Search results for: decline curve analysis

Authors: İsmail Karaca, Ömer Söner

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The use of advanced methods has been increasing day by day in the maritime sector, which is one of the sectors least affected by the COVID-19 pandemic. It is aimed to minimize accidents, especially by using advanced methods in the investigation of marine accidents. This research aimed to conduct an exploratory statistical analysis of particular ship accidents in the Transport Safety Investigation Center of Turkey database. 46 ship accidents, which occurred between 2010-2018, have been selected from the database. In addition to the availability of a reliable and comprehensive database, taking advantage of the robust statistical models for investigation is critical to improving the safety of ships. Thus, descriptive analysis has been used in the research to identify causes and conditional factors related to different types of ship accidents. The research outcomes underline the fact that environmental factors and day and night ratio have great influence on ship safety.

Keywords: descriptive analysis, maritime industry, maritime safety, ship accident statistics

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Authors: Sh. Heidari, A. J. Andrews, A. Oberoi

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Electrochemical storage of hydrogen in activated carbon electrodes as part of a reversible fuel cell offers a potentially attractive option for storing surplus electrical energy from inherently variable solar and wind energy resources. Such a system – which we have called a proton flow battery – promises to have a roundtrip energy efficiency comparable to lithium ion batteries, while having higher gravimetric and volumetric energy densities. In this paper, a theoretical model is presented of the process of H+ ion (proton) conduction through an acid electrolyte into a highly porous activated carbon electrode where it is neutralised and absorbed on the inner surfaces of pores. A Butler-Volmer type equation relates the rate of adsorption to the potential difference between the activated carbon surface and the electrolyte. This model for the hydrogen storage electrode is then incorporated into a more general computer model based on MATLAB software of the entire electrochemical cell including the oxygen electrode. Hence a theoretical voltage-current curve is generated for given input parameters for a particular activated carbon electrode. It is shown that theoretical VI curves produced by the model can be fitted accurately to experimental data from an actual electrochemical cell with the same characteristics. By obtaining the best-fit values of input parameters, such as the exchange current density and charge transfer coefficient for the hydrogen adsorption reaction, an improved understanding of the adsorption reaction is obtained. This new model will assist in designing improved proton flow batteries for storing solar and wind energy.

Keywords: electrochemical hydrogen storage, proton flow battery, butler-volmer equation, activated carbon

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Authors: Fariborz Shekari, Abdollah Javanmard, Amin Abbasi

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A pot experiment conducted to evaluate the response of two red bean cultivars, Sayad and Derakhshan, to water deficit stress during post-flowering growth stage and recovery potential of plants after stress. Treatments were included regular irrigation or control, water deficit during flowering stage, water deficit during pod formation and water deficit during pod filling period. Results showed that plant height had positive effects on yield of cultivars so that, the tall cultivar, ‘Sayad’, had higher yields. Stress application during flowering stage showed the highest negative impact on plant height and subsequently yield. The longest and the higher number of pods as well as the greatest number of seeds in pods were recorded in control treatment in ‘Sayad’. Stress application during pod formation resulted in the minimum amount of all studied traits in both cultivars. Stress encountered during seed filling period had the least effect on number and length of pods and seed/pod. However, 100 seeds weight significantly decreased. The highest amount for 100 seeds weight was record in control plants in ‘Derakhshan’. Under all treatments, ‘Sayad’ had higher biologic and seed yield compared to ‘Derakhshan’. The least amount of yield was recorded during stress application in pod formation and flowering period for ‘Sayad’ and ‘Derakhshan’ respectively. Harvest index of ‘Sayad’ was more affect by stress application. Data related to photosynthetic rate showed that during stress application, ‘Derakhshan’ owned rapid decline in photosynthesis. Beyond stress alleviation and onset of irrigation, recovery potential of ‘Sayad’ was higher than ‘Derakhshan’ and this cultivar was able to rapidly restore the photosynthesis rate of stress faced plants near control ones. In total, stress had lower impacts on photosynthetic rate of ‘Sayad’ cultivar.

Keywords: common bean, water stress, yield, yield components, photosynthetic rate

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Authors: Abbas Al-Refaie, Nour Bata

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A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.

