Search results for: machine learning tools and techniques

Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

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Authors: Tamar Bikashvili, Tamar Lordkipanidze, Ilia Lazrishvili

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Heavy metals remain one of serious environmental problems due to their toxic effects. The effect of arsenic and manganese compounds on rat behavior and neuromorphology was studied. Wistar rats were assigned to four groups: rats in control group were given regular water, while rats in other groups drank water with final manganese concentration of 10 mg/L (group A), 20 mg/L (group B) and final arsenic concentration 68 mg/L (group C), respectively, for a month. To study exploratory and anxiety behavior and also to evaluate aggressive performance in “home cage” rats were tested in “Open Field” and to estimate learning and memory status multi-branched maze was used. Statistically significant increase of motor and oriental-searching activity in experimental groups was revealed by an open field test, which was expressed in increase of number of lines crossed, rearing and hole reflexes. Obtained results indicated the suppression of fear in rats exposed to manganese. Specifically, this was estimated by the frequency of getting to the central part of the open field. Experiments revealed that 30-day exposure to 10 mg/ml manganese did not stimulate aggressive behavior in rats, while exposure to the higher dose (20 mg/ml), 37% of initially non-aggressive animals manifested aggressive behavior. Furthermore, 25% of rats were extremely aggressive. Obtained data support the hypothesis that excess manganese in the body is one of the immediate causes of enhancement of interspecific predatory aggressive and violent behavior in rats. It was also discovered that manganese intoxication produces non-reversible severe learning disability and insignificant, reversible memory disturbances. Studies of rodents exposed to arsenic also revealed changes in the learning process. As it is known, the distribution of metal ions differs in various brain regions. The principle manganese accumulation was observed in the hippocampus and in the neocortex, while arsenic was predominantly accumulated in nucleus accumbens, striatum, and cortex. These brain regions play an important role in the regulation of emotional state and motor activity. Histopathological analyzes of brain sections illustrated two morphologically distinct altered phenotypes of neurons: (1) shrunk cells with indications of apoptosis - nucleus and cytoplasm were very difficult to be distinguished, the integrity of neuronal cytoplasm was not disturbed; and (2) swollen cells - with indications of necrosis. Pyknotic nucleus, plasma membrane disruption and cytoplasmic vacuoles were observed in swollen neurons and they were surrounded by activated gliocytes. It’s worth to mention that in the cortex the majority of damaged neurons were apoptotic while in subcortical nuclei –neurons were mainly necrotic. Ultrastructural analyses demonstrated that all cell types in the cortex and the nucleus caudatus represent destructed mitochondria, widened neurons’ vacuolar system profiles, increased number of lysosomes and degeneration of axonal endings.

Keywords: arsenic, manganese, behavior, learning, neuron

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Paul B Stone, Subhashini Ganapathy, Mary E. Fendley, Layla Akilan

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As notifications become more common through mobile devices, it is important to understand the impact of wearable devices on the improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer-simulated petrochemical system. The key research question was to determine how using the information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch, and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.

Keywords: computer applications, haptic feedback, petrochemical systems, situational awareness, wearable technology

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Authors: Nawras Kurzom, Avi Mendelsohn

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The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

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Authors: Yi Yang, Jiasong Sun

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Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

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Authors: Salman Ahmad, Muhammad Aown Sammar Raza, Muhammad Farrukh Saleem, Rashid Iqbal, Muhammad Saqlain Zaheer, Muhammad Usman Aslam, Imran Haider, Muhammad Adnan Nazar, Muhammad Ali

