Search results for: real-world learning experiences

Authors: Sabitha Rahim

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In the context of teaching vocabulary of English as Foreign Language (EFL), the confluence of memory and retention is one of the most significant factors in students' language acquisition. The progress of students engaged in foreign language acquisition is often stymied by vocabulary attrition, which leads to learners' lack of confidence and motivation. However, among other factors, little research has investigated the importance of neuroplasticity in Foreign Language acquisition and how underused neural pathways lead to the loss of plasticity, thereby affecting the learners’ vocabulary retention and motivation. This research explored the effect of enhancing vocabulary acquisition of EFL students in the Foundation Year at King Abdulaziz University through various methods and neuroplasticity exercises that reinforced their attention, motivation, and engagement. It analyzed the results to determine if stimulating the brain of EFL learners by various physical and mental activities led to the improvement in short and long term memory in vocabulary retention. The main data collection methods were student surveys, assessment records of teachers, student achievement test results, and students' follow-up interviews. A key implication of this research is for the institutions to consider having multiple varieties of student activities promoting brain plasticity within the classrooms as an effective tool for foreign language acquisition. Building awareness among the faculty and adapting the curriculum to include activities that promote brain plasticity ensures an enhanced learning environment and effective language acquisition in EFL classrooms.

Keywords: language acquisition, neural paths, neuroplasticity, vocabulary attrition

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Authors: Sanjay Ranade

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Traditional film theory assumes the cinema audience in a darkened room where cinema is projected on to a white screen, and the audience suspends their sense of reality. Shifts in audiences due to changes in cultural tastes or trends have been studied for decades. In the past two decades, however, the audience, especially the youth, has shifted to digital media for the consumption of cinema. As a result, not only are audiences watching cinema on different devices, they are also consuming cinema in places and ways never imagined before. Public transport often crowded to the brim with a lot of ambient content, and a variety of workplaces have become sites for cinema viewing. Cinema is watched piecemeal and at different times of the day. Audiences use devices such as mobile phones and tablets to watch cinema. The cinema viewing experience is getting redesigned by the user. The emerging design allows the spectator to not only consume images and narratives but also produce, reproduce, and manipulate existing images and narratives, thereby participating in the process and influencing it. Spectatorship studies stress on the importance of subjectivity when dealing with the structure of the film text and the cultural and psychological implications in the engagement between the spectator and the film text. Indian cinema has been booming and contributing to global movie production significantly. In 2005 film production was 1000 films a year and doubled to 2000 by 2016. Digital technology helped push this growth in 2012. Film studies in India have had a decided Euro-American bias. The studies have chiefly analysed the content for ideological leanings or myth or as reflections of society, societal changes, or articulation of identity or presented retrospectives of directors, actors, music directors, etc. The one factor relegated to the background has been the spectator. If they have been addressed, they are treated as a collective of class or gender. India has a performative tradition going back several centuries. How Indians receive cinema is an important aspect to study with respect to film studies. This exploratory and descriptive study looked at 162 young media students studying cinema at the undergraduate and postgraduate levels. The students, speaking as many as 20 languages amongst them, were drawn from across the country’s media schools. The study looked at nine film societies registered with the Federation of Film Societies of India. A structured questionnaire was made and distributed online through media teachers for the students. The film societies were approached through the regional office of the FFSI in Mumbai. Lastly, group discussions were held in Mumbai with students and teachers of media. A group consisted of between five and twelve student participants, along with one or two teachers. All the respondents looked at themselves as spectators and shared their experiences of spectators of cinema, providing a very rich insight into Indian conditions of viewing cinema and challenges for cinema ahead.

Keywords: audience, digital, film studies, reception, reception spectatorship

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Authors: Olubiyi Johnson Ezekiel

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Basic science curriculum is an on-going effort towards developing the potential of manner to produce individuals in a holistic and integrated person, who are intellectually, spiritually, emotionally and physically balanced and harmonious. The main focus of this study is to determine the relationship between students’ achievement in junior school certificate examination (JSCE) and senior school basic science achievement test (SSBSAT) on the basis of all the components of basic science. The study employed the descriptive research of the survey type and utilized junior school certificate examination and senior school basic science achievement test(r = .87) scores as instruments. The data collected were subjected to Pearson product moment correlation, Spearman rank correlation, regression analysis and analysis of variance. The result of the finding revealed that the mean effects of the achievement in all the components of basic science on SSBSAT are significantly different from zero. Based on the results of the findings, it was concluded that the relationship between students’ achievement in JSCE and SSBSAT was weak and to achieve a unit increase in the students’ achievement in the SSBSAT when other subjects are held constant, we have to increase the learning of: -physics by 0.081 units; -chemistry by 0.072 units; -biology by 0.025 units and general knowledge by 0.097 units. It was recommended among others, that general knowledge aspect of basic science should be included in either physics or chemistry aspect of basic science.

