Search results for: scene text recognition

Authors: Slwa Al-Hammad

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Adaptation studies have been closely aligned to translation studies as both deal with the process of rendering the meaning from one culture to another. These two disciplines are related to each other, but the theories are still being developed. This research aims to fill this gap and provide a contribution to the growing discipline of adaptation studies through a theoretical perspective while investigating how different cultural interpretations of adaptation influence the final literary product. This research focuses on the theoretical concepts of Barthes’s death of the author and Benjamin’s afterlife of the text in translation, which is believed to lead to the birth of the adapter in a literary work. That is, in adaptation, the ‘death’ of the author allows for the ‘birth’ of the adapter, offering them all the creative possibilities of authorship. It also explores the differences between the meanings of adaptation in the West and the Arab world through the analysis of adapted texts in Arabic initially deriving from the European and American literature of the 19th and 20th centuries. The methodology of this thesis is based upon qualitative literary analysis, in which original and adapted works are compared and contrasted, with the additional insights of literary and adaptation theories and prior scholarship. The main works discussed are the Arabic adaptations of William Faulkner’s novels. The analysis is guided by theories of adaptation studies to help in explaining the concepts of relocating, recreating, and rewriting in the process of adaptation. It draws on scholarship on adaptations to inquire into the status of the adapted texts in relation to the original texts. Also, these theories prove that adaptation is the process that is used to transfer text from source to adapted text, not some other analytical practice. Through the textual analysis, concepts of the death of the author and the birth of the adapter will be illustrated, as will the roles of the adapter and the task of rendering works for a different culture, and the understanding of adaptation and Arabization in Arabic literature.

Keywords: adaptation, Arabization, authorship, recreating, relocating

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Authors: Mark Herman Sumagang Potoy

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State of the City Address (SOCA) is a speech, modelled after the State of the Nation Address, given not as mandated by law but usually a matter of practice or tradition delivered before the chief executive’s constituents. Through this, the general public is made to know the performance of the local government unit and its agenda for the coming year. Therefore, it is imperative for SOCAs to clearly convey its message and carry out the myriad function of enlightening its readers which could be achieved through the proper use of reference. Anaphora and cataphora are the two major types of reference; the former refer back to something that has already been mentioned while the latter points forward to something which is yet to be said. This paper seeks to identify the types of reference employed on the SOCAs from 2014 to 2016 of Hon. Rosalina Garcia Jalosjos, Mayor of Dapitan City and look into how the references contribute to the clarity of the message of the text. The qualitative method of research is used in this study through an in-depth analysis of the corpus. As soon as the copies of the SOCAs are secured from the Office of the City Mayor, they are then analyzed using documentary technique categorizing the types of reference as to anaphora and cataphora, counting each of these types and describing the implications of the dominant types used in the addresses. After a thorough analysis, it is found out that the two reference types namely, anaphora and cataphora are both employed on the three SOCAs, the former being used more frequently than the latter accounting to 80% and 20% of actual usage, respectively. Moreover, the use of anaphors and cataphora on the three addresses helps in conveying the message clearly because they primarily become aids to avoid the repetition of the same element in the text especially when there wasn’t a need to emphasize a point. Finally, it is recommended that writers of State of the City Addresses should have a vast knowledge on how reference should be used and the functions they take in the text since this is a vital tool to clearly transmit a message. Moreover, English teachers should explicitly teach the proper usage of anaphora and cataphora, as instruments to develop cohesion in written discourse, to enable students to write not only with sense but also with fluidity in tying utterances together.

