Search results for: text representation

Authors: Mousouris Spiridon, Kavakli Evangelia

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This paper focuses on Digital Libraries (DLs) that contain and geovisualise cultural data, highlighting the need to define them as a separate category termed Cultural Mapping Libraries, based on their inherent connection of culture with geographic location and their design requirements in support of visual representation of cultural data on the map. An exploratory analysis of DLs that conform to the above definition brought forward the observation that existing Cultural Mapping Libraries fail to geovisualise the entirety of cultural data per point of interest thus resulting in a Cultural Snapshot phenomenon. The existence of this phenomenon was reinforced by the results of a systematic bibliographic research. In order to address the Cultural Snapshot, this paper proposes the use of the Semantic Web principles to efficiently interconnect spatial cultural data through time, per geographic location. In this way points of interest are transformed into scenery where culture evolves over time. This evolution is expressed as occurrences taking place chronologically, in an event oriented approach, a conceptualization also endorsed by the CIDOC Conceptual Reference Model (CIDOC CRM). In particular, we posit the use of CIDOC CRM as the baseline for defining the logic of Cultural Mapping Libraries as part of the Culture Domain in accordance with the Digital Library Reference Model, in order to define the rules of cultural data management by the system. Our future goal is to transform this conceptual definition in to inferencing rules that resolve the Cultural Snapshot and lead to a more complete geovisualisation of cultural data.

Keywords: digital libraries, semantic web, geovisualization, CIDOC-CRM

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Authors: Yun-Ju Chiu, Feng-Yi Chen

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Kinematics is the beginning to learn mechanics in physics course. The concept of acceleration plays an important role in learning kinematics. Teachers usually instruct the conception through the formulas and graphs of kinematics and the well-known law F = ma. However, over the past few decades, a lot of researchers reveal numerous students’ difficulties in learning acceleration. One of these difficulties is that students frequently confuse acceleration with velocity and force. Why is the concept of acceleration so difficult to learn? The aim of this study is to understand the conceptual evolution of acceleration through the historical textual analysis. Text analysis and one-to-one interviews with high school students and teachers are used in this study. This study finds the history of science constructed from textbooks is usually quite different from the real evolution of history. For example, most teachers and students believe that the best-known law F = ma was written down by Newton. The expression of the second law is not F = ma in Newton’s best-known book Principia in 1687. Even after more than one hundred years, a famous Cambridge textbook titled An Elementary Treatise on Mechanics by Whewell of Trinity College did not express this law as F = ma. At that time of Whewell, the early mid-nineteenth century Britain, the concept of acceleration was not only ambiguous but also confused with the concept of force. The process of learning the concept of acceleration is analogous to its conceptual development in history. The study from the perspective of historical textual analysis will promote the understanding of the concept learning difficulties, the development of professional physics teaching, and the improvement of the context of physics textbooks.

Keywords: acceleration, textbooks, mechanics, misconception, history of science

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Authors: Alexander G. Yushchenko

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From a multi-science point of view, we analyze threats to security resulting from globalization of international information space and information and communication aggression of Russia. A definition of Ruschism is formulated as an ideology supporting aggressive actions of modern Russia against the Euro-Atlantic community. Stages of the hybrid war Russia is leading against Ukraine are described, including the elements of subversive activity of the special services, the activation of the military phase and the gradual shift of the focus of confrontation to the realm of information and communication technologies. We reveal an emergence of a threat for democratic states resulting from the destabilizing impact of a target state’s mass media and social networks being exploited by Russian secret services under freedom-of-speech disguise. Thus, we underline the vulnerability of cyber- and information security of the network society in regard of hybrid war. We propose to define the latter a synergetic war. Our analysis is supported with a long-term qualitative monitoring of representation of top state officials on popular TV channels and Facebook. From the memetics point of view, we have detected a destructive psycho-information technology used by the Kremlin, a kind of information catastrophe, the essence of which is explained in detail. In the conclusion, a comprehensive plan for information protection of the public consciousness and mentality of Euro-Atlantic citizens from the aggression of the enemy is proposed.

