Search results for: semantic processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4133

Search results for: semantic processing

3713 A Systematic Review of Sensory Processing Patterns of Children with Autism Spectrum Disorders

Authors: Ala’a F. Jaber, Bara’ah A. Bsharat, Noor T. Ismael

Abstract:

Background: Sensory processing is a fundamental skill needed for the successful performance of daily living activities. These skills are impaired as parts of the neurodevelopmental process issues among children with autism spectrum disorder (ASD). This systematic review aimed to summarize the evidence on the differences in sensory processing and motor characteristic between children with ASD and children with TD. Method: This systematic review followed the guidelines of the preferred reporting items for systematic reviews and meta-analysis. The search terms included sensory, motor, condition, and child-related terms or phrases. The electronic search utilized Academic Search Ultimate, CINAHL Plus with Full Text, ERIC, MEDLINE, MEDLINE Complete, Psychology, and Behavioral Sciences Collection, and SocINDEX with full-text databases. The hand search included looking for potential studies in the references of related studies. The inclusion criteria included studies published in English between years 2009-2020 that included children aged 3-18 years with a confirmed ASD diagnosis, according to the DSM-V criteria, included a control group of typical children, included outcome measures related to the sensory processing and/or motor functions, and studies available in full-text. The review of included studies followed the Oxford Centre for Evidence-Based Medicine guidelines, and the Guidelines for Critical Review Form of Quantitative Studies, and the guidelines for conducting systematic reviews by the American Occupational Therapy Association. Results: Eighty-eight full-text studies related to the differences between children with ASD and children with TD in terms of sensory processing and motor characteristics were reviewed, of which eighteen articles were included in the quantitative synthesis. The results reveal that children with ASD had more extreme sensory processing patterns than children with TD, like hyper-responsiveness and hypo-responsiveness to sensory stimuli. Also, children with ASD had limited gross and fine motor abilities and lower strength, endurance, balance, eye-hand coordination, movement velocity, cadence, dexterity with a higher rate of gait abnormalities than children with TD. Conclusion: This systematic review provided preliminary evidence suggesting that motor functioning should be addressed in the evaluation and intervention for children with ASD, and sensory processing should be supported among children with TD. More future research should investigate whether how the performance and engagement in daily life activities are affected by sensory processing and motor skills.

Keywords: sensory processing, occupational therapy, children, motor skills

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3712 Robust and Real-Time Traffic Counting System

Authors: Hossam M. Moftah, Aboul Ella Hassanien

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In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

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3711 A Comparative Study of Motion Events Encoding in English and Italian

Authors: Alfonsina Buoniconto

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The aim of this study is to investigate the degree of cross-linguistic and intra-linguistic variation in the encoding of motion events (MEs) in English and Italian, these being typologically different languages both showing signs of disobedience to their respective types. As a matter of fact, the traditional typological classification of MEs encoding distributes languages into two macro-types, based on the preferred locus for the expression of Path, the main ME component (other components being Figure, Ground and Manner) characterized by conceptual and structural prominence. According to this model, Satellite-framed (SF) languages typically express Path information in verb-dependent items called satellites (e.g. preverbs and verb particles) with main verbs encoding Manner of motion; whereas Verb-framed languages (VF) tend to include Path information within the verbal locus, leaving Manner to adjuncts. Although this dichotomy is valid altogether, languages do not always behave according to their typical classification patterns. English, for example, is usually ascribed to the SF type due to the rich inventory of postverbal particles and phrasal verbs used to express spatial relations (i.e. the cat climbed down the tree); nevertheless, it is not uncommon to find constructions such as the fog descended slowly, which is typical of the VF type. Conversely, Italian is usually described as being VF (cf. Paolo uscì di corsa ‘Paolo went out running’), yet SF constructions like corse via in lacrime ‘She ran away in tears’ are also frequent. This paper will try to demonstrate that such a typological overlapping is due to the fact that the semantic units making up MEs are distributed within several loci of the sentence –not only verbs and satellites– thus determining a number of different constructions stemming from convergent factors. Indeed, the linguistic expression of motion events depends not only on the typological nature of languages in a traditional sense, but also on a series morphological, lexical, and syntactic resources, as well as on inferential, discursive, usage-related, and cultural factors that make semantic information more or less accessible, frequent, and easy to process. Hence, rather than describe English and Italian in dichotomic terms, this study focuses on the investigation of cross-linguistic and intra-linguistic variation in the use of all the strategies made available by each linguistic system to express motion. Evidence for these assumptions is provided by parallel corpora analysis. The sample texts are taken from two contemporary Italian novels and their respective English translations. The 400 motion occurrences selected (200 in English and 200 in Italian) were scanned according to the MODEG (an acronym for Motion Decoding Grid) methodology, which grants data comparability through the indexation and retrieval of combined morphosyntactic and semantic information at different levels of detail.

