed both for a perfect reading (‘the state resulting from V holds at the moment of speech’) and an inferential reading (‘(I infer from its result that) V has taken place’). In Western Tibetic, *V-s-’dug grammaticalized in its perfect meaning as it became contrasted with perfect *V-s-yod ‘is there, having undergone V’ (employing the existential copula yod); that is, *V-s-’dug came to mean that the speaker directly witnessed the profiled result of V, whereas *V-s-yod came to mean that the speaker does not depend on direct evidence of the result, as s/he simply knows that it holds. In Eastern Tibetic, on the other hand, V-s-’dug grammaticalized in its inferential past meaning as it became contrasted with past *V-thal ‘went past V-ing’ (employing the simple past of thal ‘go past’); that is, *V-s-’dug came to mean that the profiled past event was inferred from its result, while *V-thal came to mean that it was directly witnessed. Hence, depending on whether it became contrasted with a perfect or a past construction, resultative V-s-’dug grammaticalized either its direct evidential perfect or its inferential past function. This means that in both cases, evidential readings of constructions with distinct but overlapping TA-values became contrasted, and in order for their contrasting meanings to grammaticalize, the constructions had to agree on their tertium comparationis, which was their shared TA-value. By showing that other types of evidential contrasts in the GHR are also TA-aligned, while no single markers (or privative contrasts) are found to have grammaticalized evidential functions, the present study suggests that, at least in this region of the world, evidential meanings grammaticalize only in equipollent contrasts, which always end up TA-aligned.

Keywords: evidential contrasts, functional-diachronic accounts, grammatical change, himalayan languages, tense/aspect-alignment

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Authors: Alemayehu Muluneh, Saskia Keesstra, Leo Stroosnijder, Woldeamlak Bewket, Ashenafi Burka

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There are some scientific evidences and a belief by many that forests attract rain and deforestation contributes to a decline of rainfall. However, there is still a lack of concrete scientific evidence on the role of forests in rainfall amount. In this paper, we investigate the forest-rainfall relationships in the environmentally hot spot area of the Central Rift Valley (CRV) of Ethiopia. Specifically, we evaluate long term (1970-2009) rainfall variability and its relationship with historical forest cover and the relationship between existing forest cover and topographical variables and rainfall distribution. The study used 16 long term and 15 short term rainfall stations. The Mann-Kendall test, bi variate and multiple regression models were used. The results show forest and wood land cover continuously declined over the 40 years period (1970-2009), but annual rainfall in the rift valley floor increased by 6.42 mm/year. But, on the escarpment and highlands, annual rainfall decreased by 2.48 mm/year. The increase in annual rainfall in the rift valley floor is partly attributable to the increase in evaporation as a result of increasing temperatures from the 4 existing lakes in the rift valley floor. Though, annual rainfall is decreasing on the escarpment and highlands, there was no significant correlation between this rainfall decrease and forest and wood land decline and also rainfall variability in the region was not explained by forest cover. Hence, the decrease in annual rainfall on the escarpment and highlands is likely related to the global warming of the atmosphere and the surface waters of the Indian Ocean. Spatial variability of number of rainy days from systematically observed two-year’s rainfall data (2012-2013) was significantly (R2=-0.63) explained by forest cover (distance from forest). But, forest cover was not a significant variable (R2=-0.40) in explaining annual rainfall amount. Generally, past deforestation and existing forest cover showed very little effect on long term and short term rainfall distribution, but a significant effect on number of rainy days in the CRV of Ethiopia.

Keywords: elevation, forest cover, rainfall, slope

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Taner Ersoz, Filiz Ersoz

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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: multiple correspondence analysis, multivariate categorical data, health care services, health satisfaction survey

