Search results for: opposition based learning

Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Ersin Bozkurt

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The aim of the study is to develop materials for understanding image formations through virtual objects in geometric optics. The images in physics course books are formed by using real objects. This results in mistakes in the features of images because of generalizations which leads to conceptual misunderstandings in learning. In this study it was intended to identify pre-service physics teachers misunderstandings arising from false generalizations. Focused group interview was used as a qualitative method. The findings of the study show that students have several misconceptions such as "the image in a plain mirror is always virtual". However a real image can be formed in a plain mirror. To explain a virtual object's image formation in a more understandable way an overhead projector and episcope and their design was illustrated. The illustrations are original and several computer simulations will be suggested.

Keywords: computer simulations, geometric optics, physics education, students' misconceptions in physics

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Authors: Ilham Benali, Nasser Hajji, Nawfel Acha

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The pharmaceutical sector is ongoing different constraints related to the Research and Development (R&D) costs, the patents extinction, the demand pressing, the regulatory requirement and the generics development, which drive leading firms in the sector to undergo technological change and to shift to biotechnological paradigm. Based on a large literature review, we present a background of innovation trajectory in pharmaceutical industry and reasons behind this technological transformation. Then we investigate the role that Information and Communication Technology (ICT) is playing in this revolution. In order to situate pharmaceutical firms in developing countries in this trajectory, and to examine the degree of their involvement in the innovation process, we did not find any previous empirical work or sources generating gathered data that allow us to analyze this phenomenon. Therefore, and for the case of Morocco, we tried to do it from scratch by gathering relevant data of the last five years from different sources. As a result, only about 4% of all innovative drugs that have access to the local market in the mentioned period are made locally which substantiates that the industrial model in pharmaceutical sector in developing countries is based on the 'license model'. Finally, we present another alternative, based on ICT use and big data tools that can allow developing countries to shift from status of simple consumers to active actors in the innovation process.

Keywords: biotechnologies, developing countries, innovation, information and communication technology, pharmaceutical firms

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Authors: Fairouz Beggas

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Due to the large number of exchanges in the networks, the security of communications is essential. Most ways of keeping communication secure rely on encryption. In this work, a symmetric encryption technique is offered to encrypt and decrypt simple Arabic scripts based on a multi-level security. A proposed technique uses an idea of Playfair encryption with a larger table size and an additional layer of encryption to ensure more security. The idea of the proposed algorithm aims to generate a dynamic table that depends on a secret key. The same secret key is also used to create other secret keys to over-encrypt the plaintext in three steps. The obtained results show that the proposed algorithm is faster in terms of encryption/decryption speed and can resist to many types of attacks.

Keywords: arabic data, encryption, playfair, symmetric algorithm

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Authors: Babak Nemat

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Background and Purpose: Non-alcoholic fatty liver is one of the most common liver disorders, which, as the most important cause of death from liver disease, has unpleasant consequences and complications. The aim of this study was to investigate the effect of an educational intervention based on a health belief model to prevent non-alcoholic fatty liver among women. Materials and Methods: This experimental study was performed among 110 women referring to comprehensive health service centers in Malayer City, west of Iran, in 2023. Using the available sampling method, 110 participants were divided into experimental and control groups. The data collection tool included demographic characteristics and a questionnaire based on the health belief model. In the experimental group, three one-hour training sessions were conducted in the form of pamphlets, lectures, and group discussions. Data were analyzed using SPSS software version 21, by correlation tests, paired t-tests, and independent t-tests. Results: The mean age of participants was 38.07±6.28 years, and most of the participants were middle-aged, married, housewives with academic education, middle-income, and overweight. After the educational intervention, the mean scores of the constructs include perceived sensitivity (p=0.01), perceived severity (p=0.01), perceived benefits (p=0.01), guidance for internal (p=0.01), and external action (p=0.01), and perceived self-efficacy (p=0.01) in the experimental group were significantly higher than the control group. The score of perceived barriers in the experimental group decreased after training. The perceived obstacles score in the test group decreased after the training (15.2 ± 3.9 v.s 11.2 ± 3.3, (p<0.01). Conclusion: The findings of the study showed that the design and implementation of educational programs based on the constructs of the health belief model can be effective in preventing women from developing higher levels of non-alcoholic fatty liver.