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Among the various abiotic stresses, drought stress is one of the most challenging for field crops. Wheat is one of the major staple food of the world, which is highly affected by water deficit stress in the current scenario of climate change. In order to ensure food security by depleting water resources, there is an urgent need to adopt technologies which result in sufficient crop yield with less water consumption. Mulching and partial rootzone drying (PRD) are two important management techniques used for water conservation and to mitigate the negative impacts of drought. The experiment was conducted to screen out the best-suited mulch for wheat under PRD system. Two water application techniques (I1= full irrigation I2= PRD irrigation) and four mulch treatments (M0= un-mulched, M1= black plastic mulch, M2= wheat straw mulch and M4= cotton sticks mulch) were conducted in completely randomized design with four replications. The treatment, black plastic mulch was performed the best than other mulch treatments. For irrigation levels, higher values of growth, physiological and water-related parameters were recorded in control treatment while, quality traits and enzymatic activities were higher under partial root zone drying. The current study concluded that adverse effects of drought on wheat can be significantly mitigated by using mulches but black plastic mulch was best suited for partial rootzone drying irrigation system in wheat.

Keywords: antioxidants, leaf water relations, Mulches, osmolytes, partial root zone drying, photosynthesis

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Authors: S. Nagheli, N. Samani, D. A. Barry

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In this paper, the velocity potential and stream function of capture zone for a well field in an aquifer bounded by two parallel streams with or without a uniform regional flow of any directions are presented. The well field includes any number of extraction or injection wells or a combination of both types with any pumping rates. To delineate the capture envelope, the potential and streamlines equations are derived by conformal mapping method. This method can help us to release constrains of other methods. The equations can be applied as useful tools to design in-situ groundwater remediation systems, to evaluate the surface–subsurface water interaction and to manage the water resources.

Keywords: complex potential, conformal mapping, image well theory, Laplace’s equation, superposition principle

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Authors: Ledeza Jordan Babiano

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Translating statements into mathematical notations is one of the processes in word problem-solving. However, based on the literature, students still have difficulties with this skill. The purpose of this study was to investigate the translation errors of the students when they translate algebraic word problems into mathematical structures and locate the errors via the lens of the Translation-Verification Model. Moreover, this qualitative research study employed content analysis. During the data-gathering process, the students were asked to answer a six-item algebra word problem questionnaire, and their answers were analyzed by experts through blind coding using the Translation-Verification Model to determine their translation errors. After this, a focus group discussion was conducted, and the data gathered was analyzed through thematic analysis to determine the causes of the students’ translation errors. It was found out that students’ prevalent error in translation was the interpretation error, which was situated in the Attribute construct. The emerging themes during the FGD were: (1) The procedure of translation is strategically incorrect; (2) Lack of comprehension; (3) Algebra concepts related to difficulty; (4) Lack of spatial skills; (5) Unprepared for independent learning; and (6) The content of the problem is developmentally inappropriate. These themes boiled down to the major concept of independent learning preparedness in solving mathematical problems. This concept has subcomponents, which include contextual and conceptual factors in translation. Consequently, the results provided implications for instructors and professors in Mathematics to innovate their teaching pedagogies and strategies to address translation gaps among students.

Keywords: mathematical structure, algebra word problems, translation, errors

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Authors: Elizabeth McDonald, Sarah Larkin, Bunmi Malu-Aduli

