Search results for: scenario training

Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: Arsalan Ghaderi

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Introduction: Inactivity is one of the most important risk factors for cardiovascular disease. According to the study prevalence of inactivity in Iran, about 67.5% and in the staff, and especially nurses, are similar. The inflammatory index (HS-CRP) is highly predictive of the progression of these diseases. Physical activity education is very important in preventing these diseases. One of the modern educational methods is web-based theory-based education. Methods: This is a semi-experimental interventional study which was conducted in Isfahan and Kurdistan universities of medical sciences in two stages. A cross-sectional study was done to determine the status of physical activity and its predictive factors. Then, intervention was performed, and six months later the data were retrieved. The data was collected using a demographic questionnaire, an integrative model of behavior prediction constructs, a standard physical activity questionnaire and (HS-CRP) test. Data were analyzed by SPSS software. Results: Physical activity was low in 66.6% of nurses, 25.4% were moderate and 8% severe. According to Pearson correlation matrix, the highest correlation was found between behavioral intention and skill structures (0.553**), subjective norms (0.222**) and self-efficacy (0.198**). The relationship between age and physical activity in the first study was reverse and significant. After intervention, there was a significant change in attitudes, self-efficacy, skill and behavioral intention in the intervention group. This change was significant in attitudes, self-efficacy and environmental conditions of the control group. HS-CRP index decreased significantly after intervention in both groups, but there was not a significant relationship between inflammatory index and physical activity score. The change in physical activity level was significant only in the control group. Conclusion: Despite the effect of educational intervention on attitude, self-efficacy, skill, and behavioral intention, the results showed that if factors such as environmental factors are not corrected, training and changing structures cannot lead to physical activity behavior. On the other hand, no correlation between physical activity and HS-CRP showed that this index can be influenced by other factors, and this should be considered in any intervention to reduce the HS-CRP index.

Keywords: HS-CRP, integrative model of behavior prediction, physical activity, nurses, web-based education

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Authors: Moldir Makenova

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Alongside the implementation of trilingual education in schools, the Ministry of Education and Science of the Republic of Kazakhstan innovated the school curriculum in 2013 to include a Content and Language Integrated Learning (CLIL) approach. In this regard, some transition issues have arisen, such as unprepared teachers, a need for more awareness of the CLIL approach, and teaching resources. Some teachers view it as a challenge due to its combination of both content and language. This often creates anxiety among teachers who are knowledgeable about their subject areas in Kazakh or Russian but are deficient in delivering the subject’s content in English. Thus, with this new teaching approach, teachers encounter to choose the role of language and answer how language works in the CLIL classroom. This study aimed to explore how teachers experience the changing role of language in the curriculum and to find out what challenges teachers face related to CLIL implementation and how their language proficiency influences their teaching practices. A qualitative comparative case study was conducted in an X Lyceum and a mainstream school piloting CLIL. Data collection procedures were conducted via semi-structured interviews, classroom observations, and document analysis. Eight content teachers were chosen from these two schools as the target group of this study. Subject teachers, rather than language teachers, were chosen as the target group to grasp how the language-related issues in the new curriculum are interpreted by educators who do not necessarily identify themselves as language experts at the outset. The findings showed that mainstream teachers prioritize content over language because, as content teachers, the knowledge of content is more essential for them rather than the language. In contrast, most X Lyceum teachers balance language and content and additionally showed their preferences to support the ‘English language only' policy among 10-11 graders. Moreover, due to the low-level English proficiency, mainstream teachers did highlight the necessity of CLIL training and further collaboration with language teachers. This study will be beneficial for teachers and policy-makers to enable them to solve the issues mentioned above related to the implementation of CLIL. Larger-scale research conducted in the future would further inform its successful deployment country-wide.

Keywords: role of language, trilingual education, updated curriculum, teacher practices

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: Stephen Anim, Emmanuel O. Sarpong, Daniel Apaak

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This study investigates the relationship between morphological predictors and running ability, emphasizing gender-specific variations among male and female athletes in Cape Coast Metropolis (CCM), Ghana. The dynamic interplay between an athlete's physique and their performance capabilities holds particular relevance in the realm of sports science, influencing training methodologies and talent identification processes. The research aims to contribute comprehensive insights into the morphological determinants of running proficiency, with a specific focus on the local athletic community in Cape Coast Metropolis. Utilizing a correlational research design, a thorough analysis of morphological features, encompassing 22 morphological features including body weight, 6 measurements related to body length, 7 body girth, and knee diameter, and 7 skinfold measurements against 50m dash, among male and female athletes, was conducted. The study involved 420 athletes both male (N=210) and female (N=210) aged 16-22 from 10 Senior High Schools (SHS) in the Cape Coast Metropolis, providing a representative sample of the local athletic community. The collected data were statistically analysed using means and standard deviation, and stepwise multiple regression to determine how morphological variables contribute to and predict running proficiency outcomes. The investigation revealed that athletes from Senior High Schools (SHS) in Cape Coast Metropolis (CCM) exhibit well-developed physiques and sufficient fitness levels suitable for overall athletic performance, taking into account gender differences. Moreover, the findings suggested that approximately 77% of running ability could be attributed to morphological factors, leading to diverse predictive models for male and female athletes within SHS in CCM, Ghana. Consequently, these formulated equations hold promise for predicting running ability among young athletes, particularly in the context of SHS environments.

