Search results for: American Sign Language
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4818

Search results for: American Sign Language

2208 Biological Optimization following BM-MSC Seeding of Partially Demineralized and Partially Demineralized Laser-Perforated Structural Bone Allografts Implanted in Critical Femoral Defects

Authors: S. AliReza Mirghasemi, Zameer Hussain, Mohammad Saleh Sadeghi, Narges Rahimi Gabaran, Mohamadreza Baghaban Eslaminejad

Abstract:

Background: Despite promising results have shown by osteogenic cell-based demineralized bone matrix composites, they need to be optimized for grafts that act as structural frameworks in load-bearing defects. The purpose of this experiment is to determine the effect of bone-marrow-mesenchymal-stem-cells seeding on partially demineralized laser-perforated structural allografts that have been implanted in critical femoral defects. Materials and Methods: P3 stem cells were used for graft seeding. Laser perforation in four rows of three holes was achieved. Cell-seeded grafts were incubated for one hour until they were planted into the defect. We used four types of grafts: partially demineralized only (Donly), partially demineralized stem cell seeded (DST), partially demineralized laser-perforated (DLP), and partially demineralized laser-perforated stem cell seeded (DLPST). histologic and histomorphometric analysis were performed at 12 weeks. Results: Partially demineralized laser-perforated had the highest woven bone formation within graft limits, stem cell seeded demineralized laser-perforated remained intact, and the difference between partially demineralized only and partially demineralized stem cell seeded was insignificant. At interface, partially demineralized laser-perforated and partially demineralized only had comparable osteogenesis, but partially demineralized stem cell seeded was inferior. The interface in stem cell seeded demineralized laser-perforated was almost replaced by distinct endochondral osteogenesis with higher angiogenesis in the vicinity. Partially demineralized stem cell seeded and stem cell seeded demineralized laser-perforated graft surfaces had extra vessel-ingrowth-like porosities, a sign of delayed resorption. Conclusion: This demonstrates that simple cell-based composites are not optimal and necessitates the supplementation of synergistic stipulations and surface changes.

Keywords: structural bone allograft, partial demineralization, laser perforation, mesenchymal stem cell

Procedia PDF Downloads 414
2207 On the Absence of BLAD, CVM, DUMPS and BC Autosomal Recessive Mutations in Stud Bulls of the Local Alatau Cattle Breed of the Republic of Kazakhstan

Authors: Yessengali Ussenbekov, Valery Terletskiy, Orik Zhanserkenova, Shynar Kasymbekova, Indira Beyshova, Aitkali Imanbayev, Almas Serikov

Abstract:

Currently, there are 46 hereditary diseases afflicting cattle with known molecular genetic diagnostic methods developed for them. Genetic anomalies frequently occur in the Holstein cattle breeds from American and Canadian bloodlines. The data on the incidence of BLAD, CVM, DUMPS and BC autosomal recessive lethal mutations in pedigree animals are discordant, the detrimental allele incidence rates are high for the Holstein cattle breed, whereas the incidence rates of these mutations are low in some breeds or they are completely absent. Data were obtained on the basis of frozen semen of stud bulls. DNA was extracted from the semen with the DNA-Sorb-B extraction kit. The lethal mutation in the genes CD18, SLC35A3, UMP and ASS of Alatau stud bulls (N=124) was detected by polymerase chain reaction and RFLP analysis. It was established that stud bulls of the local Alatau breed were not carriers of the BLAD, CVM, DUMPS, and BC detrimental mutations. However, with a view to preventing the dissemination of hereditary diseases it is recommended to monitor the pedigree stock using molecular genetic methods.

Keywords: PCR, autosomal recessive point mutation, BLAD, CVM, DUMPS, BC, stud bulls

Procedia PDF Downloads 443
2206 Building an Opinion Dynamics Model from Experimental Data

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

Abstract:

Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

Procedia PDF Downloads 109
2205 Detailed Quantum Circuit Design and Evaluation of Grover's Algorithm for the Bounded Degree Traveling Salesman Problem Using the Q# Language

Authors: Wenjun Hou, Marek Perkowski

Abstract:

The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

Procedia PDF Downloads 190
2204 Review of Current Literature on Use of Prazosin for Treatment of Post-Traumatic Stress Disorder Related Sleep Disturbances in Child and Adolescent Population

Authors: Davit Khachatryan, Shuo Xiang

Abstract:

Numerous published studies on the use of prazosin in the treatment of PTSD-related sleep disturbances in adult population have resulted in updates to the recommendation for prazosin for nightmares that showed its strength of evidence elevated from C to B in the US Department of Veterans Affairs clinical practice guideline. In addition, the American Academy of Sleep Medicine clinical practice guideline gave prazosin a level-A recommendation for the treatment of PTSD-associated nightmares. The aim of this review is to summarize the available literature for prazosin use for nightmares and other sleep disturbances in children and adolescents with PTSD. Method: A comprehensive search for studies on prazosin use for sleep disturbances in child and adolescent population with PTSD has been performed. We looked at MEDLINE, EMBASE, PsycINFO, CINAHL, AMED, Scopus, Web of Science, and Cochrane CENTRAL databases. Results: Compared to adult population with similar psychopathology, the available literature in child and adolescent population is scarce. Despite increased interest in prazosin in the management of PTSD, only six studies investigating this medication in children and adolescents have been published. Conclusion: A large randomized control trial on this topic is needed for more definite evidence on the efficacy and safety of prazosin in the treatment of nightmares in children and adolescents with PTSD.

Keywords: guidelines, prazosin, PTSD, sleep disturbance

Procedia PDF Downloads 388
2203 Impact of a Training Course in Cardiopulmonary Resuscitation for Primary Care Professionals

Authors: Luiz Ernani Meira Jr., Antônio Prates Caldeira, Gilson Gabriel Viana Veloso, Jackson Andrade

Abstract:

Background: In Brazil, primary health care (PHC) system has developed with multidisciplinary teams in facilities located in peripheral areas, as the entrance doors for all patients. So, professionals must be prepared to deal with patients with simple and complex problems. Objective: To evaluate the knowledge and the skills of physicians and nurses of PHC on cardiorespiratory arrest (CRA) and cardiopulmonary resuscitation (CPR) before and after training in Basic Life Support. Methods: This is a before-and-after study developed in a Simulation Laboratory in Montes Claros, Brazil. We included physicians and nurses randomly chosen from PHC services. Written tests on CRA and CPR were carried out and performances in a CPR simulation were evaluated, based on the American Heart Association recommendations. Training practices were performed using special manikins. Statistical analysis included Wilcoxon’s test to compare before and after scores. Results: Thirty-two professionals were included. Only 38% had previous courses and updates on emergency care. Most of professionals showed poor skills to attend to CRA in a simulated situation. Subjects showed an increased in knowledge and skills about CPR after training (p-value=0.003). Conclusion: Primary health care professionals must be continuously trained to assist urgencies and emergencies, like CRA.

Keywords: primary health care, professional training, cardiopulmonary resuscitation, cardiorespiratory, emergency

Procedia PDF Downloads 314
2202 Effects of Malachite Green Contaminated Water on Production of Pak Choy and Chinese Convolvulus

Authors: N. Piwpuan, J. Tosalee, N. Phonkerd

Abstract:

Malachite green (MG), a synthetic dye, is used in industries and aquaculture and also disposed in the effluent. Use of wastewater in irrigation increases due to water shortage. However, wastewater containing dyes, MG, are toxic to biological systems. Therefore, effects of MG on growth of vegetables were evaluated in order to utilize dye-contaminated wastewater for irrigation. In this study, Pak choy (Brassica chinensis) and Chinese convolvulus (Ipomoea aquatica) were grown in growing material (mixture of soil, coconut fiber, and compost) for four weeks and afterward kept watering with 200 ml of tap water containing MG at the concentrations of 0 (control), 1, 2, 10, and 20 mg/L. At harvest, number of leaf and shoot and root dry weight of the treated plants were measured and compared with control. For both species, their biomass values were similar among treatments and did not differ from the control plants (dry weight were 0.6-1.0 and 1.1-1.7 g/plant for B. chinensis and I. aquatica, respectively). B. chinensis treated with 2, 10, and 20 mg/L of MG produced lower number of new leaf and had smaller and shorter leaf compared to control and treatment of 1 mg/L. These results indicate the different responses between plant species, which B. chinensis is more sensitive to contaminant compared to I. aquatica. There was no sign of MG and leucomalachite green (LMG) detected in root and shoot tissues of plants treated with MG at 20 mg/L, tested by thin layer chromatography. After plant harvest, toxicity of the growing material from all treatments was tested on mung beans. Percent germination (83-97%), seedling fresh weight (0.3-0.5 g/plant), and shoot length (11-12.5 cm) were similar to the control. These indicated that contaminant in growing material did not pose detrimental effect on mung beans. Based on these results, the water contaminated with low concentration of MG, such as discharge from aquaculture, may serve as ferti-irrigation water to compensate water shortage.