Keywords: basic science curriculum, students’ achievement, science test, secondary school students

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Authors: Rida Akzar, Risti Permani, Wahida , Wendy Umberger

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Adoption of farm innovations may increase farm productivity, and therefore improve market access and farm incomes. However, most studies that look at the level and drivers of innovation adoption only focus on a specific type of innovation. Farmers may consider multiple innovation options, and constraints such as budget, environment, scarcity of labour supply, and the cost of learning. There have been some studies proposing different methods to combine a broad variety of innovations into a single measurable index. However, little has been done to compare these methods and assess whether they provide similar information about farmer segmentation by their ‘innovativeness’. Using data from a recent survey of 220 dairy farm households in West Java, Indonesia, this study compares and considers different methods of deriving an innovation index, including expert-weighted innovation index; an index derived from the total number of adopted technologies; and an index of the extent of adoption of innovation taking into account both adoption and disadoption of multiple innovations. Second, it examines the distribution of different farming systems taking into account their innovativeness and farm characteristics. Results from this study will inform policy makers and stakeholders in the dairy industry on how to better design, target and deliver programs to improve and encourage farm innovation, and therefore improve farm productivity and the performance of the dairy industry in Indonesia.

Keywords: adoption, dairy, household survey, innovation index, Indonesia, multiple innovations dairy, West Java

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Authors: Ali Akyar, Osman Serdar Gedik

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Depth estimation is a challenging computer vision task that involves estimating the distance between objects in a scene and the camera. It predicts how far each pixel in the 2D image is from the capturing point. There are some important Monocular Depth Estimation (MDE) studies that are based on Vision Transformers (ViT). We benchmark three major studies. The first work aims to build a simple and powerful foundation model that deals with any images under any condition. The second work proposes a method by mixing multiple datasets during training and a robust training objective. The third work combines generalization performance and state-of-the-art results on specific datasets. Although there are studies with thermal images too, we wanted to benchmark these three non-thermal, state-of-the-art studies with a hybrid image dataset which is taken by Multi-Spectral Dynamic Imaging (MSX) technology. MSX technology produces detailed thermal images by bringing together the thermal and visual spectrums. Using this technology, our dataset images are not blur and poorly detailed as the normal thermal images. On the other hand, they are not taken at the perfect light conditions as RGB images. We compared three methods under test with our thermal dataset which was not done before. Additionally, we propose an image enhancement deep learning model for thermal data. This model helps extract the features required for monocular depth estimation. The experimental results demonstrate that, after using our proposed model, the performance of these three methods under test increased significantly for thermal image depth prediction.

Keywords: monocular depth estimation, thermal dataset, benchmarking, vision transformers

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Authors: Gina Aurora Necula

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From its transformation into a taboo and its hiding under the so-called “Moldovan language” or under the euphemistic expression “state language” to its regained status recognition as an official language, the Romanian language spoken in the Republic of Moldova has undergone impressive reforms in the last 60 years. Meant to erase the awareness of citizens’ ethnic identity and turn a majority language into a minority one, all the laws and regulations issued on the field succeeded into setting numerous barriers for speakers of Romanian. Either manifested as social constraints or materialized into assumed rejection of mother tongue usage, all these laws have demonstrated their usefulness and major impact on the Romanian-speaking population. This article is the result of our research carried out over 10 years with the support of students, and Moldovan citizens, from the master's degree program "Romanian language - identity and cultural awareness." We present here a retrospective insight of the reforms, laws, and regulations that contributed to the shifted status of the Romanian language from the official language, seen as the language of common use both in the public and private spheres, in the minority language that surrendered its privileged place to the Russian language, firstly in the public sphere, and then, slowly but surely, in the private sphere. Our main goal here is to identify and make speakers understand what the barriers to learning Romanian language are nowadays when the social pressure on using Russian no longer exists.