Keywords: body fat, body girth, body length, morphological features, running ability, senior high school

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Authors: Gülcan Taşkıran, Ülkü Tatar Baykal

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Aim: To identify nurses’ perceived competencies for disaster preparedness. Background: Recently, the number of disasters has increased worldwide. Since disasters often strike without warning, healthcare providers, especially nurses must be prepared with appropriate competencies for disaster procedures. Nurses’ perceptions of their own competencies for disaster preparedness need to be evaluated to aid in the creation of effective national plans and educational programs. Design: This study was conducted with a descriptive and cross-sectional design. Methods: Nurses’ perceptions were assessed using the 13-item Demographic Profile Questionnaire that is based on previous literature and the 45-item Nurses’ Perception of Core Competencies for Disaster Preparedness Scale (NPCDPS). Data were collected from June to September 2014 from 406 (79.9% return rate) Turkish nurses working in the western region of Turkey. Results: At the end of the study, it was found that out of the nurses whose mean age was 31.27 ± 5.86 and mean of working time was 8.07 ± 6.60 by the time vast majority of the nurses were women (85.7%), married (59.4%), bachelor’s degree holder (88.2%) and service nurses (56.2%). The most potential disaster that nurses think is an earthquake (70.9%) by the time majority of nurses consider having a role as a nurse at every stage of disasters. The mean total point score of nurses’ perception of disaster preparedness was 4.62. The mean total point score of the nurses from the Nurses’ Perception of Core Competencies for Disaster Preparedness Scale was 133.96. When the subscales’ mean scores are examined, the highest average of the mean score is for Technical Skills (44.52), and the lowest is for Critical Thinking Skills (10.47). When the subscales of Nurses’ Perception of Core Competencies for Disaster Preparedness Scale compared with sex, marital status and education level out of independent variable of nurses there is no significant difference (p > 0.05); compared with age group, working years, duty and being with a disaster out of independent variable of nurses there is a significant difference (p ≤ 0.05). Conclusion: Nurses generally perceive themselves as sufficient at a ‘medium level’ in terms of meeting the core competencies that are required for disaster preparedness. Nurses are not adequately prepared for disasters, but they are aware of the need for such preparation and disaster education. Disaster management training should be given to all nurses in their basic education.

Keywords: disaster competencies, disaster management, disaster nursing, disaster preparedness, nursing, nursing administration, Turkish nurses

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Authors: Sonda Jallouli, Omar Hammouda, Imen Ben Dhia, Salma Sakka, Chokri Mhiri, Mohamed Habib Elleuch, Abedlmoneem Yahia, Sameh Ghroubi

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Multiple sclerosis (MS) is characterized by gender differences with affecting women two to four times more than men, but the disease progression is faster and more severe in men. Fatigue represents one of the most frequent and disabling symptoms related to MS. Results of previous studies regarding gender differences in fatigue perception in MS persons are contradictory. Besides, fatigue has been shown to affect negatively postural balance and functional mobility in MS persons. However, no study has taken into account gender differences in the response of these physical parameters to a fatiguing protocol in MS persons. Given the reduction of autonomy due to the alteration of these parameters induced by fatigue and the importance of gender differences in postural balance training programs in fatigued men and women with MS, the aim of this study was to investigate the effect of gender difference on unipedal postural balance and functional mobility after performing a fatiguing task in MS adults. Methods: Eleven women (30.29 ± 7.99 years) and seven men (30.91 ± 8.19 years) with relapsing-remitting MS performed a fatiguing protocol: three sets of the 5×sit to stand test (5-STST), six-minute walk test (6MWT) followed by three sets of the 5-STST. Unipedal balance, functional mobility, and fatigue perception were measured prefatigue (T0) and post fatigue (T3) using a clinical unipedal balance test, timed up and go test (TUGT), and analogic visual scale of fatigue (VASF), respectively. Heart rate (HR) and rate of perceived exertion (RPE) were recorded before, during and after the fatiguing task. Results: Compared to women, men showed an impairment of unipedal balance on the dominant leg (p<0.001, d=0.52) and mobility (p<0.001, d=3) via reducing unipedal stance time and increasing duration of TUGT execution, respectively. No gender differences were observed in 6MWT, 5-STST, HR, RPE and VASF scores. Conclusion: Fatiguing protocol negatively affected unipedal postural balance and mobility only in men. These gender differences were inconclusive but can be taken into account in postural balance rehabilitation programs for persons with MS.

Keywords: functional mobility, fatiguing exercises, multiple sclerosis, sex differences, unipedal balance

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Authors: Sunethra Jayathilake, Vathsala Jayasuriya-Illesinghe, Kerstin Samarasinghe, Himani Molligoda, Rasika Perera

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In Sri Lanka, postnatal care in the state hospitals is provided by different professional categories: Midwifery trained registered nurses (MTRNs), Registered Nurses (RNs) who do not have midwifery training, doctors and midwives. Even though four professional categories provide postnatal care to mothers and newborn babies, they are not aware of their own tasks and responsibilities in postnatal care. Particularly MTRN’s role in the postnatal unit is unclear. The current study aimed to identify nurses’ (both MTRN and RNs) perception on MTRN’s tasks and responsibilities in postnatal care. This is a descriptive cross sectional study using postal survey. All nurses who were currently working in postnatal units at five selected tertiary care hospitals in the Western Province at that time were invited to participate in the study. Accordingly, the pre evaluated self-administered questionnaire was sent to 201 nurses (53 MTRNs and 148 RNs) in the study setting. The number of valid return questionnaire was 166; response rate was 83%. Respondents rated the responsibility of four professional categories: MTRN, RN, doctor and midwife whether they are 'primarily responsible', 'responsible in absence' and 'not responsible', for each of 15 postnatal (PN) tasks which were previously identified from focus group discussions with care providers during the first phase of the study. Data were analyzed using SPSS version 20; descriptive statistics were calculated. Out of the 15 PN tasks, 13 were identified as MTRNs’ primary responsibilities by 71%-93% of respondents. The respondents also considered six (6) tasks out of 15 as primary responsibility of both MTRN and RN, seven (7) tasks as primary responsibility of MTRN, RN and doctor and the remaining two (2) tasks were identified as the primary responsibility of MTRN, RN and midwife. All 15 PN tasks overlapped with other professional categories. Overlapping tasks may create role confusion leading to conflicts among professional categories which affect the quality of care they provide, eventually, threaten the safety of the client. It is recommended that an official job description for each care provider is needed to recognize their own professional boundaries for ensuring safe, quality care delivery in Sri Lanka.

