Search results for: ongoing training

Authors: Yahia A. M. AlKhoudary

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This Study presents the outcome of an investigation to evaluate the importance of autonomous learning as a means of motivation. However, very little research done in this field. Thus, the aims of this study are to ascertain the needs of the learners and to investigate their attitudes and motivation towards the mode of learning. Various suggestions made on how to improve learners’ participation in the learning process. A survey conducted on a sample group of 60 Omani College students. Self-report questionnaires and retrospective interviews conducted to find out their material-type preferences in a self-access learning context. Achieving autonomous learning system, which learners is one of the Ministry of Education goals in the Sultanate of Oman. As a result, this study presents the outcome of an investigation to evaluate the students’ performance in English as a Foreign Language (EFL). It focuses on the effect of autonomous learning that encourages students to learn English, a research conducted at Buraimi city, the Sultanate of Oman. The procedure of this investigation based on four dimensions: (1) sixty students are selected and divided into two groups, (2) pre and posttest projects are given to them, and (3) questionnaires are administered to both students who are involved in the experiment and 50 teachers (25 males and 25 females) to collect accurate data, (4) an interview with students and teachers to find out their attitude towards autonomous learning. Analysis of participants’ responses indicated that autonomous learning motivates students to learn English independently and increase the intrinsic rather than extrinsic motivation to improve their English language as a long-life active learning. The findings of this study show that autonomous learning approach is the best remedy to empower the students’ skills and overcome all relevant difficulties. They also show that secondary school teachers can fully rely on this learning approach that encourages language learners to monitor their progress, increase both learners and teachers’ motivation and ameliorate students’ behavior in the classroom. This approach is also an ongoing process, which takes time, patience and support to be lifelong learning.

Keywords: Omani, autonomous learning system, English as a Foreign Language (EFL), learning approach

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Authors: Liu Lin Xin

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With the increasing complexity of systems, log parsing and anomaly detection have become crucial for maintaining system stability. However, traditional methods often struggle with adaptability and accuracy, especially when dealing with rapidly evolving log content and unfamiliar domains. To address these challenges, this paper proposes approach that integrates Retrieval Augmented Generation (RAG) technology with Prompt Engineering for Large Language Models, applied specifically in LogPrompt. This approach enables dynamic log parsing and intelligent anomaly detection by combining real-time information retrieval with prompt optimization. The proposed method significantly enhances the adaptability of log analysis and improves the interpretability of results. Experimental results on several public datasets demonstrate the method's superior performance, particularly in scenarios lacking training data, where it significantly outperforms traditional methods. This paper introduces a novel technical pathway for log parsing and anomaly detection, showcasing the substantial theoretical value and practical potential.

Keywords: log parsing, anomaly detection, RAG, prompt engineering, LLMs

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Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

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Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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Authors: M. F. Abreu, A. I. Aguiar, R. Gaio, R. Duarte

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Background: Prison establishments constitute high-risk environments for the transmission and spread of tuberculosis (TB), given their epidemiological context and the difficulty of implementing preventive and control measures. Guidelines for control and prevention of tuberculosis in prisons have been described as incomplete and heterogeneous internationally, due to several identified obstacles, for example scarcity of human resources and funding of prisoner health services. In Portugal, a protocol was created in 2014 with the aim to define and standardize procedures of detection and prevention of tuberculosis within prisons. Objective: The main objective of this study was to identify and describe barriers to tuberculosis detection in prisons of Porto and Lisbon districts in Portugal. Methods: A cross-sectional study was conducted from 2ⁿᵈ January 2018 till 30ᵗʰ June 2018. Semi-structured questionnaires were applied to health care professionals working in the prisons of the districts of Porto (n=6) and Lisbon (n=8). As inclusion criteria we considered having work experience in the area of tuberculosis (either in diagnosis, treatment, or follow up). The questionnaires were self-administered, in paper format. Descriptive analyses of the questionnaire variables were made using frequencies and median. Afterwards, a hierarchical agglomerative clusters analysis was performed. After obtaining the clusters, the chi-square test was applied to study the association between the variables collected and the clusters. The level of significance considered was 0.05. Results: From the total of 186 health professionals, 139 met the criteria of inclusion and 82 health professionals were interviewed (62,2% of participation). Most were female, nurses, with a median age of 34 years, with term employment contract. From the cluster analysis, two groups were identified with different characteristics and behaviors for the procedures of this protocol. Statistically significant results were found in: elements of cluster 1 (78% of the total participants) work in prisons for a longer time (p=0.003), 45,3% work > 4 years while 50% of the elements of cluster 2 work for less than a year, and more frequently answered they know and apply the procedures of the protocol (p=0.000). Both clusters answered frequently the need of having theoretical-practical training for TB (p=0.000), especially in the areas of diagnosis, treatment and prevention and that there is scarcity of funding to prisoner health services (p=0.000). Regarding procedures for TB screening (periodic and contact screening) and procedures for transferring a prisoner with this disease, cluster 1 also answered more frequently to perform them (p=0.000). They also referred that the material/equipment for TB screening is accessible and available (p=0.000). From this clusters we identified as barriers scarcity of human resources, the need to theoretical-practical training for tuberculosis, inexperience in working in health services prisons and limited knowledge of protocol procedures. Conclusions: The barriers found in this study are the same described internationally. This protocol is mostly being applied in portuguese prisons. The study also showed the need to invest in human and material resources. This investigation bridged gaps in knowledge that could help prison health services optimize the care provided for early detection and adherence of prisoners to treatment of tuberculosis.