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Medical schools enroll high achieving students who demonstrate firm intentions to be a professional doctor. Some medical students experience academic difficulty and underperformance that creates negative impacts on students, medical education faculties, clinical training institutions and healthcare consumers. A prevailing deficit view of resultant wide-ranging challenges can offer a limited perspective that narrows processes for student supportive guidance. It is also largely unknown if there are any long-term influences on junior doctors who underperformed in training. This qualitative study offered an alternative viewpoint. Through guiding research questions, it aimed to explore medical student and junior doctor lived experiences of academic difficulty, and their perceptions of inner character strengths developments that enabled short, and long-term positive outcomes. A theoretical framework of epistemological constructivism with a Strengths-Based theoretical stance, sustained Reflexive Thematic Analysis (RTA) and Interpretive Phenomenological Analysis (IPA) phenomenologically based analysis and interpretation methods. Semi-structured, in-person interviews were conducted with 18 medical students and eight junior doctors from two Australian medical schools. In-depth, iterative exploration of meanings within transcripts and cross referencing techniques, produced four key themed findings, and 12 sub-themes. Findings demonstrated that struggling students could rise above pervasive feelings of despair and decreased confidence after underperformance or failure. A strong sense of purpose with focused determination seemed to empower student confidence and increase self-efficacy. Other confidence-boosting intrapersonal character traits like motivation and perseverance fostered academic success to graduation. Subsequent positive gains included improved knowledge and clinical skills for safe practice; enhanced empathetic understanding and compassion, that produced long-term benefits linked to effective patient interactions with satisfying clinical experiences. Doctors indicated that lessons learned from undergraduate underperformance influenced postgraduate studies related to career progression. Generally, participants felt a general satisfaction with current support initiatives at both universities, and expected contrasting responses to interview questions could not be found. Participant recommendations for future management of struggling students centered on student-targeted medical education and clinical training environments, that adhered to concepts aligned with educational psychological safety in an atmosphere of trust. This study challenges the deficit based discussions predominant in relevant literature and substitutes a positive viewpoint highlighting beneficial outcomes. Medical educators, curricula developers and remediation programmers could take note of the power of enhanced, inherent student strengths to ameliorate the negative affects of academic difficulty. Practical implications offer medical education and other healthcare disciplines, information about the value of supportive learning environments and resilience training, to improve outcomes for struggling students and junior doctors. Such a model would also move the onus of failure from just the student to a more collegial, positive interplay between educators and students. Thus, this knowledge can be utilised to reference processes in support of a psychologically safe, holistic learning environments that addresses the individual needs of all medical students, and especially those who struggle

Keywords: academic difficulty, medical student, motivation, resilience, strengths

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Authors: Per Blomqvist

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The overall aim of this study is to highlight how the degree project-course in teacher education has developed over time at Swedish universities, above all regarding changes in the formative assessment practices in relation to student's opportunities to take part in writing processes that can develop both their independent critical thinking, subject knowledge, and academic writing skills. Theoretically, the study is based on deliberative and transformative perspectives of teaching academic writing in higher education. The deliberative perspective is motivated by the fact that it is the universities and their departments' responsibility to give the students opportunities to develop their academic writing skills, while there is little guidance on how this can be implemented. The transformative perspective is motivated by the fact that education needs to be adapted to the student's prior knowledge and developed in relation to the student group. Given the academisation of education and the new student groups, this is a necessity. The empirical data consists of video recordings of teacher groups' conversations at three Swedish universities. The conversations were conducted as so-called collective remembering interviews, a method to stimulate the participants' memory through social interaction, and focused on addressing issues on how the degree project-course in teacher education has changed over time. Topic analysis was used to analyze the conversations in order to identify common descriptions and expressions among the teachers. The result highlights great similarities in how the degree project-course has changed over time, both from a deliberative and a transformative perspective. The course is characterized by a “strong framing,” where the teachers have great control over the work through detailed instructions for the writing process and detailed templates for the text. This is justified by the fact that the education has been adapted based on the student teachers' lack of prior subject knowledge. The strong framing places high demands on continuous discussions between teachers about, for example, which tools the students have with them and which linguistic and textual tools are offered in the education. The teachers describe that such governance often leads to conflicts between teachers from different departments because reading and writing are always part of cultural contexts and are linked to different knowledge, traditions, and values. The problem that is made visible in this study raises questions about how students' opportunities to develop independence and make critical judgments in academic writing are affected if the writing becomes too controlled and if passing students becomes the main goal of education.

Keywords: formative assessment, academic writing, degree project, higher education, deliberative perspective, transformative perspective

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Authors: Tiffany Wicks

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Queer patients can face issues with self-advocating due to the factors of implicit provider bias, lack of tools and resources to self-advocate, and lack of comfortability in self-advocating based on prior experiences. In this study, five participants who identify as queer discussed their interactions with their healthcare providers. This exploratory study revealed that there is a need for healthcare provider education to reduce implicit bias and judgments about queer patients. There is also an important need for peer advocates in order to further inform healthcare promotion and decision-making before and during provider visits in an effort for a better outcome. Through this exploration, queer patients voiced their experiences and concerns to inform a need for change in healthcare collaboration between providers and patients in the queer community.

