Search results for: hidden motives of buyers and sellers

Authors: Pajaree Naramitpanich, Natchanok Jansawang, Panwilai Chomchid

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The aims of this are compared between the students’ logical thinking abilities of their learning for designing the 5-lesson instructional plans of the 2-instructional methods, namely; the STEM Education and the Creative Learning Process (CLP) for developing students’ logical thinking abilities that a sample consisted of 90 students from two chemistry classes of different learning outcomes in Wapi Phathum School with the cluster random sampling technique was used at the 11th grade level. To administer of their learning environments with the 45-experimenl student group by the STEM Education method and the 45-controlling student group by the Creative Learning Process. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of the STEM Education and the Creative Learning Process to enhance the logical thinking tests on Mineral issue were used. The efficiency of the Creative Learning Processes (CLP) Model and the STEM Education’s innovations of these each five instructional lesson plans based on criteria are higher than of 80/80 standard level with the IOC index from the expert educators. The averages mean scores of students’ learning achievement motives were assessed with the Pre and Post Techniques and Logical Thinking Ability Test (LTAT) and dependent t-test analysis were differentiated between the CLP and the STEM, significantly. Students’ perceptions of their chemistry classroom environment inventories with the MCI with the CLP and the STEM methods also were found, differently. Associations between students’ perceptions of their chemistry classroom learning environment inventories on the CLP Model and the STEM Education learning designs toward their logical thinking abilities toward chemistry, the predictive efficiency of R2 values indicate that 68% and 76% of the variances in students’ logical thinking abilities toward chemistry to their controlling and experimental chemistry classroom learning environmental groups with the MCI were correlated at .05 levels, significantly. Implementations of this result are showed the students’ learning by the CLP of the potential thinking life-changing roles in most their logical thinking abilities that it is revealed that the students perceive their abilities to be highly learning achievement in chemistry group are differentiated with the STEM education of students’ outcomes.

Keywords: design, the lesson instructional plans, the stem education, the creative learning process, logical thinking ability, different, learning outcome, student, chemistry class

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Karakhalis N. B.

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This study aimed to determine the prevalence of heparin resistance among cardiac surgical pediatric and neonatal patients and identify associated risk factors. Materials and Methods: The study included 306 pediatric and neonatal patients undergoing on-pump cardiac surgery. Patients whose activated clotting time (ACT) targets were achieved after the first administration of heparin formed the 1st group (n=280); the 2nd group (n=26) included patients with heparin resistance. The initial assessment of the haemostasiological profile included determining the PT, aPPT, FG, AT III activity, and INR. Intraoperative control of heparinization was carried out with a definition of ACT using a kaolin activator. A weight-associated protocol at the rate of 300 U/kg with target values of ACT >480 sec was used for intraoperative heparinization. Results: The heparin resistance was verified in 8.5% of patients included in the study. Repeated heparin administration at the maximum dose of≥600 U/kg is required in 80.77% of cases. Despite additional heparinization, 19.23% of patients had FFP infusion. There was reduced antithrombin activity in the heparin resistance group (p=0.01). Most patients with heparin resistance (57.7%) were pretreated with low molecular weight heparins during the preoperative period. Conclusion: Determining the initial level of antithrombin activity can predict the risk of developing heparin resistance. The factor analysis verified hidden risk factors for heparin resistance to the heparin pretreatment, chronic hypoxia, and chronic heart failure.