Keywords: construction typology, motion event encoding, parallel corpora, satellite-framed vs. verb-framed type

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3710 Translation of the Verbal Nouns (Masadars) Originating from Three-Letter Verbs in the Holy Quran: Verbal Noun with More than One Pattern (Wazn) As a Model

Authors: Montasser Mohamed Abdelwahab Mahmoud, Abdelwahab Saber Esawi

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The language of the Qur’an has a wide range of understanding, reflection, and meanings. Therefore, translation of the Qur’an is inevitably nothing but a translation of the interpretation of the meanings of the Qur’an. It requires special competencies and skills for translators so that they can get close to the intended meaning of the verse of the Qur’an and convey it with precision. In the Arabic language, the verbal noun “AlMasdar” is a very important derivative that properly expresses the verbal idea in the form of a noun. It sounds the same as the base form of the verb with minor changes in the vowel pattern. It is one of the important topics in morphology. The morphologists divided verbal nouns into auditory and analogical, and they stated that that the verbal nouns (Masadars) originating from three-letter verbs are auditory, although they set controls for some of them in order to preserve them. As for the lexicographers, they mentioned the verbal nouns while talking about the lexical materials, and in some cases, their explanation of them exceeded that made by the morphologists, especially in their discussion of structures that the morphologists did not refer to in their books. The verb kafara (disbelief), for example, has three patterns, namely: al-kufْr, al-kufrān, and al-kufūr, and it was mentioned in the Holy Qur’an with different connotations. The verb ṣāma (fasted) with his two patterns (al-ṣaūm and al-ṣīām) was mentioned in the Holy Qur’an while their semantic meaning is different. The problem discussed in this research paper lied in the "linguistic loss" committed by translators when dealing with Islamic religious texts, especially the Qur'an. The study tried to identify the strategy adopted by translators of the Holy Qur'an in translating words that were classified as verbal nouns through analyzing the translation rendered by five translations of the Qur’an into English: Yusuf Ali, Pickthall, Mohsin Khan, Muhammad Sarwar, and Shakir. This study was limited to the verbal nouns in the Quraan that originate from three-letter verbs and have different semantic meanings.

Keywords: pattern, three-letter verbs, translation of the Quran, verbal nouns

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3709 Automated Fact-Checking by Incorporating Contextual Knowledge and Multi-Faceted Search

Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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3708 StockTwits Sentiment Analysis on Stock Price Prediction

Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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3707 Swahili Codification of Emotions: A Cognitive Linguistic Analysis

Authors: Rosanna Tramutoli

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Studies on several languages have demonstrated how different emotions are categorized in various linguistic constructions. It exists in several writings on the codification of emotions in Western African languages. A recent study on the semantic description of Swahili body terminology has demonstrated that body part terms, such as moyo (heart), uso (face) and jicho (eye) are involved in several metaphorical expressions describing emotions. However, so far hardly anything has been written on the linguistic description of emotions in Swahili. Thus, this study describes how emotional concepts, such as ‘love’ and ‘anger’ are codified in Swahili, in order to highlight common semantic and syntactic patterns, etymological sources and metaphorical expressions. The research seeks to answer a number of questions, such as which are the Swahili terms for ‘emotions’? Is there a distinction between ‘emotions’ and ‘feelings’? Which emotional lexical items have Bantu origin and which come from Arabic? Which metaphorical expressions/cognitive schemas are used to codify emotions? (e.g. kumpanda mtu kichwani, lit. ‘to climb on somebody’s head’, to make somebody feel angry, kushuka moyo, lit. ‘to be down the heart’, to feel discouraged, kumpa mtu moyo lit. ‘to give someone heart’, to encourage someone). Which body terms are involved as ‘containers/locus of emotions’? For instance, it has been shown that moyo (‘heart’) occurs as container of ‘love’ (e.g. kumtia mtu moyoni, lit. ‘to put somebody in the heart’, to love somebody very much) and ‘kindness’ (moyo wake ulijaa hisani, ‘his heart was filled with kindness’). The study also takes into account the syntactic patterns used to code emotions. For instance, when does the experiencer occur in subject position? (e.g. nina furaha, nimefurahi, ‘I am happy’) and when in object position (e.g. Huruma iliniingia moyoni, lit. ‘Pity entered me inside my heart’, ‘I felt pity’)? Data have been collected mostly through the analysis of Swahili digital corpora, containing different kinds of Swahili texts (e.g. novels, drama, political essays).