Keywords: ferti-irrigation, soil toxicity, triphenylmethane dye, wastewater reuse

Procedia PDF Downloads 199
2201 Neural Network based Risk Detection for Dyslexia and Dysgraphia in Sinhala Language Speaking Children

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 64
2200 Collaborative Online International Learning with Different Learning Goals: A Second Language Curriculum Perspective

Authors: Andrew Nowlan

Abstract:

During the Coronavirus pandemic, collaborative online international learning (COIL) emerged as an alternative to overseas sojourns. However, now that face-to-face classes have resumed and students are studying abroad, the rationale for doing COIL is not always clear amongst educators and students. Also, the logistics of COIL become increasingly complicated when participants involved in a potential collaboration have different second language (L2) learning goals. In this paper, the researcher will report on a study involving two bilingual, cross-cultural COIL courses between students at a university in Japan and those studying in North America, from April to December, 2022. The students in Japan were enrolled in an intercultural communication class in their L2 of English, while the students in Canada and the United States were studying intermediate Japanese as their L2. Based on a qualitative survey and journaling data received from 31 students in Japan, and employing a transcendental phenomenological research design, the researcher will highlight the students’ essence of experience during COIL. Essentially, students benefited from the experience through improved communicative competences and increased knowledge of the target culture, even when the L2 learning goals between institutions differed. Students also reported that the COIL experience was effective in preparation for actual study abroad, as opposed to a replacement for it, which challenges the existing literature. Both educators and administrators will be exposed to the perceptions of Japanese university students towards COIL, which could be generalized to other higher education contexts, including those in Southeast Asia. Readers will also be exposed to ideas for developing more effective pre-departure study abroad programs and domestic intercultural curriculum through COIL, even when L2 learning goals may differ between participants.

Keywords: collaborative online international learning, study abroad, phenomenology, EdTech, intercultural communication

Procedia PDF Downloads 82
2199 Microbiota Effect with Cytokine in Hl and NHL Patient Group

Authors: Ekin Ece Gürer, Tarık Onur Tiryaki, Sevgi Kalayoğlu Beşışık, Fatma Savran Oğuz, Uğur Sezerman, Fatma Erdem, Gülşen Günel, Dürdane Serap Kuruca, Zerrin Aktaş, Oral Öncül

Abstract:

Aim: Chemotherapytreatment in HodgkinLymphomaandNon-HodgkinLymphoma (NHL) diseasescausesgastrointestinalepithelialdamage, disruptstheintestinalmicrobiotabalanceandcausesdysbiosis. Inourstudy, it wasaimedtoshowtheeffect of thedamagecausedbychemotherapy on themicrobiotaandtheeffect of thechangingmicrobiota flora on thecourse of thedisease. Materials And Methods: Seven adult HL and seven adult HL patients to be treatedwithchemotherapywereincluded in the study. Stoolsamplesweretakentwice, beforechemotherapytreatmentandafterthe 3th course of treatment. SamplesweresequencedusingNextGenerationSequencing (NGS) methodafternucleicacidisolation. OTU tableswerepreparedusing NCBI blastnversion 2.0.12 accordingtothe NCBI general 16S bacterialtaxonomyreferencedated 10.08.2021. Thegenerated OTU tableswerecalculatedwith R Statistical Computer Language version 4.04 (readr, phyloseq, microbiome, vegan, descrand ggplot2 packages) to calculate Alpha diversityandtheirgraphicswerecreated. Statistical analyzeswerealsoperformedusing R Statistical Computer Language version 4.0.4 and studio IDE 1.4 (tidyverse, readr, xlsxand ggplot2 packages). Expression of IL-12 and IL-17 cytokineswasperformedbyrtPCRtwice, beforeandaftertreatment. Results: InHL patients, a significantdecreasewasobserved in themicrobiota flora of Ruminococcaceae_UCG-014 genus (p:0.036) andUndefined Ruminococcaceae_UCG-014 species (p:0.036) comparedtopre-treatment. When the post-treatment of HL patientswerecomparedwithhealthycontrols, a significantdecreasewasfound in themicrobiota of Prevotella_7 genus (p:0.049) andButyricimonas (p:0.006) in the post-treatmentmicrobiota of HL patients. InNHL patients, a significantdecreasewasobserved in themicrobiota flora of Coprococccus_3 genus (p:0.015) andUndefined Ruminoclostridium_5 (p:0.046) speciescomparedtopre-treatment. When post-treatment of NHL patientswerecomparedwithhealthycontrols, a significantabundance in theBacilliclass (p:0.029) and a significantdecrease in theUndefinedAlistipesspecies (p:0.047) wereobserved in the post-treatmentmicrobiota of NHL patients. While a decreasewasobserved in IL-12 cytokineexpressionuntilbeforetreatment, an increase in IL-17 cytokineexpressionwasdetected. Discussion: Intestinal flora monitoringafterchemotherapytreatmentshowsthat it can be a guide in thetreatment of thedisease. It is thoughtthatincreasingthediversity of commensalbacteria can alsopositivelyaffecttheprognosis of thedisease.