Keywords: linguistic barriers, lingua franca, private sphere, public sphere, reformation

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Authors: P. Panwalkar, K. Veravalli, M. Tofighi, A. Mofidi

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Introduction: Anterior femoral perforation or distal anterior nail position is a known complication of femoral nailing specifically in pertrochantric fractures fixed with cephalomedullary nail. This has been attributed to wrong entry point for the femoral nail, nail with large radius of curvature or malreduced fracture. Left alone anterior perforation of femur or abutment of nail on anterior femur will result in pain and risk stress riser at distal femur and periprosthetic fracture. There have been multiple techniques described to avert or correct this problem ranging from using different nail, entry point change, poller screw to deflect the nail position, use of shorter nail or use of curved guidewire or change of nail to ensure a nail with large radius of curvature Methods: We present this technique which we have used in order to centralise the femoral nail either when the nail has been put anteriorly or when the guide wire has been inserted too anteriorly prior to the insertion of the nail. This technique requires the use of femoral reduction spool from the nailing set. This technique was used by eight trainees of different level of experience under supervision. Results: This technique was easily reproducible without any learning curve without a need for opening of fracture site or change in the entry point with three different femoral nailing sets in twenty-five cases. The process took less than 10 minutes even when revising a malpositioned femoral nail. Conclusion: Our technique of using femoral reduction spool is easily reproducible and repeatable technique for avoidance of non-centralised femoral nail insertion and distal anterior perforation of femoral nail.

Keywords: femoral fracture, nailing, malposition, surgery

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Aisha Zubair, Anila Kamal

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Leadership styles and practices greatly influence the organizational effectiveness and productivity. It also plays an important role in employees’ experiences of positive emotions at workplace and creative work behaviors. Authentic leadership as a newly emerging concept has been found as a significant predictor of various desirable work related outcomes. However, leadership practices and its work related outcomes, to a great extent, are determined by the very nature of the organizational structures (tall and flat). Tall organizations are characterized by multiple hierarchical layers with predominant vertical communication patterns, and narrow span of control; while flat organizations are featured by few layers of management employing both horizontal and vertical communication styles, and wide span of control. Therefore, the present study was undertaken to determine the work related outcomes of perceived authentic leadership; that is work related flow and creative work behavior among employees of flat and tall organizations. Moreover, it was also intended to determine the moderating role of organizational structure (flat and tall) in the relationship between perceived authentic leadership with work related flow and creative work behavior. In this regard, two types of companies have been considered; that is, banks as a form of tall organizational structure with multiple hierarchical structures while software companies have been considered as flat organizations with minimal layers of management. Respondents (N = 1180) were full time regular employees of marketing departments of banks (600) and software companies (580) including both men and women with age range of 22-52 years (M = 33.24; SD = 7.81). Confirmatory Factor Analysis yielded factor structures of measures of work related flow and creative work behavior in accordance to the theoretical models. However, model of authentic leadership exhibited variation in terms of two items which were not included in the final measure of the perceived authentic leadership. Results showed that perceived authentic leadership was positively associated with work related flow and creative work behavior. Likewise, work related flow was positively aligned with creative work behavior. Furthermore, type of organizational structure significantly moderated the relationship of perceived authentic leadership with work related flow and creative work behavior. Results of independent sample t-test showed that employees working in flat organization reflected better perceptions of authentic leadership; higher work related flow and elevated levels of creative work behavior as compared to those working in tall organizations. It was also found that employees with extended job experience and more job duration in the same organization displayed better perceptions of authentic leadership, reported more work related flow and augmented levels of creative work behavior. Findings of the present study distinctively highlighted the similarities as well as differences in the interactions of major constructs which function differentially in the context of tall (banks) and flat (software companies) organizations. Implications of the present study for employees and management as well as future recommendations were also discussed.

Keywords: creative work behavior, organizational structure, perceived authentic leadership, work related flow