Keywords: non-alcoholic fatty liver, health belief model, education, women

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Authors: Robin Gengan

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The film industry is one of the most impactful creative sectors in modern social influence. It has relational effects on knowledge and psychological impact on the youth. Much focus in current filmmaking is either in fictional drama or documentary. The purpose of this article is to combine the two into a third genre; edutainment in which film is approached as a visual educational text. Similar to language text, cinema can be applied to semiotic reading. Film interpretation is a phenomenological order, unique to each viewer. There are cultural norms and tropes that are more universal between the practice of semiotic reading, symbolism and interpretation. Film semiotics and narration are a juxtaposition of moving visual texts and sound to create meaning through film codes and social conventions to form an educational narrative that makes the medium effective for learning and teaching. The aim of this article is to explore and set precedence for more creative building-blocks into future research on edutainment cinema. This will further stimulate and benefit innovative entrepreneurial filmmaking and future academic research.

Keywords: cinema, edutainment, epistemology, multimodality, semiotics, structuralism

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Authors: Tuong Thi Van Thuy, Dao Van Toan, Nguyen Duc Phuc

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Mesenchymal stem cells (MSCs) were discovered in the 1970s with their unique properties of differentiation, immunomodulation, multiple secreting, and homing factors to injured organs. MSC-based therapies have emerged as a promising strategy for various diseases such as cancer, tissue regeneration, or immunologic/inflammatory-related diseases. This study evaluated the clinical application of MSCs for cancer therapy in trials registered on Clinical Trial as of July 2022. The results showed 40 clinical trials used MSCs in various cancer conditions. 62% of trials used MSCs for therapeutic purposes to minimize the side effects of cancer treatment. Besides, 38% of trials were focused on using MSCs as a therapeutic agent to treat cancer directly. Most trials (38/40) are ongoing phase I/II, and 2 are entering phase III. 84% of trials used allogeneic MSCs compared with 13% using autologous sources and 3% using both. 25/40 trials showed participants received a single dose of MSCs, while the most times were 12 times in a pancreatic cancer treatment trial. Conclusion: MSC-based therapy for cancer in clinical trials should be applied to (1) minimize the side effects of oncological treatments and (2) directly affect the tumor via selectively delivering anti-cancer payloads to tumor cells. Allogeneic MSCs are a priority selected in clinical cancer therapy.

Keywords: mesenchymal stem cells, MSC-based therapy, cancer condition, cancer treatment, clinical trials

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Authors: Behdokht Mall-Amiri, Sara Farzaminejad

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The purpose of the present study was to discover which of the two writing activities, a self-assessment questioner or a critical thinking skills handout, is more effective on Iranian EFL learners’ writing ability. To fulfill the purpose of the study, a sample of 120 undergraduate students of English SAT for a standardized sample of PET. Eighty-two students whose scores fell one standard deviation above and below the sample mean were selected and randomly divided into two equal groups. One group practiced self-assessment and the other group practiced critical thinking skills while they were learning process writing. A writing posttest was finally administered to the students in both groups and the mean rank scores were compared by t-test. The result led to the rejection of the null hypothesis, indicating that practicing critical thinking skills had a significantly higher effect on the writing ability. The implications of the study for students and teachers as well as course book designers are discussed.

Keywords: writing ability, process writing, critical thinking skills, self-assessment

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Authors: Saheed A. Gbadegeshin

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Lean Commercialization (LC) is a transformation of new technologies and knowledge to products and services through application of lean/agile principle. This principle focuses on how resources can be minimized on development, manufacturing, and marketing new products/services, which can be accepted by customers. To understand how the LC has been employed by the technology-based companies, a case study approach was employed by interviewing the founders, observing their high technologies, and interviewing the commercialization experts. Two serial entrepreneurs were interviewed in 2012, and their commercialized technologies were monitored from 2012 till 2016. Some results were collected, but to validate the commercialization strategies of these entrepreneurs, four commercialization experts were interviewed in 2017. Initial results, observation notes, and experts’ opinions were analyzed qualitatively. The final findings showed that the entrepreneurs applied the LC unknowingly, and the experts were aware of the LC. Similarly, the entrepreneurs used the LC due to the financial constraints, and their need for success. Additionally, their commercialization practices revealed that LC appeared to be one of their commercialization strategies. Thus, their practices were analyzed, and a framework was developed. Furthermore, the experts noted that LC is a new dawn, which technologists and scientists need to consider for their high technology commercialization. This article contributes to the theory and practice of commercialization. Theoretically, the framework adds value to the commercialization discussion. And, practically the framework can be used by the technology entrepreneurs (technologists and scientists), technology-based enterprises, and technology entrepreneurship educators as a guide in their commercialization adventures.