Keywords: market segmentation, conjoint analysis, market strategies, optimization

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Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering　severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

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Authors: Sataroopa Mishra, Mona Basker, Sneha Varkki, Ram Kumar Pandian, Grace Rebekah

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Background: Sleep deprivation is a matter of public health importance among adolescents. We used adolescent sleep wake scale and adolescent sleep hygiene scale to determine the sleep quality and sleep hygiene respectively of school going adolescents in Vellore city of India. The objective of the study was to do factorial analysis of the scales and validate it for use in local population. Methods: Observational questionnaire based cross sectional study. Setting: Community based school survey in a semi-urban setting in three schools in Vellore city. Data collection: Non probability sample was collected form students studying in standard 9 and 11. Students filled Adolescent Sleep Wake scale (ASWS) and Adolescent Sleep Hygiene Scale (ASHS) translated into vernacular language. Data Analysis: Exploratory Factorial Analysis was used to see the factor loading of various components of the two scales. Confirmatory factorial analysis is subsequently planned for assessing the internal validity of the scales.Results: 557 adolescents were included in the study of 12 – 17 years old. Exploratory factorial analysis of adolescent sleep hygiene scale indicated significant factor loading for 18 items from 28 items originally devised by the authors and has been reconstructed to four domains instead of 9 domains in the original scale namely sleep stability, cognitive – emotional, Physiological - bed time routine - behavioural arousal factor (activites before bedtime and during bed time), Sleep environment (lighting and bed sharing). Factorial analysis of Adolescent sleep wake scale showed factor loading of 18 items out of 28 items in original scale reconstructed into 5 aspects of sleep quality. Conclusions: The factorial analysis gives a reconstructed scale useful for the local population. Further a confirmatory factorial analysis has been subsequently planned to determine the internal consistency of the scale for local population.

Keywords: factorial analysis, sleep hygiene, sleep quality, adolescent sleep scale

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Authors: Ananth Malali, Rohan Prasad, Ananth Revankar, Chiranth Hulgur

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This paper aims to show evidence that value creation by sustainable methods is achieved when a relation is shared with a sustainability attribute between two or more companies in every stage of the supply chain. The pillars of this paper, the value creation factors, attributes of sustainability and various relations that exist between firms in a horizontally integrated supply chain are defined. Further, a relational analysis was done using a simple analysis tool built based on research. Couple of case studies from the German manufacturing and Australian retail sectors were considered for the intra industry analysis and comparison. Taking the analysis ahead, for inter-industry comparison, the same cases were scrutinised in order to understand how the sustainability attributes change across each industry. Concluding, this paper gives an overview of how companies can plan their strategies to attain sustainability through horizontal integration.

Keywords: horizontal integration, value creation, sustainable supply chain

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Authors: M. Chavleishvili

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The paper presents the analysis of the current situation of agricultural development in Georgia. The investment environment that supports development of the agricultural sector is evaluated and the key priorities are identified. The analysis of the projects already implemented with state and EU support, as well as those that are being currently implemented is presented. The policy and the programs supporting development of agricultural sector are analyzed. Based on an analysis of the evaluations of experts and the primary accounting documents, the outcomes of investment programs, their advantages and disadvantages, are studied. Through identifying investment programs in the agricultural sector of Georgia, corresponding conclusions are made, based on which some recommendations are developed.

Keywords: agriculture, investments, investment programs, projects

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Authors: Amin AminiKhafri, James M. Dawson-Edwards, Ryan M. Simpson, Simaan M. AbouRizk

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Earned value management (EVM) has been introduced as an integrated method to combine schedule, budget, and work breakdown structure (WBS). EVM provides various indices to demonstrate project performance including the cost performance index (CPI). CPI is also used to forecast final project cost at completion based on the cost performance during the project execution. Knowing the final project cost during execution can initiate corrective actions, which can enhance project outputs. CPI, however, is not constant during the project, and calculating the final project cost using a variable index is an inaccurate and challenging task for practitioners. Since CPI is based on the cumulative progress values and because of the learning curve effect, CPI variation dampens and stabilizes as project progress. Although various definitions for the CPI stability have been proposed in literature, many scholars have agreed upon the definition that considers a project as stable if the CPI at 20% completion varies less than 0.1 from the final CPI. While 20% completion point is recognized as the stability point for military development projects, construction projects stability have not been studied. In the current study, an empirical study was first conducted using construction project data to determine the stability point for construction projects. Early findings have demonstrated that a majority of construction projects stabilize towards completion (i.e., after 70% completion point). To investigate the effect of CPI stability on cost forecast accuracy, the correlation between CPI stability and project cost at completion forecast accuracy was also investigated. It was determined that as projects progress closer towards completion, variation of the CPI decreases and final project cost forecast accuracy increases. Most projects were found to have 90% accuracy in the final cost forecast at 70% completion point, which is inlined with findings from the CPI stability findings. It can be concluded that early stabilization of the project CPI results in more accurate cost at completion forecasts.