Keywords: hodgkin lymphoma, non-hodgkin, microbiota, cytokines

Procedia PDF Downloads 108
2198 The Emergence of the Knowledge-Based Urban Development: An Evaluation of Sydney, New York and London's Race to the Top

Authors: Richard W. Jelier

Abstract:

This research examines the emergence of the knowledge-based economies in three world cities in a comparative context. The Australian, American and British approaches to (KBE) are analyzed through the study of three premier world cities of Sydney, New York and London. Long considered leaders in the KBE, London and New York’s pre-imminence in this race to the top is not surprising. Sydney, Australia however has seen a remarkable transformation from an old economy to an emerging success in the new economy. After an examination of national KBE indicators (GDP comparisons and Knowledge Economy indexes) the research turns to a detailed investigation of specific strategies advanced in greater Sydney, New York City and London to advance the creative sector and compete for a spot among the world leaders in the knowledge age. These intense efforts at restructuring national and local economies have led to increasingly intense competition between cities and nations and there are clear winners and losers. Overall the conclusion of this research suggests that as Australia is rising, America is struggling to keep its position as a global world leader in the new economy. London’s urban primacy has helped elevate it role in the UK new economy and recent transformations have led London to compete successfully with New York City for the top position as the premier global city.

Keywords: knowledge-based economy, knowledge economy indexes, sustainable transformation, creative economies, New York, London and Sydney

Procedia PDF Downloads 243
2197 Arduino Pressure Sensor Cushion for Tracking and Improving Sitting Posture

Authors: Andrew Hwang

Abstract:

The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion

Procedia PDF Downloads 134
2196 Deep Learning-Based Approach to Automatic Abstractive Summarization of Patent Documents

Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty

Abstract:

A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.

Keywords: abstractive summarization, deep learning, natural language Processing, patent document

Procedia PDF Downloads 123
2195 Key Drivers Motivating Prospective International Students to Study Abroad and Their Attitude to University Rankings

Authors: Dasha Karzunina, Laura Bridgestock

Abstract:

Our oral presentation will be based on our qualitative and quantitative findings into motivations and challenges faced by international and UK students when choosing a university abroad. The insight was gathered through a series of over 60 focus groups held with prospective university students all over the world, including masters and PhD applicants. We spoke to students face-to-face in Latin America, North American, India, China, South East Asia and the major European cities. A survey was carried out alongside, to gather additional insight on their priorities and attitudes to universities’ reputation, collecting over 1,800 responses. The session’s aims are to break down some of the myths about the perspectives of international students and inform university leaders interested in recruiting more highly talented students from abroad and those currently working with international students. As a provider of one of the most demanded resources in higher education, QS World University Rankings, we specialize in understanding universities’ performance, their institutional brand and the impact of rankings on student recruitment. We therefore feel we are well placed to carry out and present this research. We hope for our findings to act as a bridge between bright students and their future universities abroad. We intend for our session to be interactive and so are happy to go into more depth on any of the destinations we visited, depending on what the audience is most interested in and which questions we receive.

Keywords: international student recruitment, market research, rankings, study abroad

Procedia PDF Downloads 236
2194 The Effects of Adlerian Supervision on Enhancing Career Consultants’ Case Conceptualization

Authors: Lin Shang Neng

Abstract:

Due to rapid changes in the societal environment, career development and planning have become increasingly crucial, leading more individuals to seek the assistance of career consultations. However, the training process for career consultants often emphasizes the application of assessment tools and guidance in job-seeking behavior. The abilities of case conceptualization and consulting skills require further in-service supervision. This study aims to inquire about the supervised experiences of employment specialists at the Employment Service Center of the Taiwan Ministry of Labor or career consultants who held private clinics for at least three years. The research participants were continuously supervised by the Adlerian approach twice a month for at least one year, helping them integrate the whole picture of the client through Lifestyle Assessment (the qualitative way, specific diagnosis) and other Adlerian assessment tools (the quantitative way, general diagnosis.) The supervisor was familiar with Adlerian Psychology and certified by the North American Society of Adlerian Psychology. The research method involves semi-structured interviews and qualitative analysis. For the ethical considerations, the participants were invited to interview after the supervision sessions finished. The findings of this research were discussed with possible implications, like how they applied Adlerian Psychology to their career consultations, especially to case conceptualizations and consulting skills. Recommendations for further research and training for career consultants are also discussed.