Keywords: emotions, cognitive linguistics, metaphors, Swahili

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3706 Yoghurt Kepel Stelechocarpus burahol as an Effort of Functional Food Diversification from Region of Yogyakarta

Authors: Dian Nur Amalia, Rifqi Dhiemas Aji, Tri Septa Wahyuningsih, Endang Wahyuni

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Kepel fruit (Stelechocarpus burahol) is a scarce fruit that belongs as a logogram of Daerah Istimewa Yogyakarta. Kepel fruit can be used as substance of beauty treatment product, such as deodorant and good for skin health, and also contains antioxidant compound. Otherwise, this fruit is scarcely cultivated by people because of its image as a palace fruit and also the flesh percentage just a little, so it has low economic value. The flesh of kepel fruit is about 49% of its whole fruit. This little part as supporting point why kepel fruit has to be extracted and processed with the other product. Yoghurt is milk processing product that also have a role as functional food. Economically, the price of yoghurt is higher than whole milk or other milk processing product. Yoghurt is usually added with flavor of dye from plant or from chemical substance. Kepel fruit has a role as flavor in yoghurt, besides as product that good for digestion, yoghurt with kepel also has function as “beauty” food. Writing method that used is literature study by looking for the potential of kepel fruit as a local fruit of Yogyakarta and yoghurt as milk processing product. The process just like making common yoghurt because kepel fruit just have a role as flavor substance, so it does not affect to the other processing of yoghurt. Food diversification can be done as an effort to increase the value of local resources that proper to compete in Asean Economic Community (AEC), one of the way is producing kepel yoghurt.

Keywords: kepel, yoghurt, Daerah Istimewa Yogyakarta, functional food

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3705 Research on the Risks of Railroad Receiving and Dispatching Trains Operators: Natural Language Processing Risk Text Mining

Authors: Yangze Lan, Ruihua Xv, Feng Zhou, Yijia Shan, Longhao Zhang, Qinghui Xv

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Receiving and dispatching trains is an important part of railroad organization, and the risky evaluation of operating personnel is still reflected by scores, lacking further excavation of wrong answers and operating accidents. With natural language processing (NLP) technology, this study extracts the keywords and key phrases of 40 relevant risk events about receiving and dispatching trains and reclassifies the risk events into 8 categories, such as train approach and signal risks, dispatching command risks, and so on. Based on the historical risk data of personnel, the K-Means clustering method is used to classify the risk level of personnel. The result indicates that the high-risk operating personnel need to strengthen the training of train receiving and dispatching operations towards essential trains and abnormal situations.

Keywords: receiving and dispatching trains, natural language processing, risk evaluation, K-means clustering

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3704 Analyzing Environmental Emotive Triggers in Terrorist Propaganda

Authors: Travis Morris

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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: propaganda analysis, emotive triggers environmental security, frames

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3703 Design of New Alloys from Al-Ti-Zn-Mg-Cu System by in situ Al3Ti Formation

Authors: Joao Paulo De Oliveira Paschoal, Andre Victor Rodrigues Dantas, Fernando Almeida Da Silva Fernandes, Eugenio Jose Zoqui