Keywords: cost performance index, earned value management, empirical study, final project cost

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Authors: Omar Abdillah, Mirna Adriani

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In this work, we perform new approach for analyzing public sentiment towards the presidential candidate in the 2014 Indonesian election that expressed in Twitter. In this study we propose such procedure for analyzing sentiment over Indonesian political message by understanding the behavior of Indonesian society in sending message on Twitter. We took different approach from previous works by utilizing punctuation mark and Indonesian sentiment lexicon that completed with the new procedure in determining sentiment towards the candidates. Our experiment shows the performance that yields up to 83.31% of average precision. In brief, this work makes two contributions: first, this work is the preliminary study of sentiment analysis in the domain of political message that has not been addressed yet before. Second, we propose such method to conduct sentiment analysis by creating decision making procedure in which it is in line with the characteristic of Indonesian message on Twitter.

Keywords: unsupervised sentiment analysis, political message, lexicon based, user behavior understanding

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Authors: Hasan Çiçekli, Ahmet Gökçen, Uğur Çam

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In this paper, a comparative performance analysis of mostly used four nonlinearity cancellation techniques used to realize the passive resistor by MOS transistors is presented. The comparison is done by using an integrator circuit which is employing sequentially Op-amp, OTRA and ICCII as active element. All of the circuits are implemented by MOS-C realization and simulated by PSPICE program using 0.35 µm process TSMC MOSIS model parameters. With MOS-C realization, the circuits became electronically tunable and fully integrable which is very important in IC design. The output waveforms, frequency responses, THD analysis results and features of the nonlinearity cancellation techniques are also given.

Keywords: integrator circuits, MOS-C realization, nonlinearity cancellation, tuneable resistors

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Authors: Habib Khodaverdiloo, Fatemeh Afrasiabi, Farrokh Asadzadeh, Martinus Th. Van Genuchten

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The soil particle-size distribution (PSD) is known to affect a broad range of soil physical, mechanical and hydraulic properties. Complete descriptions of a PSD curve should provide more information about these properties as opposed to having only information about soil textural class or the soil sand, silt and clay (SSC) fractions. We compared the accuracy of 19 different models of the cumulative PSD in terms of fitting observed data from a large number of Iranian soils. Parameters of the six most promising models were correlated with measured values of the field saturated hydraulic conductivity (Kfs), the mean weight diameter of soil aggregates (MWD), bulk density (ρb), and porosity (∅). These same soil properties were correlated also with conventional PSD parameters (SSC fractions), selected geometric PSD parameters (notably the mean diameter dg and its standard deviation σg), and several other PSD parameters (D50 and D60). The objective was to find the best predictions of several soil physical quality indices and the soil hydraulic properties. Neither SSC nor dg, σg, D50 and D60 were found to have a significant correlation with both Kfs or logKfs, However, the parameters of several cumulative PSD models showed statistically significant correlation with Kfs and/or logKfs (|r| = 0.42 to 0.65; p ≤ 0.05). The correlation between MWD and the model parameters was generally also higher than either with SSC fraction and dg, or with D50 and D60. Porosity (∅) and the bulk density (ρb) also showed significant correlation with several PSD model parameters, with ρb additionally correlating significantly with various geometric (dg), mechanical (D50 and D60), and agronomic (clay and sand) representations of the PSD. The fitted parameters of selected PSD models furthermore showed statistically significant correlations with Kfs,, MWD and soil porosity, which may be viewed as soil quality indices. Results of this study are promising for developing more accurate pedotransfer functions.