Keywords: barriers, health care professionals, prisons, protocol, tuberculosis

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Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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Authors: Sehrish Qayyum

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Active military power contention is shifting to economic and cyberwar to retain hegemony. Attuned Pestle analysis confirms that structural stress of hegemon’s power loss drives a containment approach towards caging actions. Ongoing diplomatic, asymmetric, proxy and direct wars are increasing stress hegemon’s power retention due to tangled military and economic alliances. It creates the condition of catalepsy with defective reflexive control which affects the core warfare operations. When one’s own power is doubted it gives power to one’s own doubt to ruin all planning either done with superlative cost-benefit analysis. Strategically calculated estimation of Hegemon’s power game since the early WWI to WWII, WWII-to Cold War and then to the current era in three chronological periods exposits that Thucydides’s trap became the reason for war broke out. Thirst for power is the demise of imagination and cooperation for better sense to prevail instead it drives ashes to dust. Pestle analysis is a wide array of evaluation from political and economic to legal dimensions of the state matters. It helps to develop the Pacification and Security Policy Plan (PSPP) to avoid hegemon’s structural stress of power loss in fact, in turn, creates an alliance with maximum amicable outputs. PSPP may serve to regulate and pause the hurricane of power clashes. PSPP along with a strategic work plan is based on Pestle analysis to deal with any conceivable war condition and approach for saving international peace. Getting tangled into self-imposed epistemic dilemmas results in regret that becomes the only option of performance. It is a generic application of probability tests to find the best possible options and conditions to develop PSPP for any adversity possible so far. Innovation in expertise begets innovation in planning and action-plan to serve as a rheostat approach to deal with any plausible power clash.

Keywords: alliance, hegemon, pestle analysis, pacification and security policy plan, security

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Authors: Akalework Mengesha

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The adoption of improved agricultural technologies has been connected with higher earnings and lower poverty, enhanced nutritional status, lower staple food prices, and increased employment opportunities for landless laborers. The adoption and extension of the technologies are vastly crucial in that it enables the countries to achieve the millennium development goals (MDG) of reducing extreme poverty and hunger. There are efforts which directed to the enlargement and provision of modern crop varieties in sub-Saharan Africa in the past 30 years. Nevertheless, by and large, the adoption and expansion of rates for improved technologies have insulated behind other regions. This research aims to assess social and economic barriers in the adoption and expansion of agricultural technologies by local communities living around a private agricultural farm in Woliatta Zone, Southern Ethiopia. The study has been carried out among rural households which are located in the three localities selected for the study in the Woliatta zone. Across sectional mixed method, the design was used to address the study objective. The qualitative method was employed (in-depth interview, key informant, and focus group discussion) involving a total of 42 in-depth informants, 17 key-informant interviews, 2 focus group discussions comprising of 10 individuals in each group through purposive sampling techniques. The survey method was mainly used in the study to examine the impact of attitudinal, demographic, and socioeconomic variables on farmers’ adoption of agricultural technologies for quantitative data. The finding of the study revealed that Amibara commercial farm has not made a resolute and well-organized effort to extend agricultural technology to the surrounding local community. A comprehensive agricultural technology transfer scheme hasn’t been put in place by the commercial farm ever since it commenced operating in the study area. Besides, there is an ongoing conflict of interest between the farm and the community, which has kept on widening through time, bounds to be irreversible.

