Search results for: adaptive random testing

Authors: Yiquan Liao, Quanhong Jiang

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Since terahertz was observed by German scientists, we have obtained terahertz through different generation technologies of broadband and narrowband. Then, with the development of semiconductor and other technologies, the imaging technology of terahertz has become increasingly perfect. From the earliest application of nondestructive testing in aviation to the present application of information transmission and human safety detection, the role of terahertz will shine in various fields. The weapons produced by terahertz were epoch-making, which is a crushing deterrent against technologically backward countries. At the same time, terahertz technology in the fields of imaging, medical and livelihood, communication and communication are for the well-being of the country and the people.

Keywords: terahertz, imaging, communication, medical treatment

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Zina Benouaret, Djamil Aissani

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In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis

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Authors: N. Dunleavy, E. Lovemore, K. Siljeur, D. Jackson, M. Hendricks, M. Hoosain, N. Plastow, S. Marais

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Background: The work requirements of sewing machine operators cause physical and emotional strain. Past ergonomic interventions have been provided to alleviate physical concerns; however, a holistic, multimodal intervention was needed to improve these factors. Aim: The study aimed to examine the effect of an occupational therapy programme on sewing machine operators’ pain, mental health, and productivity within a factory in the South African context. Methods: A pilot randomised control trial was conducted with 22 sewing machine operators within a single factory. Stratified randomisation was used to determine the experimental (EG) and control groups (CG), using measures for pain intensity, level of depression (mental health), and productivity rates as stratification variables. The EG received the multimodal intervention, incorporating education, seating adaptations, and mental health intervention. In three months, the CG will receive the same intervention. Pre- and post-intervention testing have occurred with upcoming three- and six-month follow-ups. Results: Immediate results indicate a statistically significant decrease in pain in both experimental and control groups; no change in productivity scores and depression between the two groups. This may be attributed to external factors. The values for depression further showed no statistical significance between the two groups and within pre-and post-test results. The Statistical Program for Social Sciences (SPSS) version-24 was used as the data analysis testing, where all the tests will be evaluated at a 5% significance level. Contribution of research: The research adds to the body of knowledge informing the Occupational Therapy role in work settings, providing evidence on the effectiveness of workplace-based multimodal interventions. Conclusion: The study provides initial data on the effectiveness of a pilot randomised control trial on pain and mental health in South Africa. Results indicated no quantitative change between the experimental and control groups; however, qualitative data suggest a clinical significance of the findings.

Keywords: ergonomics programme, occupational therapy, sewing machine operators, workplace-based multimodal interventions

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Authors: Hassan Naseh, Javad Roozgard

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This paper represents the methodology based on Artificial Intelligent (AI) applied to Liquid Propellant Engine (LPE) optimization. The AI methodology utilized from Adaptive neural Fuzzy Inference System (ANFIS). In this methodology, the optimum objective function means to achieve maximum performance (specific impulse). The independent design variables in ANFIS modeling are combustion chamber pressure and temperature and oxidizer to fuel ratio and output of this modeling are specific impulse that can be applied with other objective functions in LPE design optimization. To this end, the LPE’s parameter has been modeled in ANFIS methodology based on generating fuzzy inference system structure by using grid partitioning, subtractive clustering and Fuzzy C-Means (FCM) clustering for both inferences (Mamdani and Sugeno) and various types of membership functions. The final comparing optimization results shown accuracy and processing run time of the Gaussian ANFIS Methodology between all methods.

Keywords: ANFIS methodology, artificial intelligent, liquid propellant engine, optimization

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Authors: Jonjaua Ranogajec, Ognjen Rudic, Snezana Pasalic, Snezana Vucetic, Damir Cjepa

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The paper involves a chain of activities from synthesis, establishment of the methodology for characterization and testing of novel protective materials through the pilot production and application on model supports. It summarizes the results regarding the development of the pilot production protocol for newly developed self-cleaning materials. The optimization of the production parameters was completed in order to improve the most important functional properties (mineralogy characteristics, particle size, self-cleaning properties and photocatalytic activity) of the newly designed nanocomposite material.