Keywords: particle size distribution, soil texture, hydraulic conductivity, pedotransfer functions

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Authors: B. Arend, P. Sunnen, P. Caire

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In a single case study, we show how a conversation analysis (CA) approach can shed light onto the sequential unfolding of human-robot interaction. Relying on video data, we are able to show that CA allows us to investigate the respective turn-taking systems of humans and a NAO robot in their dialogical dynamics, thus pointing out relevant differences. Our fine grained video analysis points out occurring breakdowns and their overcoming, when humans and a NAO-robot engage in a multimodally uttered multi-party communication during a sports guessing game. Our findings suggest that interdisciplinary work opens up the opportunity to gain new insights into the challenging issues of human robot communication in order to provide resources for developing mechanisms that enable complex human-robot interaction (HRI).

Keywords: human robot interaction, conversation analysis, dialogism, breakdown, museum

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Authors: Maxime Vignon

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This study delves into the discourse surrounding Africatown ancestors’ will, through a rigorous discourse analysis, to reveal the intricate narratives shaping heritage and identity within this unique community. Situated near Mobile, Alabama, Africatown traces its origins to the Clotilda, the last known slave ship to bring captives from Africa to the United States. Through a meticulous examination of Africatown ancestors posthumous will, this analysis aims to uncover the spiritual linguistic nuances which will contribute to the preservation of Africatown's ancestral heritage and the construction of individual self and collective empowerment. This research will be grounded in Michel Foucault discourse. In its attempt to analyze the four core elements of discourse, this study explores the role of rituals and spiritual discourses within the will of Africatown ancestors. Additionally, it delves into the descendants’ public appearance scrutinizing the use of ancestral names and identities. Ultimately, this discourse analysis contributes to a nuanced understanding of how language and narrative from the ancestors would shape unity, a valuable insight into the complexities of identity formation and the enduring impact of the transatlantic slave trade on this resilient community.

Keywords: applied linguistics, culture, discourse analysis, identity, spirituality, transatlantic slave trade

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Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba

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The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.

Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry

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Authors: Tiantian Ma

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The district of Doumen, Zhuhai has a sophisticated seabass value chain. However, unlike typical Global Value Chain (GVC) industries, the seabass value chain in Doumen is highly domestic both in terms of production and consumption. Still, since the highly-industrialized and capital-intensive industry involves many off-farm segments in both upstream and downstream, this paper will be utilizing the method of value chain analysis. To be specific, the paper will concentrate on two research goals: 1) the value chain mapping of the seabass industry, such as identifying actors in the hatchery, fish feed, fishponds, processing, logistics, and distribution, 2) the SWOT analysis of the seabass industry in Doumen, including incompetence of the waste disposal, the strategy of marketing, and the supportive role of the government, etc. In general, the seabass industry in Doumen is a sophisticated but not yet comprehensive value chain. It has achieved a lot in industrializing aqua-food products and fostering development, but there are still improvements that could be carried out, such as upholding environmental sustainability and promoting the brand better.

Keywords: agricultural value chain, fish farming, regional development, SWOT analysis, value chain mapping

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Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Rotem Mashkov, Noam Shoval

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In an age when a tourist’s gaze is more focused on the daily lives of locals, it is evident that local food markets are being rediscovered. Traditional urban markets succeed in reinventing themselves as a space for consumption, recreation, and culture, enabling authentic experiences and interpersonal interactions with the local culture. Alongside this, the pressure of tourism development may result in commercialization and retail gentrification to the point of losing the sense of local identity. The issue of finding a balance between tourism development and the preservation of unique local features is at the heart of this study and is being tested using the case of the Mahane Yehuda market in Jerusalem. The research question—how merchants respond to tourism development in the Mahane Yehuda food market— focuses on local traders, a group of players who are usually absent from the research arenas, although they influence tourism development as well as influenced by it. Three main research methods were integrated into this study. The first two methods, a survey of articles survey and comparative mapping of the business mix, were used to characterize the changes in the Mahane Yehuda market both consciously and physically. The third research method, involving in-depth interviews with merchants, was used to examine the traders' attitudes and responses to tourism development. The findings indicate that there has been a turnaround in the market image over the past decade and a half. Additionally, there has been a significant physical change in the business mix, reflected by a decline of 15% in the number of stalls selling food products and delicacies. The data from the interviews on the traders’ attitudes towards tourism development were inconclusive; there were disagreements among the traders about the economic contribution of tourism development in relation to their dependence on the tourism industry. However, there was a consensus on the need for authentic elements in the marketplace. The findings of the study also indicate a strong link between the merchants’ response to tourism development and their stall ownership status as the merchant could exercise their position in various ways depending on the possession type.