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With the adoption of High Pressure Die Casting technologies for the production of automotive bodies by the famous Giga Castings, the technology of processing metal alloys in the semi-solid state (SSM) becomes interesting because it allows for higher product quality, such as lower porosity and shrinkage voids. However, the alloys currently processed are derived from the foundry industry and are based on the Al-Si-(Cu-Mg) system. High-strength alloys, such as those of the Al-Zn-Mg-Cu system, are not usually processed, but the benefits of using this system, which is susceptible to heat treatments, can be associated with the advantages obtained by processing in the semi-solid state, promoting new possibilities for production routes and improving product performance. The current work proposes a new range of alloys to be processed in the semi-solid state through the modification of aluminum alloys of the Al-Zn-Mg-Cu system by the in-situ formation of Al3Ti intermetallic. Such alloys presented the thermodynamic stability required for semi-solid processing, with a sensitivity below 0.03(Celsius degrees * -1), in a wide temperature range. Furthermore, these alloys presented high hardness after aging heat treatment, reaching 190HV. Therefore, they are excellent candidates for the manufacture of parts that require low levels of defects and high mechanical strength.

Keywords: aluminum alloys, semisolid metals processing, intermetallics, heat treatment, titanium aluminide

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3702 Translatability of Sylistic Devices in Poetry Across Language-Cultures: An Intercultural Rhetoric Perspective

Authors: Hazel P. Atilano

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Contrastive rhetoricians working on L2 writing are often unfamiliar with the theories and research of scholars in translation studies. Publications on translation studies give little or no attention to describing the translation strategies of translators, with a focus on the influence of their L1 on the language they produce. This descriptive qualitative study anchored on Eugene Nida’s Translation Theory employed stylistic, lexico-semantic, and grammatical analyses of the stylistic devices employed by poets across nine language cultures to reveal the translation strategies employed by translators and to establish the type of equivalence manifested in the translated texts. The corpus consists of 27 poems written in Bahasa Indonesia, Hiligaynon, Tagalog (Malayo-Polynesian languages), French, Italian, Spanish (Romance languages), German, Icelandic, and Norwegian (Germanic Languages), translated into English. Stylistic analysis reveals that both original texts and English translations share the same stylistic devices, suggesting that stylistic devices do not get lost in translation. Lexico-semantic and grammatical analyses showed that translators of Malayo-Polynesian languages employed idiomatic translation as a compensatory strategy, producing English translations that manifest Dynamic Equivalence or transparency; translators of Romance languages resorted to synonymous substitution or literal translation, suggesting Formal Equivalence or fidelity; and translators of Germanic languages used a combination of idiomatic and literal translation strategies, with noticeable preference for Dynamic Equivalence, evidenced by the prevalence of metaphorical translations as compensatory strategy. Implications on the intricate relationship between culture and language in the translation process were drawn based on the findings.

Keywords: translation strategy, dynamic equivalence, formal equivalence, translation theory, transparency, fidelity

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3701 A Fast Parallel and Distributed Type-2 Fuzzy Algorithm Based on Cooperative Mobile Agents Model for High Performance Image Processing

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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3700 Thermodynamic Analysis and Experimental Study of Agricultural Waste Plasma Processing