Keywords: queer, LGBT, patient, self-advocacy, healthcare

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Authors: Tomasz Robert Kuczerski

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The high complexity of the algorithm of the autonomous tandem detonator system creates an optimization problem due to the parallel operation of several machine states of the system. Many years of experience and classic analyses have led to a partially optimized model. Limitations on the energy resources of this class of autonomous systems make it necessary to search for more effective methods of optimisation. The use of the Quantum Approximate Optimization Algorithm (QAOA) in these studies shows the most promising results. With the help of multiple evaluations of several qubit quantum circuits, proper results of variable parameter optimization were obtained. In addition, it was observed that the increase in the number of assessments does not result in further efficient growth due to the increasing complexity of optimising variables. The tests confirmed the effectiveness of the QAOA optimization method.

Keywords: algorithm analysis, autonomous system, quantum optimization, tandem detonator

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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This paper proposes a method to optimize the layout of an emergency department (ED) based on real executions of care processes by considering several planning objectives simultaneously. Recently, demand for healthcare services has been dramatically increased. As the demand for healthcare services increases, so do the need for new healthcare buildings as well as the need for redesign and renovating existing ones. The importance of implementation of a standard set of engineering facilities planning and design techniques has been already proved in both manufacturing and service industry with many significant functional efficiencies. However, high complexity of care processes remains a major challenge to apply these methods in healthcare environments. Process mining techniques applied in this study to tackle the problem of complexity and to enhance care process analysis. Process related information such as clinical pathways extracted from the information system of an ED. A 0-1 goal programming approach is then proposed to find a single layout that simultaneously satisfies several goals. The proposed model solved by optimization software CPLEX 12. The solution reached using the proposed method has 42.2% improvement in terms of walking distance of normal patients and 47.6% improvement in walking distance of critical patients at minimum cost of relocation. It has been observed that lots of patients must unnecessarily walk long distances during their visit to the emergency department because of an inefficient design. A carefully designed layout can significantly decrease patient walking distance and related complications.

Keywords: healthcare operation management, goal programming, facility layout problem, process mining, clinical processes

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Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

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Authors: Tony R. Walker, N. Devin MacAskill, Andrew Thalhiemer

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Sydney Harbour, Nova Scotia, Canada has long been subject to effluent and atmospheric inputs of contaminants, including thousands of tons of PAHs from a large coking and steel plant which operated in Sydney for nearly a century. Contaminants comprised of coal tar residues which were discharged from coking ovens into a small tidal tributary, which became known as the Sydney Tar Ponds (STPs), and subsequently discharged into Sydney Harbour. An Environmental Impact Statement concluded that mobilization of contaminated sediments posed unacceptable ecological risks, therefore immobilizing contaminants in the STPs using solidification and stabilization was identified as a primary source control remediation option to mitigate against continued transport of contaminated sediments from the STPs into Sydney Harbour. Recent developments in contaminant mass flux techniques focus on understanding “mobile” vs. “immobile” contaminants at remediation sites. Forensic source evaluations are also increasingly used for understanding origins of PAH contaminants in soils or sediments. Flux and forensic source evaluation-informed remediation decision-making uses this information to develop remediation end point goals aimed at reducing off-site exposure and managing potential ecological risk. This study included reviews of previous flux studies, calculating current mass flux estimates and a forensic assessment using PAH fingerprint techniques, during remediation of one of Canada’s most polluted sites at the STPs. Historically, the STPs was thought to be the major source of PAH contamination in Sydney Harbour with estimated discharges of nearly 800 kg/year of PAHs. However, during three years of remediation monitoring only 17-97 kg/year of PAHs were discharged from the STPs, which was also corroborated by an independent PAH flux study during the first year of remediation which estimated 119 kg/year. The estimated mass efflux of PAHs from the STPs during remediation was in stark contrast to ~2000 kg loading thought necessary to cause a short term increase in harbour sediment PAH concentrations. These mass flux estimates during remediation were also between three to eight times lower than PAHs discharged from the STPs a decade prior to remediation, when at the same time, government studies demonstrated on-going reduction in PAH concentrations in harbour sediments. Flux results were also corroborated using forensic source evaluations using PAH fingerprint techniques which found a common source of PAHs for urban soils, marine and aquatic sediments in and around Sydney. Coal combustion (from historical coking) and coal dust transshipment (from current coal transshipment facilities), are likely the principal source of PAHs in these media and not migration of PAH laden sediments from the STPs during a large scale remediation project.