Keywords: business mix, Jerusalem, local food markets, Mahane Yehuda market, merchants’ attitude, ownership status, retail gentrification, tourism development, traditional urban markets

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Khulud M. Rahuma, Ibrahim B. Younis

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Assessment of petrophysical parameters are very essential for reservoir engineer. Three techniques can be used to predict reservoir properties: well logging, well testing, and core analysis. Cementation factor and saturation exponent are very required for calculation, and their values role a great effect on water saturation estimation. In this study a sensitive analysis was performed to investigate the influence of cementation factor and saturation exponent variation applying logs, and core analysis. Measurements of water saturation resulted in a maximum difference around fifteen percent.

Keywords: porosity, cementation factor, saturation exponent, formation factor, water saturation

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Nadim Zgheib, Sivaramakrishnan Balachandar

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We present results on the initial formation of ripples from an initially flattened erodible bed. We use direct numerical simulations (DNS) of turbulent open channel flow over a fixed sinusoidal bed coupled with hydrodynamic stability analysis. We use the direct forcing immersed boundary method to account for the presence of the sediment bed. The resolved flow provides the bed shear stress and consequently the sediment transport rate, which is needed in the stability analysis of the Exner equation. The approach is different from traditional linear stability analysis in the sense that the phase lag between the bed topology, and the sediment flux is obtained from the DNS. We ran 11 simulations at a fixed shear Reynolds number of 180, but for different sediment bed wavelengths. The analysis allows us to sweep a large range of physical and modelling parameters to predict their effects on linear growth. The Froude number appears to be the critical controlling parameter in the early linear development of ripples, in contrast with the dominant role of particle Reynolds number during the equilibrium stage.

Keywords: direct numerical simulation, immersed boundary method, sediment-bed interactions, turbulent multiphase flow, linear stability analysis

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Authors: A. D. Parekh, P. R. Tailor

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The Montreal protocol and Kyoto protocol underlined the need of substitution of CFC’s and HCFC’s due to their adverse impact on atmospheric ozone layer which protects earth from U.V rays. The CFCs have been entirely ruled out since 1995 and a long-term basis HCFCs must be replaced by 2020. All this events motivated HFC refrigerants which are harmless to ozone layer. In this paper thermodynamic analysis of cascade refrigeration system has been done using three different refrigerant pairs R13-R12, R290-R23, and R404A-R23. Effect of various operating parameters i.e evaporator temperature, condenser temperature, temperature difference in cascade condenser and low temperature cycle condenser temperature on performance parameters viz. COP, exergetic efficiency and refrigerant mass flow ratio have been studied. Thermodynamic analysis shows that out of three refrigerant pairs R12-R13, R290-R23 and R404A-R23 the COP of R290-R23 refrigerant pair is highest.

Keywords: thermodynamic analysis, cascade refrigeration system, COP, exergetic efficiency

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Authors: Siddhartha Dhungana

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This article primarily explores dimensions in English language teacher's professionalism so that a teacher could reflect and make a strategic professional devotion to implement effective educational programs for the present and the future. The paper substantially incorporates the eastern Hindu practices, especially life values from the Bhagavad Gita, as a basis of teacher’s professional enrichment. Basically, it applies three categorical practices, i.e., Karma Yoga, Jnana Yoga, and Bhakti Yoga, in teachers’ professionality to illustrate, ignite further ahead and sharpen academic journey, professional journey, and professional devotion reflecting common practices. In this journey, a teacher comes to a stage of professional essence as s/he surpasses Karma Yoga, Jnana Yoga, and Bhakti Yoga with their basic quality formation. To illustrate their essence-making process, the three narrative stories for each category mentioned above are analyzed. The data collected from a research participant who has a high level of professional success and who inspires all English Language teachers in Nepal to develop stories for narrative analysis. The narrative analysis is based on eastern themes that are supported by Vygotsky's concept of developmental psychology. Moreover, the structural analysis is based on Gary Barkhuizen's narrative analysis.