Authors: V. E. Messerle, A. B. Ustimenko, O. A. Lavrichshev

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A large amount of manure and its irrational use negatively affect the environment. As compared with biomass fermentation, plasma processing of manure enhances makes it possible to intensify the process of obtaining fuel gas, which consists mainly of synthesis gas (CO + H₂), and increase plant productivity by 150–200 times. This is achieved due to the high temperature in the plasma reactor and a multiple reduction in waste processing time. This paper examines the plasma processing of biomass using the example of dried mixed animal manure (dung with a moisture content of 30%). Characteristic composition of dung, wt.%: Н₂О – 30, С – 29.07, Н – 4.06, О – 32.08, S – 0.26, N – 1.22, P₂O₅ – 0.61, K₂O – 1.47, СаО – 0.86, MgO – 0.37. The thermodynamic code TERRA was used to numerically analyze dung plasma gasification and pyrolysis. Plasma gasification and pyrolysis of dung were analyzed in the temperature range 300–3,000 K and pressure 0.1 MPa for the following thermodynamic systems: 100% dung + 25% air (plasma gasification) and 100% dung + 25% nitrogen (plasma pyrolysis). Calculations were conducted to determine the composition of the gas phase, the degree of carbon gasification, and the specific energy consumption of the processes. At an optimum temperature of 1,500 K, which provides both complete gasification of dung carbon and the maximum yield of combustible components (99.4 vol.% during dung gasification and 99.5 vol.% during pyrolysis), and decomposition of toxic compounds of furan, dioxin, and benz(a)pyrene, the following composition of combustible gas was obtained, vol.%: СО – 29.6, Н₂ – 35.6, СО₂ – 5.7, N₂ – 10.6, H₂O – 17.9 (gasification) and СО – 30.2, Н₂ – 38.3, СО₂ – 4.1, N₂ – 13.3, H₂O – 13.6 (pyrolysis). The specific energy consumption of gasification and pyrolysis of dung at 1,500 K is 1.28 and 1.33 kWh/kg, respectively. An installation with a DC plasma torch with a rated power of 100 kW and a plasma reactor with a dung capacity of 50 kg/h was used for dung processing experiments. The dung was gasified in an air (or nitrogen during pyrolysis) plasma jet, which provided a mass-average temperature in the reactor volume of at least 1,600 K. The organic part of the dung was gasified, and the inorganic part of the waste was melted. For pyrolysis and gasification of dung, the specific energy consumption was 1.5 kWh/kg and 1.4 kWh/kg, respectively. The maximum temperature in the reactor reached 1,887 K. At the outlet of the reactor, a gas of the following composition was obtained, vol.%: СO – 25.9, H₂ – 32.9, СO₂ – 3.5, N₂ – 37.3 (pyrolysis in nitrogen plasma); СO – 32.6, H₂ – 24.1, СO₂ – 5.7, N₂ – 35.8 (air plasma gasification). The specific heat of combustion of the combustible gas formed during pyrolysis and plasma-air gasification of agricultural waste is 10,500 and 10,340 kJ/kg, respectively. Comparison of the integral indicators of dung plasma processing showed satisfactory agreement between the calculation and experiment.

Keywords: agricultural waste, experiment, plasma gasification, thermodynamic calculation

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3699 Open-Source YOLO CV For Detection of Dust on Solar PV Surface

Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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3698 Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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3697 Valorization Cascade Approach of Fish By-Products towards a Zero-Waste Future: A Review

Authors: Joana Carvalho, Margarida Soares, André Ribeiro, Lucas Nascimento, Nádia Valério, Zlatina Genisheva

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Following the exponential growth of human population, a remarkable increase in the amount of fish waste has been produced worldwide. The fish processing industry generates a considerable amount of by-products which represents a considerable environmental problem. Accordingly, the reuse and valorisation of these by-products is a key process for marine resource preservation. The significant volume of fish waste produced worldwide, along with its environmental impact, underscores the urgent need for the adoption of sustainable practices. The transformative potential of utilizing fish processing waste to create industrial value is gaining recognition. The substantial amounts of waste generated by the fish processing industry present both environmental challenges and economic inefficiencies. Different added-value products can be recovered by the valorisation industries, whereas fishing companies can save costs associated with the management of those wastes, with associated advantages, not only in terms of economic income but also considering the environmental impacts. Fish processing by-products have numerous applications; the target portfolio of products will be fish oil, fish protein hydrolysates, bacteriocins, pigments, vitamins, collagen, and calcium-rich powder, targeting food products, additives, supplements, and nutraceuticals. This literature review focuses on the main valorisation ways of fish wastes and different compounds with a high commercial value obtained by fish by-products and their possible applications in different fields. Highlighting its potential in sustainable resource management strategies can play and important role in reshaping the fish processing industry, driving it towards circular economy and consequently more sustainable future.

Keywords: fish process industry, fish wastes, by-products, circular economy, sustainability

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3696 Text Based Shuffling Algorithm on Graphics Processing Unit for Digital Watermarking

Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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3695 On Privacy-Preserving Search in the Encrypted Domain

Authors: Chun-Shien Lu

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Privacy-preserving query has recently received considerable attention in the signal processing and multimedia community. It is also a critical step in wireless sensor network for retrieval of sensitive data. The purposes of privacy-preserving query in both the areas of signal processing and sensor network are the same, but the similarity and difference of the adopted technologies are not fully explored. In this paper, we first review the recently developed methods of privacy-preserving query, and then describe in a comprehensive manner what we can learn from the mutual of both areas.