Keywords: cyber and information security, hybrid war, psycho-information technology, synergetic war, Ruschism

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Authors: Ari Istiany, Guspri Devi Artanti, M. Si

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Based on the results Riskesdas, it is known that breastfeeding awareness about the importance of exclusive breastfeeding is still low at only 15.3 %. These conditions resulted in a very infant at risk for infectious diseases, such as diarrhea and acute respiratory infection. Therefore, the aim of this study to evaluate the video development about exclusive breastfeeding as a nutrition education media for posyandu cadre. This research used development methods for making the video about exclusive breastfeeding. The study was conducted in urban areas Rawamangun, East Jakarta. Respondents of this study were 1 media experts from the Department of Educational Technology - UNJ, 2 subject matter experts from Department of Home Economics - UNJ and 20 posyandu cadres to assess the quality of the video. Aspects assessed include the legibility of text, image display quality, color composition, clarity of sound, music appropriateness, duration, suitability of the material and language. Data were analyzed descriptively likes frequency distribution table, the average value, and deviation standard. The result of this study showed that the average score assessment according to media experts, subject matter experts, and posyandu cadres respectively was 3.43 ± 0.51 (good), 4.37 ± 0.52 (very good) and 3.6 ± 0.73 (good). The conclusion is on exclusive breastfeeding video as feasible as a media for nutrition education. While suggestions for the improvement of visual media is multiply illustrations, add material about the correct way of breastfeeding and healthy baby pictures.

Keywords: exclusive breastfeeding, posyandu cadre, video, nutrition education

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Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

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In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Kuan-Han Lin, Kuan-Yin Lin, Ka-Chun Siu

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The purpose of this systematic review was to determine the impact of post-traumatic stress disorders (PTSD) symptom or depressive symptoms on return to work (RTW) after occupational injury. The original articles of clinical trials and observational studies from PubMed, MEDLINE, and PsycINFO between January 1980 and November 2016 were retrieved. Two reviewers evaluated the abstracts identified by the search criteria for full-text review. To be included in the final analysis, studies were required to use either intervention or observational study design to examine the association between psychiatric symptoms and RTW. A modified checklist designed by Downs & Black and Crombie was used to assess the methodological quality of included study. A total of 58 articles were identified from the electronic databases after duplicate removed. Seven studies fulfilled the inclusion criteria and were critically reviewed. The rates of RTW in the included studies were reported to be 6% to 63.6% among workers after occupational injuries. This review found that post-traumatic stress symptom and depressive symptoms were negatively associated with RTW. Although the impact of psychiatric symptoms on RTW after occupational injury remains poorly understood, this review brought up the important information that injured workers with psychiatric symptoms had poor RTW outcome. Future work should address the effective management of psychiatric factors affecting RTW among workers.

Keywords: depressive symptom, occupational injury, post-traumatic stress disorder, return to work

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Khushboo Gokani, Renu Josan

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Mahasweta Devi and Toni Morrison are the two stalwarts of the Indian-English and the Afro-American literature respectively. The writings of these two novelists are authentic and powerful records of the lives of the people because much of their personal experiences have gone into the making of their works. Devi, a representative force of the Indian English literature, is also a social activist working with the tribals of Bihar, Jharkhand, Orissa and West Bengal. Most of her works echo the lives and struggles of the subalterns as is evident in her 'best-beloved book' Chotti Munda and His Arrow. The novelist focuses on the struggle of the tribals against the colonial and the feudal powers to create their identity, thereby, embarking on the ideological project called Setting the Record Straight. The Nobel laureate Toni Morrison, on the other hand, brings to the fore the crucial issues of gender, race, and class in many of her significant works. In one of her representative works, Sula, the protagonist emerges as a non-conformist and directly confronts the notion of a ‘good woman’ nurtured by the community of the Blacks. In addition to this, the struggle of the Blacks against the White domination, also become an important theme of the text. The thrust of the paper lies in making a critical analysis of the portrayal of the heroic attempts of the subaltern protagonist and the artistic endeavor of the novelists in challenging the stereotypes.