Keywords: lean commercialization, high technologies, lean start-up, technology-based companies

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Authors: Nicolas Zufferey

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Ant algorithms are well-known metaheuristics which have been widely used since two decades. In most of the literature, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. Generally, at each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (also called the visibility, the short term profit or the heuristic information) and the trail system (central memory which collects historical information of the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed, namely SMART (for Solution Methods with Ants Running by Types). It relies on the use of different population of ants, where each population has its own personality.

Keywords: ant algorithms, evolutionary procedures, metaheuristics, optimization, population-based methods

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Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa

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In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.

Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis

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Authors: Gokhan Sir, Muhammed Ergun, Onder Balioglu

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Nowadays, laundry dryers containing heaters and heat pumps are used to provide fast and efficient drying. In this system, as the drying capacity changes, the sensible and latent heat transfer rate in the evaporator changes. Therefore, the drying time measured for the unit capacity increases as the drying capacity decreases. The objective of this study is to investigate the evaporator efficiency according to load amount and textile type in hybrid heat pump dryers. Air side flow rate and system temperatures (air side and refrigeration side) were monitored instantly, and the specific moisture extraction rate (SMER), evaporator efficiency, and heat transfer mechanism between the textile and hybrid heat pump system were examined. Evaporator efficiency of heat pump dryers for cotton and synthetic based textile types in load amounts of 2, 5, 8 and 10 kg were investigated experimentally. As a result, the maximum evaporator efficiency (%72) was obtained in drying cotton and synthetic based textiles with a capacity of 5 kg; the minimum evaporator efficiency (%40) was obtained in drying cotton and synthetic based textiles with a capacity of 2 kg. The experimental study also reveals that capacity-dependent flow rate changes are the major factor for evaporator efficiency.

Keywords: evaporator, heat pump, hybrid, laundry dryer, textile

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Authors: Xuerui Niu, Bolin Wang, Xinchuang Zhang, Xiaohua Ma, Bin Hou, Ling Yang

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The application of discrete GaN-based power switches requires the collaboration of silicon-based peripheral circuit structures. However, the packages and interconnection between the Si and GaN devices can introduce parasitic effects to the circuit, which has great impacts on GaN power transistors. GaN-based monolithic power integration technology is an emerging solution which can improve the stability of circuits and allow the GaN-based devices to achieve more functions. Complementary logic circuits consisting of GaN-based E-mode p-channel heterostructure field-effect transistors (p-HFETs) and E-mode n-channel HEMTs can be served as the gate drivers. E-mode p-HFETs with recessed gate have attracted increasing interest because of the low leakage current and large gate swing. However, they suffer from a poor interface between the gate dielectric and polarized nitride layers. The reliability of p-HFETs is analyzed and discussed in this work. In circuit applications, the inverter is always operated with dynamic gate voltage (VGS) rather than a constant VGS. Therefore, dynamic electrical stress has been simulated to resemble the operation conditions for E-mode p-HFETs. The dynamic electrical stress condition is as follows. VGS is a square waveform switching from -5 V to 0 V, VDS is fixed, and the source grounded. The frequency of the square waveform is 100kHz with the rising/falling time of 100 ns and duty ratio of 50%. The effective stress time is 1000s. A number of stress tests are carried out. The stress was briefly interrupted to measure the linear IDS-VGS, saturation IDS-VGS, As VGS switches from -5 V to 0 V and VDS = 0 V, devices are under negative-bias-instability (NBI) condition. Holes are trapped at the interface of oxide layer and GaN channel layer, which results in the reduction of VTH. The negative shift of VTH is serious at the first 10s and then changes slightly with the following stress time. However, different phenomenon is observed when VDS reduces to -5V. VTH shifts negatively during stress condition, and the variation in VTH increases with time, which is different from that when VDS is 0V. Two mechanisms exists in this condition. On the one hand, the electric field in the gate region is influenced by the drain voltage, so that the trapping behavior of holes in the gate region changes. The impact of the gate voltage is weakened. On the other hand, large drain voltage can induce the hot holes generation and lead to serious hot carrier stress (HCS) degradation with time. The poor-quality interface between the oxide layer and GaN channel layer at the gate region makes a major contribution to the high-density interface traps, which will greatly influence the reliability of devices. These results emphasize that the improved etching and pretreatment processes needs to be developed so that high-performance GaN complementary logics with enhanced stability can be achieved.