Keywords: congenital heart disease, heparin, antithrombin, activated clotting time, heparin resistance

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Authors: Hussain Hameed Mayuuf

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The study is an attempt to investigate the conceptual metonymies is used in political discourse about COVID-19. Thus, this study tries to analyze and investigate how the conceptual metonymies in Johnson's speech about coronavirus are constructed. This study aims at: Identifying how are metonymies relevant to understand the messages in Boris Johnson speeches and to find out how can conceptual blending theory help people to understand the messages in the political speech about COVID-19. Lastly, it tries to Point out the kinds of integration networks are common in political speech. The study is based on the hypotheses that conceptual blending theory is a powerful tool for investigating the intended messages in Johnson's speech and there are different processes of blending networks and conceptual mapping that enable the listeners to identify the messages in political speech. This study presents a qualitative and quantitative analysis of four speeches about COVID-19; they are said by Boris Johnson. The selected data have been tackled from the cognitive-semantic perspective by adopting Conceptual Blending Theory as a model for the analysis. It concludes that CBT is applicable to the analysis of metonymies in political discourse. Its mechanisms enable listeners to analyze and understand these speeches. Also the listener can identify and understand the hidden messages in Biden and Johnson's discourse about COVID-19 by using different conceptual networks. Finally, it is concluded that the double scope networks are the most common types of blending of metonymies in the political speech.

Keywords: cognitive, semantics, conceptual, metonymical, Covid-19

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Rogaleva Liudmila, Malkin Valery

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Physical culture lessons are considered not only to be a means of physical development of students, but a matter of their personal development. Physical culture lessons can enable to develop such qualities of students as activity and initiation, readiness to cooperate, self-confidence, ability to define and reach targets, readiness to overcome difficulties and assess their abilities (and disadvantages) properly in any precise situation as well to be responsible for their own decision. The solution of this problem is possible under the circumstance if the students aware themselves as the subject of the activity that are able to develop their possibilities. The research was aimed to learn the matters that enable female teenagers of senior forms to become strong personalities attending physical culture lessons. There were two stages of the research. At the first stage we define the interests and demands of the girls. According the results of research we changed the programme of physical culture lessons. We took into consideration values of youth subculture: youth music, preferences to sport-dancing physical activities, demand of self-determination, revealing their individualities, needs of cooperative work. At the second stage we worked out motivating technology of course. This technology was aimed to create sush conditions under which students could show themselves as the subjects of activity and self-development. The active participation sport-dance festivals during 2-3 years creates the conditions for their self-realization. 78% students of the experimental groups considered their main motives to were: the interest, developing of their abilities, the satisfaction of the achievements of targets. Control groups 67% of the students claimed the success school good marks. The girls said that due to festivals they became self-confident (94%), responsible (86%), ability to cooperate (73%), aspiration for reaching the target (68%), self-exactingness (57 %). The main factors that provide successful performance were called: efforts to reach the target (87%), mutual support and mutual understanding (77%). The research on values showed that in the experimental groups we can find increase of importance of such values as: social initiative (active life) 83%, friends (75%), self-control (73%), effectiveness in deeds (58%).

Keywords: physical culture, subject, personal development, self-determination

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Authors: Ankita Wadhawan, Parteek Kumar, Umesh Kumar

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Gesture is any body movement that expresses some attitude or any sentiment. Gestures as a sign language are used by deaf people for conveying messages which helps in eliminating the communication barrier between deaf people and normal persons. Nowadays, everybody is using mobile phone and computer as a very important gadget in their life. But there are some physically challenged people who are blind/deaf and the use of mobile phone or computer like device is very difficult for them. So, there is an immense need of a system which works on body gesture or sign language as input. In this research, Microsoft Kinect Sensor, SDK V2 and Hidden Markov Toolkit (HTK) are used to recognize the object, motion of object and human body joints through Touch less NUI (Natural User Interface) in real-time. The depth data collected from Microsoft Kinect has been used to recognize gestures of Indian Sign Language (ISL). The recorded clips are analyzed using depth, IR and skeletal data at different angles and positions. The proposed system has an average accuracy of 85%. The developed Touch less NUI provides an interface to recognize gestures and controls the cursor and click operation in computer just by waving hand gesture. This research will help deaf people to make use of mobile phones, computers and socialize among other persons in the society.