Keywords: the struggle of the muted groups, subaltern, center and periphery, challenging the stereotypes

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Authors: Sahib Dino Naseerani

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The presented scientific text discusses the concept of imaginary pressure and its role in different relative motions. It explores how imaginary pressure, which is the combined effect of external atmospheric pressure and real pressure, affects various substances and their physical properties. The study aims to understand the impact of imaginary pressure and its potential applications in different contexts, such as spaceflight. The main objective of this study is to investigate the role of imaginary pressure on different relative motions. Specifically, the researchers aim to examine how imaginary pressure affects the contraction and mass variation of a body when it is in motion at the speed of light. The study seeks to provide insights into the behavior and consequences of imaginary pressure in various scenarios. The data was collected using three research papers. This research contributes to a better understanding of the theoretical implications of imaginary pressure. It elucidates how imaginary pressure is responsible for the contraction and mass variation of a body in motion, particularly at the speed of light. The findings shed light on the behavior of substances under the influence of imaginary pressure, providing valuable insights for future scientific studies. The study addresses the question of how imaginary pressure influences various relative motions and their associated physical properties. It aims to understand the role of imaginary pressure in the contraction and mass variation of a body, particularly at high speeds. By examining different substances in liquid and solid forms, the research explores the consequences of imaginary pressure on their volume, length, and mass.

Keywords: imaginary pressure, contraction, variation, relative motion

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Authors: Lakhoua Najeh

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Aims of the work: After a presentation of the functionality of an example of a mechatronic system which is a paint mixer system, we present the concepts of modeling and safe operation. This paper briefly discusses how to model and protect the functioning of a mechatronic system relying mainly on functional analysis and safe operation techniques. Methods: For the study of an example of a mechatronic system, we use methods for external functional analysis that illustrate the relationships between a mechatronic system and its external environment. Thus, we present the Safe-Structured Analysis Design Technique method (Safe-SADT) which allows the representation of a mechatronic system. A model of operating safety and automation is proposed. This model enables us to use a functional analysis technique of the mechatronic system based on the GRAFCET (Graphe Fonctionnel de Commande des Etapes et Transitions: Step Transition Function Chart) method; study of the safe operation of the mechatronic system based on the Safe-SADT method; automation of the mechatronic system based on a software tool. Results: The expected results are to propose a model and safe operation of a mechatronic system. This methodology enables us to analyze the relevance of the different models based on Safe-SADT and GRAFCET in relation to the control and monitoring functions and to study the means allowing exploiting their synergy. Conclusion: In order to propose a general model of a mechatronic system, a model of analysis, safety operation and automation of a mechatronic system has been developed. This is how we propose to validate this methodology through a case study of a paint mixer system.

Keywords: mechatronic systems, system modeling, safe operation, Safe-SADT

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Authors: Vivien Chee Pei Wei

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Today we live in a scenario in which letters share space with images on screens that vary in size, shape, and style. The popularization of television, then the computer and now the e-readers, tablets, and smartphones made the electronic assume the role that previously was restricted to printed materials. Since the extensive use of new technologies to produce, disseminate, collect and access electronic publications began, the changes to reading has been intensified. To be able to read online, it involves more than just utilizing specific skills, strategies, and practices, but also in negotiating multiple information sources. In this study, different perspectives of digital reading are being explored in order to define the key aspects of the term. The focus is to explore how new technologies affect how undergraduates’ reading behavior, which in turn, gives readers different reading levels and engagement with the text and other support materials in the same media. There is also the importance of the relationship between reading platforms, reading levels and formats of electronic publications. The study looks at the online reading practices of about 100 undergraduates from a local university. The data collected using the survey and interviews with the respondents are analyzed thematically. Findings from this study found that both digital and traditional reading are interrelated, and should not be viewed as separate, but complementary to each other. However, reading online complicates some of the skills required by traditional reading. Consequently, in order to successfully read and comprehend multiple sources of information online, undergraduates need regular opportunities to practice and develop their skills as part of their natural reading practices.

Keywords: concepts, digital reading, literacy, traditional reading

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Nasa'i Muhammad Gwadabe

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This study seeks to find the extent to which the old Islamophobic prejudice was tilted towards a more negative direction in the United States following the 9/11 terrorist attacks. It is hypothesized that, the 9/11 attacks in the United States reshaped the old Islamophobic prejudice through the reinforcement of a strong social identity construction of Muslims as “out-group”. The “social identity” and “discourse representation” theories are used as framework for analysis. To test the hypothesis, two categories were created: the prejudice (out-group) and the tolerance (in-group) categories. The Prejudice (out-group) against Muslims category was coded to include six attributes: (Terrorist, Threat, Women's Rights violation, Undemocratic, Backward and Intolerant); while the tolerance (In-group) for Muslims category was also coded to include six attributes: (Peaceful, civilized, educated, partners trustworthy and honest). Data are generated from the archives of three American newspapers: The Los Angeles Times, New York Times and USA Today using specific search terms and specific date range; from 9/11/1996 to 9/11/2006, that is five years before and five years after the 9/11. An aggregate of 20595 articles were generated from the search of the three newspapers throughout the search periods. Conclusively, for both pre and post 9/11 periods, the articles generated under the category of prejudice (out-group) against Muslims revealed a higher frequency, against that of tolerance (in-group) for them, which is lesser. Finally, The comparison between the pre and post 9/11 periods showed that, the increased Prejudice (out-group) against Muslims was most influenced through libeling them as terrorist, which signaled a skyrocketed increase from pre to post 9/11.