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

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Authors: James Moir

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Recent evidence suggests that academic staff face difficulties in applying new technologies as a means of assessing higher order assessment outcomes such as critical thinking, problem solving and creativity. Although higher education institutional mission statements and course unit outlines purport the value of these higher order skills there is still some question about how well academics are equipped to design curricula and, in particular, assessment strategies accordingly. Despite a rhetoric avowing the benefits of these higher order skills, it has been suggested that academics set assessment tasks up in such a way as to inadvertently lead students on the path towards lower order outcomes. This is a controversial claim, and one that this papers seeks to explore and critique in terms of challenging the conceptual basis of assessing higher order skills through new technologies. It is argued that the use of digital media in higher education is leading to a focus on students’ ability to use and manipulate of these products as an index of their flexibility and adaptability to the demands of the knowledge economy. This focus mirrors market flexibility and encourages programmes and courses of study to be rhetorically packaged as such. Curricular content has become a means to procure more or less elaborate aggregates of attributes. Higher education is now charged with producing graduates who are entrepreneurial and creative in order to drive forward economic sustainability. It is argued that critical independent learning can take place through the democratisation afforded by cultural and knowledge digitization and that assessment needs to acknowledge the changing relations between audience and author, expert and amateur, creator and consumer.

Keywords: higher education, curriculum, new technologies, assessment, higher order skills

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Jennifer K. Bowerman, Rhonda L. Reich

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The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.

Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy

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Authors: Hiroki Kikuchi, Atsushi Fukuda, Hirokazu Akahane, Satoru Kobayakawa, Tuenjai Fukuda, Takeru Miyokawa

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According to WHO reports, fatalities by road traffic accidents in many countries of South-East Asia region especially Thailand and Malaysia are increasing year by year. In order to overcome these serious problems, both governments are focusing on road safety measures. In response, the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan and Japan International Cooperation Agency (JICA) have begun active support based on the experiences to reduce the number of fatalities in road accidents in Japan in the past. However, even if the successful road safety measures in Japan is adopted in South-East Asian countries, it is not sure whether it will work well or not. So, it is necessary to clarify the issues and systematize the process for the implementation of road safety measures in South-East Asia. On the basis of the above, this study examined the applicability of "information sharing traffic safety measure" which is one of the successful road safety measures in Japan to the social implementation of road safety measures in South-East Asian countries. The "Information sharing traffic safety measure" is carried out traffic safety measures by stakeholders such as residents, administration, and experts jointly. In this study, we extracted the issues of implementation of road safety measures under local context firstly. This is clarifying the particular issues with its implementation in South-East Asian cities. Secondly, we considered how to implement road safety measures for solving particular issues based on the method of "information sharing traffic safety measure". In the implementation method, the location of the occurrence of a dangerous event was extracted based on the “HIYARI-HATTO” data which were obtained from the residents. This is because it is considered that the implementation of the information sharing traffic safety measure focusing on the location where the dangerous event occurs leads to the reduction of traffic accidents. Also, the target locations for the implementation of measures differ for each city. In Penang, we targeted the intersections　in the downtown, while in Suphan Buri, we targeted mainly traffic control on the intercity highway. Finally, we proposed a method for implementing traffic safety measures. For Penang, we proposed a measure to improve the signal phase and showed the effect of the measure on the micro traffic simulation. For Suphan Buri, we proposed the suitable measures for the danger points extracted by collecting the “HIYARI-HATTO” data of residents to the administration. In conclusion, in order to successfully implement the road safety measure based on the "information sharing traffic safety measure", the process for social implementation of the road safety measures should be consistent and carried out repeatedly. In particular, by clarifying specific issues based on local context in South-East Asian countries, the stakeholders, not only such as government sectors but also local citizens can share information regarding road safety and select appropriate countermeasures. Finally, we could propose this approach to the administration that had the authority.

Keywords: information sharing road safety measure, social implementation, South-East Asia, HIYARI-HATTO

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Authors: Dasom Kim, Chen Liu, Myungsu Lim, Su-Hyeon Jeon, ByeoungKug Jeon, Kee-Young Kwahk, Namgyu Kim

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Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we previously proposed a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. In this paper, we design a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: big data analysis, document classification, multi-category, text mining, topic analysis

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Authors: P. H. G. J. Pushpakumara, A. M. P. Adikari, S. U. B. Tennakoon, Ranil Abeysinghe, Andrew Dawson