Keywords: contaminated sediment, mass flux, forensic source evaluations, remediation

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Authors: Nicole A. Alford

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The study of online graduate education started just 30 years ago, with the first online graduate program in the 1990s. Institutions are looking for ways to increase retention and support the needs of students with the rapid expansion of online higher education due to the global pandemic. Online education provides access and opportunities to those who otherwise would be unable to pursue an advanced degree for logistical reasons. Thus, the objective of the critical literature review is to survey current research of student experiences given the expanding role of online doctoral programs. The guiding research questions are: What are the personal, professional, and student life practices of graduate students who enrolled in a fully online university doctoral program or course? and How do graduate students who enrolled in a fully online doctoral program or course describe the factors that contributed to their continued study? The systematic literature review was conducted employing a variety of databases to locate articles using key Boolean terms and synonyms within three categories of the e-learning, doctoral education, and student perspectives. Inclusion criteria for the literature review consisted of empirical peer-reviewed studies with original data sources that focused on doctoral programs and courses within a fully online environment and centered around student experiences. A total of 16 articles were selected based on the inclusion criteria and systemically analyzed through coding using the Boote and Beile criteria. Major findings suggest that doctoral students face stressors related to social and emotional wellbeing in the online environment. A lack of social connection, isolation, and burnout were the main challenges experienced by students. Students found support from their colleagues, advisors, and faculty to persist. Communities and cohorts of online doctoral students were found to guard against these challenges. Moreover, in the methods section of the articles, there was a lack of specificity related to student demographics, general student information, and insufficient detail about the online doctoral program. Additionally, descriptions regarding the experiences of cohorts and communities in the online environment were vague and not easily replicable with the given details. This literature review reveals that doctoral students face social and emotional challenges related to isolation and the rigor of the academic process and lean on others for support to continue in their studies. Given the lack of current knowledge about online doctoral students, it proves to be a challenge to identify effective practices and create high-retention doctoral programs in online environments. The paucity of information combined with the dramatic transition to e-learning due to the global pandemic can provide a perfect storm for attrition in these programs. Several higher education institutions have transitioned graduate studies online, thus providing an opportunity for further exploration. Given the new necessity of online learning, this work provides insight into examining current practices in online doctoral programs that have moved to this modality during the pandemic. The significance of the literature review provides a springboard for research into online doctoral programs as the solution to continue advanced education amongst a global pandemic.