Keywords: overlapping, postnatal, responsibilities, tasks

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Andrew Fox, Tao Zhang, Yuanhong Zhao, Qingping Yang

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The furniture manufacturing industry has been slow in general to adopt the latest manufacturing technologies, historically relying heavily upon specialised conventional machinery. This approach not only requires high levels of specialist process knowledge, training, and capital investment but also suffers from significant subtractive manufacturing waste and high logistics costs due to the requirement for centralised manufacturing, with high levels of furniture product not re-cycled or re-used. This paper aims to address the problems by introducing suitable digital manufacturing technologies to create step changes in furniture manufacturing design, as the traditional design practices have been reported as building in 80% of environmental impact. In this paper, a 3D printing robot for furniture manufacturing is reported. The 3D printing robot mainly comprises a KUKA industrial robot, an Arduino microprocessor, and a self-assembled screw fed extruder. Compared to traditional 3D printer, the 3D printing robot has larger motion range and can be easily upgraded to enlarge the maximum size of the printed object. Generative design is also investigated in this paper, aiming to establish a combined design methodology that allows assessment of goals, constraints, materials, and manufacturing processes simultaneously. ‘Matrixing’ for part amalgamation and product performance optimisation is enabled. The generative design goals of integrated waste reduction increased manufacturing efficiency, optimised product performance, and reduced environmental impact institute a truly lean and innovative future design methodology. In addition, there is massive future potential to leverage Single Minute Exchange of Die (SMED) theory through generative design post-processing of geometry for robot manufacture, resulting in ‘mass customised’ furniture with virtually no setup requirements. These generatively designed products can be manufactured using the robot based additive manufacturing. Essentially, the 3D printing robot is already functional; some initial goals have been achieved and are also presented in this paper.

Keywords: additive manufacturing, generative design, robot, sustainability

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Authors: K. Appasamy, P. Paul

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Mauritius, a developing small-island-state, is facing a recession which is having a considerable economic impact particularly on its construction sector. Further, the presence of foreign entities, both as companies and workers, within this sector is creating a very competitive environment for local firms. This study investigates the key drivers that allow foreign firms to participate in this sector, in particular looking at the international and local tender processes, and the capacity of local industry to participate. This study also looks at how the current set up may hinder the latter’s involvement. The methodology used included qualitative semi-structured interviews conducted with established foreign companies, local companies, and public bodies. Study findings indicate: there is an adequate availability of professional skills and expertise within the Mauritian construction industry but a lack of skilled labour especially at the operative level; projects awarded to foreign firms are either due to their uniqueness and hence lack of local knowledge, or due to foreign firms having lower tender bids; tendering systems and processes are weak, including monitoring and enforcement, which encourages corruption and favouritism; a high level of ignorance of this sector’s characteristics and opportunities exists amongst the local population; local entities are very profit oriented and have short term strategies that discourage long term investment in workforce training and development; but most importantly, stakeholders do not grasp the importance of encouraging youngsters to join this sector, they have no long term vision, and there is a lack of mutual involvement and collaboration between them. Although local industry is highly competent, qualified and experienced, the tendering and procurement systems in Mauritius are not conducive enough to allow for effective strategic planning and an equitable allocation of projects during an economic downturn so that the broadest spread of stakeholders’ benefit. It is of utmost importance that all sector and government entities collaborate to formulate strategies and reforms on tender processes and capacity building to ensure fairness and continuous growth of this sector in Mauritius.

Keywords: construction industry, tender process, international firms, local capacity, Mauritius

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Authors: Bendes Ákos

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Digital evidence will be the most widely used type of evidence in the future. With the development of the modern world, more and more new types of crimes have evolved and transformed. For this reason, it is extremely important to examine these types of crimes in order to get a comprehensive picture of them, with which we can help the authorities work. In 1865, with early technologies, people were able to forge a picture of a quality that is not even recognized today. With the help of today's technology, authorities receive a lot of false evidence. Officials are not able to process such a large amount of data, nor do they have the necessary technical knowledge to get a real picture of the authenticity of the given evidence. The digital world has many dangers. Unfortunately, we live in an age where we must protect everything digitally: our phones, our computers, our cars, and all the smart devices that are present in our personal lives and this is not only a burden on us, since companies, state and public utilities institutions are also forced to do so. The training of specialists and experts is essential so that the authorities can manage the incoming digital evidence at some level. When analyzing evidence, it is important to be able to examine it from the moment it is created. Establishing authenticity is a very important issue during official procedures. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. Otherwise, they will not have sufficient probative value and in case of doubt, the court will always decide in favor of the defendant. One of the most common problems in the world of digital data and evidence is doubt, which is why it is extremely important to examine the above-mentioned problems. The most effective way to avoid digital crimes is to prevent them, for which proper education and knowledge are essential. The aim is to present the dangers inherent in the digital world and the new types of digital crimes. After the comparison of the Hungarian investigative techniques with international practice, modernizing proposals will be given. A sufficiently stable yet flexible legislation is needed that can monitor the rapid changes in the world and not regulate afterward but rather provide an appropriate framework. It is also important to be able to distinguish between digital and digitalized evidence, as the degree of probative force differs greatly. The aim of the research is to promote effective international cooperation and uniform legal regulation in the world of digital crimes.