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Authors: Najih Amina

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Our study focuses on monitoring the spatial evolution of a number of physico-chemical parameters of wells waters located at different distances from the discharge of the city of Khouribga (S0 upstream station, S1, S2 et S3 are respectively located at 5.5, 7.5, 11 Km away from solid waste discharge of the city). The absence of a source of drinking water in this region involves the population to feeding on its groundwater wells. Through the results, we note that most of the analyzed parameters exceed the potable water standards from S1. At this source of water, we find that the conductivity (1290 μmScm-1; Standard 1000 μmScm-1), Total Hardness TH (67.2°F/ Standard 50° F), Ca2 + (146 mg l-1 standard 60 mg l-1), Cl- (369 mg l-1 standard 150 mg l-1), NaCl (609 mgl-1), Methyl orange alakanity “M. alk” (280 mg l-1) greatly exceed the drinking water standards. By following these parameters, it is obvious that some values have decreased in the downstream stations, while others become important. We find that the conductivity is always higher than 950 μmScm-1; the TH registers 72°F in S3; Ca 2+ is in the range of 153 mg l-1 in S3, Cl- and NaCl- reached 426 mg l-1 and 702 mg l-1 respectively in S2, M alk becomes higher and reaches 430 to 350 in S3. At the wells S2, we found that the nitrites are well beyond the standard 1.05 mg l-1. Whereas, at the control station S0, the values are lower or at the limit of drinking water standards: conductivity (452 μmScm-1), TH (34 F°), Ca2+ (68 mg l-1), Cl- (157 mg l-1), NaCl- (258 mg l-1), M alk (220 mg l-1). Thus, the diagnosis reveals the presence of a high pollution caused by the leachates of the household waste discharge and by the effluents of the sewage waste water plant (SWWP). The phenomenon of the water hardness could, also, be generated by the processes of erosion, leaching and soil infiltration in the region (phosphate layers, intercalated layers of marl and limestone), phenomenons also caused by the acidity due to this surrounding pollution. The source S1 is the nearest surrounding site of the discharge and the most affected by the phenomenon of pollution, especially, it is near to a superficial water source S’1 polluted by the effluents coming from the sewage waste water plant of the city. In the light of these data, we can deduce that the consumption of this water from S1 does not conform the standards of drinking waters, and could affect the human health.

Keywords: physico-chemical parameters, ground water wells, infiltration, leaching, pollution, leachate discharge effluent SWWP, human health.

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Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Probuddha Mukhopadhyay

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The infiltration of key elements to the civil structure is foraying its way to reclaim, what is its own. The reclamation of lives and spaces, once challenged, becomes a consistent process of ingress, disguised as parallels to the moving city, disperses into discourses often unheard of and conveniently forgotten. In this age of 'hyper'-urbanization, there are solutions suggested to a plethora of issues faced by citizens, in improving their standards of living. Problems are ancillary to proposals that emerge out of the underlying disorders of the townscape. These interventions result in the formulation of urban policies, to consolidate and optimize, to regularize and to streamline resources. Policy and practice are processes where the politics in policies define the way in which urban solutions are prescribed. Social constraints, that formulate the various cycles of order and disorders within the urban realm, are the stigmas for such interventions. There is often a direct relation of policy to place, no matter how people-centric it may seem to be projected. How we live our lives depends on where we live our lives - a relative statement for urban problems, varies from city to city. Communal compositions, welfare, crisis, socio-economic balance, need for management are the generic roots for urban policy formulation. However, in reality, the gentry administering its environmentalism is the criterion, that shapes and defines the values and expanse of such policies. In relation to the psycho-spatial characteristic of urban spheres with respect to the other side of this game, there have been instances, where the associational values have been reshaped by interests. The public domain reclaimed for exclusivity, thus creating fortified neighborhoods. Here, the citizen cumulative is often drifted by proposals that would over time deplete such landscapes of the city. It is the organized rebellion that in turn formulates further inward looking enclaves of latent aggression. In recent times, it has been observed that the unbalanced division of power and the implied processes of regulating the weak, stem the rebellion who respond in kits and parts. This is a phenomenon that mimics the guerilla warfare tactics, in order to have systems straightened out, either by manipulations or by force. This is the form of the city determined by the various forms insinuated by the state of city wide decisions. This study is an attempt at understanding the way in which development is interpreted by the state and the civil society and the role that community driven processes undertake to reinstate their claims to the city. This is a charter of consolidated patterns of negotiations that tend to counter policies. The research encompasses a study of various contested settlements in two cities of India- Mumbai and Kolkata, tackling dissent through spatial order. The study has been carried out to identify systems - formal and informal, catering to the most challenged interests of the people with respect to their habitat, a model to counter the top-down authoritative framework challenging the legitimacy of such settlements.

Keywords: urban design, insurgence, tactical urbanism, urban governance, civil society, state

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Authors: Burcu Guvenek, Duygu Baysal Kurt

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The impact of foreign trade on economic growth has been discussed since the Classical Economists. Today, foreign trade has become more important for the country's economy with the increasing globalization. When it comes to foreign trade, policies which may vary from country to country and from time to time as protectionism or free trade are implemented. In general, the positive effect of foreign trade on economic growth is alleged. However, as studies supporting this general acceptance take place in the economics literature, there are also studies in the opposite direction. In this paper, the impact of foreign trade on economic growth will be investigated with the help of panel data analysis. For this research, 24 OECD countries’ GDP and foreign trade data, including the period of 1990 and 2010, will be used.