Keywords: Karma Yoga, Jnana Yoga, Bhakti Yoga, Vygotsky's concepts, narrative analysis

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: dynamic analysis, finite element methods, ship structure, vibration analysis

Procedia PDF Downloads 128

Authors: Chun-Liang Wu, Kai-Ping Shaw, Cheng-Ping Yu, Wu-Chien Chien, Hsiao-Ting Chen, Shao-Huang Wu

Abstract:

Objective: This study analyzed three criminal judicial cases. We applied the damage analysis of the two vehicles to verify other evidence, such as dashboard camera records of each accident, reconstruct the scenes, and pursue the truth. Methods: Evidence analysis, the method is to collect evidence and the reason for the results in judicial procedures, then analyze the involved damage evidence to verify other evidence. The collision damage analysis method is to inspect the damage to the vehicles and utilize the principles of tool mark analysis, Newtonian physics, and vehicle structure to understand the relevant factors when the vehicles collide. Results: Case 1: Sedan A turned right at the T junction and collided with Scooter B, which was going straight on the left road. The dashboard camera records showed that the left side of Sedan A’s front bumper collided with the body of Scooter B and rider B. After the analysis of the study, the truth was that the front of the left side of Sedan A impacted the right pedal of Scooter B and the right lower limb of rider B. Case 2: Sedan C collided with Scooter D on the left road at the crossroads. The dashboard camera record showed that the left side of the Sedan C’s front bumper collided with the body of Scooter D and rider D. After the analysis of the study, the truth was that the left side of the Sedan C impacted the left side of the car body and the front wheel of Scooter D and rider D. Case 3: Sedan E collided with Scooter F on the right road at the crossroads. The dashboard camera record showed that the right side of the Sedan E’s front bumper collided with the body of Scooter F and rider F. After the analysis of the study, the truth was that the right side of the front bumper and the right side of the Sedan F impacted the Scooter. Conclusion: The application of collision damage analysis in the reconstruction of a sedan-scooter collision could discover the truth and provide the basis for judicial justice. The cases and methods could be the reference for the road safety policy.

Keywords: evidence analysis, collision damage analysis, accident reconstruction, sedan-scooter collision, dashboard camera records

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Authors: Azmat Farooq Ahmad Khurram, Sadaf Aslam

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This meta-analysis systematically examines the use of artificial intelligence (AI) in instructional methods across diverse educational settings through a thorough analysis of empirical research encompassing various disciplines, educational levels, and regions. This study aims to assess the effects of AI integration on teaching methodologies, classroom dynamics, teachers' roles, and student engagement. Various research methods were used to gather data, including literature reviews, surveys, interviews, and focus group discussions. Findings indicate paradigm shifts in teaching and education, identify emerging trends, practices, and the application of artificial intelligence in learning, and provide educators, policymakers, and stakeholders with guidelines and recommendations for effectively integrating AI in educational contexts. The study concludes by suggesting future research directions and practical considerations for maximizing AI's positive influence on pedagogical practices.

Keywords: artificial intelligence, teaching practices, meta-analysis, teaching-learning

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Authors: Vramori Mitra, Bornali Sarma, Arun K. Sarma

Abstract:

Recurrence is a ubiquitous feature of any real dynamical system. The states in phase space trajectory of a system have an inherent tendency to return to the same state or its close state after certain time laps. Recurrence quantification analysis technique, based on this fundamental feature of a dynamical system, detects evaluation of state under variation of control parameter of the system. The paper presents the investigation of nonlinear dynamical behavior of plasma floating potential fluctuations obtained by using a Langmuir probe in different magnetic field under the variation of discharge voltages. The main measures of recurrence quantification analysis are considered as determinism, linemax and entropy. The increment of the DET and linemax variables asserts that the predictability and periodicity of the system is increasing. The variable linemax indicates that the chaoticity is being diminished with the slump of magnetic field while increase of magnetic field enhancing the chaotic behavior. Fractal property of the plasma time series estimated by DFA technique (Detrended fluctuation analysis) reflects that long-range correlation of plasma fluctuations is decreasing while fractal dimension is increasing with the enhancement of magnetic field which corroborates the RQA analysis.

Keywords: detrended fluctuation analysis, chaos, phase space, recurrence

Procedia PDF Downloads 324