Keywords: supervision, Adlerian psychology, case conceptualization, career consultant

Procedia PDF Downloads 78
2193 Neural Network-based Risk Detection for Dyslexia and Dysgraphia in Sinhala Language Speaking Children

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 114
2192 A Bayesian Hierarchical Poisson Model with an Underlying Cluster Structure for the Analysis of Measles in Colombia

Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

Abstract:

In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

Procedia PDF Downloads 151
2191 Enhancing the Interpretation of Group-Level Diagnostic Results from Cognitive Diagnostic Assessment: Application of Quantile Regression and Cluster Analysis

Authors: Wenbo Du, Xiaomei Ma

Abstract:

With the empowerment of Cognitive Diagnostic Assessment (CDA), various domains of language testing and assessment have been investigated to dig out more diagnostic information. What is noticeable is that most of the extant empirical CDA-based research puts much emphasis on individual-level diagnostic purpose with very few concerned about learners’ group-level performance. Even though the personalized diagnostic feedback is the unique feature that differentiates CDA from other assessment tools, group-level diagnostic information cannot be overlooked in that it might be more practical in classroom setting. Additionally, the group-level diagnostic information obtained via current CDA always results in a “flat pattern”, that is, the mastery/non-mastery of all tested skills accounts for the two highest proportion. In that case, the outcome does not bring too much benefits than the original total score. To address these issues, the present study attempts to apply cluster analysis for group classification and quantile regression analysis to pinpoint learners’ performance at different proficiency levels (beginner, intermediate and advanced) thus to enhance the interpretation of the CDA results extracted from a group of EFL learners’ reading performance on a diagnostic reading test designed by PELDiaG research team from a key university in China. The results show that EM method in cluster analysis yield more appropriate classification results than that of CDA, and quantile regression analysis does picture more insightful characteristics of learners with different reading proficiencies. The findings are helpful and practical for instructors to refine EFL reading curriculum and instructional plan tailored based on the group classification results and quantile regression analysis. Meanwhile, these innovative statistical methods could also make up the deficiencies of CDA and push forward the development of language testing and assessment in the future.

Keywords: cognitive diagnostic assessment, diagnostic feedback, EFL reading, quantile regression

Procedia PDF Downloads 146
2190 Chinese “Wolf Warrior” Diplomacy And Foreign Public Opinion

Authors: Chaohong Pan

Abstract:

Through public diplomacy on social media, governments have attempted to influence foreign public opinion. What is the impact of digital public diplomacy? Public diplomacy research often relies on content analysis to study the strategies employed by communicators but has rarely examined its actual impact on the audience. In addition, we do not know if giving a communicator an explicit label, as Twitter does with “government account”, would change the effects of the messages. Can the government label reduce the percussiveness of public diplomacy messages by sending a warning signal? Using a 2 × 2 survey experiment, the present paper contributes to the study of public diplomacy by randomly exposing American participants to four types of tweets from Chinese diplomats. The stimulus materials vary in terms of the tweets’ content (“positive-china” vs. “negative-US) and Twitter government labels (with vs. without the labels). I found that positive tweets about China have a significant positive effect on Americans’ attitudes toward China, whereas negative tweets about the US have little effect on their opinions. Furthermore, positive-China tweets are effective only on China-related issues, which indicates that Chinese diplomats’ tweets have limited effects on shaping a foreign audience’s attitudes toward their own country. Lastly, I find that labels largely have no impact on a diplomatic tweet’s effect. These results contribute to our understanding of the effects of public diplomacy in the digital age.

Keywords: public diplomacy, china, foreign public opinion, twitter

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2189 Catered Lunch Suspected Outbreak in a Garment Factory, Sleman District, Yogyakarta, Indonesia, 2017

Authors: Rieski Prihastuti, Meliana Depo, Trisno A. Wibowo, Misinem

Abstract:

On October 19, 2017, Yogyakarta Islamic Hospital reported 38 garment employees with nausea, vomiting, headache, abdominal pain, and diarrhea after they had lunch on October 18, 2017, to Sleman District Health Office. Objectives of this study were to ensure the outbreak and identify source and route of transmission. Case-control study was conducted to analyze food items that caused the outbreak. A case was defined as a person who got symptoms such as abdominal pain, diarrhea, nausea with/without vomiting, fever, and headache after they had lunch on October 18, 2017. Samples included leftover lunch box, vomit, tap water and drinking water had been sent to the laboratory. Data were analyzed descriptively as frequency table and analyzed by using chi-square in bivariate analysis. All of 196 garment employee was included in this study. The common symptoms of this outbreak were abdominal pain (84.4%), diarrhea (72.8%), nausea (61.6%), headache (52.8%), vomiting (12.8%), and fever (6.4%) with median incubation period 13 hours (range 1-34 hours). Highest attack rate and odds ratio was found in grilled chicken (Attack Rate 58,49%) with Odds Ratio 11,023 (Confidence Interval 95% 1.383 - 87.859; p value 0,005). Almost all samples showed mold, except drinking water. Based on its sign and symptoms, also incubation period, diarrheal Bacillus cereus and Clostridium perfringens were suspected to be the causative agent of the outbreak. Limitation of this study was improper sample handling and no sample of food handler and stools in the food caterer. Outbreak investigation training needed to be given to the hospital worker, and monitoring should be done to the food caterer to prevent another outbreak.