Keywords: gesture recognition, Indian sign language, Microsoft Kinect, natural user interface, sign language

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Authors: Yi Yin Chen, Changsoo Hur

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This study explores the role of totems and decorative texts on an indigenous primary school campus in Taiwan, as well as how they affect the building of the cultural identity of indigenous students. By employing Roland Barthes' semiotic theory, this research aims to uncover the cultural meanings and social functions contained in these visual symbols, as well as their significance for building a cultural identity among indigenous students. The study uses a qualitative method, combining observations, interviews, and document analysis to explore how these symbols perform as carriers of hidden meaning and contribute to educational and cultural settings. The findings show that totems on the indigenous school campus reflect the ethnic group's cultural background knowledge, allowing students to study their cultural heritage and providing a sense of belonging. However, certain textual decorations also reflect the historical influence of the hegemonic government attempting to establish moral norms in the ethnic group. This coexistence of traditional ethnic totems and hegemonic textual admonitions in the school environment creates a complex identity landscape for students, leading to a multiplicity of cultural identities. It underlines the importance of culturally relevant symbols in enhancing students' cultural heritage and identity and presents the challenges posed by conflicting cultural messages within the educational context.

Keywords: Roland Barthes, semiotic, Indigenous, Bunun

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Authors: Xian Chen

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In recent years, the tendency that the decline of material and social vitality of old city in China becomes more and more serious. Nowadays, transformation and renewal of the old city have become a hot topic in urban research. The traditional mode of large-scale promotion has been criticized. Thus, exploration of new ways to update the city turns to be a necessity on the way of sustainable urban development. Pocket Park is a small city open space, its location choose is based on abandoned or idle lands on urban structure, is scattered or hidden in corner of the urban. It has a great significance on improving the old city environment. Based on the theory of ‘pocket park’, this paper summarizes the successful experience of domestic and foreign practice, and discusses the update strategies which are suitable for China's national conditions according to the characteristics and predicament of the old city in China. The main methods and results are as follows: 1)Based on the conception of ‘pocket park’, though describing the research status in domestic and foreign, summarizing the experience which is worth learning and existing problems. 2) From the analysis of ‘pocket park’ function, general design principles and types of the deep-seated difficulties in renewal the old city and the possibility of the application of ‘pocket park’,the varied implementation of ‘pocket park’ form are established, and application value in the old city renewal are summed up. 3) It can’t be denied that pocket park plays an irreplaceable role in solving the recession and renewing the vitality of the old city. Anymore, It is recommended to develop corresponding supportive development policies.

Keywords: sustainable development, strategy, old city renewal, pocket park

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Authors: Baglan Bazylova

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The purpose of our article is to consider the social and psychological conflicts in Lyudmila Petrushevskaya’s stories as an artistic presentation of gender structure of modern society; to reveal originality of the characters’ inner world, the models of their behavior expressing the gender specific nature of modern feminine prose. Gender conflicts have taken the leading place in the modern prose. L. Petrushevskaya represents different types of conflicts including those which are shown in the images of real contradictions in the stories "Narratrix", "Thanks to Life”, "Virgin's Case", "Father and Mother". In the prose of Petrushevskaya the gender conflicts come out in two dimensions: The first one is love relations between a man and a woman. Because of the financial indigence, neediness a woman can’t afford herself even to fall in love and arrange her family happiness. The second dimension is the family conflict because of the male adultery. Petrushevskaya fixed on the unmanifistated conflict in detail. In the real life such gender conflict can appear in different forms but for the writer is important to show it as a life basis, hidden behind the externally safe facade of “the family happiness”. In the stories of L. Petrushevskaya the conflicts reflect the common character of the social and historical situations in which her heroines find themselves, in situations where a woman feels her opposition to the customary mode of life. The types of gender conflicts of these stories differ in character of verbal images. They are presented by the verbal and event ranks creating the conflicts just in operation.