Keywords: e-learning, experiences, higher education, literature review

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Authors: Randall E. Osborne

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In a course on International Psychology, 8 theoretical perspectives (Critical Psychology, Liberation Psychology, Post-Modernism, Social Constructivism, Social Identity Theory, Social Reduction Theory, Symbolic Interactionism, and Vygotsky’s Sociocultural Theory) are used as a framework for getting students to understand the concept of and need for Globalization. One of critical psychology's main criticisms of conventional psychology is that it fails to consider or deliberately ignores the way power differences between social classes and groups can impact the mental and physical well-being of individuals or groups of people. Liberation psychology, also known as liberation social psychology or psicología social de la liberación, is an approach to psychological science that aims to understand the psychology of oppressed and impoverished communities by addressing the oppressive sociopolitical structure in which they exist. Postmodernism is largely a reaction to the assumed certainty of scientific, or objective, efforts to explain reality. It stems from a recognition that reality is not simply mirrored in human understanding of it, but rather, is constructed as the mind tries to understand its own particular and personal reality. Lev Vygotsky argued that all cognitive functions originate in, and must therefore be explained as products of social interactions and that learning was not simply the assimilation and accommodation of new knowledge by learners. Social Identity Theory discusses the implications of social identity for human interactions with and assumptions about other people. Social Identification Theory suggests people: (1) categorize—people find it helpful (humans might be perceived as having a need) to place people and objects into categories, (2) identify—people align themselves with groups and gain identity and self-esteem from it, and (3) compare—people compare self to others. Social reductionism argues that all behavior and experiences can be explained simply by the affect of groups on the individual. Symbolic interaction theory focuses attention on the way that people interact through symbols: words, gestures, rules, and roles. Meaning evolves from human their interactions in their environment and with people. Vygotsky’s sociocultural theory of human learning describes learning as a social process and the origination of human intelligence in society or culture. The major theme of Vygotsky’s theoretical framework is that social interaction plays a fundamental role in the development of cognition. This presentation will discuss how these theoretical perspectives are incorporated into a course on International Psychology, a course on the Politics of Hate, and a course on the Psychology of Prejudice, Discrimination and Hate to promote student thinking in a more ‘global’ manner.

Keywords: globalization, international psychology, society and culture, teaching interculturally

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Authors: Ubaid Ur Rahman, Waqar Younas, Sooraj Kumar Chhabira

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Environmentally sustainable building construction has experienced significant growth during the past 10 years at international level. This paper shows that the conceptual framework adopts sustainability techniques in construction to develop environment friendly building called green building. Waste occurs during the different construction phases which causes the environmental problems like, deposition of waste on ground surface creates major problems such as bad smell. It also gives birth to different health diseases and produces toxic waste agent which is specifically responsible for making soil infertile. Old recycled building material is used in the construction of new building. Sustainable construction is economical and saves energy sources. Sustainable construction is the major responsibility of designer and project manager. The designer has to fulfil the client demands while keeping the design environment friendly. Project manager has to deliver and execute sustainable construction according to sustainable design. Steel is the most appropriate sustainable construction material. It is more durable and easily recyclable. Steel occupies less area and has more tensile and compressive strength than concrete, making it a better option for sustainable construction as compared to other building materials. New technology like green roof has made the environment pleasant, and has reduced the construction cost. It minimizes economic, social and environmental issues. This paper presents an overview of research related to the material use of green building and by using this research recommendation are made which can be followed in the construction industry. In this paper, we go through detailed analysis on construction material. By making suitable adjustments to project management practices it is shown that a green building improves the cost efficiency of the project, makes it environmental friendly and also meets future generation demands.

Keywords: sustainable construction, green building, recycled waste material, environment

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Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Adetunji A. Adeyanju., Mathew O. Omeike, Johnson O. Adeniran, Biodun S. Badmus

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In this paper, we discuss certain conditions for uniform asymptotic stability and uniform ultimate boundedness of solutions to some systems of Aizermann-type of differential equations by means of second method of Lyapunov. In achieving our goal, some Lyapunov functions are constructed to serve as basic tools. The stability results in this paper, extend some stability results for some Aizermann-type of differential equations found in literature. Also, we prove some results on uniform boundedness and uniform ultimate boundedness of solutions of systems of equations study.