Keywords: disease outbreak, foodborne disease, food poisoning, outbreak

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2188 Study and Fine Characterization of the SS 316L Microstructures Obtained by Laser Beam Melting Process

Authors: Sebastien Relave, Christophe Desrayaud, Aurelien Vilani, Alexey Sova

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Laser beam melting (LBM) is an additive manufacturing process that enables complex 3D parts to be designed. This process is now commonly employed for various applications such as chemistry or energy, requiring the use of stainless steel grades. LBM can offer comparable and sometimes superior mechanical properties to those of wrought materials. However, we observed an anisotropic microstructure which results from the process, caused by the very high thermal gradients along the building axis. This microstructure can be harmful depending on the application. For this reason, control and prediction of the microstructure are important to ensure the improvement and reproducibility of the mechanical properties. This study is focused on the 316L SS grade and aims at understanding the solidification and transformation mechanisms during process. Experiments to analyse the nucleation and growth of the microstructure obtained by the LBM process according to several conditions. These samples have been designed on different type of support bulk and lattice. Samples are produced on ProX DMP 200 LBM device. For the two conditions the analysis of microstructures, thanks to SEM and EBSD, revealed a single phase Austenite with preferential crystallite growth along the (100) plane. The microstructure was presented a hierarchical structure consisting columnar grains sizes in the range of 20-100 µm and sub grains structure of size 0.5 μm. These sub-grains were found in different shapes (columnar and cellular). This difference can be explained by a variation of the thermal gradient and cooling rate or element segregation while no sign of element segregation was found at the sub-grain boundaries. A high dislocation concentration was observed at sub-grain boundaries. These sub-grains are separated by very low misorientation walls ( < 2°) this causes a lattice of curvature inside large grain. A discussion is proposed on the occurrence of these microstructures formation, in regard of the LBM process conditions.

Keywords: selective laser melting, stainless steel, microstructure

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2187 Investigating Introvert and Extrovert University Students’ Perception of the Use of Interactive Digital Tools in a Face-To-Face ESP Class

Authors: Eunice Tang

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The main focus of this study is investigating introvert and extrovert university students’ perception of the use of interactive digital tools (such as Padlet and Mentimeter) in a face-to-face English for Specific Purposes (ESP) class after all classes in the university had been switched to online mode for three semesters. The subjects of the study were business students from three ESP classes at The Hong Kong University of Science and Technology. The basic tool for data collection was an anonymous online survey, which included 3 required multiple-choice questions and 3 open questions (2 required; 1 optional) about the effects of interactive digital tools on their amount of contribution to the class discussions, their perception of the role of interactive digital tools to the sharing of ideas and whether the students considered themselves introvert or extrovert. The online survey will be emailed to all 54 students in the three ESP classes and subjected to a three-week data collection period. The survey results will then be analyzed qualitatively, particularly on the effect the use of interactive digital tools had on the amount of contribution to the class among introvert and extrovert students, their perception of a language class with and without digital tools and most importantly, the implication to educators about how interactive digital tools can be used (or not) to cater for the needs of the introvert and extrovert students. The pandemic has given educators various opportunities to use interactive digital tools in class, especially in an online environment. It is interesting for educators to explore the potential of such tools when classes are back face-to-face. This research thus offers the students’ perspective on using interactive digital tools in a face-to-face classroom. While a lot has been said about introverted students responding positively to digital learning online, the student's perception of their own personality collected in the survey and the digital impact tools have on their contribution to class may shed some light on the potential of interactive digital tools in a post-pandemic era.

Keywords: psychology for language learning, interactive digital tools, personality-based investigation, ESP

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2186 Federal Bureau of Investigation Opposition to German Nationalist Organizations in the United States (1941-45)

Authors: Yaroslav Alexandrovich Levin

Abstract:

In modern research on the history of the United States in World War II, it is quite popular to study the opposition of the American special services and, in particular, the Federal Bureau of Investigation (FBI) to various organizations of the German diasporas in new historical conditions. The appeal to traditional methods of historical research, comparative studies, and the principles of historicism will make it possible to more accurately trace the process of tightening the counterintelligence work of the Bureau and the close connection of concerns about the involvement of public organizations in the intelligence activities of the enemy. The broadcast of nationalist ideas by various communities of Germans under the auspices of their governments quickly attracted the attention of the FBI, which is in the process of consolidating its powers as the main US counterintelligence service. At the same time, the investigations and trials conducted by the John Edgar Hoover Department following these investigations often had an openly political color and increasingly consolidated the beginning of a political investigation in this service. This practice and its implementation ran into a tough contradiction between the legal norms of America, which proclaimed "democratic values," the right to freedom of speech, and the need to strengthen the internal security of the state and society in wartime. All these processes and the associated nuances and complexities are considered in specific examples of the work of federal agents against various pro-German organizations in the period 1941-45.