Keywords: gender behavior of heroes, gender conflict, gender picture of the world, gender structure

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Authors: Nana Weng

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From 2008, Chinese Foreign Direct Investment flows to the European Union continued its rapid rise. Currently, the industrial structure adjustment in developing countries has also been placed on the international movement of factors of production. Now China economy is in an important period of transformation on industrial structure adjustment. Under the international transfer of industry background, the adjustment of industrial structure upgrading and sophistication are the key elements of a successful economic transformation. In order to achieve a virtuous cycle of foreign investment patterns and optimize the industrial structure of foreign direct investment as well, the research on the positive the role of the EU direct investment and how it impact China’s industrial structure optimization and upgrading is of great significance. In this paper, the author explained how the EU as an investment destination is different with the United States and ASEAN. Then, based on the theory of FDI and industrial structure and combining the four kinds of motives of China’s ODI in EU, this paper explained the impact mechanism which has influenced China domestic industrial structure primarily through the Transfer effect, Correlation effect and Competitive effect. On the premise that FDI activities do affect the home country’s domestic industrial structure, this paper made empirical analysis with industrial panel data. With the help of Gray Correlation Method and Limited Distributed Lags, this paper found that China/s ODI in the EU impacted the tertiary industry strongly and had a significant positive impact, particularly the manufacturing industry and the financial industry. This paper also pointed out that Chinese MNEs should realize several issues, such as pay more attention to high-tech industries so that they can make the best use of reverse technology spillover. When Chinese enterprises ‘go out,' they ought to keep in mind that domestic research and development capital contribution can make greater economic growth. Finally, based on theoretical and empirical analysis results, this paper presents the industry choice recommendations in the future of the EU direct investment, particularly through the development of the proper rational industrial policy and industrial development strategic to guide the industrial restructuring and upgrading.

Keywords: china ODI in european union, industrial structure optimization, impact mechanism, empirical analysis

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Authors: Ashok Sachdeva

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This research paper delves into the application of digital tools, especially Voyant Tools and AntConc version 4.0, for the analysis and interpretation of Seamus Heaney's poems. Scholars and literary aficionados can acquire deeper insights into Heaney's writings by utilising these tools, revealing hidden nuances and improving their knowledge. This paper outlines the methodology used, presents sample analyses and evaluates the merits and limitations of using digital tools in literary analysis. The combination of traditional close reading with digital analysis tools promises to offer new paths for understanding Heaney's vast tapestry of poetry. Seamus Heaney, a Nobel winner known for his vivid poetry, provides a treasure mine of literary discovery. The advent of digital tools gives an exciting opportunity to reveal previously unknown layers of meaning within his works. This paper investigates the use of Voyant Tools and AntConc version 4.0 to analyse and understand Heaney's writings, demonstrating the symbiotic relationship between traditional literary analysis and cutting-edge digital methodologies. Methodology: To demonstrate the efficiency of digital tools in the analysis of Heaney's poetry, a sample of his notable works will be entered into Voyant Tools and AntConc version 4.0. The former provides a graphic representation of word frequency, word clouds, and patterns over numerous poems. The latter, a concordance tool, enables detailed linguistic analysis, revealing patterns, and linguistic subtleties.

Keywords: digital tools, resonance, assonance, alliteration, creative quotient

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Authors: Abdolmajid Mosleh, Afzal Ghasimi

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The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.

Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company

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Authors: John Hardy

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The early twenty-first century national security environment has been characterized by political coercion. Despite an abundance of political commentary on the various forms of non-state coercion leveraged against the state, there is a lack of literature which distinguishes between the mechanisms and the mediums of coercion. Frequently non-state movements seeking to coerce the state are labelled by their tactics, not their strategies. Terrorists, insurgencies and social movements are largely defined by the ways in which they seek to influence the state, rather than by their political aims. This study examines the strategies of coercion used by non-state actors against states. This approach includes terrorist groups, insurgencies, and social movements who seek to coerce state politics. Not all non-state actors seek political coercion, so not all examples of different group types are considered. This approach also excludes political coercion by states, focusing on the non-state actor as the primary unit of analysis. The study applies a general theory of political coercion, which is defined as attempts to change the policies or action of a polity against its will, to the strategies employed by terrorist groups, insurgencies, and social movements. This distinguishes non-state actors’ strategic objectives from their actions and motives, which are variables that are often used to differentiate between types of non-state actors and the labels commonly used to describe them. It also allows for a comparative analysis of theoretical perspectives from the disciplines of terrorism, insurgency and counterinsurgency, and social movements. The study finds that there is a significant degree of overlap in the way that different disciplines conceptualize the mechanism of political coercion by non-state actors. Studies of terrorism and counterterrorism focus more on the notions of cost tolerance and collective punishment, while studies of insurgency focus on a contest of legitimacy between actors, and social movement theory tend to link political objectives, social capital, and a mechanism of influence to leverage against the state. Each discipline has a particular vernacular for the mechanism of coercion, which is often linked to the means of coercion, but they converge on three core theoretical components of compelling a polity to change its policies or actions: exceeding resistance to change, using political or violent punishments, and withholding legitimacy or consent from a government.

Keywords: counter terrorism, homeland security, insurgency, political coercion, social movement theory, terrorism

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Lin-Han Chiang Hsieh, Hsiao-Yi Lin

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This study aims to determine the impact of the disclosure of flood potential map on housing prices. The disclosure is supposed to mitigate the market failure by reducing information asymmetry. On the other hand, opponents argue that the official disclosure of simulated results will only create unnecessary disturbances on the housing market. This study identifies the impact of the disclosure of the flood potential map by comparing the hedonic price of flood potential before and after the disclosure. The flood potential map used in this study is published by Taipei municipal government in 2015, which is a result of a comprehensive simulation based on geographical, hydrological, and meteorological factors. The residential property sales data of 2013 to 2016 is used in this study, which is collected from the actual sales price registration system by the Department of Land Administration (DLA). The result shows that the impact of flood potential on residential real estate market is statistically significant both before and after the disclosure. But the trend is clearer after the disclosure, suggesting that the disclosure does have an impact on the market. Also, the result shows that the impact of flood potential differs by the severity and frequency of precipitation. The negative impact for a relatively mild, high frequency flood potential is stronger than that for a heavy, low possibility flood potential. The result indicates that home buyers are of more concern to the frequency, than the intensity of flood. Another contribution of this study is in the methodological perspective. The classic hedonic price analysis with OLS regression suffers from two spatial problems: the endogeneity problem caused by omitted spatial-related variables, and the heterogeneity concern to the presumption that regression coefficients are spatially constant. These two problems are seldom considered in a single model. This study tries to deal with the endogeneity and heterogeneity problem together by combining the spatial fixed-effect model and geographically weighted regression (GWR). A series of literature indicates that the hedonic price of certain environmental assets varies spatially by applying GWR. Since the endogeneity problem is usually not considered in typical GWR models, it is arguable that the omitted spatial-related variables might bias the result of GWR models. By combing the spatial fixed-effect model and GWR, this study concludes that the effect of flood potential map is highly sensitive by location, even after controlling for the spatial autocorrelation at the same time. The main policy application of this result is that it is improper to determine the potential benefit of flood prevention policy by simply multiplying the hedonic price of flood risk by the number of houses. The effect of flood prevention might vary dramatically by location.

Keywords: flood potential, hedonic price analysis, endogeneity, heterogeneity, geographically-weighted regression

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Mai Awad

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This paper aims to focus on the phenomenon of martyrdom—particularly its performative aspect—and how social and popular cultural representations address the multiple meanings of the loaded image of a Palestinian martyr. This focus will help us to explore the possible reasons that might push Palestinians to consider pursuing “martyrdom” or suicide operations. Tracing what happened in the past and what is currently happening (that is, haunting) will aid in theorizing how the act/practice of “martyrdom” is produced. It is believed that there are social and political forces, particularly in a colonial society like Palestine, that influence the subject and its experience. But what is unique about this paper is its attempt to disclose the invisible, hidden narratives and complexities of Palestinian life that we do not see. By giving “martyrs” a chance to speak and express their own narratives—since “martyrs” usually leave written letters for their families, which are published after their death—this study must broaden the whole picture and discuss what is missing. The analytic method to be used: For the methodology, the paper recruits discourse analysis as a method for tracing the emergence, circulation, and productivity of the martyrdom discourse across a range of social practices in Palestinians’ everyday life after the Nakba. The paper analyzes the letters that “martyrs” left to their families, relatives, and the Palestinian community after their death. By letting “martyrs” speak for themselves and hearing their unique discourses, the research would suggest that more explanation is needed to describe the “martyr” identity. Hence, it is not possible to study the “martyr” identity in Palestine without understanding the colonial context that governs it and shapes their subjective experience.