Keywords: foreign trade, economic growth, OECD countries, panel data analysis

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Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: Enerit Sacdanaku, Idriz Haxhiu

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This study was conducted in the area of Vlora Bay, Albania. Data about Sea Turtles Caretta caretta and Chelonia mydas, belonging to two periods of time (1984–1991; 2008–2014) are given. All data gathered were analyzed using recent methodologies. For all turtles captured (as by catch), the Curve Carapace Length (CCL) and Curved Carapace Width (CCW) were measured. These data were statistically analyzed, where the mean was 67.11 cm for CCL and 57.57 cm for CCW of all individuals studied (n=13). All untagged individuals of marine turtles were tagged using metallic tags (Stockbrand’s titanium tag) with an Albanian address. Sex was determined and resulted that 45.4% of individuals were females, 27.3% males and 27.3% juveniles. All turtles were studied for the presence of the epibionts. The area of Vlora Bay is used from marine turtles (Caretta caretta) as a migratory corridor to pass from the Mediterranean to the northern part of the Adriatic Sea.

Keywords: Caretta caretta, Chelonia mydas, CCL, CCW, tagging, Vlora Bay

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Authors: Samuel Hyellamada Jerry

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This study focused on assessing conservation priorities within the Karlahi Forest Reserve of Fufore Local Government in Adamawa State. The main objective was to identify specific areas within the forest reserve that require immediate conservation attention. The research employed remote sensing and GIS techniques to achieve this goal. By overlaying the IDRIS Silva module results, a spatial distribution map was generated, highlighting the cumulative priority areas within and outside the forest. Among the total vegetated area of 26.38 km² in the Karlahi Forest Reserve, the analysis revealed that 16.16 km² were classified as high-priority conservation zones. Additionally, 4.59 km² and 5.63 km² were identified as medium and low-priority areas, respectively. In light of these findings, it is recommended that conservation efforts incorporate detailed land cover information and regular assessments of species diversity. Furthermore, strict adherence to national and state policies regarding forest reserves and parks is crucial for effective conservation management.

Keywords: priority, Karlahi, forest, reserve, IDRISI Silva, species diversity

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Authors: Farhat Imtiaz, Umar Farooq

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In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

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Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur

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The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially Long Range Wide Area Network (LoRaWAN). In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated from each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems by getting access to a wider band.

Keywords: IoT, LPWAN, LoRa, effective signal power, onsite measurement

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Farouk Lawan Gambo

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Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning.

Keywords: data analysis, compression techniques, learning content, traditional learning approach

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Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Rajkumar Ghosh, Bhabani Prasad Mukhopadhay

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Groundwater contamination with fluoride has emerged as a global concern affecting millions of people, leading to the widespread occurrence of fluorosis. It affects bones and teeth, leading to dental and skeletal fluorosis. This study presents a comprehensive analysis of the relationship between groundwater contamination and fluorosis. It delves into the causes of fluoride contamination in groundwater, its spatial distribution, and adverse health impacts of fluorosis on affected communities. Fluoride contamination in groundwater can be attributed to both natural and anthropogenic sources. Geogenic sources involve the dissolution of fluoride-rich minerals present in the aquifer materials. On the other hand, anthropogenic activities such as industrial discharges, agricultural practices, and improper disposal of fluoride-containing waste contribute to the contamination of groundwater. The spatial distribution of fluoride contamination varies widely across different regions and geological formations. High fluoride levels are commonly observed in areas with fluorine-rich geological deposits. Additionally, agricultural and industrial centres often exhibit elevated fluoride concentrations due to anthropogenic contributions. Excessive fluoride ingestion during tooth development leads to dental fluorosis, characterized by enamel defects, discoloration, and dental caries. The severity of dental fluorosis varies based on fluoride exposure levels during tooth development. Long-term consumption of fluoride-contaminated water causes skeletal fluorosis, resulting in bone and joint pain, decreased joint mobility, and skeletal deformities. In severe cases, skeletal fluorosis can lead to disability and reduced quality of life. Various defluoridation techniques such as activated alumina, bone char, and reverse osmosis have been employed to reduce fluoride concentrations in drinking water. These methods effectively remove fluoride, but their implementation requires careful consideration of cost, maintenance, and sustainability. Diversifying water sources, such as rainwater harvesting and surface water supply, can reduce the reliance on fluoride-contaminated groundwater, especially in regions with high fluoride concentrations. Groundwater contamination with fluoride remains a significant public health challenge, leading to the widespread occurrence of fluorosis globally. This scientific report emphasizes the importance of understanding the relationship between groundwater contamination and fluorosis. Implementing effective mitigation strategies and preventive measures is crucial to combat fluorosis and ensure sustainable access to safe drinking water for communities worldwide. Collaborative efforts between government agencies, local communities, and scientific researchers are essential to address this issue and safeguard the health of vulnerable populations. Additionally, the report explores various mitigation strategies and preventive measures to address the issue and offers recommendations for sustainable management of groundwater resources to combat fluorosis effectively.