Keywords: World War II, internal security, countering extremism, counterintelligence, political investigation, FBI

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2185 Imperialism, Sustainability and Role of United States of America

Authors: Subhashini Chaturvedi

Abstract:

The New World Order of the 21st century which is largely lead by Global Technological Leadership, and a workforce of United Nations coming together in the wake of our planet's future. The objective of this study is to understand the approach taken to implement sustainable use of resources and adequate architectural interventions. The framework of global policies in terms of sustainability has to be checked whether they commensurate and do justice to various nations with highly variable resource availability and development index. The method used to analyse the subject is a study of linkage between Age, Development, and exertion of the land, which attribute to the history of nations worldwide. The study also questions whether the use of term Sustainability is even ethical to be suggested in under developed or developing nations. Evolving through examples of American Imperialism to steady decline of Indian state of Punjab over last few decades, shows how sustainability has acted like scoop taken from a whole container in case of developed societies whereas it has acted like scratching the bottom of an empty container in case of embryonic societies where needs for sustenance are still far fed. The result comes out in favour of more innovative and rational implementation of architecture, sustainability and urban planning in context to indigenous space of a society and its statistics. The bridge to reduce the gap of fiscal deficit in resource premises can be consolidated by balancing on a global level majorly and this research paper is in the pursuance of the same idea.

Keywords: developing nations, economy, holistic development, innovation, logical approach, statistics, USA

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2184 Unravelling the Interplay: Chinese Government Tweets, Anti-US Propaganda Cartoons and Social Media Dynamics in US-China Relations

Authors: Mitchell Gallagher

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This investigation explores the relationship between Chinese government ministers' tweets and publicized anti-US propaganda political cartoons by Chinese state media. Defining "anti-US" tweets as expressions with negative impressions about the United States, its policies, or cultural values, the study considers their context-dependent nature. Analyzing social media's growing role, this research probes the Chinese government's attitudes toward the United States. While China traditionally adhered to a non-interference stance, instances of verbal and visual retorts occurred, driven by efforts to enhance soft power and counter unfavorable portrayals. To navigate global challenges, China embraced proactive image construction, utilizing political cartoons as a messaging tool. As Sino-American political relations continue deteriorating, it has become increasingly commonplace for Chinese officials to circulate anti-US messages and negative impressions of the United States via tweets. The present study is committed to inspecting the nature and frequency of political cartoons casting the United States in an unfavorable light, with the aim of gaining a comprehensive understanding the degree to which the Chinese government and state-affiliated media are aligned in their corresponding messaging.

Keywords: China, political cartoons, propaganda, twitter, social media

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2183 Information Extraction for Short-Answer Question for the University of the Cordilleras

Authors: Thelma Palaoag, Melanie Basa, Jezreel Mark Panilo

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Checking short-answer questions and essays, whether it may be paper or electronic in form, is a tiring and tedious task for teachers. Evaluating a student’s output require wide array of domains. Scoring the work is often a critical task. Several attempts in the past few years to create an automated writing assessment software but only have received negative results from teachers and students alike due to unreliability in scoring, does not provide feedback and others. The study aims to create an application that will be able to check short-answer questions which incorporate information extraction. Information extraction is a subfield of Natural Language Processing (NLP) where a chunk of text (technically known as unstructured text) is being broken down to gather necessary bits of data and/or keywords (structured text) to be further analyzed or rather be utilized by query tools. The proposed system shall be able to extract keywords or phrases from the individual’s answers to match it into a corpora of words (as defined by the instructor), which shall be the basis of evaluation of the individual’s answer. The proposed system shall also enable the teacher to provide feedback and re-evaluate the output of the student for some writing elements in which the computer cannot fully evaluate such as creativity and logic. Teachers can formulate, design, and check short answer questions efficiently by defining keywords or phrases as parameters by assigning weights for checking answers. With the proposed system, teacher’s time in checking and evaluating students output shall be lessened, thus, making the teacher more productive and easier.