Keywords: pilot production, self-cleaning materials, compatibility, cultural heritage

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Authors: Suyeb Ahmed Khan, Mahmood Mian

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Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

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Authors: Joon Hock Yeo, Munirah Ismail

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Chronic venous insufficiency is a condition where the venous wall or venous valves fail to operate properly. As such, it is difficult for the blood to return from the lower extremities back to the heart. Chronic venous insufficiency affects many people worldwide. In last decade, there have been many new and innovative designs of prosthetic venous valves to replace the malfunction native venous valves. However, thus far, to the authors’ knowledge, there is no successful prosthetic venous valve. In this project, we have developed a venous valve which could operate under low pressure. While further testing is warranted, this unique valve could potentially alleviate problems associated with chronic venous insufficiency.

Keywords: prosthetic venous valve, bi-leaflet valve, chronic venous insufficiency, valve hemodynamics

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Authors: Atitallah Sofien, Bouyahia Olfa, Attar Souleima, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Ciliopathies are a spectrum of diseases that have in common a defect in the synthesis of ciliary proteins. It is a rare cause of neonatal cholestasis. Clinical presentation varies extremely, and the main affected organs are the kidneys, liver, and pancreas. Methodology: This is a descriptive case report of a newborn who was admitted for exploration of neonatal cholestasis in the Paediatric Department C at the Children’s Hospital of Tunis, where the investigations concluded with a rare genetic mutation. Results: This is the case of a newborn male with no family history of hepatic and renal diseases, born to consanguineous parents, and from a well-monitored uneventful pregnancy. He developed jaundice on the second day of life, for which he received conventional phototherapy in the neonatal intensive care unit. He was admitted at 15 days for mild bronchiolitis. On clinical examination, intense jaundice was noted with normal stool and urine colour. Initial blood work showed an elevation in conjugated bilirubin and a high gamma-glutamyl transferase level. Transaminases and prothrombin time were normal. Abdominal sonography revealed hepatomegaly, splenomegaly, and undifferentiated renal cortex with bilateral medullar micro-cysts. Kidney function tests were normal. The infant received ursodeoxycholic acid and vitamin therapy. Genetic testing showed a homozygous mutation in the DCDC2 gene that hadn’t been documented before confirming the diagnosis of renal-hepatic ciliopathy. The patient has regular follow-ups, and his conjugated bilirubin and gamma-glutamyl transferase levels have been decreasing. Conclusion: Genetic testing has revolutionized the approach to etiological diagnosis in pediatric cholestasis. It enables personalised treatment strategies to better enhance the quality of life of patients and prevent potential complications following adequate long-term monitoring.

Keywords: cholestasis, newborn, ciliopathy, DCDC2, genetic

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Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

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Authors: Jihène Khalifa

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This study analyzed the relationships between Tunisia’s economic growth, food security, agricultural productivity, and climate change using the ARDL model for the period from 1990 to 2022. The ARDL model reveals a positive correlation between economic growth and lagged agricultural productivity. Additionally, the vector autoregressive (VAR) model highlights the beneficial impact of lagged agricultural productivity on economic growth and the negative effect of rainfall on economic growth. Granger causality analysis identifies unidirectional relationships from economic growth to agricultural productivity, crop production, food security, and temperature variations, as well as from temperature variations to crop production. Furthermore, a bidirectional causality is established between crop production and food security. The study underscores the impact of climate change on crop production and suggests the need for adaptive strategies to mitigate these climate effects.

Keywords: economic growth, agriculture, food security, climate change, ARDl, VAR

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Authors: Avinash S. Jagtap, Sharad D. Gore, Rajendra G. Gurao

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Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule

Keywords: strategic, tactical, operational, adaptive, innovative

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Authors: Sorcha Bennett, Joe Sullivan

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Triple-Level Cell (TLC) NAND Flash memory at, and below, 20nm (nanometer) is still largely unexplored by researchers, and with the ever more commonplace existence of Flash in consumer and enterprise applications there is a need for such gaps in knowledge to be filled. At the time of writing, there was little published data or literature on TLC, and more specifically reliability testing, with a further emphasis on both endurance and retention. This paper will give an introduction to NAND Flash memory, followed by an overview of the relevant current research on the reliability of Flash memory, along with the planned future work which will provide results to help characterise the reliability of TLC memory.