Keywords: adoption, technology transfer, agriculture, barriers

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Authors: Wesley Too, Christine Chesiror

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Hypertension is a public health challenge that globally, with the World Health Organization estimating that by 2025, more than 1.5 billion people would have been diagnosed with it. Kenya’s prevalence of hypertension is estimated at 24.6 percent; however, 55% of the affected have uncontrolled blood pressure, which is worst in some parts of the country with different lifestyle: nomads and migratory communities. Kenyan pastoralists comprise 20% of the nation's population and are constantly on the move for search of water, pasture for their herd, and desertification have driven nomadic populations to the brink, given their unique and dynamic challenges. Nomads face myriad of challenges and barriers towards the management of their health care problems. Nomadic area is predominantly rural, with a low population density and a nomadic population. Health care access and quality are further hampered by poor telecommunications, infrastructure, and security. In Kenya, nomadic communities experience the worst health outcomes, disproportionate health disparities, and inequalities due to unresponsive, culturally sensitive health care system to nomad’s lifestyle and their health care needs. Marsabit covering a surface area of 66,923.1 km2, is the second largest county in Kenya, constituting about 2.3 million people of North-Eastern region, with only 2.3 percent and 1.9 percent of Kenya's total number of doctors and nurses in the country. In Kenya, there are scanty research on hypertension managementin this region and, at best, non-existent study on hypertension among nomads-migratory communities of Northern Kenya. Therefore, the purpose seeks to determine the prevalence of hypertension among nomads and document nomads' practices regarding early detections, management, and levels of control of hypertension in one of the Counties in Kenya with high- hypertensive case load per year. Methods: A cross-sectional study design was used to collect data from multiple sites and health facilities. A total of 260 participants were enrolled into the study. The study is currently ongoing. It is anticipated that by September, we will have initial findings & recommendations to share for conference

Keywords: pastoralists, hypertension, health, kenya

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

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

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

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Authors: Yollande Sènan Djivoh, Dominique de Jaeger

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Background: Abdominal exercises are commonly practised nowadays. Specific techniques of abdominal muscles strengthening like hypopressive exercises have recently emerged and their practice is encouraged against the practice of Curl-up especially in postpartum. The acute and the training effects of these exercises did not allow to advise one exercise to the detriment of another. However, physiotherapists remain reluctant to perform Curl-up with postpartum women because of its potential harmful effect on the pelvic floor. Design: This study was a randomized control trial registered under the number PACTR202110679363984. Objective: to observe the training effect of two experimental protocols (Curl-up versus Drawing-in+Diaphragmatic aspiration) on the abdominal wall (interrecti distance, rectus and transversus abdominis thickness, abdominal strength) in Beninese postpartum women. Pelvic floor function (tone, endurance, urinary incontinence) will be assessed to evaluate potential side effects of exercises on the pelvic floor. Method: Postpartum women diagnosed with diastasis recti were randomly assigned to one of three groups (Curl-up, Drawingin+Diaphragmatic aspiration and control). Abdominal and pelvic floor parameters were assessed before and at the end of the 6-week protocol. The interrecti distance and the abdominal muscles thickness were assessed by ultrasound and abdominal strength by dynamometer. Pelvic floor tone and strength were assessed with Biofeedback and urinary incontinence was quantified by pad test. To compare the results between the three groups and the two measurements, a two-way Anova test with repeated measures was used (p<0.05). When interaction was significant, a posthoc using Student t test, with Bonferroni correction, was used to compare the three groups regarding the difference (end value minus initial value). To complete these results, a paired Student t test was used to compare in each group the initial and end values. Results: Fifty-eight women participated in this study, divided in three groups with similar characteristics regarding their age (29±5 years), parity (2±1 children), BMI (26±4 kg/m2 ), time since the last birth (10±2 weeks), weight of their baby at birth (330±50 grams). Time effect and interaction were significant (p<0.001) for all abdominal parameters. Experimental groups improved more than control group. Curl-up group improved more (p=0.001) than Drawing-in+Diaphragmatic aspiration group regarding the interrecti distance (9.3±4.2 mm versus 6.6±4.6 mm) and abdominal strength (20.4±16.4 Newton versus 11.4±12.8 Newton). Drawingin+Diaphragmatic aspiration group improved (0.8±0.7 mm) more than Curl-up group (0.5±0.7 mm) regarding the transversus abdominis thickness (p=0.001). Only Curl-up group improved (p<0.001) the rectus abdominis thickness (1.5±1.2 mm). For pelvic floor parameters, both experimental groups improved (p=0.01) except for tone which improved (p=0.03) only in Drawing-in+Diaphragmatic aspiration group from 19.9±4.1 cmH2O to 22.2±4.5 cmH2O. Conclusion: Curl-up was more efficient to improve abdominal function than Drawingin+Diaphragmatic aspiration. However, these exercises are complementary. None of them degraded the pelvic floor, but Drawing-in+Diaphragmatic aspiration improved further the pelvic floor function. Clinical implications: Curl-up, Drawing-in and Diaphragmatic aspiration can be used for the management of abdominal function in postpartum women. Exercises must be chosen considering the specific needs of each woman’s abdominal and pelvic floor function.