Keywords: GaN-based E-mode p-HFETs, dynamic electric stress, threshold voltage, monolithic power integration technology

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Authors: Asiya Mahtab, Sushama Talegaonkar

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The research is aimed at developing targeted lipid-based nanocarrier systems of chondroitin sulfate (CS) to deliver an antirheumatic drug to the inflammatory site in arthritic paw. Lipid-based nanoparticle (TEF-lipo) was prepared by using a thin-film hydration method. The coating of prepared drug-loaded nanoparticles was done by the ionic interaction mechanism. TEF-lipo and CS-coated lipid nanoparticle (CS-lipo) were characterized for mean droplet size, zeta potential, and surface morphology. TEF-lipo and CS-lipo were further subjected to in vitro cell line studies on RAW 264.7 murine macrophage, U937, and MG 63 cell lines. The pharmacodynamic study was performed to establish the effectiveness of the prepared lipid-based conventional and targeted nanoparticles in comparison to pure drugs. Droplet size and zeta potential of TEF-lipo were found to be 128. 92 ± 5.42 nm and +12.6 ± 1.2 mV. It was observed that after the coating of TEF-lipo with CS, particle size increased to 155.6± 2.12 nm and zeta potential changed to -10.2± 1.4mV. Transmission electron microscopic analysis revealed that the nanovesicles were uniformly dispersed and detached from each other. Formulations followed sustained release pattern up to 24 h. Results of cell line studies ind icated that CS-lipo formulation showed the highest cytotoxic potential, thereby proving its enhanced ability to kill the RAW 264.7 murine macrophage and U937 cells when compared with other formulations. It is clear from our in vivo pharmacodynamic results that targeted nanocarriers had a higher inhibitory effect on arthritis progression than nontargeted nanocarriers or free drugs. Results demonstrate that this approach will provide effective treatment for rheumatoid arthritis, and CS served as a potential prophylactic against the advancement of cartilage degeneration.

Keywords: adjuvant induced arthritis, chondroitin sulfate, rheumatoid arthritis, teriflunomide

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Julia Wimmers Klick

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Interprofessional Education (IPE) is widely recognized as a valuable approach in healthcare education, despite the challenges it presents. This study explores IP surface anatomy lab sessions, with a focus on fostering trust and collaboration among healthcare students. The research is conducted within the context of rural healthcare settings in British Columbia (BC), where a medical school and a physical therapy (PT) program operate under the Faculty of Medicine at the University of British Columbia (UBC). While IPE sessions addressing soft skills have been implemented, the integration of hard skills, such as Anatomy, remains limited. To address this gap, a pilot feasibility study was conducted with a positive outcome, a follow-up study involved these IPE sessions aimed at exploring the influence of bonding and trust between medical and PT students. Data were collected through focus groups comprising participating students and faculty members, and a structured SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis was conducted. The IPE sessions, 3 in total, consisted of a 2.5-hour lab on surface anatomy, where PT students took on the teaching role, and medical students were newly exposed to surface anatomy. The focus of the study was on the relationship-building process and trust development between the two student groups, rather than assessing the acquisition of surface anatomy skills. Results indicated that the surface anatomy lab served as a suitable tool for the application and learning of soft skills. Faculty members observed positive outcomes, including productive interaction between students, reversed hierarchy with PT students teaching medical students, practicing active listening skills, and using a mutual language of anatomy. Notably, there was no grade assessment or external pressure to perform. The students also reported an overall positive experience; however, the specific impact on the development of soft skill competencies could not be definitively determined. Participants expressed a sense of feeling respected, welcomed, and included, all of which contributed to feeling safe. Within the small group environment, students experienced becoming a part of a community of healthcare providers that bonded over a shared interest in health professions education. They enjoyed sharing diverse experiences related to learning across their varied contexts, without fear of judgment and reprisal that were often intimidating in single professional contexts. During a joint Christmas party for both cohorts, faculty members observed students mingling, laughing, and forming bonds. This emphasized the importance of early bonding and trust development among healthcare colleagues, particularly in rural settings. In conclusion, the findings emphasize the potential of IPE sessions to enhance trust and collaboration among healthcare students, with implications for their future professional lives in rural settings. Early bonding and trust development are crucial in rural settings, where healthcare professionals often rely on each other. Future research should continue to explore the impact of content-concentrated IPE on the development of soft skill competencies.