Keywords: endurance, patterns, raw flash, reliability, retention, TLC NAND flash memory, trade-off

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Authors: K. Suganya Devi, P. Srinivasan, M. P. Vaishnave, G. Arutperumjothi

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Today’s internet world is highly prone to various online attacks, of which the most harmful attack is phishing. The attackers host the fake websites which are very similar and look alike. We propose an image based authentication using steganography and visual cryptography to prevent phishing. This paper presents a secure steganographic technique for true color (RGB) images and uses Discrete Cosine Transform to compress the images. The proposed method hides the secret data inside the cover image. The use of visual cryptography is to preserve the privacy of an image by decomposing the original image into two shares. Original image can be identified only when both qualified shares are simultaneously available. Individual share does not reveal the identity of the original image. Thus, the existence of the secret message is hard to be detected by the RS steganalysis.

Keywords: image security, random LSB, steganography, visual cryptography

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: Xiaohuan Li, Wangmin Yi, Xinghui Wu

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In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. Moreover, the test equipment is necessary for the test. The functions and the key points of the equipment is presented to satisfy the requirements of the test，and the design scheme is proposed. The composition, the major function and the critical parts’ design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved.

Keywords: landing-impact test, lunar lander, releasing device, test equipment

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Authors: Princess Ncube

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In the context of South Africa's banking sector, the prevention of bank failures is of paramount importance to ensure financial stability and economic growth. This paper focuses on the role of regulatory frameworks in safeguarding the resilience of South African banks and mitigating the risks of failures. It aims to assess the effectiveness of existing regulatory measures and proposes strategies to enhance the resilience of financial institutions in the country. The paper begins by examining the specific regulatory frameworks in place in South Africa, including capital adequacy requirements, stress testing methodologies, risk management guidelines, and supervisory practices. It delves into the evolution of these measures in response to lessons learned from past financial crises and their relevance in the unique South African banking landscape. Drawing on empirical evidence and case studies specific to South Africa, this paper evaluates the effectiveness of regulatory frameworks in preventing bank failures within the country. It analyses the impact of these frameworks on crucial aspects such as early detection of distress signals, improvements in risk management practices, and advancements in corporate governance within South African financial institutions. Additionally, it explores the interplay between regulatory frameworks and the specific economic environment of South Africa, including the role of macroprudential policies in preventing systemic risks. Based on the assessment, this paper proposes recommendations to strengthen regulatory frameworks and enhance their effectiveness in bank failure prevention in South Africa. It explores avenues for refining existing regulations to align capital requirements with the risk profiles of South African banks, enhancing stress testing methodologies to capture specific vulnerabilities, and fostering better coordination among regulatory authorities within the country. Furthermore, it examines the potential benefits of adopting innovative approaches, such as leveraging technology and data analytics, to improve risk assessment and supervision in the South African banking sector.

Keywords: banks, resolution, liquidity, regulation

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Authors: Taghrid Asfar, Olusanya J. Oluwole, Michael Schmidt, Alejandra Casas, Zoran Bursac, Wasim Maziak.