Keywords: encryption, privacy-preserving, search, security

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3694 Effect of Different Processing Methods on the Quality Attributes of Pigeon Pea Used in Bread Production

Authors: B. F. Olanipekun, O. J. Oyelade, C. O. Osemobor

Abstract:

Pigeon pea is a very good source of protein and micronutrient, but it is being underutilized in Nigeria because of several constraints. This research considered the effect of different processing methods on the quality attributes of pigeon pea used in bread production towards enhancing its utility. Pigeon pea was obtained at a local market and processed into the flour using three processing methods: soaking, sprouting and roasting and were used to bake bread in different proportions. Chemical composition and sensory attributes of the breads were thereafter determined. The highest values of protein and ash contents were obtained from 20 % substitution of sprouted pigeon pea in wheat flour and may be attributable to complex biochemical changes occurring during hydration, to invariably lead to protein constituent being broken down. Hydrolytic activities of the enzymes from the sprouted sample resulted in improvement in the constituent of total protein probably due to reduction in the carbohydrate content. Sensory qualities analyses showed that bread produced with soaked and roasted pigeon pea flours at 5 and 10% inclusion, respectively were mostly accepted than other blends, and products with sprouted pigeon pea flour were least accepted. The findings of this research suggest that supplementing wheat flour with sprouted pigeon peas have more nutritional potentials. However, with sensory analysis indices, the soaked and roasted pigeon peas up to 10% are majorly accepted, and also can improve the nutritional status. Overall, this will be very beneficial to population dependent on plant protein in order to combat malnutrition problems.

Keywords: pigeon pea, processing, protein, malnutrition

Procedia PDF Downloads 252
3693 Intelligent Chatbot Generating Dynamic Responses Through Natural Language Processing

Authors: Aarnav Singh, Jatin Moolchandani

Abstract:

The proposed research work aims to build a query-based AI chatbot that can answer any question related to any topic. A chatbot is software that converses with users via text messages. In the proposed system, we aim to build a chatbot that generates a response based on the user’s query. For this, we use natural language processing to analyze the query and some set of texts to form a concise answer. The texts are obtained through web-scrapping and filtering all the credible sources from a web search. The objective of this project is to provide a chatbot that is able to provide simple and accurate answers without the user having to read through a large number of articles and websites. Creating an AI chatbot that can answer a variety of user questions on a variety of topics is the goal of the proposed research project. This chatbot uses natural language processing to comprehend user inquiries and provides succinct responses by examining a collection of writings that were scraped from the internet. The texts are carefully selected from reliable websites that are found via internet searches. This project aims to provide users with a chatbot that provides clear and precise responses, removing the need to go through several articles and web pages in great detail. In addition to exploring the reasons for their broad acceptance and their usefulness across many industries, this article offers an overview of the interest in chatbots throughout the world.

Keywords: Chatbot, Artificial Intelligence, natural language processing, web scrapping

Procedia PDF Downloads 66
3692 Creative Potential of Children with Learning Disabilities

Authors: John McNamara

Abstract:

Growing up creative is an important idea in today’s classrooms. As education seeks to prepare children for their futures, it is important that the system considers traditional as well as non-traditional pathways. This poster describes the findings of a research study investigating creative potential in children with learning disabilities. Children with learning disabilities were administered the Torrance Test of Creative Problem Solving along with subtests from the Comprehensive Test of Phonological Processing. A quantitative comparative analysis was computed using paired-sample t-tests. Results indicated statistically significant difference between children’s creative problem-solving skills and their reading-based skills. The results lend support to the idea that children with learning disabilities have inherent strengths in the area of creativity. It can be hypothesized that the success of these children may be associated with the notion that they are using a type of neurological processing that is not otherwise used in academic tasks. Children with learning disabilities, a presumed left-side neurological processing problem, process information with the right side of the brain – even with tasks that should be processed with the left side (i.e. language). In over-using their right hemisphere, it is hypothesized that children with learning disabilities have well-developed right hemispheres and, as such, have strengths associated with this type of processing, such as innovation and creativity. The current study lends support to the notion that children with learning disabilities may be particularly primed to succeed in areas that call on creativity and creative thinking.