Keywords: interprofessional education, rural healthcare settings, trust, surface anatomy

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Qiang Zhang, Xiaojian Hu

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In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

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Authors: Akram Rasheed

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Background: Simulation in the health care field has been increasingly used over the last years in the training of resuscitation and life support practices. It has shown the advantage of improving the decision-making and technical skills through deliberate practice and return demonstration. Local Problem: This article reports on the integration of simulation-based training (SBT) in the training program about proper team dynamics and leadership skills during cardiopulmonary resuscitation (CPR) in the intensive care unit (ICU). Method and Intervention: Training of 180 critical care nurses was conducted using SBT between 1st January and 30th 2020. We had conducted 15 workshops, with the integration of SBT using high fidelity manikins and using demonstration and return-demonstration approach to train the nursing staff about proper team dynamics and leadership skills during CPR. Results: After completing the SBT session, all 180 nurses completed the evaluation form. The majority of evaluation items were rated over 95% for the effectiveness of the education; four items were less than 95% (88–94%). Lower rated items considered training and practice time, improved competency, and commitment to apply to learn. The team dynamics SBT was evaluated as an effective means to improve team dynamics and leadership skills during CPR in the intensive care unit (ICU). Conclusion: The use of simulation-based training to improve team dynamics and leadership skills is an effective method for better patient management during CPR. Besides skills competency, closed-loop communication, clear messages, clear roles, and assignments, knowing one’s limitations, knowledge sharing, constructive interventions, re-evaluating and summarizing, and mutual respect are all important concepts that should be considered during team dynamics training. However, participants reported the need for a repeated practice opportunity to build competency.

Keywords: cardiopulmonary resuscitation, high fidelity manikins, simulation-based training, team dynamics

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

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Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

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The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity

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Authors: Othmane Essahili, Mohamed Ilsouk, Carine Duhayon, Omar Moudam

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Due to their excellent and promising properties, a great deal of attention has recently been devoted to luminescent materials, particularly those utilizing rare earth elements. These materials play an essential role in low-cost energy conversion technology applications, such as luminescent solar concentrators (LSCs). They also have potential applications in Agri-PV systems and smart building windows. Luminescent materials based on europium (III) complexes are known for their high luminescence efficiency, long fluorescence lifetimes, and sharp emission bands. However, they present certain drawbacks related to their limited absorption capacity due to the forbidden 4f-4f electronic transitions. To address these drawbacks, using β-diketonate ligands as sensitizers appears as a promising solution to enhance luminescence intensity through the antenna effect, where the ligand's excited energy is transferred to the europium ions. In this study, we synthesized β-diketonate-based europium complexes with phenanthroline derivatives, modified with various methyl groups, to examine their effects on the complexes' stability in poly(methyl methacrylate) (PMMA) films. Our findings reveal that these complexes exhibit remarkable red emission and high photoluminescence quantum yield. Stability tests under different conditions for 1200 hours showed that complexes with a higher number of methyl substitutions offer improved photoluminescent stability and resistance to degradation, particularly in outdoor settings. This research underscores the potential of chemically tuned phenanthroline ligands in developing stable, efficient luminescent materials for future optoelectronic devices, including efficient and durable LSCs.