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Waterpipe (WP) smoking (a.k.a. hookah) has increased dramatically in the US mainly due to the misperception that it is safer than cigarette smoking. Mounting evidence show that WP smoking is addictive and harmful. Health warning labels (HWLs) are effective in communicating smoking-related risks. Currently, the FDA requires that WP tobacco packages have a textual HWL about nicotine. While this represents a good step, it is inadequate given the established harm of WP smoking beyond addiction and the superior performance of pictorial HWLs over text-only ones. We developed 24 WP pictorial HWLs in a Delphi study among international expert panel. HWLs were grouped into 6 themes: addiction, harm compared to cigarettes, harm to others, health effects, quitting, and specific harms. This study aims to compare the effect of the pictorial HWLs compared to the FDA HWL, and 2) the effect of pictorial HWLs between the 6 themes. A 2x7 between/within subject online factorial experimental study was conducted among a national convenience sample of 300 (50% current WP smokers; 50% nonsmokers) US adults (females 71.1%; mean age of 31.1±3.41 years) in March 2022. The first factor varied WP smoking status (smokers, nonsmokers). The second factor varied the HWL theme and type (text, pictorial). Participants were randomized to view and rate 7 HWLs: 1 FDA text HWL (control) and 6 HWLs, one from each of the 6 themes, all presented in random order. HWLs were rated based on the message impact framework into five categories: attention, reaction (believability, relevance, fear), perceived effectiveness, intentions to quit WP among current smokers, and intention to not initiate WP among nonsmokers. measures were assessed on a 5-point Likert scale (1=not at all to 5=very much) for attention and reaction and on a 7-point Likert scale (1=not at all to 7=very much) for the perceived effectiveness and intentions to quit or not initiate WP smoking. Means and SDs of outcome measures for each HWL type and theme were calculated. Planned comparisons using Friedman test followed by pairwise Wilcoxon signed-rank test for multiple comparisons were used to examine distributional differences of outcomes between the HWL type and themes. Approximately 74.4 % of participants were non-Hispanic Whites, 68.4% had college degrees, and 41.5% were under the poverty level. Participants reported starting WTS on average at 20.3±8.19 years. Compared with the FDA text HWL, pictorial HWLs elicited higher attention (p<0.0001), fear (p<0.0001), harm perception (p<0.0003), perceived effectiveness (p<0.0001), and intentions to quit (p=0.0014) and not initiate WP smoking (p<0.0003). HWLs in theme 3 (harm to others) achieved the highest rating in attention (4.14±1), believability (4.15±0.95), overall perceived effectiveness (7.60±2.35), harm perception (7.53±2.43), and intentions to quit (7.35±2.57). HWLs in theme 2 (WP harm compared to cigarettes) achieved the highest rating in discouraging WP smoking initiation (7.32±2.54). Pictorial HWLs were superior to the FDA text-only for several communication outcomes. Pictorial HWLs related to WP harm to others and WP harm compared to cigarette are promising. These findings provide strong evidence for the potential implementation of WP-specific pictorial HWLs.

Keywords: health communication, waterpipe smoking, factorial experiment, reaction, harm perception, tobacco regulations

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Authors: V. Agostini, S. Gino, S. Inturri, A. Piccinini

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In cases of corpse identification or parental testing performed on exhumed alleged dead father, usually, we seek and acquire organic samples as bones and/or bone fragments, teeth, nails and muscle’s fragments. The DNA analysis of these cadaveric matrices usually leads to identifying success, but it often happens that the results of the typing are not satisfactory with highly degraded, partial or even non-interpretable genetic profiles. To aggravate the interpretative panorama deriving from the analysis of such 'classical' organic matrices, we must add a long and laborious treatment of the sample that starts from the mechanical fragmentation up to the protracted decalcification phase. These steps greatly increase the chance of sample contamination. In the present work, instead, we want to report the use of 'unusual' cadaveric matrices, demonstrating that their forensic genetics analysis can lead to better results in less time and with lower costs of reagents. We report six case reports, result of on-field experience, in which eyeswabs and cartilage were sampled and analyzed, allowing to obtain clear single genetic profiles, useful for identification purposes. In all cases we used the standard DNA tissue extraction protocols (as reported on the user manuals of the manufacturers such as QIAGEN or Invitrogen- Thermo Fisher Scientific), thus bypassing the long and difficult phases of mechanical fragmentation and decalcification of bones' samples. PCR was carried out using PowerPlex® Fusion System kit (Promega), and capillary electrophoresis was carried out on an ABI PRISM® 310 Genetic Analyzer (Applied Biosystems®), with GeneMapper ID v3.2.1 (Applied Biosystems®) software. The software Familias (version 3.1.3) was employed for kinship analysis. The genetic results achieved have proved to be much better than the analysis of bones or nails, both from the qualitative and quantitative point of view and from the point of view of costs and timing. This way, by using the standard procedure of DNA extraction from tissue, it is possible to obtain, in a shorter time and with maximum efficiency, an excellent genetic profile, which proves to be useful and can be easily decoded for later paternity tests and/or identification of human remains.