Keywords: learning disabilities, educational psychology, education, creativity

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3691 The Universal Cultural Associations in the Conceptual Metaphors Used in the Headlines of Arab News and Saudi Gazette Newspapers: A Critical Cognitive Study

Authors: Hind Hassan Arruwaite

Abstract:

Conceptual metaphor is a cognitive semantic tool that provides access to people's conceptual systems. The correlation in the human conceptual system surpasses limited time and specific cultures. The universal associations provide universal schemas that organize people's conceptualization of the world. The study aims to explore how the cultural associations used in conceptual metaphors create commonalities and harmony between people of the world. In the research methodology, the researcher implemented Critical Metaphor Analysis, Metaphor Candidate Identification and Metaphor Identification Procedure models to deliver qualitative and descriptive findings. The semantic tension was the key criterion in identifying metaphorically used words in the headlines. The research materials are the oil trade conceptual metaphors used in the headlines of Arab News and Saudi Gazette Newspapers. The data will be uploaded to the self-constructed corpus to examine electronic lists for identifying conceptual metaphors. The study investigates the types of conceptual metaphors used in the headlines of the newspapers, the cultural associations identified in the conceptual metaphors, and whether the identified cultural associations in conceptual metaphors create universal conceptual schemas. The study aligned with previous seminal works on conceptual metaphor theory in emphasizing the distinctive power of conceptual metaphors in exposing the cultural associations that unify people's perceptions. The correlation of people conceptualization provides universal schemas that involve elements of human sensorimotor experiences. The study contributes to exposing the shared cultural associations that ensure the commonality of all humankind's thinking mechanism.

Keywords: critical discourse analysis, critical metaphor analysis, conceptual metaphor theory, primary and specific metaphors, corpus-driven approach, universal associations, image schema, sensorimotor experience, oil trade

Procedia PDF Downloads 203
3690 Prompt Design for Code Generation in Data Analysis Using Large Language Models

Authors: Lu Song Ma Li Zhi

Abstract:

With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

Procedia PDF Downloads 43
3689 Mindfulness, Reinvestment, and Rowing under Pressure: Evidence for Moderated Moderation of the Anxiety-Performance Relationship

Authors: Katherine Sparks, Christopher Ring

Abstract:

This study aimed to investigate whether dispositional sport-specific mindfulness moderated the moderation effect of conscious processing on the relationship between anxiety and rowing race performance. Using a sport-specific (Rowing-Specific) Reinvestment Scale (RSRS) to measure state conscious processing, we examined the effects of trait sport-related mindfulness on the conscious processes of rowers under competitive racing pressure at a number of UK regattas. 276 rowers completed a survey post competitive race. The survey included the RSRS, mindfulness, a perceived performance rating scale, demographic and race information to identify and record the rower’s actual race performance. Results from the research demonstrated that high levels of dispositional mindfulness are associated with a superior performance under pressure. In relation to the moderating moderation effect, conscious processing amplifies the detrimental effects of anxiety on performance. However, mindfulness, mindful awareness, and mindful non-judgement all proved to attenuate this amplification effect by moderating the conscious processing moderation on the anxiety-performance relationship. Therefore, this study provides initial support for the speculation that dispositional mindfulness can help prevent the deleterious effects of rowing-specific reinvestment under pressure.

Keywords: mindful, reinvestment, under pressure, performance, rowing

Procedia PDF Downloads 157
3688 Rapid Processing Techniques Applied to Sintered Nickel Battery Technologies for Utility Scale Applications

Authors: J. D. Marinaccio, I. Mabbett, C. Glover, D. Worsley

Abstract:

Through use of novel modern/rapid processing techniques such as screen printing and Near-Infrared (NIR) radiative curing, process time for the sintering of sintered nickel plaques, applicable to alkaline nickel battery chemistries, has been drastically reduced from in excess of 200 minutes with conventional convection methods to below 2 minutes using NIR curing methods. Steps have also been taken to remove the need for forming gas as a reducing agent by implementing carbon as an in-situ reducing agent, within the ink formulation.