Keywords: martyrdom, palestine, haunting, nakba 1948

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Vertika Goswami, Gargi Sharma

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The rapid evolution of fintech has led to the rise of robo-advisor platforms that utilize artificial intelligence (AI) and machine learning to offer personalized investment solutions efficiently and cost-effectively. This research paper conducts a comprehensive sentiment analysis of investor experiences with these platforms, employing natural language processing (NLP) and sentiment classification techniques. The study investigates investor perceptions, engagement, and satisfaction, identifying key drivers of positive sentiment such as clear communication, low fees, consistent returns, and robust security. Conversely, negative sentiment is linked to issues like inconsistent performance, hidden fees, poor customer support, and a lack of transparency. The analysis reveals that addressing these pain points—through improved transparency, enhanced customer service, and ongoing technological advancements—can significantly boost investor trust and satisfaction. This paper contributes valuable insights into the fields of behavioral finance and fintech innovation, offering actionable recommendations for stakeholders, practitioners, and policymakers. Future research should explore the long-term impact of these factors on investor loyalty, the role of emerging technologies, and the effects of ethical investment choices and regulatory compliance on investor sentiment.

Keywords: artificial intelligence in finance, automated investment, financial technology, investor satisfaction, investor sentiment, robo-advisors, sentimental analysis

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Authors: Saimir Heta, Kers Kapaj, Rialda Xhizdari, Ilma Robo

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Dealing with emerging cases of dental malpractice with justifications that stem from the clear rules of dental ethics is a phenomenon with an increasing trend in today's dental practice. Dentists should clearly understand how far the limit of malpractice goes, with or without minimal or major consequences, for the affected patient, which can be justified as a complication of dental treatment, in support of the rules of dental ethics in the dental office. Indeed, malpractice can occur in cases of lack of professionalism, but it can also come as a consequence of anatomical and physiological limitations in the implementation of the dental protocols, predetermined and indicated by the patient in the paragraph of the treatment plan in his personal card. This study is of the review type with the aim of the latest findings published in the literature about the problem of dealing with these phenomena. The combination of keywords is done in such a way with the aim to give the necessary space for collecting the right information in the networks of publications about this field, always first from the point of view of the dentist and not from that of the lawyer or jurist. From the findings included in this article, it was noticed the diversity of approaches towards the phenomenon depends on the different countries based on the legal basis that these countries have. There is a lack of or a small number of articles that touch on this topic, and these articles are presented with a limited number of data on the same topic. Conclusions: Dental malpractice should not be hidden under the guise of various dental complications that we justify with the strict rules of ethics for patients treated in the dental chair. The individual experience of dental malpractice must be published with the aim of serving as a source of experience for future generations of dentists.

Keywords: dental ethics, malpractice, professional protocol, random deviation

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Authors: Tarek Soliman Mostafa Soliman Al-Nana'i