Keywords: anaphora, cataphora, reference, State of the City Address

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: C. Brierley, H. El-Farahaty, A. Farhan

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The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

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Authors: Hafiza Javaria Ashraf, Xinghong Wang, Zhanghong Shi, Youming Hou

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Insect’s innate immunity depends on a variety of defense responses for the recognition of invading pathogens. Pathogen recognition involves particular proteins known as pattern recognition receptors (PRRs). These PRRs interact with pathogen-associated molecular patterns (PAMPs) present on the surface of pathogens to distinguish between self and non-self. C-type lectins (CTLs) belong to a superfamily of PPRs which involved in insect immunity and defense mechanism. Rhynchophorus ferrugineus Olivier is a devastating pest of Palm cultivations in China. Although studies on R. ferrugineus immune mechanism and host defense have conducted, however, the role of CTL in immune responses of R. ferrugineus remains elusive. Here, we report RfCTL, which is a secreted protein containing a single-CRD domain. The open reading frame (ORF) of CTL is 226 bp, which encodes a putative protein of 168 amino acids. Transcript expression analysis revealed that RfCTL highly expressed in immune-related tissues, i.e., hemolymph and fat body. The abundance of RfCTL in the gut and fat body dramatically increased upon Staphylococcus aureus and Escherichia coli bacterial challenges, suggesting a role in defense against gram-positive and gram-negative bacterial infection. Taken together, we inferred that RfCTL might be involved in the immune defense of R. ferrugineus and established a solid foundation for future studies on R. ferrugineus CTL domain proteins for better understanding of insect immunity.

Keywords: biological invasion, c-type lectin, insect immunity, Rhynchophorus ferrugineus Oliver

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Authors: R. Chinnaiyaprabhu, S. Bharanidharan, V. Dharsana, Rajalavanya

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The concept of the Metaverse represents a potential evolution in the realm of cyberspace. In the early stages of Web 2.0, we observed a proliferation of online pseudonyms or 'nyms,' which increased the prevalence of fake accounts and made it challenging to establish unique online identities for various roles. However, in the era of Web 3.0, particularly in the context of the Metaverse, an individual's digital identity is intrinsically linked to their real-world identity. Consequently, actions taken in the Metaverse can carry significant consequences in the physical world. In light of these considerations, we propose the development of an innovative authentication system known as 'Metasec.' This system is designed to enhance security for digital assets, online identities, avatars, and user accounts within the Metaverse. Notably, Metasec operates as a password less authentication solution, relying on a multifaceted approach to security, encompassing device attestation, facial recognition, and pattern-based security keys.

Keywords: metaverse, multifactor authentication, security, facial recognition, patten password

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Makhim Artikova, Shavkat Duschanov

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So far, there have been a plethora of attempts to improve learners’ academic writing skills. However, this issue remains to be a real concern among the majority of students, especially those who are standing on their academic life threshold. The purpose of this research is improving students’ academic writing skills through 'Questions and Answer Reading' activities. Using well-prepared and well-chosen reading materials (from textbooks, scientific journals, or magazines) and applying questions and answer activities in the classroom facilitate learners to become great critical readers. Furthermore, it boosts their writing skills, which are the most crucial part of students’ personal and academic developments. In this activity, the class is divided into small groups of four. Then, the instructor will give students whether one section of the text or full text asking them to read and to find unfamiliar words within the group. After discovering the meaning of unknown words, each group has to share their findings with the class. In the next stage of the activity, students should be asked to create questions in a group based on the given reading material. Follow by each group should ask the other groups their questions which are an excellent opportunity to challenge leads to improve critical thinking skills. In the last part, the students are asked to write the text or article summary, which is the activity core that pilots to the writing skills perfection. This engaging activity highlights the effectiveness of incorporating reading materials into the classroom when it comes to improving students’ composition writings. Structural writing after every reading activity resulted in improving students’ coherence and cohesion in writing well-organized essays. Having experimented with high school 9th and 11th-grade students, implementing reading activities into the classroom is proved to be a productive tool to enhance one’s academic writing skills. In the future, this method planning to be implemented among university students.

