Search results for: tweet processing

Authors: Amira Dhokar, Lobna Hlaoua, Lotfi Ben Romdhane

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Tweet contextualization (TC) is a new issue that aims to answer questions of the form 'What is this tweet about?' The idea of this task was imagined as an extension of a previous area called multi-document summarization (MDS), which consists in generating a summary from many sources. In both TC and MDS, the summary should ideally contain the most relevant information of the topic that is being discussed in the source texts (for MDS) and related to the query (for TC). Furthermore of being informative, a summary should be coherent, i.e. well written to be readable and grammatically compact. Hence, coherence is an essential characteristic in order to produce comprehensible texts. In this paper, we propose a new approach to improve readability and coherence for tweet contextualization based on bipartite graphs. The main idea of our proposed method is to reorder sentences in a given paragraph by combining most expressive words detection and HITS (Hyperlink-Induced Topic Search) algorithm to make up a coherent context.

Keywords: bipartite graphs, readability, summarization, tweet contextualization

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Authors: Sarra Hasni, Sami Faiz

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In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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Authors: Judith Enriquez-Gibson

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This paper meddles with the notion of phatic communion introduced 90 years ago by Malinowski, who was a Polish-born British anthropologist. It explores the phatic in Twitter within the contents of tweets related to moocs (massive online open courses) as a topic or trend. It is not about moocs though. It is about practices that could easily be hidden or neglected if we let big or massive topics take the lead or if we simply follow the computational or secret codes behind Twitter itself and third party software analytics. It draws from media and cultural studies. Though at first it appears data-driven as I submitted data collection and analytics into the hands of a third party software, Twitonomy, the aim is to follow how phatic communion might be practised in a social media site, such as Twitter. Lurking becomes its research method to analyse mooc-related tweets. A total of 3,000 tweets were collected on 11 October 2013 (UK timezone). The emphasis of lurking is to engage with Twitter as a system of connectivity. One interesting finding is that a click is in fact a phatic practice. A click breaks the silence. A click in one of the mooc website is actually a tweet. A tweet was posted on behalf of a user who simply chose to click without formulating the text and perhaps without knowing that it contains #mooc. Surely, this mechanism is not about reciprocity. To break the silence, users did not use words. They just clicked the ‘tweet button’ on a mooc website. A click performs and maintains connectivity – and Twitter as the medium in attendance in our everyday, available when needed to be of service. In conclusion, the phatic culture of breaking silence in Twitter does not have to submit to the power of code and analytics. It is a matter of human code.

Keywords: click, Twitter, phatic communion, social media data, mooc

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Authors: Noor Farizah Ibrahim, Christopher Durugbo

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This study aims to investigate how the Twittersphere reacted during the recent historical event of robotic landing on a comet. The news is about Philae, a robotic lander from European Space Agency (ESA), which successfully made the first-ever rendezvous and touchdown of its kind on a nucleus comet on November 12, 2014. In order to understand how Twitter is practically used in spreading messages on historical events, we conducted an analysis of one-week tweet feeds that contain the #CometLanding hashtag. We studied the trends of tweets, the diffusion of the information and the characteristics of the social network created. The results indicated that the use of Twitter as a platform enables online communities to engage and spread the historical event through social media network (e.g. tweets, retweets, mentions and replies). In addition, it was found that comprehensible and understandable hashtags could influence users to follow the same tweet stream compared to other laborious hashtags which were difficult to understand by users in online communities.

Keywords: diffusion of information, hashtag, social media, Twitter

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Authors: Smah Almotiri

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

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

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert

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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.

Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

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Authors: Nor Diana Ahmad, Eric Atwell, Brandon Bennett

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Text processing techniques for English have been developed for several decades. But for the Malay language, text processing methods are still far behind. Moreover, there are limited resources, tools for computational linguistic analysis available for the Malay language. Therefore, this research presents the use of natural language processing (NLP) in processing Malay translated Qur’an text. As the result, a new language resource for Malay translated Qur’an was created. This resource will help other researchers to build the necessary processing tools for the Malay language. This research also develops a simple question-answer prototype to demonstrate the use of the Malay Qur’an resource for text processing. This prototype has been developed using Python. The prototype pre-processes the Malay Qur’an and an input query using a stemming algorithm and then searches for occurrences of the query word stem. The result produced shows improved matching likelihood between user query and its answer. A POS-tagging algorithm has also been produced. The stemming and tagging algorithms can be used as tools for research related to other Malay texts and can be used to support applications such as information retrieval, question answering systems, ontology-based search and other text analysis tasks.

Keywords: language resource, Malay translated Qur'an, natural language processing (NLP), text processing

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Authors: Mariana T. Teixeira, Joana P. Luz

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This paper is based on assumptions of psycholinguistics and investigates the processing of ambiguous sentences in Brazilian Portuguese. Specifically, it aims to verify if there is a difference in processing time between sentences with lexical ambiguity and sentences with structural (or syntactic) ambiguity. We hypothesize, based on the Garden Path Theory, that the two types of ambiguity entail different cognitive efforts, since sentences with structural ambiguity require that two structures be processed, whereas ambiguous phrases whose root of ambiguity is in a word require the processing of a single structure, which admits a variation of punctual meaning, within the scope of only one lexical item. In order to test this hypothesis, 25 undergraduate students, whose average age was 27.66 years, native speakers of Brazilian Portuguese, performed a self-monitoring reading task of ambiguous sentences, which had lexical and structural ambiguity. The results suggest that unambiguous sentence processing is faster than ambiguous sentence processing, whether it has lexical or structural ambiguity. In addition, participants presented a mean reading time greater for sentences with syntactic ambiguity than for sentences with lexical ambiguity, evidencing a greater cognitive effort in sentence processing with structural ambiguity.

Keywords: Brazilian portuguese, lexical ambiguity, sentence processing, syntactic ambiguity

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Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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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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Authors: Amirreza Razzaghipour Sorkhab

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The exploration of the connection between cognition and Auditory Processing Disorder (APD) holds significant value. Individuals with APD experience challenges in processing auditory information through the central auditory nervous system's varied pathways. Understanding the importance of auditory attention in individuals with APD, as well as the primary diagnostic tools such as language and auditory attention tests, highlights the critical need for assessing their auditory attention abilities. While not all children with Auditory Processing Disorder (APD) show deficits in auditory attention, there are often deficiencies in cognitive and attentional performance. The link between various types of attention deficits and APD suggests impairments in sustained and divided auditory attention. Research into the origins of APD should also encompass higher-level processes, such as auditory attention. It is evident that investigating the interaction between APD and auditory and cognitive functions holds significant value. Furthermore, it was demonstrated that APD tests may be influenced by cognitive factors, but despite signs of auditory attention interaction with auditory processing skills and the influence of cognitive factors on tests for this disorder, auditory attention measures are not typically included in APD diagnostic protocols. Therefore, incorporating attention assessment tests into the battery of tests for individuals with auditory processing disorder will be beneficial for obtaining useful insights into their attentional abilities.

Keywords: auditory processing disorder, auditory attention, central auditory processing disorder, top-down pathway

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Authors: T. Vijayashree, A. Gopal

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The aim of the work is to classify and authenticate medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these raw materials are to be ensured for the preparation of herbal medicines. These raw materials are to be carefully screened, analyzed and documented due to mistaken of look-alike materials which do not have medicinal characteristics.