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There are non-steady voiced augments in the Semitic languages, and in the morphological and structural augmentation, two sounds were augments in all Semitic languages at the level of the spoken language and two letters at the level of the written language, which are the hamza and the ta’. This research studies only the second of them; Therefore, we defined it as “The Voiceless Dental- alveolar common augment” (VDACA) to distinguish it from the glottal sound “Hamza”, first, middle, or last, in a noun or in a verb, in Arabic and its equivalent in the Semitic languages. What is meant by “VDACA” is the ta’ that is in addition to the root of the word at the morphological level: the word “voiceless” takes out the voiced sounds that we studied before, and the “dental- alveolar common augment” takes out the laryngeal sound of them, which is the “Hamza”: and the word “common” brings out the uncommon voiceless sounds, which are sīn, shīn, and hā’. The study is limited to the ta' alone among the Arabic sounds, and this title faced a problem in identifying it with the ta'. Because the designation of the ta is not the same in most Semitic languages. Hebrew, for example, has “tav” and is pronounced with the voiced fa (v), which is not in Arabic. It is called different names in other Semitic languages, such as “taw” or “tAu” in old Syriac. And so on. This goes hand in hand with the insistence on distance from the written level and the reference to the phonetic aspect in this study that is closely and closely linked to the morphological level. Therefore, the study is “morphophonemic”. What is meant by Semitic languages in this study are the following: Akkadian, Ugaritic, Hebrew, Syriac, Mandaean, Ge'ez, and Amharic. The problem of the study is the agreement or difference between these languages in the position of that augment, first, middle, or last. And in determining the distinguishing characteristics of each language from the other. As for the study methodology, it is determined by the comparative approach in Semitic languages, which is based on the descriptive approach for each language. The study is divided into an introduction, four sections, and a conclusion: Introduction: It included the subject of the study, its importance, motives, problem, methodology, and division. The first section: VDACA as a non-common phoneme. The second: VDACA as a common phoneme. The third: VDACA as a functional morpheme. The fourth section: Commentary and conclusion with the most important results. The positions of VDACA in Arabic and other Semitic languages, and in nouns and verbs, were limited to first, middle, and last. The research identified the individual addition, which is common with other augments, and the research proved that this augmentation is constant in all Semitic languages, but there are characteristics that distinguish each language from the other.

Keywords: voiceless -, dental- alveolar, augment, Arabic - semitic languages

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Ali Essam El Shazly

Abstract:

The slum survey of 'Sequina' area in Alexandria details the building rooms of twenty-building samples according to the integral measure of space syntax. The essence of room organization sets the most integrative 'visitor' domain between the 'inhabitant' wings of less integrated 'parent' than the 'children' structure with visual ring of 'balcony' space. Despite the collective real relative asymmetry of 'pheno-type' aggregation, the relative asymmetry of individual layouts reveals 'geno-type' structure of spatial diversity. The multifunction of rooms optimizes the integral structure of graph and visibility merge, which contrasts with the deep tailing structure of distinctive social domains. The most integrative layout inverts the geno-type into freed rooms of shallow 'inhabitant' domain against the off-centered 'visitor' space, while the most segregated layout further restricts the pheno-type through isolated 'visitor' from 'inhabitant' domains across the 'staircase' public domain. The catalyst 'kitchen & living' spaces demonstrate multi-structural dimensions among the various social domains. The former ranges from most exposed central integrity to the most hidden 'motherhood' territories. The latter, however, mostly integrates at centrality or at the further ringy 'childern' domain. The study concludes social structure of spatial integrity for redevelopment, which is determined through the micro-level survey of rooms with integral dimensions.

Keywords: Alexandria, Sequina slum, spatial integration, space syntax

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Authors: Yue Hao

Abstract:

COVID-19 vaccines not only protect individuals but society as a whole. In this case, having an understanding of the change and trend of vaccination conditions may shed some light on revising and making up-to-date policies regarding large-scale public health promotions and calls in order to lead and encourage the adoption of COVID-19 vaccines. However, vaccination status change over time and vary from place to place hidden patterns that were not fully explored in previous research. In our research, we took advantage of the spatial-temporal analytical methods in the domain of geographic information science and captured the spatial-temporal changes regarding COVID-19 vaccination status in the United States during 2020 and 2021. After conducting the emerging hot spots analysis on both the state level data of the US and county level data of California we found that: (1) at the macroscopic level, there is a continuously increasing trend of the vaccination rate in the US, but there is a variance on the spatial clusters at county level; (2) spatial hotspots and clusters with high vaccination amount over time were clustered around the west and east coast in regions like California and New York City where are densely populated with considerable economy conditions; (3) in terms of the growing trend of the daily vaccination among, Los Angeles County alone has very high statistics and dramatic increases over time. We hope that our findings can be valuable guidance for supporting future decision-making regarding vaccination policies as well as directing new research on relevant topics.