Keywords: digital crime, digital law, cyber crime, international cooperation, new crimes, skepticism

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Authors: Geum Yeon Sim, Tyler Pigott, Julio Vasquez

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A 38-year-old obese female with no apparent past medical history presented with left knee pain. Six months ago, she sustained a left knee dislocation in a motor vehicle accident that was managed with a skin graft over the left lower extremity without any reconstructive surgery. She developed persistent pain and stiffness in her left knee that worsened with walking and stair climbing. Examination revealed healed extensive skin graft over the left lower extremity, including the left knee. Palpation showed moderate tenderness along the superior border of the patella, exquisite tenderness over MCL, and mild tenderness on the tibial tuberosity. There was normal sensation, reflexes, and strength in her lower extremities. There was limited active and passive range of motion of her left knee during flexion. There was instability noted upon the valgus stress test of the left knee. Left knee magnetic resonance imaging showed high-grade (grade 2-3) injury of the proximal superficial fibers of the MCL and diffuse thickening and signal abnormality of the cruciate ligaments, as well as edema-like subchondral marrow signal change in the anterolateral aspect of the lateral femoral condyle weight-bearing surface. There was also notable extensive scarring and edema of the skin, subcutaneous soft tissues, and musculature surrounding the knee. The patient was managed with left knee immobilization for five months, which was complicated by limited knee flexion. Physical therapy consisting of quadriceps, hamstrings, gastrocnemius stretching and strengthening, range of motion exercises, scar/soft tissue mobilization, and gait training was given with marked improvement in pain and range of motion. The patient experienced a further reduction in pain as well as an improvement in function with home exercises consisting of continued strengthening and stretching.

Keywords: ligamentous injury, trauma, rehabilitation, knee pain

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Authors: Elham A. Kwildi, Yahia S. Abugnah, Nuri S. Madi

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This study was designed to evaluate the microbiological quality and safety of two types of salads prepared at a catering center affiliated with Libyan Airlines in Tripoli, Libya. Two hundred and twenty-one (221) samples (132 economy-class and 89 first- class) were used in this project which lasted for ten months. Biweekly, microbiological tests were performed which included total plate count (TPC) and total coliforms (TCF), in addition to enumeration and/or detection of some pathogenic bacteria mainly Escherichia coli, Staphylococcus aureus, Bacillus cereus, Salmonella sp, Listeria sp and Vibrio parahaemolyticus parahaemolyticus, By using conventional as well as compact dry methods. Results indicated that TPC of type 1 salad ranged between (<10 – 62 x 103 cfu/gm) and (<10 to 36 x103 cfu/g), while TCF were (<10 – 41 x 103 cfu/gm) and (< 10 to 66 x102 cfu/g) using both methods of detection respectively. On the other hand, TPC of type 2 salad were: (1 × 10 – 52 x 103) and (<10 – 55 x 103 cfu/gm) and in the range of (1 x10 to 45x103 cfu/g), and the (TCF) counts were between (< 10 to 55x103 cfu/g) and (< 10 to 34 x103 cfu/g) using the 1st and the 2nd methods of detection respectively. Also, the pathogens mentioned above were detected in both types of salads, but their levels varied according to the type of salad and the method of detection. The level of Staphylococcus aureus, for instance, was 17.4% using conventional method versus 14.4% using the compact dry method. Similarly, E. coli was 7.6% and 9.8%, while Salmonella sp. recorded the least percentage i.e. 3% and 3.8% with the two mentioned methods respectively. First class salads were also found to contain the same pathogens, but the level of E. coli was relatively higher in this case (14.6% and 16.9%) using conventional and compact dry methods respectively. The second rank came Staphylococcus aureus (13.5%) and (11.2%), followed by Salmonella (6.74%) and 6.70%). The least percentage was for Vibrio parahaemolyticus (4.9%) which was detected in the first class salads only. The other two pathogens Bacillus cereus and Listeria sp. were not detected in either one of the salads. Finally, it is worth mentioning that there was a significant decline in TPC and TCF counts in addition to the disappearance of pathogenic bacteria after the 6-7th month of the study which coincided with the first trial of the HACCP system at the center. The ups and downs in the counts along the early stages of the study reveal that there is a need for some important correction measures including more emphasis on training of the personnel in applying the HACCP system effectively.

Keywords: air travel, vegetable salads, foodborne outbreaks, Libya

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Authors: Kunkanit Sutamchai, Kate E. Rowlands

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Recent public ethical scandals in many organizations around the world have raised concern about organizational ethics, which have, in turn, made ethical behaviors and conducts on the part of leaders become more critical topics in organizational studies. However, current research on the benefits of mindfulness within the workplace contexts has predominantly focused on stress reduction and work performance enhancement, while the aspects of ethical behavior development have been far less investigated in mindfulness research in the organizational and management fields. Only recently has there been an emerging call for organizational researchers and practitioners to study mindfulness concepts and practices from the original Buddhist perspectives given that ethics is regarded as a foundation for Buddhist mindfulness. Yet little, if any, empirical research on the contributions of mindfulness practices to ethical leadership has been done in Eastern Buddhist contexts. Therefore, this study aims to explore the extent to which and how Buddhist-based mindfulness practices can influence organizational leaders’ ethical values and practices. On this basis, Thailand was selected as a context of study due to a predominantly Buddhist society and culture. Qualitative data were gathered through in-depth semi-structured interviews with twenty executive leaders from various private organizations in Thailand, who practice Buddhist-based mindfulness meditation regularly. The findings from this study shed light on the role Buddhist-based mindfulness practices can play in promoting ethical behavior among executive leaders in Thailand. The results also suggest that ethical values and practices influenced by Buddhist-based mindfulness practices are well aligned with the elements appeared in the inter-disciplinary and cross-cultural ethical leadership framework, namely: humane, justice, sustainability and responsibility, and moderation. This study concludes that the integration of ethical dimensions to mindfulness practices may provide promising opportunities for ethical leadership development, particularly in the context of Thailand. This could contribute significantly to the future development of both organizations and society at large. The study also suggests that mindfulness interventions in organizational contexts should place more explicit emphasis on ethics. This may be done by relating the ethical principles underlying Buddhist-based mindfulness to other ethical systems in different contexts and cultures where they can be aligned.