Keywords: authenticity, standardization, principal component analysis, imaging processing, signal processing

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Authors: Fares Alsewailem

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Material recycling of thermoplastic waste offers practical solution for municipal solid waste reduction. Post-consumer plastics such as polyethylene (PE), polyethyleneterephtalate (PET), and polystyrene (PS) may be separated from each other by physical methods such as density difference and hence processed as single plastic, however one should be cautious about the contaminants presence in the waste stream inform of paper, glue, etc. since these articles even in trace amount may deteriorate properties of the recycled plastics especially the mechanical properties. furthermore, melt processing methods used to recycle thermoplastics such as extrusion and compression molding may induce degradation of some of the recycled plastics such as PET and PS. In this research, it is shown that care should be taken when processing recycled plastics by melt processing means in two directions, first contaminants should be extremely minimized, and secondly melt processing steps should also be minimum.

Keywords: Recycling, PET, PS, HDPE, mechanical

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Authors: Khaled M. Alhawiti

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This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research.

Keywords: data retrieval, information retrieval, natural language processing, text structuring

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Authors: Nileshkumar Vishnav, Aditya Tatu

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A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction.

Keywords: graph signal processing, algebraic signal processing, graph similarity, isospectral graphs, nonuniform signal processing

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Javeed Akhtar, R. K. Pandey, Z. R. Azaz Ahmad Azad

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For the purpose of making different uses of food material for the development of extruded foods are produced using single and twin extruders. Extrusion cooking is a useful and economical tool for processing of novel food. This high temperature, short time processing technology causes chemical and physical changes that alter the nutritional and physical quality of the product. Extrusion processing of food ingredients characteristically depends on associating process conditions that influence the product qualities. The process parameters are optimized for extrusion of food material in order to obtain the maximum nutritive value by inactivating the anti-nutritional factors. The processing conditions such as moisture content, temperature and time are controlled to avoid over heating or under heating which otherwise would result in a product of lower nutritional quality.

Keywords: extrusion processing, single and twin extruder, operating condition of extruders and extruded novel foods, food and agricultural engineering

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Authors: A. A. Adekunle, A. M. Omoare, W. O. Oyediran

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This study was carried out to assess rural women’s skill acquisition in the processing of locust bean in Ipokia Local Government Area of Ogun State, Nigeria. Simple random sampling technique was used to select 90 women locust bean processors for this study. Data were analyzed with descriptive statistics and Pearson Product Moment Correlation. The result showed that the mean age of respondents was 40.72 years. Most (70.00%) of the respondents were married. The mean processing experience was 8.63 years. 93.30% of the respondents relied on information from fellow locust beans processors and friends. All (100%) the respondents did not acquire improved processing skill through trainings and workshops. It can be concluded that the rural women’s skill acquisition on modernized processing techniques was generally low. It is hereby recommend that the rural women processors should be trained by extension service providers through series of workshops and seminars on improved processing techniques.

Keywords: locust bean, processing, skill acquisition, rural women

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Authors: Yeimy L. Quintana, Juan G. Zuluaga, Sandra S. Arango

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The comet assay is a method based on electrophoresis that is used to measure DNA damage in cells and has shown important results in the identification of substances with a potential risk to the human population as innumerable physical, chemical and biological agents. With this technique is possible to obtain images like a comet, in which the tail of these refers to damaged fragments of the DNA. One of the main problems is that the image has unequal luminosity caused by the fluorescence microscope and requires different processing to condition it as well as to know how many optimal comets there are per sample and finally to perform the measurements and determine the percentage of DNA damage. In this paper, we propose the design and implementation of software using Image Processing Toolbox-MATLAB that allows the automation of image processing. The software chooses the optimum comets and measuring the necessary parameters to detect the damage.

Keywords: artificial vision, comet assay, DNA damage, image processing

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Authors: Zuzana Komrsková

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This paper shows the connection between emoticons and politeness in written computer-mediated communication. It studies if there are some differences in the use of emoticon between Czech and English written tweets. My assumptions about the use of emoticons were based on the use of greetings and thanks in real, face to face situations. The first assumption, that welcome greeting phrase would be accompanied by positive emoticon was correct. But for the farewell greeting both positive and negative emoticons are possible. My results show lower frequency of negative emoticons in this context. I also found quite often both positive and negative emoticon in the same tweet. The expression of gratitude is associated with positive emotions. The results show that emoticons accompany polite phrases of greeting and thanks very often both in Czech and English. The use of emoticons with studied polite phrases shows that emoticons have become an integral part of these phrases.