Keywords: curl-up, drawing-in, diaphragmatic aspiration, hypopressive exercise, postpartum women

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Authors: Julie Furst-Bowe

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Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

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Authors: Pauline Calleja, Brooke Alexander

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In 2010 the College of Emergency Nursing Australasia (CENA) undertook sole administration of the Trauma Nursing Program (TNP) across Australia. The original TNP was developed from recommendations by the Review of Trauma and Emergency Services-Victoria. While participant and faculty feedback about the program was positive, issues were identified that were common for industry training programs in Australia. These issues included didactic approaches, with many lectures and little interaction/activity for participants. Participants were not necessarily encouraged to undertake deep learning due to the teaching and learning principles underpinning the course, and thus participants described having to learn by rote, and only gain a surface understanding of principles that were not always applied to their working context. In Australia, a trauma or emergency nurse may work in variable contexts that impact on practice, especially where resources influence scope and capacity of hospitals to provide trauma care. In 2011, a program review was undertaken resulting in major changes to the curriculum, teaching, learning and assessment approaches. The aim was to improve learning including a greater emphasis on pre-program preparation for participants, the learning environment and clinically applicable contextualized outcomes participants experienced. Previously if participants wished to undertake assessment, they were given a take home examination. The assessment had poor uptake and return, and provided no rigor since assessment was not invigilated. A new assessment structure was enacted with an invigilated examination during course hours. These changes were implemented in early 2012 with great improvement in both faculty and participant satisfaction. This presentation reports on a comparison of participant evaluations collected from courses post implementation in 2012 and in 2015 to evaluate if positive changes were sustained. Methods: Descriptive statistics were applied in analyzing evaluations. Since all questions had more than 20% of cells with a count of <5, Fisher’s Exact Test was used to identify significance (p = <0.05) between groups. Results: A total of fourteen group evaluations were included in this analysis, seven CENA TNP groups from 2012 and seven from 2015 (randomly chosen). A total of 173 participant evaluations were collated (n = 81 from 2012 and 92 from 2015). All course evaluations were anonymous, and nine of the original 14 questions were applicable for this evaluation. All questions were rated by participants on a five-point Likert scale. While all items showed improvement from 2012 to 2015, significant improvement was noted in two items. These were in regard to the content being delivered in a way that met participant learning needs and satisfaction with the length and pace of the program. Evaluation of written comments supports these results. Discussion: The aim of redeveloping the CENA TNP was to improve learning and satisfaction for participants. These results demonstrate that initial improvements in 2012 were able to be maintained and in two essential areas significantly improved. Changes that increased participant engagement, support and contextualization of course materials were essential for CENA TNP evolution.