Keywords: information extraction, short-answer question, natural language processing, application

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2182 Validating the Micro-Dynamic Rule in Opinion Dynamics Models

Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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2181 Content Analysis of Video Translations: Examining the Linguistic and Thematic Approach by Translator Abdullah Khrief on the X Platform

Authors: Easa Almustanyir

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This study investigates the linguistic and thematic approach of translator Abdullah Khrief in the context of video translations on the X platform. The sample comprises 15 videos from Khrief's account, covering diverse content categories like science, religion, social issues, personal experiences, lifestyle, and culture. The analysis focuses on two aspects: language usage and thematic representation. Regarding language, the study examines the prevalence of English while considering the inclusion of French and German content, highlighting Khrief's multilingual versatility and ability to navigate cultural nuances. Thematically, the study explores the diverse range of topics covered, encompassing scientific, religious, social, and personal narratives, underscoring Khrief's broad subject matter expertise and commitment to knowledge dissemination. The study employs a mixed-methods approach, combining quantitative data analysis with qualitative content analysis. Statistical data on video languages, presenter genders, and content categories are analyzed, and a thorough content analysis assesses translation accuracy, cultural appropriateness, and overall quality. Preliminary findings indicate a high level of professionalism and expertise in Khrief's translations. The absence of errors across the diverse range of videos establishes his credibility and trustworthiness. Furthermore, the accurate representation of cultural nuances and sensitive topics highlights Khrief's cultural sensitivity and commitment to preserving intended meanings and emotional resonance.

Keywords: audiovisual translation, linguistic versatility, thematic diversity, cultural sensitivity, content analysis, mixed-methods approach

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2180 Motivational Strategies for Young Learners in Distance Education

Authors: Saziye Darendeli

Abstract:

Motivation has a significant impact on a second/foreign language learning process, so it plays a vital role while achieving the learning goal. As it is defined by Simon (1967, p. 29), motivation is “a goal terminating mechanism, permitting goals to be processed serially.”AccordingtoSimon, if a learning goal is activated and enough attention is given, the learner starts learning. In connection with this view, the more attention is given on a subject, and the more activation takes place on it, the quicker learning will occur. Moreover, today almost every teacher is familiar with the term “distance education” regardless of their student's age group. As it is stated by Visser (2002), when compared to the traditional classrooms, in distance education, the rate and success of language learningdecreasesandone of the most essential reasons is that motivating students in distance education contexts, in which interaction is lower, is much more challenging than face-to-face training especially with young learners(Lim& Kim, 2003). Besides, there are limited numbers of studies conducted on motivational strategies for young learners in distance education contexts since we have been experiencing full time the online schooling process recently, yet online teaching seems to be permanent in our lives with the new technological era. Therefore, there appears to be a need for various strategies to motivate young learners in distance education, and the current study aims to find out the strategies that young learners’ teachers use to increase their students’ motivation level in distance education. To achieve this aim, a qualitative research approach and a phenomenological method with an interpretive design will be used. The participants, who are teachers of young learners, will be interviewed using a structured interview format consisting of 7 questions. As the participants are young learners’teacherswhohavebeenexperiencingteaching online, exploring thestrategiesthattheyusetoincreasetheirstudents’ motivationlevelwillprovidesomesuggestionsaboutthemotivationalstrategiesforfuture online classes. Also, in this paper, I will move beyond the traditional classrooms that have face-to-face lessons and discuss the effective motivational strategies for young learners in distance education.

Keywords: motivation, distance education, young learners, strategies

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2179 Characterization of Emissions from the open burning of Municipal Solid Waste (MSW) under Tropical Environment

Authors: Anju Elizbath Peter, S. M. Shiva Nagendra, Indumathi M.Nambi

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The deliberate fires initiated by dump managers and human scavengers to reduce the volume of waste and recovery of valuable metals/materials are common at municipal solid waste (MSW) disposal sites in developed country. A large amount of toxic gases released due to this act is responsible for the deterioration of regional and local air quality, which causes visibility impairment and acute respiratory diseases. The present study was aimed at the characterization of MSW and emission characteristics of burning of MSW in the laboratory. MSW samples were collected directly from the one of the open dumpsite located in Chennai city. Solid waste sampling and laboratory analysis were carried out according to American Society of Testing and Materials (ASTM) standards. Results indicated the values of moisture content, volatile solids (VS) and calorific values of solid waste samples were 16.67%,8%,9.17MJ/kg, respectively. The elemental composition showed that the municipal solid waste contains 25.84% of carbon, 3.69% of hydrogen, 1.57% of nitrogen and 0.26% of sulphur. The calorific value of MSW was found to be 9.17 MJ/Kg which is sufficient to facilitate self-combustion of waste. The characterization of emissions from the burning of 1 kg of MSW in the test chamber showed a total of 90 mg/kg of PM10 and 243 mg/kg of PM2.5. The current research study results will be useful for municipal authorities to formulate guideline and policy structure regarding the MSW management to reduce the impact of air emissions at an open dump site.

Keywords: characterization, MSW, open burning, PM10, PM2.5

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