Keywords: luminescent materials, photochemistry, luminescent solar concentrators, β-diketonate-based europium complexes

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Authors: V. Verma, Syed Riyaz-ul-Hassan

Abstract:

Staphylococcus aureus is one of the most commonly found pathogenic bacteria and is hard to eliminate from the human environment. It is responsible for many nosocomial infections, besides being the main causative agent of food intoxication by virtue of its variety of enterotoxins. Routine detection of S. aureus in food is usually carried out by traditional methods based on morphological and biochemical characterization. These methods are time-consuming and tedious. In addition, misclassifications with automated susceptibility testing systems or commercially available latex agglutination kits have been reported by several workers. Consequently, there is a need for methods to specifically discriminate S. aureus from other staphylococci as quickly as possible. Data on protocols developed using molecular means like PCR technology will be presented for rapid and specific detection of this pathogen in food, clinical and environmental samples, especially milk.

Keywords: food Pathogens, PCR technology, rapid and specific detection, staphylococcus aureus

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Authors: B. Chandra

Abstract:

In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Erika Ruiz, Nestor Ortiz

Abstract:

Lean philosophy has evolved over time and has been implemented both in manufacturing and services, more recently lean has been integrated in the companies of the health sector. Currently it is important to understand the successful way to implement this philosophy and try to identify barriers and enablers to the sustainability of lean healthcare. The main purpose of this research is to identify the barriers and enablers in the implementation of Lean Healthcare based on case studies of Colombian healthcare centers. In order to do so, we conducted semi-structured interviews based on a maturity model. The main results indicate that the success of Lean implementation depends on its adaptation to contextual factors. In addition, in the Colombian context were identified new factors such as organizational culture, management models, integration of the care and administrative departments and triple helix relationship.

Keywords: barriers, enablers, implementation, lean healthcare, sustainability

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Authors: Orisakwe Chimuanya Favour Israel

Abstract:

In a world filled with the products of scientific inquiry, scientific literacy has become a necessity for everyone because it is indispensable to achieving technological development of any nation. Everyone needs to use scientific information to make choices that arise every day. Everyone needs to be able to engage intelligently in public discourse and debate about important issues that involves science and technology. And everyone deserves to share in the excitement and personal fulfillment that can come from -understanding and learning about the natural world. No doubt that industrialized countries have, through their control of science and technology education, developed the potential to increase production, and to improve the standard of living of their people. The main thrust of this paper therefore, is to present an overview of science education, strategies for achieving application of science in national development, such as teaching science with the right spirit of inquiry. Also, the paper discussed three research models that can help in national development and suggests the best out of the three which is more realistic for a developing country like ours (Nigeria) to follow for a sustainable national development and finally suggests some key ways of solving problems of development.

Keywords: scientific inquiry, scientific literacy, strategies, sustainable national development

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Authors: Mohammadhossein Moghimi, Robert Stone, Pia Rotshtein

Abstract:

Recording psychological and physiological correlates of human performance within virtual environments and interpreting their impacts on human engagement, ‘immersion’ and related emotional or ‘effective’ states is both academically and technologically challenging. By exposing participants to an effective, real-time (game-like) virtual environment, designed and evaluated in an earlier study, a psychophysiological database containing the EEG, GSR and Heart Rate of 30 male and female gamers, exposed to 10 games, was constructed. Some 174 features were subsequently identified and extracted from a number of windows, with 28 different timing lengths (e.g. 2, 3, 5, etc. seconds). After reducing the number of features to 30, using a feature selection technique, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) methods were subsequently employed for the classification process. The classifiers categorised the psychophysiological database into four effective clusters (defined based on a 3-dimensional space – valence, arousal and dominance) and eight emotion labels (relaxed, content, happy, excited, angry, afraid, sad, and bored). The KNN and SVM classifiers achieved average cross-validation accuracies of 97.01% (±1.3%) and 92.84% (±3.67%), respectively. However, no significant differences were found in the classification process based on effective clusters or emotion labels.

Keywords: virtual reality, effective computing, effective VR, emotion-based effective physiological database

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

Abstract:

Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

Procedia PDF Downloads 162