Keywords: Buddhism, ethical leadership, leadership development, mindfulness, Thailand, training

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Authors: Ali Kharazi, Hassanali Aghajani, Hesami Azizi

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Tourism entrepreneurship is a growing field that has the potential to create new opportunities for sustainable development. The purpose of this study is to identify and classify the entrepreneurial opportunities in the blind tourism industry in Khuzestan Province of Iran that can be created through the operation of blinds’ tours. This study used a mixed methods approach. The qualitative data was collected through semi-structured interviews with 15 tourist guides and tourism activists, while the quantitative data was collected through a questionnaire survey of 40 blind people who had participated in blinds’ tours. The findings of this study suggest that there are a number of entrepreneurial opportunities in the blind tourism industry in Khuzestan Province, including (1) developing and providing accessible tourism services, such as tours, accommodations, restaurants, and transportation, (2) creating and marketing blind-friendly tourism products and experiences (3) training and educating tourism professionals on how to provide accessible and inclusive tourism services. This study contributes to the theoretical understanding of tourism entrepreneurship by providing insights into the entrepreneurial opportunities in the blind tourism industry. The findings of this study can be used to develop policies and programs that support the development of the blind tourism industry. The qualitative data were analyzed using content analysis. The quantitative data were analyzed using descriptive statistics and inferential statistics. This study examines the entrepreneurial opportunities within the blind tourism industry in Khuzestan Province, Iran. In addition, Khuzestan province has made relatively good development in the field of blinds’ tourism. Blind tourists have become loyal customers of blinds’ tours, which has increased their self-confidence and social participation. Tourist guides and centers of tourism services are interested in participating in blinds’ tours more than before, and even other parts outside the tourism field have encouraged sponsorship. Education had a great impact on the quality of tourism services, especially for the blind. It has played a significant role in improving the quality of tourism services for the blind. However, the quality and quantity of infrastructure should be increased in different sectors of tourism services to foster future growth. These opportunities can be used to create new businesses and jobs and to promote sustainable development in the region.

Keywords: entrepreneurship, tourism, blind, sustainable development, Khuzestan

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Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: Kriti Jain, Sucha Singh Gill

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Subsidies have been a major part of agricultural policies around the world, and more extensively since the green revolution in developing countries, for the sake of attaining higher agricultural productivity and achieving food security. But entrenched subsidies lead to distorted incentives and promote inefficiencies in the agricultural sector, threatening the viability of these very subsidies and sustainability of the agricultural production systems, posing a threat to the livelihood of farmers and laborers dependent on it. This paper analyzes the economic and ecological sustainability implications of prolonged input and output subsidies in agriculture by studying the case of Indian Punjab, an agriculturally developed state responsible for ensuring food security in the country when it was facing a major food crisis. The paper focuses specifically on the environmentally unsustainable cropping pattern changes as a result of Minimum Support Price (MSP) and assured procurement and on the resource use efficiency and cost implications of power subsidy for irrigation in Punjab. The study is based on an analysis of both secondary and primary data sources. Using secondary data, a time series analysis was done to capture the changes in Punjab’s cropping pattern, water table depth, fertilizer consumption, and electrification of agriculture. This has been done to examine the role of price and output support adopted to encourage the adoption of green revolution technology in changing the cropping structure of the state, resulting in increased input use intensities (especially groundwater and fertilizers), which harms the ecological balance and decreases factor productivity. Evaluation of electrification of Punjab agriculture helped evaluate the trend in electricity productivity of agriculture and how free power imposed further pressure on the extant agricultural ecosystem. Using data collected from a primary survey of 320 farmers in Punjab, the extent of wasteful application of groundwater irrigation, water productivity of output, electricity usage, and cost of irrigation driven electricity subsidy to the exchequer were estimated for the dominant cropping pattern amongst farmers. The main findings of the study revealed how because of a subsidy has driven agricultural framework, Punjab has lost area under agro climatically suitable and staple crops and moved towards a paddy-wheat cropping system, that is gnawing away the state’s natural resources like water table has been declining at a significant rate of 25 cms per year since 1975-76, and excessive and imbalanced fertilizer usage has led to declining soil fertility in the state. With electricity-driven tubewells as the major source of irrigation within a regime of free electricity and water-intensive crop cultivation, there is both wasteful application of irrigation water and electricity in the cultivation of paddy crops, burning an unproductive hole in the exchequer’s pocket. There is limited access to both agricultural extension services and water-conserving technology, along with policy imbalance, keeping farmers in an intensive and unsustainable production system. Punjab agriculture is witnessing diminishing returns to factor, which under the business-as-usual scenario, will soon enter the phase of negative returns to factor.

Keywords: cropping pattern, electrification, subsidy, sustainability

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Authors: Ferran Paulí Pla, Pere Palacín Farré, Albert Fornells Herrera, Pol Toldrà Fernández

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Poor image acquisition is limiting the promising growth of industrial vision in food control. In recent years, the food industry has witnessed a significant increase in the implementation of automation in quality control through artificial vision, a trend that continues to grow. During the packaging process, some defects may appear, compromising the proper sealing of the products and diminishing their shelf life, sanitary conditions and overall properties. While failure to detect a defective product leads to major losses, food producers also aim to minimize over-rejection to avoid unnecessary waste. Thus, accuracy in the evaluation of the products is crucial, and, given the large production volumes, even small improvements have a significant impact. Recently, efforts have been focused on maximizing the performance of classification neural networks; nevertheless, their performance is limited by the quality of the input data. Monochrome linear backlight systems are most commonly used for online inspections of food packaging thermo-sealing zones. These simple acquisition systems fit the high cadence of the production lines imposed by the market demand. Nevertheless, they provide a limited amount of data, which negatively impacts classification algorithm training. A desired situation would be one where data quality is maximized in terms of obtaining the key information to detect defects while maintaining a fast working pace. This work presents a backlight hyperspectral imaging system designed and implemented replicating an industrial environment to better understand the relationship between visual data quality and spectral illumination range for a variety of packed food products. Furthermore, results led to the identification of advantageous spectral bands that significantly enhance image quality, providing clearer detection of defects.