Keywords: academic writing, coherence and cohesion, questions and answer activities, scientific reading

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Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

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Authors: Lutendo Nendauni

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Colonialism breaks things, colonisers exploded native cultural solidarity, producing the spiritual confusion, psychic wounding, and economic exploitation of a new and dominated ‘other’. Colonialism as the cultural and economic exploitation began when the West defended in their seizure of foreign territories for the exploitation of its natural resources; this resulted in brutal socio-economic imbalances. The Western profited at the detriment of the weak Africa. However, colonialism has since passed, but the effects are still evident culturally, socially, and economically. This paper explored how postcolonial writers and critics attempt to reverse the socio-economic imbalances resulting from the fragmentation of colonialism, with a focus on the play 'I will Marry When I Want' by Ngugi wa Thiong’o and Ngugi wa Mirii, as a primary text. Using qualitative discourse-textual analysis as the research methodology, the researcher purposively extracts discourse segments from the text for analysis and interpretation. The findings reveal that Postcolonial critics and writers attempt to reverse the socio-economic effects of colonialism through various counter discourses; their literature is concerned with the destruction of colonised identity, the search for this identity, and its assertion. It is manifest in the text that writers offer corrective views about Africans; they stress that they write their literary texts to conscientise their fellow Africans. Postcolonial writers and critics argue that language is a carrier of culture and that the only way to break free from colonial influence is by not adopting a foreign language. They further through their poems, novels, plays, and music strategically shine the spotlight on the previously nameless and destitute people so that they can develop the human spirit’s desire to overcome defeat, socio-political deprivation, and isolation.

Keywords: colonialism, postcoloniality, critics, socio-economic imbalances

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Authors: Slava Kalyuga, Sujanya Sombatteera

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In multimedia learning, written text is often transformed into spoken (narrated) text. This transient information may overwhelm limited processing capacity of working memory and inhibit learning instead of improving it. The paper reviews recent empirical studies in modality and verbal redundancy effects within a cognitive load framework and outlines conditions under which negative effects of transiency may occur. According to the modality effect, textual information accompanying pictures should be presented in an auditory rather than visual form in order to engage two available channels of working memory – auditory and visual - instead of only one of them. However, some studies failed to replicate the modality effect and found differences opposite to those expected. Also, according to the multimedia redundancy effect, the same information should not be presented simultaneously in different modalities to avoid unnecessary cognitive load imposed by the integration of redundant sources of information. However, a few studies failed to replicate the multimedia redundancy effect too. Transiency of information is used to explain these controversial results.

Keywords: cognitive load, transient information, modality effect, verbal redundancy effect

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Authors: Tao Feng, Wei-Wei Zhang, Chang-Ming Ding

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Cross-site scripting (XSS) is one of the most popular WEB Attacking methods at present, and also one of the most risky web attacks. Because of the population of JavaScript, the scene of the cross site scripting attack is also gradually expanded. However, since the web application developers tend to only focus on functional testing and lack the awareness of the XSS, which has made the on-line web projects exist many XSS vulnerabilities. In this paper, different various techniques of XSS attack are analyzed, and a method automatically to detect it is proposed. It is easy to check the results of vulnerability detection when running it as a plug-in.

Keywords: XSS, no target attack platform, automatic detection，XSS detection

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Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

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A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

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Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

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Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

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Authors: Minh Huynh, Aaron Heuser, Luke Patterson, Chris Zhang, Mason Miller, Daniel Wang, Sandeep Shetty, Mike Trinh, Abigail Miller, Adaeze Enekwechi, Tenille Daniels, Lu Huynh