Keywords: emergency nursing education, industry training programs, teaching and learning, trauma education

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Authors: Vishal Jaunky, Jonas Grafström

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The development of the European Union’s (EU) single economic market and rapid technological change has resulted in major structural changes in EU’s member states economies. The general liberalization process that the countries has undergone together has convinced the governments of the member states of need to upgrade their economic and training systems in order to be able to face the economic globalization. Several signs of economic convergence have been found but less is known about the knowledge production. This paper addresses the convergence pattern of technological innovation in 13 European Union (EU) states over the time period 1990-2011 by means of parametric and non-parametric techniques. Parametric approaches revolve around the neoclassical convergence theories. This paper reveals divergence of both the β and σ types. Further, we found evidence of stochastic divergence and non-parametric convergence approach such as distribution dynamics shows a tendency towards divergence. This result is supported with the occurrence of γ-divergence. The policies of the EU to reduce technological gap among its member states seem to be missing its target, something that can have negative long run consequences for the market.

Keywords: convergence, patents, panel data, European union

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Authors: Amina Beldjazia, Djamel Alatou, Khaled Missaoui

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The forest of Mahouna is a part of the mountain range of the Tell Atlas in the northeast of Algeria. It is characterized by a significant biodiversity. The management of this resource requires thorough the understanding of the current state of the vegetation (inventories), degradation factors and ongoing monitoring of the various long-term ecological changes. Digital mapping is a very effective way to in-depth knowledge of natural resources. The realization of a vegetation map based on satellite images, aerial photographs and the use of geographic information system (GIS), shows large values results of the vegetation of the massif in the scientific view point (the development of a database of the different formations that exist on the site, ecological conditions) and economic (GIS facilitate our task of managing the various resources and diversity of the forest). The methodology is divided into three stages: the first involves an analysis of climate data (1988 to 2013); the second is to conduct field surveys (soil and phytoecological) during the months of June and July 2013 (10 readings), the third is based on the development of different themes and synthetic cards by software of GIS (ENVI 4.6 and 10 ARCMAP). The results show: cork oak covers an area of 1147 ha. Depending on the environmental conditions, it rests on sandstone and individualizes between 3 layers of vegetation from thermo-mediterranean (the North East part with 40ha), meso-Mediterranean (1061 ha) and finally the supra-Mediterranean (46ha ). The map shows the current actual state of the cork oak forest massif of Mahouna, it is an older forest (>150 years) where regeneration is absent because of several factors (fires, overgrazing, leaching, erosion, etc.). The cork oak is in the form of dense forest with Laburnum and heather as the dominant species. It may also present in open forest dominated by scrub species: Daphne gniduim, Erica arborea, Calycotome spinosa, Phillyrea angustifolia, Lavandula stoechas, Cistus salvifolius.

Keywords: biodiversity, environmental, Mahouna, Cork oak

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Mohamed R. Mhereeg

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The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spread-sheet developers competency over a network. It is designed to automatically and autonomously monitor spread-sheet users and gather their development activities based on the utilization of the software Multi-Agent Technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spread-sheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: classification, design, MACS, MAS, prometheus

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Authors: Yuda Purwana Roswanjaya, Wouter Kohlen, Rene Geurts

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The Trema genus represents a group of fast-growing tropical tree species within the Cannabaceae. Interestingly, five species nested in this lineage -known as Parasponia- can establish rhizobium nitrogen-fixing root nodules, similar to those found in legumes. Parasponia and legumes use a conserved genetic network to control root nodule formation, among which are genes also essential for mycorrhizal symbiosis (the so-called common symbiotic pathway). However, Trema species lost several genes that function exclusively in nodulation, suggesting a loss-of the nodulation trait in Trema. Strikingly, in a Trema orientalis population found in Malaysian Borneo we identified a truncated SYMBIOSIS RECEPTOR KINASE (SYMRK) mutant allele lacking a large portion of the c-terminal kinase domain. In legumes this gene is essential for nodulation and mycorrhization. This raises the question whether Trema orientalis can still be mycorrhized. To answer this question, we established quantitative mycorrhization assay for Parasponia andersonii and Trema orientalis. Plants were grown in closed pots on half strength Hoagland medium containing 20 µM potassium phosphate in sterilized sand and inoculated with 125 spores of Rhizopagus irregularis (Agronutrion-DAOM197198). Mycorrhization efficiency was determined by analyzing the frequency of mycorrhiza (%F), the intensity of the mycorrhizal colonization (%M) and the arbuscule abundance (%A) in the root system. Trema orientalis RG33 can be mycorrhized, though with lower efficiency compared to Parasponia andersonii. From this we conclude that a functional SYMRK kinase domain is not essential for Trema orientalis mycorrhization. In ongoing experiments, we aim to investigate the role of SYMRK in Parasponia andersonii mycorrhization and nodulation. For this two Parasponia andersonii symrk CRISPR-Cas9 mutant alleles were created. One mimicking the TorSYMRKRG33 allele by deletion of exon 13-15, and a full Parasponia andersonii SYMRK knockout.