Keywords: Czech, emoticon, english, politeness, twitter

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Authors: A. M. Omoare, O. O. Sofowora, W. O. Oyediran

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The study was carried out to assess the factors affecting the sustainability of rice processing and marketing in Ogun State, Nigeria. Multi-stage sampling technique was used to select one hundred and twenty (120) respondents for the study. Descriptive statistics was used to describe the objectives while hypotheses were analyzed with Pearson Product Moment Correlation. The result showed that most (85%) of the respondents was less than 50 years old and had been in rice business for more than 6 years. The majority (66.67%) of the respondents got their capitals from cooperative societies. All (100%) the respondents used rice as household food security and source of income. However, efficient rice processing and marketing were affected by inadequate manpower capacity development and inputs. There was a positive and significant relationship between socio-economic characteristics and processing techniques (p < 0.05). It is hereby recommended that extension service providers should introduce improved rice processing systems to the rice millers traders in the study area.

Keywords: sustainability, rice processing, marketing, constraints, millers traders

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Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

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This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

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Authors: Elif Unveren, Ozlem Bozkurt

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Emotion processing happens when someone has a negative, stressful experience and gets over it in time, and it is a different experience for every person. As to look into emotion processing can be categorised by intensity, awareness, coordination, speed, accuracy and response. It may vary depending on people’s age, sex and conditions. Each emotion processing shows different activation patterns in different brain regions. Activation is significantly higher in the right frontal areas. The highest activation happens in extended frontotemporal areas during the processing of happiness, sadness and disgust. Those emotions also show widely disturbed differences and get produced earlier than anger and fear. For different occasions, listed variables may have less or more importance. A borderline personality disorder is a condition that creates an unstable personality, sudden mood swings and unpredictability of actions. According to a study that was made with healthy people and people who had BPD, there were significant differences in some categories of emotion processing, such as intensity, awareness and accuracy. According to another study that was made to show the emotional processing differences between puberty and was made for only females who were between the ages of 11 and 17, it was perceived that for different ages and hormone levels, different parts of the brain are used to understand the given task. Also, in the different study that was made for kids that were between the age of 4 and 15, it was observed that the older kids were processing emotion more intensely and expressing it to a greater extent. There was a significant increase in fear and disgust in those matters. To sum up, we can say that the activity of undertaking negative experiences is a unique thing for everybody for many different reasons.

Keywords: age, sex, conditions, brain regions, emotion processing

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Authors: Shreya Borthakur, Aastha Vartak

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This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education.

Keywords: RSVP, attention, visual processing, attentional blink, EEG

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Authors: Abbas Nesayan

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Background: In recent years, autism has been under consideration in public and research area. Autistic children have dysfunction in communication, socialization, repetitive and stereotyped behaviors. In addition, they clinically suffer from difficulty in attention, challenge with familiar behaviors and sensory processing problems. Several variables are linked to sensory processing problems in autism, one of these variables is working memory. Working memory is part of the executive function which provides the necessary ability to completing multiple stages tasks. Method: This study has categorized in correlational research methods. After determining of entry criteria, according to purposive sampling method, 50 children were selected. Dunn’s sensory profile school companion was used for assessment of sensory processing patterns; behavioral rating inventory of executive functions was used (BRIEF) for assessment of working memory. Pearson correlation coefficient and linear regression were used for data analyzing. Results: The results showed the significant relationship between sensory processing patterns (low registration, sensory seeking, sensory sensitivity and sensory avoiding) with working memory in autistic children. Conclusion: According to the findings, there is the significant relationship between the patterns of sensory processing and working memory. So, in order to improve the working memory could be used some interventions based on the sensory processing.

Keywords: sensory processing patterns, working memory, autism, autistic children

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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