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Machine learning and text analytics have been used to analyze child abuse, cyberbullying, domestic abuse and domestic violence, and hate speech. However, to the authors’ knowledge, no research to date has used these methods to study elder abuse in nursing homes or skilled nursing facilities from field inspection reports. We used machine learning and text analytics methods to analyze 356,000 inspection reports, which have been extracted from CMS Form-2567 field inspections of US nursing homes and skilled nursing facilities between 2016 and 2021. Our algorithm detected occurrences of the various types of abuse, including physical abuse, psychological abuse, verbal abuse, sexual abuse, and passive and active neglect. For example, to detect physical abuse, our algorithms search for combinations or phrases and words suggesting willful infliction of damage (hitting, pinching or burning, tethering, tying), or consciously ignoring an emergency. To detect occurrences of elder neglect, our algorithm looks for combinations or phrases and words suggesting both passive neglect (neglecting vital needs, allowing malnutrition and dehydration, allowing decubiti, deprivation of information, limitation of freedom, negligence toward safety precautions) and active neglect (intimidation and name-calling, tying the victim up to prevent falls without consent, consciously ignoring an emergency, not calling a physician in spite of indication, stopping important treatments, failure to provide essential care, deprivation of nourishment, leaving a person alone for an inappropriate amount of time, excessive demands in a situation of care). We further compare the prevalence of abuse before and after Covid-19 related restrictions on nursing home visits. We also identified the facilities with the most number of cases of abuse with no abuse facilities within a 25-mile radius as most likely candidates for additional inspections. We also built an interactive display to visualize the location of these facilities.

Keywords: machine learning, text analytics, elder abuse, elder neglect, nursing home abuse

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Authors: Khan Farhan Rafat, M. Junaid Hussain

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Seamless modification of an entity for the purpose of hiding a message of significance inside its substance in a manner that the embedding remains oblivious to an observer is known as steganography. Together with today's pervasive registering frameworks, steganography has developed into a science that offers an assortment of strategies for stealth correspondence over the globe that must, however, need a critical appraisal from security breach standpoint. Microsoft Word is amongst the preferably used word processing software, which comes as a part of the Microsoft Office suite. With a user-friendly graphical interface, the richness of text editing, and formatting topographies, the documents produced through this software are also most suitable for stealth communication. This research aimed not only to epitomize the fundamental concepts of steganography but also to expound on the utilization of Microsoft Word document as a carrier for furtive message exchange. The exertion is to examine contemporary message hiding schemes from security aspect so as to present the explorative discoveries and suggest enhancements which may serve a wellspring of information to encourage such futuristic research endeavors.

Keywords: hiding information in plain sight, stealth communication, oblivious information exchange, conceal, steganography

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Authors: Sundus Mona, Atif Adnan, Babar Ali, Fareeha Arshad, Allah Rakha

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Molecular diversity is the variation in the abundance of species. Forensic entomology is a neglected field in Pakistan. Insects collected from the crime scene should be handled by forensic entomologists who are currently virtually non-existent in Pakistan. Correct identification of insect specimen along with knowledge of their biodiversity can aid in solving many problems related to complicated forensic cases. Inadequate morphological identification and insufficient thermal biological studies limit the entomological utility in Forensic Medicine. Recently molecular identification of entomological evidence has gained attention globally. DNA barcoding is the latest and established method for species identification. Only proper identification can provide a precise estimation of postmortem intervals. Arthropods are known to be the first tourists scavenging on decomposing dead matter. The objective of the proposed study was to identify species by molecular techniques and analyze their phylogenetic importance with barcoded necrophagous insect species of early succession on human cadavers. Based upon this identification, the study outcomes will be the utilization of established DNA bar codes to identify carrion feeding insect species for concordant estimation of post mortem interval. A molecular identification method involving sequencing of a 658bp ‘barcode’ fragment of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene from collected specimens of unknown dipteral species from cadavers of Lahore was evaluated. Nucleotide sequence divergences were calculated using MEGA 7 and Arlequin, and a neighbor-joining phylogenetic tree was generated. Three species were identified, Chrysomya megacephala, Chrysomya saffranea, and Chrysomya rufifacies with low genetic diversity. The fixation index was 0.83992 that suggests a need for further studies to identify and classify forensically relevant insects in Pakistan. There is an exigency demand for further research especially when immature forms of arthropods are recovered from the crime scene.