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Introduction: Deliberate Self-harm (DSH) is a global public health problem. Since 1950, suicide rates in Sri Lanka are among the highest national rates in the world. It has become an increasingly common response to emotional distress in young adults. However, it remains unclear the reason for this occurrence. Objectives: The descriptive component of this study was conducted to identify of epidemiological pattern of DSH and suicide in Kurunegala District (KD). Assessment of association between DSH socio-cultural, economical and psychological factors were the objectives of the case control component. Methods: Prospective data collection of DSH and suicide was conducted at all (46) hospitals and all (28) police stations in the KD for thirty six months, from 1st January 2011, as the descriptive component. Case control component was conducted at T.H. Kurunegala (THK) for eighteen months duration, from 1st July 2011. Cases (n=439) were randomly selected from a block of 7 consecutively admitted consenting DSP patients using a computer program. Age, sex and residential divisional secretariat division one to one matched, individuals were randomly selected as controls from patients presented to Out Patient Department. Structured Clinical Interview for DSM-IV-TR Axis I and II Disorders was used to diagnose psychiatric disorders. Validated tools were used to measure other constructs. Results: Suicide incidences in KD were, 21.6, 20.7 and 24.3 per 100,000 population in 2011- 2013 (Male:female ratio 5.7, 4.4 and 6.4). 60% of suicides were due to poisoning. DSP incidences were 205.4, 248.3 and 202.5 per 100,000 population in 2011- 2013. Highest age standardized male DSP incidence reported in 20-24 years (769.6/100,000) and female in 15-19 years (1304.0/100,000). Bing married (age >25 years), monthly family income less than Rs.30,000, not achieving G.C.E (O/L) qualifications, a school drop-out, not in a permanent position in occupation, being a manual and an own account worker, were significantly associated with DSP. Perceiving the quality of relationship as bad or very bad with parents, spouse/ girlfriend/ boyfriend and sibling as associated with 8, 40 and 10.5 times higher risk respectively. Feeling and experiences of neglect, other emotional abuses, feeling of insecurity with the family, in child hood, and having a contact history carried an excess risk for DSP. Cases were less likely to seek help. Further, they had significantly lower scores for life skills and life skills application ability. 25.6% DSH patients had DSM TR axis-I and/or TR axis-II disorder. The presence of psychiatric disorder carried 7.7 (95% CI 4.3 – 13.8) times higher risk for DSP. Conclusion: In general, pattern of DSH and suicide is, unique, different from developed, upper and middle income and lower and middle income countries. It is a learned way of expressing emotions in difficult situations of vulnerable people.

Keywords: deliberate self-harm, help-seeking, life-skills, mental- health, psychological, social, suicide

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: J. H. Boonzaaier, A. C. Brent

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South Africa, a water scarce country, experiences the phenomenon that its life supporting natural water resources is seriously threatened by the users that are totally dependent on it. South Africa is globally applauded to have of the best and most progressive water laws and policies. There are however growing concerns regarding natural water resource quality deterioration and a critical void in the management of natural resources and compliance to policies due to increasing institutional uncertainties and failures. These are in accordance with concerns of many South African researchers and practitioners that call for a change in paradigm from talk to practice and a more constructive, practical approach to governance challenges in the management of water resources. A qualitative theory-building case study through longitudinal action research was conducted from 2014 to 2017. The research assessed whether a strategic positioned institutional agent can be parlayed to facilitate and execute WRM on catchment level by engaging multiple stakeholders in a polycentric setting. Through a critical realist approach a distinction was made between ex ante self-deterministic human behaviour in the realist realm, and ex post governance-management in the constructivist realm. A congruence analysis, including Toulmin’s method of argumentation analysis, was utilised. The study evaluated the unique case of a self-steering local water management institution, the Impala Water Users Association (WUA) in the Pongola River catchment in the northern part of the KwaZulu-Natal Province of South Africa. Exploiting prevailing water resource threats, it expanded its ancillary functions from 20,000 to 300,000 ha. Embarking on WRM activities, it addressed natural water system quality assessments, social awareness, knowledge support, and threats, such as: soil erosion, waste and effluent into water systems, coal mining, and water security dimensions; through structured engagement with 21 different catchment stakeholders. By implementing a proposed polycentric governance-management model on a catchment scale, the WUA achieved to fill the void. It developed a foundation and capacity to protect the resilience of the natural environment that is critical for freshwater resources to ensure long-term water security of the Pongola River basin. Further work is recommended on appropriate statutory delegations, mechanisms of sustainable funding, sufficient penetration of knowledge to local levels to catalyse behaviour change, incentivised support from professionals, back-to-back expansion of WUAs to alleviate scale and cost burdens, and the creation of catchment data monitoring and compilation centres.