Keywords: in-group, Islam, Islamophobia, Muslims, out-group, prejudice, terrorism, the 9/11 and tolerance

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Authors: Minakshi Jain, Sachin Yadav

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Gram Panchayat is the smallest unit of Democracy in India. Grassroots Democracy has been further strengthened by implementation of the 73rd Constitutional Amendment act (CAA) in 1992. To analyse the impact of grassroots democracy the three villages are selected, which have the representation of each section of the society. The selected villages belongs to the same block and district of Haryana state. Villages are selected to access the marginalized group such as women and other backward class. These groups are isolated and do not participate in the grassroots level development process. The caste continue to be a relevant factor in determining the rural leadership. The earlier models of Panchayati Raj failed to benefit the marginalized groups of the society. The 73rd CAA, advocates a uniform three tier system of Panchayat at District level (Zilla Panchayat), Taluka/Block level (Block Panchayat), and village level (Gram Panchayat). The socio-economic profile of representatives in each village is important factor in rural development. The study will highlight the socio-economic profile of elected members at gram Panchayat level, Block Level and District level. The analysis reveals that there is a need to educate and develop the capacity and capability of the elected representative. Training must be imparted to all of them to enable them to function as per provision in the act. The paper will analyse the impact of act on rural development than propose some measures to further strengthen the Panchayati Raj Institution (PRI’s) at grassroots level.

Keywords: democracy, rural development, marginalized people, function

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Authors: Devina Sethia

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This paper will examine the discourse of sense of belonging in popular Hindi language cinema in India to understand how Dalit identities and experiences are negotiated. It will situate such discourse against the emergence of new rhetorical forms of nationalism that seem to contest colonial constructs of nation and identity while clearly envisioning anti-colonial futures through the invocation of a glorious pre-colonial past. While nations have always been 'imagined communities' with the Hobsbawmian invented traditions that leverage national consciousness to establish trust and legitimacy of governance, the concept of ethnic nationalism has been at odds with the idea of India itself as the concept of nationalism in India was born out of anti colonial ideology and not ethnicity. However, in recent times, anti colonial nationalism is transforming into Hindu nationalism and hardening the boundaries around what is Indian-ness and what it means to be Indian. In the past two decades films such as Masaan (2015), Manjhi - The Mountain Man (2015), Sairat (2016), Article 15 (2019) and Vedaa (2024) have gained immense popularity amongst different audience groups across the country. The success of this cinematic genre is interesting when juxtaposed against the reinforcing of a more rigid and exclusionary understanding of Indian-ness. Hence, further exploration of this is essential to gain insights into the anti colonial future of India. In conclusion, studying the discourse of Dalit sense of belonging in film serves as more than mere representation, but rather as a crucial intervention in the comprehension and envisioning of anticolonial possibilities amidst the rise of Hindu nationalism.

Keywords: film studies, identity, sense of belonging, discourse

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Authors: Muhammad Shakeel Rehman Hissam

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This study aims at analyzing gender in Othello by applying Judith Butler’s Post-Structural theory of gender and gender performance. The analysis of the play provides us context by which we can examine what kinds of effects the drama have on understanding of the researchers regarding gender identity. The study sets out to examine that, is there any evidence or ground in Shakespearean selected work which leads to challenge the patriarchal taken for granted prescribed roles of gender? This would be the focal point in study of Othello that actions and performances of characters determine their gender identity rather than their sexuality. It argues that gender of Shakespearean characters has no constant, fixed and structural impression. On the contrary, they undergo consistent variations in their behavior and performance which impart fluidity and volatility to them. The focal point of the present study is Butler’s prominent work; Gender Trouble: Feminism and subversion of Identity and her post structural theory of Gender performativity as the theoretical underpinning of the text. It analyzes the selected play in Post-Structural gender perspective. The gender-centric plot of the play is riddled with fluidity of gender. The most fascinating aspect of the play is the transformations of genders on the basis of performances by different characters and through these transformations; gender identity is revealed and determined. The study reconstructs the accepted gender norms by challenging the traditional concept of gender that is based on sexual differences of characters.