Keywords: fluorosis, fluoride contamination, groundwater contamination, groundwater resources

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Authors: Fatemehsadat Mortazavizadeh, Amin Dehghani, Majid Mirzaei, Nurulhuda Binti Mohammad Ramli, Adnan Dehghani

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Flood is Malaysia's most common and serious natural disaster. Kelantan River Basin is a tropical basin that experiences a rainy season during North-East Monsoon from November to March. It is also one of the hardest hit areas in Peninsular Malaysia during the heavy monsoon rainfall. Considering the consequences of the flood events, it is essential to develop the flood inundation map as part of the mitigation approach. In this study, the delineation of flood inundation zone in the area of Kelantan River basin using a hydrodynamic model is done by HEC-RAS, QGIS and ArcMap. The streamflow data has been generated with the weather generator based on the observation data. Then, the data is statistically analyzed with the Extreme Value (EV1) method for 2-, 5-, 25-, 50- and 100-year return periods. The minimum depth, maximum depth, mean depth, and the standard deviation of all the scenarios, including the OBS, are observed and analyzed. Based on the results, generally, the value of the data increases with the return period for all the scenarios. However, there are certain scenarios that have different results, which not all the data obtained are increasing with the return period. Besides, OBS data resulted in the middle range within Scenario 1 to Scenario 40.

Keywords: flood inundation, kelantan river basin, hydrodynamic model, extreme value analysis

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Authors: Takele Nemomsa, Girma Mamo, Tesfaye Balemi

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Climate change refers to a change in the state of the climate that can be identified (e.g. using statistical tests) by changes in the mean and/or variance of its properties and that persists for an extended period, typically decades or longer. In Ethiopia; Maize production in relation to climate change at regional and sub- regional scales have not been studied in detail. Thus, this study was aimed to analyse the impact of climate change on maize yield in Ambo Districts, Central Ethiopia. To this effect, weather data, soil data and maize experimental data for Arganne hybrid were used. APSIM software was used to investigate the response of maize (Zea mays) yield to different agronomic management practices using current and future (2020s–2080s) climate data. The climate change projections data which were downscaled using SDSM were used as input of climate data for the impact analysis. Compared to agronomic practices the impact of climate change on Arganne in Central Ethiopia is minute. However, within 2020s-2080s in Ambo area; the yield of Arganne hybrid is projected to reduce by 1.06% to 2.02%, and in 2050s it is projected to reduce by 1.56 While in 2080s; it is projected to increase by 1.03% to 2.07%. Thus, to adapt to the changing climate; farmers should consider increasing plant density and fertilizer rate per hectare.

Keywords: APSIM, downscaling, response, SDSM

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Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Gabriel Gomez

Abstract:

The very concept of information seeking behavior, and the means by which librarians teach users to gain information, that is information literacy, are at the heart of how libraries deliver information, but big data will forever change human interaction with information and the way such behavior is both studied and taught. Just as importantly, big data will orient the study of behavior towards commercial ends because of a tendency towards instrumentalist views of human behavior, something one might also call a trend towards behaviorism. This oral presentation seeks to explore how the impact of big data on understandings of human behavior might impact a library information science (LIS) view of human behavior and information literacy, and what this might mean for social justice aims and concomitant community action normally at the center of librarianship. The methodology employed here is a non-empirical examination of current understandings of LIS in regards to social justice alongside an examination of the benefits and dangers foreseen with the growth of big data analysis. The rise of big data within the ever-changing information environment encapsulates a shift to a more mechanistic view of human behavior, one that can easily encompass information seeking behavior and information use. As commercial aims displace the important political and ethical aims that are often central to the missions espoused by libraries and the social sciences, the very altruism and power relations found in LIS are at risk. In this oral presentation, an examination of the social justice impulses of librarians regarding power and information demonstrates how such impulses can be challenged by big data, particularly as librarians understand user behavior and promote information literacy. The creeping behaviorist impulse inherent in the emphasis big data places on specific solutions, that is answers to question that ask how, as opposed to larger questions that hint at an understanding of why people learn or use information threaten library information science ideals. Together with the commercial nature of most big data, this existential threat can harm the social justice nature of librarianship.