Keywords: DNA, eye swabs and cartilage, identification human remains, paternity testing

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Authors: Mico Kenshee C. Samarista, John Harvey V. Miranda, Janne Audrae Q. Lebosada, Josef Anton R. Benitez, Juan Miguel C. Rubio

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This research paper presents the development and evaluation of a web-based application designed to simplify the process of car rental services in the Philippines. As the demand for convenient and efficient access to rental car information grows, the need for a user-friendly platform becomes increasingly crucial. The web-based application serves as a comprehensive central hub, aggregating and organizing rental car listings from various reputable websites across the Philippines. By collecting essential data through surveys and usability testing, we assess the platform's effectiveness in simplifying the rental car selection process.

Keywords: web, application, car, services

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Authors: Sukanya Sripho

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The purpose of this research was to study the role of local administration management to promote culture based on philosophy of sufficiency economy to many communities in Thailand. The philosophy was given to the Thai people by their King and become one of the important policies from the Thai government. A total of 375 local people in main district, Amnadcharoen province were selected by random sampling. A questionnaire was used as the tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analysis. The findings revealed that the role of facilitator was utilized the most from the management in order to promote culture based on philosophy of sufficiency economy to many communities in Thailand.

Keywords: administration, management, philosophy of sufficiency economy, facilitator

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Authors: Tanveer Ahmed Choudhury

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Background: Bangladesh is one of the largest deltas in the world, with high population density and high rates of poverty and illiteracy. 80% of the country is on low-lying floodplains, leaving the country one of the most vulnerable to the adverse effects of climate change: sea level rise, cyclones and storms, salinity intrusion, rising temperatures and heavy monsoon downpours. Such climatic events already limit Economic Development in the country. Although Bangladesh has had little responsibility in contributing to global climatic change, it is vulnerable to both its direct and indirect impacts. Real threats include reduced agricultural production, worsening food security, increased incidence of flooding and drought, spreading disease and an increased risk of conflict over scarce land and water resources. Currently, 8.3 million Bangladeshis live in cyclone high risk areas. However, by 2050 this is expected to grow to 20.3 million people, if proper adaptive actions are not taken. Under a high emissions scenario, an additional 7.6 million people will be exposed to very high salinity by 2050 compared to current levels. It is also projected that, an average of 7.2 million people will be affected by flooding due to sea level rise every year between 2070-2100 and If global emissions decrease rapidly and adaptation interventions are taken, the population affected by flooding could be limited to only about 14,000 people. To combat the climate change adverse effects, Bangladesh government has initiated many adaptive measures specially in infrastructure and renewable energy sector. Government is investing huge money and initiated many projects which have been proved very success full. Objectives: The objective of this paper is to describe some successful measures initiated by Bangladesh government in its effort to make the country a Climate Resilient. Methodology: Review of operation plan and activities of different relevant Ministries of Bangladesh government. Result: The following initiative projects, programs and activities are considered as best practices for Climate Change adaptation successes for Bangladesh: 1. The Infrastructure Development Company Limited (IDCOL); 2. Climate Change and Health Promotion Unit (CCHPU); 3. The Climate Change Trust Fund (CCTF); 4. Community Climate Change Project (CCCP); 5. Health, Population, Nutrition Sector Development Program (HPNSDP, 2011-2016)- "Climate Change and Environmental Issues"; 6. Ministry of Health and Family Welfare, Bangladesh and WHO Collaboration; - National Adaptation Plan. -"Building adaptation to climate change in health in least developed countries through resilient WASH". 7. COP-21 “Climate and health country profile -2015 Bangladesh. Conclusion: Due to a vast coastline, low-lying land and abundance of rivers, Bangladesh is highly vulnerable to climate change. Having extensive experience with facing natural disasters, Bangladesh has developed a successful adaptation program, which led to a significant reduction in casualties from extreme weather events. In a low income country setting, Bangladesh had successfully adapted various projects and initiatives to combat future Climate Change challenges.