Keywords: batteries, energy, iron, nickel, storage

Procedia PDF Downloads 441
3687 Numerical Implementation and Testing of Fractioning Estimator Method for the Box-Counting Dimension of Fractal Objects

Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

Abstract:

This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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3686 Mechanical Analysis and Characterization of Friction Stir Processed Aluminium Alloy

Authors: Jaswinder Kumar, Kulbir Singh Sandhu

Abstract:

Friction stir processing (FSP) is a solid-state surface processing technique. A single-pass FSP was performed on Aluminum alloy at combinations of different tool rotational speeds with cylindrical threaded pin profiled tool. The effect of these parameters on tribological properties was studied. The wear resistance is found to be increased from base metal to a single pass FSP sample. The results revealed that with an increase in tool rotational speed, the wear rate increases. The high heat generation causes matrix softening, which results in an increased wear rate; on the other hand, high heat generation leads to coarse grains, which also affected tribological properties. Furthermore, Microstructure results showed that FSPed alloy has a more refined grain structure as compare to the base material, which may be resulted in enhancement of hardness and resistance to wear in FSP.

Keywords: friction stir processing, aluminium alloy, microhardness, microstructure

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3685 Improved Processing Speed for Text Watermarking Algorithm in Color Images

Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

Abstract:

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: steganography, watermarking, time complexity measurements, private keys

Procedia PDF Downloads 144
3684 Bacteriophage Lysis Of Physiologically Stressed Listeria Monocytogenes In A Simulated Seafood Processing Environment

Authors: Geevika J. Ganegama Arachchi, Steve H. Flint, Lynn McIntyre, Cristina D. Cruz, Beatrice M. Dias-Wanigasekera, Craig Billington, J. Andrew Hudson, Anthony N. Mutukumira

Abstract:

In seafood processing plants, Listeriamonocytogenes(L. monocytogenes)likely exists in a metabolically stressed state due to the nutrient-deficient environment, processing treatments such as heating, curing, drying, and freezing, and exposure to detergents and disinfectants. Stressed L. monocytogenes cells have been shown to be as pathogenic as unstressed cells. This study investigated lytic efficacy of (LiMN4L, LiMN4p, and LiMN17) which were previouslycharacterized as virulent against physiologically stressed cells of three seafood borne L. monocytogenesstrains (19CO9, 19DO3, and 19EO3).Physiologically compromised cells ofL. monocytogenesstrains were prepared by aging cultures in TrypticaseSoy Broth at 15±1°C for 72 h; heat injuringcultures at 54±1 - 55±1°C for 40 - 60 min;salt-stressing cultures in Milli-Q water were incubated at 25±1°C in darkness for three weeks; and incubating cultures in 9% (w/v) NaCl at 15±1°C for 72 h. Low concentrations of physiologically compromised cells of three L. monocytogenesstrainswere challenged in vitrowith high titre of three phages in separate experiments using Fish Broth medium (aqueous fish extract) at 15 °C in order to mimic the environment of seafood processing plant. Each phage, when present at ≈9 log10 PFU/ml, reduced late exponential phase cells of L. monocytogenes suspended in fish protein broth at ≈2-3 log10 CFU/ml to a non-detectable level (< 10 CFU/ml). Each phage, when present at ≈8.5 log10 PFU/ml, reduced both heat-injured cells present at 2.5-3.6 log10 CFU/ml and starved cells that were showed coccoid shape, present at ≈2-3 log10 CFU/ml to < 10 CFU/ml after 30 min. Phages also reduced salt-stressed cellspresent at ≈3 log10 CFU/ml by > 2 log10. L. monocytogenes (≈8 log10 CFU/ml) were reduced to below the detection limit (1 CFU/ml) by the three successive phage infections over 16 h, indicating that emergence of spontaneous phage resistance was infrequent. The three virulent phages showed high decontamination potential for physiologically stressed L. monocytogenes strains from seafood processing environments.

Keywords: physiologically stressed L. monocytogenes, heat injured, seafood processing environment, virulent phage

Procedia PDF Downloads 135