Keywords: artificial vision, food packaging, hyperspectral imaging, image acquisition, quality control

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Authors: Smita Singh

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Objective: The Faculty of Chemistry Education at Humboldt University has developed ‘Studium’, a web application designed to enhance long-term self-regulated learning (SRL) and academic achievement. Leveraging advanced generative AI, ‘Studium’ offers a dynamic and adaptive educational experience tailored to individual learning preferences and languages. The application includes evolving tools for personalized notetaking from preferred sources, customizable presentation capabilities, and AI-assisted guidance from academic documents or textbooks. It also features workflow automation and seamless integration with collaborative platforms like Miro, powered by AI. This study aims to propose a model that combines generative AI with traditional features and customization options, empowering students to create personalized learning environments that effectively address the challenges of SRL. Method: To achieve this, the study included graduate and undergraduate students from diverse subject streams, with 15 participants each from Germany and India, ensuring a diverse educational background. An exploratory design was employed using a speed dating method with enactment, where different scenario sessions were created to allow participants to experience various features of ‘Studium’. The session lasted for 50 minutes, providing an in-depth exploration of the platform's capabilities. Participants interacted with Studium’s features via Zoom conferencing and were then engaged in semi-structured interviews lasting 10-15 minutes to gain deeper insights into the effectiveness of ‘Studium’. Additionally, online questionnaire surveys were conducted before and after the session to gather feedback and evaluate satisfaction with self-regulated learning (SRL) after using ‘Studium’. The response rate of this survey was 100%. Results: The findings of this study indicate that students widely acknowledged the positive impact of ‘Studium’ on their learning experience, particularly its adaptability and intuitive design. They expressed a desire for more tools like ‘Studium’ to support self-regulated learning in the future. The application significantly fostered students' independence in organizing information and planning study workflows, which in turn enhanced their confidence in mastering complex concepts. Additionally, ‘Studium’ promoted strategic decision-making and helped students overcome various learning challenges, reinforcing their self-regulation, organization, and motivation skills. Conclusion: This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like “Studium” can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners. This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like ‘Studium’ can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners.

Keywords: self-regulated learning (SRL), generative AI, AI-assisted educational platforms

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Authors: Umi Pudji Astuti, Dedi Sugandi

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The effectiveness of agricultural extension is determined by the component in the agricultural extension system among others are agricultural extension methods. Effective methods should be selected and defined based on the characteristics of the target, the resources, the materials, and the objectives to be achieved. Citrus agribusiness development in Lebong is certainly supported by the role of stakeholders and citrus farmers, as well as the proper dissemination methods. Adoption in the extension process substantially can be interpreted as the changes of behavior process such as knowledge (cognitive), attitudes (affective), and skill (psycho-motoric) in a person after receiving "innovation" from extension submitted by target communities. Knowledge and perception are needed as a first step in adopting a innovation, especially of citrus agribusiness development in Lebong. The process of Specific technology adoption is influenced by internal factors and farmer perceptions of technological innovation. Internal factors such as formal education, experience trying to farm, owned land, production farm goods. The output of this study: 1) to analyze the effectiveness of field trial methods in improving cognitive and affective farmers; 2) Knowing the relationship of adoption level and knowledge of farmers; 3) to analyze the factors that influence farmers' adoption of citrus technology innovation. The method of this study is through the survey to 40 respondents in Rimbo Pengadang Sub District, Lebong District in 2014. Analyzing data is done by descriptive and statistical parametric (multiple linear functions). The results showed that: 1) Field trip method is effective to improve the farmer knowledge (23,17% ) and positively affect the farmer attitude; 2) the knowledge level of PTKJS innovation farmers "positively and very closely related".; 3) the factors that influence the level of farmers' adoption are internal factors (education, knowledge, and the intensity of training), and external factors respondents (distance from the house to the garden and from the house to production facilities shop).

Keywords: affect, adoption technology, citrus gerga, effectiveness dissemination

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Authors: Christiane Dumont

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This paper proposes to revisit foreign-language learning as a tool to increase motivation through advocacy and develop effective natural communication skills, which are critical leadership qualities. To this end, collaborative initiatives undertaken by advanced university students of French with local and international community partners will be reviewed. Close attention will be paid to the acquisition of intercultural skills, the reflective process, as well as the challenges and outcomes. Two international development projects conducted in Haiti will be highlighted, i.e., collaboration with a network of providers in the Haitian cultural heritage preservation and tourism sector (2014-15) and development of investigation and teacher training tools for a primary/secondary school in the Port-au-Prince area (current). The choice of community-service learning as a framework to teach French-as-a-second-language stemmed from the need to raise awareness against stereotypes and prejudice, which hinder the development of effective intercultural skills. This type of experiential education also proved very effective in identifying and preventing miscommunication caused by the lack of face-to-face interaction in our increasingly technology-mediated world. Learners experienced first-hand, the challenges and advantages of face-to-face communication, which, in turn, enhanced their motivation for developing effective intercultural skills. Vygotsky's and Kolb's theories, current research on service learning (Dwight, Eyler), action/project-based pedagogy (Beckett), and reflective learning (TSC Farrell), will provide useful background to analyze the benefits and challenges of community-service learning. The ultimate goal of this paper is to find out what makes experiential learning truly unique and transformative for both the learners and the community they wish to serve. It will demonstrate how enhanced motivation, community engagement, and clear, concise, and respectful communication impact and empower learners. The underlying hope is to help students in high-profile, and leading-edge industries become effective global leaders.