Keywords: climate, change, success, Bangladesh

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Liu Linxin

Abstract:

As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes an approach LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimisation, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential.

Keywords: log parsing, anomaly detection, retrieval-augmented generation, prompt engineering, LLMs

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Authors: Bonchan Koo, Junhee Han, Dohyung Lee

Abstract:

The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

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Authors: Rong-Tsorng Wang

Abstract:

In this paper, we derive a pricing formula for catastrophe equity put options (or CatEPut) with non-homogeneous loss and approximated compound distributions. We assume that the loss claims arrival process is a nonhomogeneous Poisson process (NHPP) representing the clustering occurrences of loss claims, the size of loss claims is a sequence of independent and identically distributed random variables, and the accumulated loss distribution forms a compound distribution and is approximated by a heavy-tailed distribution. A numerical example is given to calibrate parameters, and we discuss how the value of CatEPut is affected by the changes of parameters in the pricing model we provided.

Keywords: catastrophe equity put options, compound distributions, nonhomogeneous Poisson process, pricing model

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Authors: Aayushi Somani, Siba P. Samal

Abstract:

Three-dimensional (3D) meshes are data structures, which store geometric information of an object or scene, generally in the form of vertices and edges. Current technology in laser scanning and other geometric data acquisition technologies acquire high resolution sampling which leads to high resolution meshes. While high resolution meshes give better quality rendering and hence is used often, the processing, as well as storage of 3D meshes, is currently resource-intensive. At the same time, web applications for data processing have become ubiquitous owing to their accessibility. For 3D meshes, the advancement of 3D web technologies, such as WebGL, WebVR, has enabled high fidelity rendering of huge meshes. However, there exists a gap in ability to stream huge meshes to a native client and browser application due to high network latency. Also, there is an inherent delay of loading WebGL pages due to large and complex models. The focus of our work is to identify the challenges faced when such meshes are streamed into and processed on hand-held devices, owing to its limited resources. One of the solutions that are conventionally used in the graphics community to alleviate resource limitations is mesh compression. Our approach deals with a two-step approach for random accessible progressive compression and its parallel implementation. The first step includes partition of the original mesh to multiple sub-meshes, and then we invoke data parallelism on these sub-meshes for its compression. Subsequent threaded decompression logic is implemented inside the Web Browser Engine with modification of WebGL implementation in Chromium open source engine. This concept can be used to completely revolutionize the way e-commerce and Virtual Reality technology works for consumer electronic devices. These objects can be compressed in the server and can be transmitted over the network. The progressive decompression can be performed on the client device and rendered. Multiple views currently used in e-commerce sites for viewing the same product from different angles can be replaced by a single progressive model for better UX and smoother user experience. Can also be used in WebVR for commonly and most widely used activities like virtual reality shopping, watching movies and playing games. Our experiments and comparison with existing techniques show encouraging results in terms of latency (compressed size is ~10-15% of the original mesh), processing time (20-22% increase over serial implementation) and quality of user experience in web browser.

Keywords: 3D compression, 3D mesh, 3D web, chromium, client-server architecture, e-commerce, level of details, parallelization, progressive compression, WebGL, WebVR

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Authors: Sina Saadati

Abstract:

Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Boris Melnikov, Dmitrii Chaikovskii, Elena Melnikova

Abstract:

The traveling salesman problem (TSP) is a well-known optimization problem that seeks to find the shortest possible route that visits a set of points and returns to the starting point. In this paper, we apply some heuristics of the TSP for the task of restoring the DNA matrix. This restoration problem is often considered in biocybernetics. For it, we must recover the matrix of distances between DNA sequences if not all the elements of the matrix under consideration are known at the input. We consider the possibility of using this method in the testing of distance calculation algorithms between a pair of DNAs to restore the partially filled matrix.

Keywords: optimization problems, DNA matrix, partially filled matrix, traveling salesman problem, heuristic algorithms

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

Abstract:

This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

Procedia PDF Downloads 342