Keywords: endomycorrhization, Parasponia andersonii, symbiosis receptor kinase (SYMRK), Trema orientalis

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R

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The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.

Keywords: cooperative-collaborative learning, educational management, formative-summative assessment, leadership training

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Authors: A. R. Nor Azlina, H. Salwana, I. Zuraeda, A. R. Rashidah, O. Normah

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Transitioning towards globalization in the business environment has necessitated more essential growing changes such as competition, business strategy, innovation in technology and effectiveness of societal trends on adopting corporate governance are seen to be drivers of the future. This transformations on business environment has a significant impact to organizations’ performances. Many organizations are demanding for more proactive entrepreneurs with dynamic team, who can run and steer their business to success. Changing on strategy, roles, tasks, entrepreneurial skills and implementing corporate governance in relationship development is important to enhance the organization’s performance towards being more cost-efficient and subsequently increase its efficiency. Small Medium Enterprises (SMEs) in most developing countries are contributors to the economic growth of a nation. However, the potential of Microfinance Institutions (MFIs) is always overlooked in contributing towards SMEs development. The adoption of corporate governance and accountability in MFIs as driving forces for these SMEs is not incorporated in measurements of organization performance. This paper attempts to address some of the governance issues associated with dimensions of accountability in improving performances of microfinance institutions. Qualitative approach was adopted in this study to analyze the data collected. The qualitative approach emerges as contributing factor in understanding and critiquing accountability processes, as well as addressing the concerns of practitioners and policymakers. A close researcher engagement with the field which concerns process, embracing of situational complexity, as well as critical and reflective understandings of organizational phenomena remain as hallmarks of the tradition. It is concluded that in describing and scrutinizing an understanding of managerial behavior, organizational factors and macro-economic relationship in SMEs firm need to be improved. This is also the case in MFIs. A framework is developed to explore the linkage of corporate governance and accountability issues related to entrepreneurship as factors affecting MFIs performances in facing ongoing transformation of organization performance within Malaysian SMEs industries.

Keywords: accountability, corporate governance, microfinance, organization performance

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Authors: Sudkhanoung Ritruechai, Somrak Choovanichwong, Kruawon Tiengtom, Peanchanan Leeudomwong

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The purposes of this qualitative research were to study the recovery experience of people with bipolar disorder and also to propose a development approach to the Bipolar Friends Club. The participants were eight people with bipolar disorder for six to twenty years (four women and four men). They have been members of the Bipolar Friends Club for two to ten years. They have no mental symptoms in order to provide sufficient information about their recovery experiences and have returned to everyday life with their family, community, and work. The data were collected by doing an in-depth interview. Two interviews were done, each from 45-90 minutes and four to five weeks apart. The researcher sent the results of the preliminary data analysis to the participants two to three days beforehand. Confirmation of the results of the preliminary data analysis from the first interview was done at the second interview. The research study found that the participants had a positive experience of being a Bipolar Club member. The club continued its activities following Recovery Oriented Service: ROS to the participants. As a result, they recovered in eight areas as follows. 1) Intellectual: The wisdom of joining the group has brought knowledge and experiences from an exchange with others in self-care as well as a positive thinking in life. 2) Social: The participants have set up a group to take care of each other and to do activities which have brought warmth. Their social network which was normally little has also been increased. 3) Spiritual: The concept of religion has been used to lead the life of the participants. 4) Occupational: One participant is a student while the others do work. All of them have done well. 5) Environmental: The participants would be able to adapt to the environment and cope with their problems better. 6) Physical: Most female participants have difficulties with losing weight which leads them saying that they are ‘not fully recovered’. 7) Emotional: The participants feel calmer than before entering the club. They have also developed more tolerance to problems. 8) Financial: The participants would be able to control their spending by themselves and with the help of their family members. The people with bipolar disorder have suggested that the services of the club are perfect and should be continued. The results of the study encourage the Bipolar Friends Club, as well as other clubs/associations that support the recovery of patients. Consideration of the recovery has highlighted the need for ongoing and various life-enhancing programs for the caregivers and their loved ones with bipolar disorder. Then, they would be able to choose the program that suits their needs to improve their life.