Keywords: experiential learning, intercultural communication, reflective learning, effective leadership, learner motivation

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Authors: Mauro Callejas-Cuervo, Andrea Catherine Alarcon-Aldana, Lorena Paola Castillo-Guerra

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The software industry requires highly-trained professionals, capable of developing the roles integrated in the cycle of software development. That is why a large part of the task is the responsibility of higher education institutions; often through a curriculum established to orientate the academic development of the students. It is so that nowadays there are different models that support proposals for the improvement of the curricula for the area of Software Engineering, such as ACM, IEEE, ABET, Swebok, of which the last stands out, given that it manages and organises the knowledge of Software Engineering and offers a vision of theoretical and practical aspects. Moreover, it has been applied by different universities in the pursuit of achieving coverage in delivering the different topics and increasing the professional quality of future graduates. This research presents the structure of teaching and learning guides from the objectives of training and methodological strategies immersed in the levels of learning of Bloom’s taxonomy with which it is intended to improve the delivery of the topics in the area of Requirements Engineering. Said guides were implemented and validated in a course of Requirements Engineering of the Systems and Computer Engineering programme in the Universidad Pedagógica y Tecnológica de Colombia (Pedagogical and Technological University of Colombia) using a four stage methodology: definition of the evaluation model, implementation of the guides, guide evaluation, and analysis of the results. After the collection and analysis of the data, the results show that in six out of the seven topics proposed in the Swebok guide, the percentage of students who obtained total marks within the 'High grade' level, that is between 4.0 and 4.6 (on a scale of 0.0 to 5.0), was higher than the percentage of students who obtained marks within the 'Acceptable' range of 3.0 to 3.9. In 86% of the topics and the strategies proposed, the teaching and learning guides facilitated the comprehension, analysis, and articulation of the concepts and processes of the students. In addition, they mainly indicate that the guides strengthened the argumentative and interpretative competencies, while the remaining 14% denotes the need to reinforce the strategies regarding the propositive competence, given that it presented the lowest average.

Keywords: pedagogic guide, pedagogic strategies, requirements engineering, Swebok, teaching-learning process

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Authors: Niloofar Zebarjad

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This research aims at finding a tool to provide basketball players with real-time audio feedback on their shooting form in free throw shots. Free throws played a pivotal role in taking the lead in fierce competitions. The major problem in performing an accurate free throw seems to be improper training. Since the arm movement during the free throw shot is complex, the coach or the athlete might miss the movement details during practice. Hence, there is a necessity to create a system that measures arm movements' critical characteristics and control for improper kinematics. The proposed setup in this study quantifies arm kinematics and provides real-time feedback as an audio signal consisting of a gyroscope sensor. Spatial shoulder angle data are transmitted in a mobile application in real-time and can be saved and processed for statistical and analysis purposes. The proposed system is easy to use, inexpensive, portable, and real-time applicable. Objectives: This research aims to modify and control the free throw using audio feedback and determine if and to what extent the new setup reduces errors in arm formations during throws and finally assesses the successful throw rate. Methods: One group of elite basketball athletes and two novice athletes (control and study group) participated in this study. Each group contains 5 participants being studied in three separate sessions over a week. Results: Empirical results showed enhancements in the free throw shooting style, shot pocket (SP), and locked position (LP). The mean values of shoulder angle were controlled on 25° and 45° for SP and LP, respectively, recommended by valid FIBA references. Conclusion: Throughout the experiments, the system helped correct and control the shoulder angles toward the targeted pattern of shot pocket (SP) and locked position (LP). According to the desired results for arm motion, adding another sensor to measure and control the elbow angle is recommended.

Keywords: audio-feedback, basketball, free-throw, locked-position, motor-control, shot-pocket

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Authors: Cemile Kütmeç Yilmaz, Güler Duru Asiret, Gulcan Bagcivan

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The aim of this study was to evaluate the reliability and validity of the Turkish version of the Carer’s Assessment of Satisfaction Index (CASI-TR). The study was conducted between the dates of June 2016 and September 2017 at the Training and Research Hospital of Aksaray University with the caregiving family members of the inpatients with chronic diseases. For this study, the sample size was calculated as at least 10 individuals for each item (item number (30)X10=300). The study sample included 300 caregiving family members, who provided primer care for at least three months for a patient (who had at least one chronic disease and received inpatient treatment in general internal medicine and palliative care units). Data were collected by using a demographic questionnaire and CASI-TR. Descriptive statistics, and psychometric tests were used for the data analysis. Of those caregivers, 76.7% were female, 86.3% were 65 years old and below, 43.7% were primary school graduates, 87% were married, 86% were not working, 66.3% were housewives, and 60.3% defined their income status as having an income covering one’s expenses. Care recipients often had problems in terms of walking, sleep, balance, feeding and urinary incontinence. The Cronbach Alpha value calculated for the CASI-TR (30 items) was 0,949. Internal consistency coefficients calculated for subscales were: 0.922 for the subscale of ‘caregiver satisfaction related to care recipient’, 0.875 for the subscale of ‘caregiver satisfaction related to themselves’, and 0.723 for the subscale of ‘dynamics of interpersonal relations’. Factor analysis revealed that three factors accounted for 57.67% of the total variance, with an eigenvalue of >1. assessed in terms of significance, we saw that the items came together in a significant manner. The factor load of the items were between 0.311 and 0.874. These results show that the CASI-TR is a valid and reliable scale. The adoption of the translated CASI in Turkey is found reliable and valid to assessing the satisfaction of caregivers. CASI-TR can be used easily in clinics or house visits by nurses and other health professionals for assessing caregiver satisfaction from caregiving.