Keywords: post structural, gender, performativity, socio-cultural gender norms, binaries, Othello, Butler, identity

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Authors: Nadia Syed

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The digital age has inevitably changed the way in which hate crime is committed. The cyber world has become a highly effective means for individuals and groups to be targeted, harmed, and marginalized , largely through online medium. Facebook has become one of the fastest growing social media platforms. At the end of 2013, Facebook had 1,23bn monthly active users and 757 million daily users who log onto Facebook. Within this online space, there are also an increasing number of online virtual communities, and hate groups who are using this freedom to share a violent, Islamophobic and racist description which attempts to create a aggressive virtual environment. This paper is a research on the rise of Islamophobia and the role of media in spreading it. This paper focusing on how the media especially Facebook is portraying Islam as the religion which promotes violence and ultimately playing a significant role in the global rise of Islamophobia against Muslims. It is important to analyse these ‘new’ communities by monitoring the activities they conduct, because the material they post, potentially can have a harmful impact on community cohesion within society. Additionally, as a result of recent figures that shows an increase in online anti-Muslim abuse, there is a pertinent need to address the issue about Islamophobia on social media. On the whole, this study found Muslims being demonized and vilified online which had manifested through negative attitudes, discrimination, stereotypes, physical threats and online harassment which all had the potential to incite violence or prejudicial action because it disparages and intimidates a protected individual or group.

Keywords: Islamophobia, online, social media, facebook, internet, extremism

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Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Sara Herrero Jaén, José María Santamaría García, María Lourdes Jiménez Rodríguez, Jorge Luis Gómez González, Adriana Cercas Duque, Alexandra González Aguna

Abstract:

Background: Health concept has evolved throughout history. The health level is determined by the own individual perception. It is a dynamic process over time so that you can see variations from one moment to the next. In this way, knowing the health of the patients you care for, will facilitate decision making in the treatment of care. Objective: To design a technological tool that calculates the people health level in a sequential way over time. Material and Methods: Deductive methodology through text analysis, extraction and logical knowledge formalization and education with expert group. Studying time: September 2015- actually. Results: A computational tool for the use of health personnel has been designed. It has 11 variables. Each variable can be given a value from 1 to 5, with 1 being the minimum value and 5 being the maximum value. By adding the result of the 11 variables we obtain a magnitude in a certain time, the health level of the person. The health calculator allows to represent people health level at a time, establishing temporal cuts being useful to determine the evolution of the individual over time. Conclusion: The Information and Communication Technologies (ICT) allow training and help in various disciplinary areas. It is important to highlight their relevance in the field of health. Based on the health formalization, care acts can be directed towards some of the propositional elements of the concept above. The care acts will modify the people health level. The health calculator allows the prioritization and prediction of different strategies of health care in hospital units.

Keywords: calculator, care, eHealth, health

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Authors: Arshad Alfoqaha, Seth Bard, Dustin Demetriou

Abstract:

A new multi-physics acoustic modeling approach using ANSYS Mechanical FEA and FLUENT CFD methods is developed for modeling servers mounted to racks, such as IBM Z and IBM Power Systems, in data centers. This new approach allows users to determine the thermal and acoustic conditions that people are exposed to within the data center. The sound pressure level (SPL) exposure for a human working inside a hot aisle containment system inside the data center is studied. The SPL is analyzed at the noise source, at the human body, on the rack walls, on the containment walls, and on the ceiling and flooring plenum walls. In the acoustic CFD simulation, it is assumed that a four-inch diameter sphere with monopole acoustic radiation, placed in the middle of each rack, provides a single-source representation of all noise sources within the rack. Ffowcs Williams & Hawkings (FWH) acoustic model is employed. The target frequency is 1000 Hz, and the total simulation time for the transient analysis is 1.4 seconds, with a very small time step of 3e-5 seconds and 10 iterations to ensure convergence and accuracy. A User Defined Function (UDF) is developed to accurately simulate the acoustic noise source, and a Dynamic Mesh is applied to ensure acoustic wave propagation. Initial validation of the acoustic CFD simulation using a closed-form solution for the spherical propagation of an acoustic point source is performed.