Keywords: big data, library information science, behaviorism, librarianship

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Authors: Min Kyung An

Abstract:

In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

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Authors: Yunos Zahri, Ariffin Aswami

Abstract:

Cyber terrorism represents the convergence of two worlds: virtual and physical. The virtual world is a place in which computer programs function and data move, whereas the physical world is where people live and function. The merging of these two domains is the interface being targeted in the incidence of cyber terrorism. To better understand why cyber terrorism acts are committed, this study presents the context of cyber terrorism from motivational perspectives. Motivational forces behind cyber terrorism can be social, political, ideological and economic. In this research, data are analyzed using a qualitative method. A semi-structured interview with purposive sampling was used for data collection. With the growing interconnectedness between critical infrastructures and Information & Communication Technology (ICT), selecting targets that facilitate maximum disruption can significantly influence terrorists. This work provides a baseline for defining the concept of cyber terrorism from motivational perspectives.

Keywords: cyber terrorism, terrorism, motivation, qualitative analysis

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Authors: Sheheryar Khan, Weidong Li, Fanqian Meng

Abstract:

The Urban Heat Island (UHI) effect is one of the foremost problems out of other ecological and socioeconomic issues in urbanization. Due to this phenomenon that human-made urban areas have replaced the rural landscape with the surface that increases thermal conductivity and urban warmth; as a result, the temperature in the city is higher than in the surrounding rural areas. To affect the evidence of this phenomenon in the Zhengzhou city area, an observation of the temperature variations in the urban area is done through a scientific method that has been followed. Landsat 8 satellite images were taken from 2013 to 2015 to calculate the effect of Urban Heat Island (UHI) along with the NPP-VRRIS night-time remote sensing data to analyze the result for a better understanding of the center of the built-up area. To further support the evidence, the correlation between land surface temperatures and the normalized difference vegetation index (NDVI) was calculated using the Red band 4 and Near-infrared band 5 of the Landsat 8 data. Mono-window algorithm was applied to retrieve the land surface temperature (LST) distribution from the Landsat 8 data using Band 10 and 11 accordingly to convert the top-of-atmosphere radiance (TOA) and to convert the satellite brightness temperature. Along with Landsat 8 data, NPP-VIIRS night-light data is preprocessed to get the research area data. The analysis between Landsat 8 data and NPP night-light data was taken to compare the output center of the Built-up area of Zhengzhou city.

Keywords: built-up area, land surface temperature, mono-window algorithm, NDVI, remote sensing, threshold method, Zhengzhou

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Authors: Robab Abdolkhani, Farzin Halabchi, Reza Safdari, Goli Arji

Abstract:

Background and purpose: The quality of health record depends on the quality of its content and proper documentation. Minimum data set makes a standard method for collecting key data elements that make them easy to understand and enable comparison. The aim of this study was to determine the minimum data set for Iranian athletes’ health records. Methods: This study is an applied research of a descriptive comparative type which was carried out in 2013. By using internal and external forms of documentation, a checklist was created that included data elements of athletes health record and was subjected to debate in Delphi method by experts in the field of sports medicine and health information management. Results: From 97 elements which were subjected to discussion, 85 elements by more than 75 percent of the participants (as the main elements) and 12 elements by 50 to 75 percent of the participants (as the proposed elements) were agreed upon. In about 97 elements of the case, there was no significant difference between responses of alumni groups of sport pathology and sports medicine specialists with medical record, medical informatics and information management professionals. Conclusion: Minimum data set of Iranian athletes’ health record with four information categories including demographic information, health history, assessment and treatment plan was presented. The proposed model is available for manual and electronic medical records.

Keywords: Documentation, Health record, Minimum data set, Sports medicine

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Authors: Abdulwahab Alalyani, Mahbub Rashid

Abstract:

Public green space promotes community health including daily activities, but these resources may not be available enough or may not equitably be distributed. This paper measures and compares the availability of public green spaces (PGS) among low, middle, and high-income neighborhoods in the Riyadh city. Additionally, it compares the total availability of PGS to WHO standard and Dubai availability of PGS per person. All PGS were mapped using geographical information systems, and total area availability of PGS compared to WHO and Dubai standards. To evaluate the significant differences in PGS availability across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences. As a result, by comparing PGS of Riyadh neighborhoods to WHO and Dubai-availability, it was found that Riyadh PGS were lower than the minimum standard of WHO and as well as Dubai. Riyadh has only 1.13 m² per capita of PGS. The second finding, the availability of PGS, was significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of PGS should be focused on increasing PGS availability and should be given priority to those low-income and unhealthy communities.

Keywords: spatial equity, green space, quality of life, built environment

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