Keywords: people with bipolar disorder, recovery, club, experience

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Authors: Constantinos Adamides, Petros Petrikkos

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In the era of growing hybrid threats, small states find themselves in need to re-evaluate existing foreign and defense policies. The pressure to establishing or maintain a status of a reliable partner in the community in which they belong to, vis-à-vis their multilateral relations with other organisations and entities, small states may need to shift their policies in the field to accommodate security needs that are not only pertinent to their security, but also to that of the organisations (bloc) in which they interact. Unlike potential shortcomings in a small state’s mainstream security and defence framework where the threat would be limited to the state itself, in more contemporary times with dominating hybrid threats, the small states’ security shortcomings may also become a security problem for the bloc in which these states belong to. An indicative example is small states like Cyprus and Malta, which belong and 'interact' in the European Union. As a result, the nature of hybrid threats can be utilised to hurt bigger states in a bloc by exploiting the small states’ vulnerabilities and security gaps. Inevitably, both the defensive and foreign policy collaborations of small states with bigger states have been and are constantly re-evaluated to tackle and prevent such problems. In essence, the goal of this ‘re-evaluation’ aims to achieve a twofold goal: The first is the small states’ quest to appear as a reliable partner within the bloc, while the second is to avoid being the weakest security link in the bloc’s defence against hybrid threats. Indeed, the hybrid arena is a security area where they can excel in the bloc, despite the potential and expected conventional military deficiencies. This new environment prompts us to think security from the perspective of small states differently and in relation to their role as members or big organisations. The paper focuses on the case of Cyprus following its accession to the European Union and examines how a country that has had a very focused security orientation –not least due to its ongoing security problems– altered its foreign and defence policies within the European Union to ensure compliance with the rest of the bloc, while at the same time maximizing its role as a security player. Specifically, it examines the methods through which the country shifted its policies as well as the challenges and opportunities that emerged from these security shifts.

Keywords: Cyprus, defence, foreign policy, hybrid threats, ontological security, small states

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Authors: Mohammad Mokhtari, Mehdi Masoodi, Parvaneh Faridi

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history of tsunami generating earthquakes along the Makran Subduction Zone provides evidence of the potential tsunami hazard for the whole coastal area. In comparison with other subduction zone in the world, the Makran region of southern Pakistan and southeastern Iran remains low seismicity. Also, it is one of the least studied area in the northwest of the Indian Ocean regarding tsunami studies. We present a review of studies dealing with the historical /and ongoing palaeotsunamis supported by IGCP of UNESCO in the Makran Subduction Zone. The historical tsunami presented here includes about nine tsunamis in the Makran Subduction Zone, of which over 7 tsunamis occur in the eastern Makran. Tsunami is not as common in the western Makran as in the eastern Makran, where a database of historical events exists. The historically well-documented event is related to the 1945 earthquake with a magnitude of 8.1moment magnitude and tsunami in the western and eastern Makran. There are no details as to whether a tsunami was generated by a seismic event before 1945 off western Makran. But several potentially large tsunamigenic events in the MSZ before 1945 occurred in 325 B.C., 1008, 1483, 1524, 1765, 1851, 1864, and 1897. Here we will present new findings from a historical point of view, immediately, we would like to emphasize that the area needs to be considered with higher research investigation. As mentioned above, a palaeotsunami (geological evidence) is now being planned, and here we will present the first phase result. From a risk point of view, the study shows as preliminary achievement within 20 minutes the wave reaches to Iranian as well Pakistan and Oman coastal zone with very much destructive tsunami waves capable of inundating destructive effect. It is important to note that all the coastal areas of all states surrounding the MSZ are being developed very rapidly, so any event would have a devastating effect on this region. Although several papers published about modelling, seismology, tsunami deposits in the last decades; as Makran is a forgotten subduction zone, more data such as the main crustal structure, fault location, and its related parameter are required.