Keywords: carer’s assessment of satisfaction index, caregiver, validity, reliability

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Authors: Mary Rosa Espinosa-Ochoa

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Some constructions appear suddenly in children’s speech and are productive from the beginning. These constructions are supported by others, previously acquired, with which they share semantic and pragmatic features. Thus, for example, the acquisition of the passive voice in German is supported by other constructions with which it shares the lexical verb sein (“to be”). This also occurs in Spanish, in the acquisition of the progressive aspectual periphrasis estar (“to be”) + verb root + -ndo (present participle), supported by locative constructions acquired earlier with the same verb. The periphrasis shares with the locative constructions not only the lexical verb estar, but also pragmatic relations. Both constructions can be used to answer the question ¿Dónde está? (“Where is he/she/it?”), whose answer could be either Está aquí (“He/she/it is here”) or Se está bañando (“He/she/it is taking a bath”).This study is a corpus-based analysis of two children (1;08-2;08) and the input directed to them: it proposes that the pragmatic and semantic support from previously-acquired constructions comes from the input, during interaction with others. This hypothesis is based on analysis of constructions with estar, whose use to express temporal change (which differentiates it from its counterpart ser [“to be”]), is given in variation sets, similar to those described by Küntay and Slobin (2002), that allow the child to perceive the change of place experienced by nouns that function as its grammatical subject. For example, at different points during a bath, the mother says: El jabón está aquí “The soap is here” (beginning of bath); five minutes later, the soap has moved, and the mother says el jabón está ahí “the soap is there”; the soap moves again later on and she says: el jabón está abajo de ti “the soap is under you”. “The soap” is the grammatical subject of all of these utterances. The Spanish verb + -ndo is a progressive phase aspect encoder of a dynamic state that generates a token. The verb + -ndo is also combined with verb estar to encode. It is proposed here that the phases experienced in interaction with the adult, in events related to the verb estar, allow a child to generate this dynamicity and token reading of the verb + -ndo. In this way, children begin to produce the periphrasis suddenly and productively, even though neither the periphrasis nor the verb + -ndo itself are frequent in adult speech.

Keywords: child language acquisition, input, variation sets, Spanish language

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Authors: Florian Tille, Heide Weishaar, Bernhard Gibis, Susanne Schnitzer

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Introduction: The quality of patient-doctor communication and of written health information is central to organizational health literacy (HL). Whether patients understand their doctors’ explanations and textual material on health, however, is understudied. This study identifies the overall levels of patient understanding of health information and its associations with patients’ social characteristics in outpatient health care in Germany. Materials & Methods: This analysis draws on data collected via a 2017 national health survey with a sample of 6,105 adults. Quality of communication was measured for consultations with general practitioners (GPs) and specialists (SPs) via the Ask Me 3 program questions, and through a question on written health material. Correlations with social characteristics were explored employing bivariate and multivariate logistic regression analyses. Results: Over 90% of all respondents reported that they had understood their doctors’ explanations during the last consultation. Failed understanding was strongly correlated with patients’ very poor health (Odds Ratio [OR]: 5.19; 95% confidence interval [CI]: 2.23–12.10; ref. excellent/very good health), current health problem (OR: 6.54, CI: 1.70–25.12; ref. preventive examination) and age 65 years and above (OR: 2.97, CI: 1.10–8.00; ref. 18 to 34 years). Fewer patients answered they understood written material well (86.7% for las visit at GP, 89.7% at SP). Understanding written material poorly was highly associated with basic education (OR: 4.20, CI: 2.76–6.39; ref. higher education) and 65 years old and above (OR: 2.66, CI: 1.43–4.96). Discussion: Overall ratings of oral patient-doctor communication and written communication of health information are high. Yet, a considerable share of patients reports not-understanding their doctors and poor understanding of the written health-related material. Interventions that can contribute to improving organizational HL in outpatient care in Germany include HL training for doctors, reducing system barriers to easily-accessible health information for patients and combining oral and written health communication means. Conclusion: This work adds to the study of organizational HL in Germany. To increase patient understanding of health-relevant information and thereby possibly reduce health disparities, meeting the communication needs especially of persons in different age groups, with basic education and in very poor health is suggested.

Keywords: health survey, organizational health literacy, patient-doctor communication, social characteristics, outpatient care, Ask Me 3

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Authors: A. Papachristou, A. Ntikoudi, L. Makris, V. Saridakis

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Introduction: More than 10 million people are imprisoned or detained worldwide. Figures from 2011-12 show that prison inmates are more likely than the general population to suffer from chronic or infectious diseases, while most inmates are overweight or obese, and more than a quarter have high blood pressure. In 2011/12, the proportion of prisoners reporting diabetes or hyperglycemia was 899 per 10,000 prisoners, almost double the 2004 figure (483 per 10,000). It is important to ensure that this population has access to the same standard of care as people outside prisons, as access to services should be need-based. Diabetes is a public health problem associated with increased morbidity and mortality worldwide. According to the International Diabetes Federation (IDF) in 2017, approximately 425 million people worldwide had diabetes. This number is expected to increase to 629 million by 2045. Poor management of diabetes in prisons can lead to poor blood sugar control and increase the risk of complications. Aim: The aim of this review was to systematically evaluate all the available literature on diabetes care in custodial settings. Methods: An extensive literature search was conducted through electronic databases (PubMed, Scopus and CINAHL) with the terms ‘custody’, ‘diabetes Mellitus, ‘detention centers and ‘chronic disease’. Articles published in English until September 2022, were included; no other criteria on publication dates were set. Results: Most of the studies mentioned a diabetes prevalence of approximately 10%, among other common chronic. Hypertension, obesity, smoking, sedentary lifestyle were the most common comorbidities associated with diabetes. Conclusion: Good glycemic control is fundamental to managing diabetes, and while many prisoners enter prison poorly, access to regular medication and meals, as well as exercise, offers the potential for improvement. Not being able to get help as quickly as in the past can be extremely stressful, and some prisoners may deliberately raise their blood sugar levels to avoid the risk of developing hypoglycemia, especially if they know they have had previous episodes of nocturnal hypoglycemia. Thus, appropriate training and resources are critical to providing quality care to incarcerated people with diabetes.

Keywords: custody, diabetes mellitus, detention centers, chronic disease

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

Procedia PDF Downloads 63