Keywords: COVID-19 vaccine, GIS, space time cube, spatial-temporal analysis

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Authors: Sanaa Riaz

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Spirits occupy a world that simultaneously dwells between the divine and the earthly binary while speaking to all forces of nature, marginality, and extremity in between. This paper examines the conceptualizations, interactions with, and experience of spiritual beings in relation to the concept of self and social agency, defined as a continuum of cooperation leaving those involved with an enhanced or diminished perception of self-agency. To do justice to the diverse mythological and popular interpretations of spirit entities, ethnographic examples from Africa, in particular, will be used. An examination of the nature and role of spirits in Africa allows one to understand the ways in which colonial influences brought by Catholicism and Islam added to the pre-colonial repertoire and syncretic imaginations of spirits. A comprehensive framework to analyze spirits requires situating them as a cognitive configuration of humans to communicate with other humans and forces of nature to receive knowledge about the normative in social roles, conduct, and action. Understanding spirits also requires a rethinking of the concept of self as not one encapsulated in the individual but one representing positionalities in collective negotiations, adversity, and alliances. To use the postmodern understanding of identity as a far from a coherent collection of selves fluidly moving between and dialoguing with gravitational and contradictory social forces, benevolent and maleficent spirit forces represent how people make sense of their origin, physiological and ecological changes, subsistence, and political environment and social relations. A discussion on spirits requires examining the rituals and mediational forces and their performance that allow participants to tackle adversity, voicelessness and continue to work safely and morally for the collective good. Moreover, it is important to see the conceptualization of spirits in unison with sorcery and spirit possession, central to voodoo practices, also because they speak volumes about the experiences of slavery and marginalization. This paper has two motives: It presents a critical literature review of ethnographic accounts of spirit entities in African spiritual experiences to examine the ways in which spirits become mediums through which the self is conceptualized and asserted. Second, the paper highlights the ways in which spirits become a medium to represent political and sociocultural ambiguities and desires along a spectrum of social agencies, including joint agency, vicarious agency, and interfered agency.

Keywords: spirits, social agency, self, ethnographic case studies

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Authors: J. Janani, S. Gomathi

Abstract:

Despite the new economy is embodied with the ample size of talent pool, the corporate world is facing the hardship in the mismatch of talent demand supply. Therefore to combat with this fallout crisis, here depicts the relevance of Employer Branding. Employer branding is gaining its popularity in Large sized companies especially IT companies but less employer branding awareness among IT SMEs (Small and Medium size Enterprises). There are N range of analysis has been dole out on employer branding from different perspectives and in different industries. The hidden factor behind the employer branding namely the post employment dissonance was not given a lot of importance into the research picture. The present study examines the employer branding as the employer image and the organizational identity. It focuses on the two fold dimensional branding initiatives namely job offer attributes and organizational attractiveness. The study will depict the dissonance level and their variations among the foresaid initiatives from the former employees and the post-employment dissonance from the present employees in IT SMEs and it will also examine the employer perception from the prospective employees towards the stated branding initiatives. The demographic factors such as generational factors (gen X and gen Y) and the career stages are majorly focused in the study. The study will promote the IT SMEs to strengthen their employer branding effectively and efficiently through implementing varied strategies and this will help them to enhance the talent pool at their best. This will eventually result in talent attraction and talent retention.

Keywords: employer image, organizational identity, post-employment dissonance, job offer attributes, organizational attractiveness, talent pool, career stages, generational factors, information technology, SMEs

Procedia PDF Downloads 496