Keywords: historical tsunami, Indian ocean, makran subduction zone, palaeotsunami

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Authors: Gabriel P. Fife, Saeyong Lee, David M. O'Sullivan

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Introduction: Although investigations into injury characteristics are represented well in the literature, few have investigated the biomechanical characteristics associated with head impacts in Taekwondo. Therefore, the purpose of this study was to identify the kinematic characteristics of head impacts due to taekwondo kicks among non-elite practitioners. Participants: Male participants (n= 11, 175 + 5.3 cm, 71 + 8.3 kg) with 7.5 + 3.6 years of taekwondo training volunteered for this study. Methods: Participants were asked to perform five repetitions of each technique (i.e., turning kick, spinning hook kick, spinning back kick, front axe kick, and clench axe kick) aimed at the Hybrid III head with their dominant kicking leg. All participants wore a protective foot pad (thickness = 12 mm) that is commonly used in competition and training. To simulate head impact in taekwondo, the target consisted of a Hybrid III 50th Percentile Crash Test Dummy (Hybrid III) head (mass = 5.1 kg) and neck (fitted with taekwondo headgear) secured to an aluminum support frame and positioned to each athlete’s standing height. The Hybrid III head form was instrumented with a 500 g tri-axial accelerometer (PCB Piezotronics) mounted to the head center of gravity to obtain resultant linear accelerations (RLA). Rotational accelerations were collected using three angular rate sensors mounted orthogonally to each other (Diversified Technical Systems ARS-12 K Angular Rate Sensor). The accelerometers were interfaced via a 3-channel, battery-powered integrated circuit piezoelectric sensor signal conditioner (PCB Piezotronics) and connected to a desktop computer for analysis. Acceleration data were captured using LABVIEW Signal Express and processed in accordance with SAE J211-1 channel frequency class 1000. Head injury criteria values (HIC) were calculated using the VSRSoftware. A one-way analysis of variance was used to determine differences between kicks, while the Tukey HSD test was employed for pairwise comparisons. The level of significance was set to an effect size of 0.20. All statistical analyses were done using R 3.1.0. Results: A statistically significant difference was observed in RLA (p = 0.00075); however, these differences were not clinically meaningful (η² = 0.04, 95% CI: -0.94 to 1.03). No differences were identified with ROTA (p = 0.734, η² = 0.0004, 95% CI: -0.98 to 0.98). A statistically significant difference (p < 0.001) between kicks in HIC was observed, with a medium effect (η2= 0.08, 95% CI: -0.98 to 1.07). However, the confidence interval of this difference indicates uncertainty. Tukey HSD test identified differences (p < 0.001) between kicking techniques in RLA and HIC. Conclusion: This study observed head impact levels that were comparable to previous studies of similar objectives and methodology. These data are important as impact measures from this study may be more representative of impact levels experienced by non-elite competitors. Although the clench axe kick elicited a lower RLA, the ROTA of this technique was higher than levels from other techniques (although not large differences in reference to effect sizes). As the axe kick has been reported to cause severe head injury, future studies may consider further study of this kick important.

Keywords: Taekwondo, head injury, biomechanics, kicking

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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Authors: Fawehinmi Olabisi Alaba, O. R. Adeniyi

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Farming households faces lots of disaster which contribute to endemic poverty. Anticipated increases in extreme weather events will exacerbate this. Primary data was administered to farming household using multi-stage random sampling technique. The result of the analysis shows that majority of the respondents (69.9%) are male, have mean household size, years of formal education and age of 5±1.14, 6±3.41, and 51.06±10.43 respectively. The major (48.9%) type of disaster experienced is flooding. Major coping mechanism adopted is sourcing for support from family and friends. Age, education, experience, access to extension agent, and mitigation control method contribute significantly to vulnerability to disaster. The major adaptation method (62.3%) is construction of drainage. The study revealed that the coping mechanisms employed may become less effective as increasingly fragile livelihood systems struggle to withstand disaster shocks. Thus there is need for training of the farmers on measures to adapt to mitigate the shock from disasters.

Keywords: adaptation, disasters, flooding, vulnerability

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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