Keywords: data centers, FLUENT, acoustics, sound pressure level, SPL, hot aisle containment, IBM

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Authors: Kun Xu, Yuan Xu, Jia Qiao

Abstract:

The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Ahmed Tahsin Shams

Abstract:

The right to dissent through any form of art has been facing challenges through various strict legal measures, particularly since 2018 when the Government of Bangladesh passed the Digital Security Act 2018 (DSA). Therefore, the references to ‘popular’ culture mostly include mainstream religious and national festivals and exclude critical intellectual representation of specific political allusions in any form of storytelling: whether wall art or fiction writing, since the post-DSA period in Bangladesh. Through inductive quantitative and qualitative methodological approaches, this paper aims to study the pattern of censorship, detention or custodial tortures against artists and the banning approach by the Bangladeshi government in the last five years, specifically against static visual arts, i.e., cartoon and wall art. The pattern drawn from these data attempts to redefine the popular notion of ‘pop culture’ as an unorganized folk or mass culture. The results also hypothesize how the post-DSA period forcefully constructs ‘pop culture’ as a very organized repetitive deception of enlightenment or entertainment. Thus the argument theorizes that this censoring trend is a fascist approach making the artists subaltern. So, in this socio-political context, these two similar and overlapping elements: culture and art, are vastly separated in two streams: the former being appreciated by the power, and the latter is a fearful concern for the power. Therefore, the purpose of art also shifts from entertainment to an act of rebellion, adding more layers to the new postmodern definition of ‘pop culture.’

Keywords: popular culture, visual arts, censoring trend, fascist approach, subaltern, digital security act

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Authors: Shafag Dadashova

Abstract:

The study discusses relativity of perception and interpretation of power, its interdependence with conformity level of an individual. It describes an autobiography as a form of epiphany. It is suggested that life-writing helps the author analyze the past and define the borders of his personal power and sources of empowerment. As all life-writings deal with behaviors, values, attitudes, relationships and emotions, their investigation requires qualitative methods to understand social norms, gender roles, religion, and their role in empowerment and disempowerment of the author. The study consists of two parts. The first part is theoretical and interrogates the notion of personal power and how writing the own life can bring to conscious empowerment. The second part presents two autobiographies by female authors from two different Muslim cultures who negotiate between the larger nationalist agenda and their own personal concerns. These autobiographies (Tehmina Durrani, Pakistani author ‘My Feudal Lord’, Banine, Azerbaijani writer 'Caucasian days' and 'Parisian days') are the end of their authors’ long silence, their revolt against the conventional norms, their decision to have an agency to confess and protest. These autobiographies are the authors’ attempts to break the established matrix of perceptions, imposed norms, and gain power to build the real picture of their identity. The study sums up with the conclusion that in spite of very similar motifs of female authors to get empowered through self-analysis, different cultures and time create specific subjectivities associated with particular historical events and geographical location.

Keywords: conformity level, empowerment, female autobiography, self-identity

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Authors: Mohammed Muzafar, Darshan Ruikar

Abstract:

BIM, an acronym for Building Information Modelling relates to the practice of creating a computer generated model which is capable of displaying the planning, design, construction and operation of a structure. The resulting simulation is a data-rich, object-oriented, intelligent and parametric digital representation of the facility, from which views and data, appropriate to various users needs can be extracted and analysed to generate information that can be used to make decisions and to improve the process of delivering the facility. BIM also refers to a shift in culture that will influence the way the built environment and infrastructure operates and how it is delivered. One of the main issues of concern in the construction industry at present in the UK is its record on Health & Safety (H&S). It is, therefore, important that new technologies such as BIM are developed to help improve the quality of health and safety. Historically the H&S record of the construction industry in the UK is relatively poor as compared to the manufacturing industries. BIM and the digital environment it operates within now allow us to use design and construction data in a more intelligent way. It allows data generated by the design process to be re-purposed and contribute to improving efficiencies in other areas of a project. This evolutionary step in design is not only creating exciting opportunities for the designers themselves but it is also creating opportunity for every stakeholder in any given project. From designers, engineers, contractors through to H&S managers, BIM is accelerating a cultural change. The paper introduces the concept behind a research project that mitigates the H&S risks associated with the construction, operation and maintenance of assets through the adoption of BIM.

Keywords: building information modeling, BIM levels, health, safety, integration

Procedia PDF Downloads 254