Keywords: Aizermann, boundedness, first order, Lyapunov function, stability

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Authors: Rafid Doulab

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Elemental Impurities in the Pharmaceuticals industryis are indispensable to ensure pharmaceuticalssafety for 24 elements. Although atomic absorption and inductively coupled plasma are used in the U.S Pharmacopeia and the European Pharmacopoeia, FESEM with energy dispersive spectrometers can be applied as an alternative analysis method for quantitative and qualitative results for a variety of elements without chemical pretreatment, unlike other techniques. This technique characterizes by shortest time, with more less contamination, no reagent consumption, and generation of minimal residue or waste, as well as sample preparations time limiting, with minimal analysis error. Simple dilution for powder or direct analysis for liquid, we analyzed the usefulness of EDS method in testing with field emission scanning electron microscopy (FESEM, SUPRA 55 Carl Zeiss Germany) with an X-ray energy dispersion (XFlash6l10 Bruker Germany). The samples analyzed directly without coating by applied 5µ of known concentrated diluted sample on carbon stub with accelerated voltage according to sample thickness, the result for this spot was in atomic percentage, and by Avogadro converted factor, the final result will be in microgram. Conclusion and recommendation: The conclusion of this study is application of FESEM-EDS in US pharmacopeia and ICH /Q3D guideline to reach a high-precision and accurate method in element impurities analysis of drugs or bulk materials to determine the permitted daily exposure PDE in liquid or solid specimens, and to obtain better results than other techniques, by the way it does not require complex methods or chemicals for digestion, which interfere with the final results with the possibility of to keep the sample at any time for re analysis. The recommendation is to use this technique in pharmacopeia as standard methods like inductively coupled plasma both ICP-AES, ICP-OES, and ICP-MS.

Keywords: pharmacopoeia, FESEM-EDS, element impurities, atomic concentration

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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Authors: Isa Moazen, Ali Nahvi

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Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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Authors: Shyaka Eugene

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The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Lazlo Fauth, Andreas Ligocki

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For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

Procedia PDF Downloads 135

Authors: Anita De Melo

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Today we live in a crucial time of ecological crisis, of environmental catastrophes worldwide, and this scenario is, arrogantly, overlooked by powerful economic forces and their politics. Thus, a critical pedagogy that leads to action and that fosters ecoliteracy, environment education, is now inevitable, and it must become an integral part of the school curriculum across the disciplines, including the social sciences and the humanities. One of the most important contemporary and emerging movement of today is ecopedagogy, a movement that blends theory and ethics towards a curriculum that focus on an environmental education that will promote ecological justice, respect, and care by educating students to become planetary citizens. This paper aims, first, to emphasize the need for discussions and investigations regarding ecoliteracy within our field of teaching foreign languages, which will consider, among others, the of role language in stimulating sustainability, and the role of second language proficiency in fostering positive transnational dialogues conducive to fighting our current planetary crisis. Second, this paper suggests and discusses some critical ecopedagogical practices -- in the form of project-based learning, service-learning and environmental-oriented study abroad programs – apropos to ecoliteracy. These interdisciplinary projects can and should bring students in contact with communities speaking the target language, and such encounter would facilitate cultural exchanges and promote positive language proficiency whilst it would also give students the opportunity to work with finding ideas/projects to fight our current ecological catastrophe.

Keywords: critical pedagogy, ecoliteracy, ecopedagogy, planetary crisis

Procedia PDF Downloads 247

Authors: Abdülcelil Mücahid Zengin, Göksel Şimşek

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Mobile phones are one of the direct marketing tools that can be used to reach todays hard to reach consumers. Mobile phones are very personal devices and they are always carried with the consumer, where ever they go. This creates an opportunity for marketers to create personalized marketing communications messages and send them on the right time and place. This study examines consumer attitudes toward mobile marketing, especially toward SMS marketing. Unlike similar studies, this study does not focus on the young, but includes consumers who are in the 18-70 age range to the field research. According to the results, it has been concluded that most participants think SMS marketing is disturbing. Most important problems with SMS marketing are about getting subscribed to message lists without the permission of the receiver; the high number of messages sent; and the irrelevancy of the message content.

Keywords: direct marketing, mobile phones mobile marketing, sms advertising, sms marketing

Procedia PDF Downloads 344

Authors: Elham Bagheri, Yalda Mohsenzadeh

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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

Procedia PDF Downloads 78