Keywords: molecular diversity, DNA barcoding, species identification, forensically relevant

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

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Authors: Yousef Abu Amrieh

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This paper explores how Arab American novelist Rabih Alameddine's recent novel The Angel of History (2016) appropriates certain motifs, tropes, and themes from Shakespeare's The Tempest. In particular, Alameddine's novel re-tells the story of Caliban and his mother from the perspective of a Yemeni bastard whose mis/fortunes take him to the US shores in the eighties of the previous century. The novel, specifically, re-writes the scene in which Caliban is gazed at by European travelers like Stephano and Trinculo whose first reaction to seeing him is to consider how to sell him or give him as a gift when they safely return to Europe. The novel contests Shakespeare's representation of Caliban as 'marketable' through depicting his daily experiences in modern day America.

Keywords: appropriation, Alameddine, Shakespeare, The Tempest

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Authors: Hong Im Shin

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Previous research demonstrated that self-objectification (women view themselves as objects for use) is related to system-justification. Three studies investigated whether cultural disposition as its system-justifying function could have an impact on self-objectification and dehumanization of sexualized women and men. Study 1 (N = 91) employed a survey methodology to examine the relationship between cultural disposition (collectivism vs. individualism), trait of system-justification, and self-objectification. The results showed that the higher tendency of collectivism was related to stronger system-justification and self-objectification. Study 2 (N = 60 females) introduced a single category implicit association task (SC-IAT) to assess the extent to which sexually objectified women were associated with uniquely human attributes (i.e., culture) compared to animal-related attributes (i.e., nature). According to results, female participants associated sexually objectified female targets less with human attributes compared to animal-related attributes. Study 3 (N = 46) investigated whether priming to individualism or collectivism was associated to system justification and sexual objectification of men and women with the use of a recognition task involving upright and inverted pictures of sexualized women and men. The results indicated that the female participants primed to individualism showed an inversion effect for sexualized women and men (person-like recognition), whereas there was no inversion effect for sexualized women in the priming condition of collectivism (object-like recognition). This implies that cultural disposition plays a mediating role for rationalizing the gender status, implicit dehumanization of sexualized females and self-objectification. Future research directions are discussed.

Keywords: cultural disposition, dehumanization, implicit test, self-objectification

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

Abstract:

While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

Abstract:

A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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Authors: Saad Alkentar, Abdulkareem Assalem

Abstract:

Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: LuoJiaoyang, Yu Hongyang

Abstract:

In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

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Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: Agoston Restas

Abstract:

Introduction: In case of managing disasters decision makers can face many times such a special situation where any pre-sign of the drastically change is missing therefore the improvised decision making can be required. The complexity, ambiguity, uncertainty or the volatility of the situation can require many times the improvisation as decision making. It can be taken at any level of the management (strategic, operational and tactical) but at tactical level the main reason of the improvisation is surely time pressure. It is certainly the biggest problem during the management. Methods: The author used different tools and methods to achieve his goals; one of them was the study of the relevant literature, the other one was his own experience as a firefighting manager. Other results come from two surveys that are referred to; one of them was an essay analysis, the second one was a word association test, specially created for the research. Results and discussion: This article proves that, in certain situations, the multi-criteria, evaluating decision-making processes simply cannot be used or only in a limited manner. However, it can be seen that managers, directors or commanders are many times in situations that simply cannot be ignored when making decisions which should be made in a short time. The functional background of decisions made in a short time, their mechanism, which is different from the conventional, was studied lately and this special decision procedure was given the name recognition-primed decision. In the article, author illustrates the limits of the possibilities of analytical decision-making, presents the general operating mechanism of recognition-primed decision-making, elaborates on its special model relevant to managers at tactical level, as well as explore and systemize the factors that facilitate (catalyze) the processes with an example with fire managers.

Keywords: decision making, disaster managers, recognition primed decision, model for making decisions in emergencies

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Authors: Luo Jiaoyang, Yu Hongyang

Abstract:

In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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