Keywords: institutional agent, water governance, polycentric water resource management, water resource management

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Stephen Osei Akyiaw, Divine Kwabena Atta Kyere-Owusu

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Malaria has been a worldwide menace of a health condition to human beings for several decades with majority of people on the African continent with most causalities where Ghana is no exception. Therefore, this study employed the use of animation to enhance awareness creation on the spread and prevention of Malaria in Effutu Communities in the Central Region of Ghana. Working with the interpretivist paradigm, this study adopted Art-Based Research, where the AIDA Model and Cognitive Theory of Multimedia Learning (CTML) served as the theories underpinning the study. Purposive and convenience sampling techniques were employed in selecting sample for the study. The data collection instruments included document review and interviews. Besides, the study developed an animation using the local language of the people as the voice over to foster proper understanding by the rural community folks. Also, indigenous characters were used for the animation for the purpose of familiarization with the local folks. The animation was publicized at Health Town Halls within the communities. The outcomes of the study demonstrated that the use of animation was effective in enhancing the awareness creation for preventing and controlling malaria disease in rural communities in Effutu Communities in the Central Region of Ghana. Health officers and community folks expressed interest and desire to practice the preventive measures outlined in the animation to help reduce the spread of Malaria in their communities. The study, therefore, recommended that animation could be used to curtail the spread and enhanced the prevention of Malaria.

Keywords: malaria, animation, prevention, communities

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Gift Udoh, Diane S. Rohlman, Benjamin Sindt

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BACKGROUND: There is concern regarding the widespread use of pesticides and impacts on public health. Farmers in Nigeria frequently apply pesticides, including organophosphate pesticides which are known neurotoxicants. They receive little guidance on how much to apply or information about safe handling practices. Pesticide poisoning is one of the major hazards that farmers face in Nigeria. Farmers continue to use highly neurotoxic pesticides for agricultural activities. Because farmers receive little or no information on safe handling and how much to apply, they continue to develop severe and mild illnesses caused by high exposures to pesticides. The project aimed to reduce pesticide exposure among rural farmers in Nigeria by identifying hazards associated with pesticide use and developing and pilot testing training to reduce exposures to pesticides utilizing the hierarchy of controls system. METHODS: Information on pesticide knowledge, behaviors, barriers to safety, and prevention methods was collected from farmers in Nigeria through workplace observations, questionnaires, and interviews. Pre and post-surveys were used to measure farmer’s knowledge before and after the delivery of pesticide safety training. Training topics included the benefits and risks of using pesticides, routes of exposure and health effects, pesticide label activity, use and selection of PPE, ways to prevent exposure and information on local resources. The training was evaluated among farmers and changes in knowledge, attitudes and behaviors were collected prior to and following the training. RESULTS: The training was administered to 60 farmers, a mean age of 35, with a range of farming experience (<1 year to > 50 years). There was an overall increase in knowledge after the training. In addition, farmers perceived a greater immediate risk from exposure to pesticides and their perception of their personal risk increased. For example, farmers believed that pesticide risk is greater to children than to adults, recognized that just because a pesticide is put on the market doesn’t mean it is safe, and they were more confident that they could get advice about handling pesticides. Also, there was greater awareness about behaviors that can increase their exposure (mixing pesticides with bare hands, eating food in the field, not washing hands before eating after applying pesticides, walking in fields recently sprayed, splashing pesticides on their clothes, pesticide storage). CONCLUSION: These results build on existing evidence from a 2022 article highlighting the need for pesticide safety training in Nigeria which suggested that pesticide safety educational programs should focus on community-based, grassroots-style, and involve a family-oriented approach. Educating farmers on agricultural safety while letting them share their experiences with their peers is an effective way of creating awareness on the dangers associated with handling pesticides. Also, for rural communities, especially in Nigeria, pesticide safety pieces of training may not be able to reach some locations, so intentional scouting of rural farming communities and delivering pesticide safety training will improve knowledge of pesticide hazards. There is a need for pesticide information centers to be situated in rural farming communities or agro supply stores, which gives rural farmers information.

Keywords: pesticide exposure, pesticide safety, nigeria, rural farming, pesticide education

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Adelina Castelo

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The increasing number of learners of Portuguese as Foreign Language in China justifies the need to define the phonetic profile of these learners and to design didactic materials that are adjusted to their specific problems in pronunciation. Different aspects of this topic have been studied, but the production of oral vowels still needs to be investigated. This study aims: (i) to identify the problems the Chinese learners of Portuguese experience in the pronunciation of oral vowels; (ii) to discuss the didactic implications drawn from those problems. The participants were eight native speakers of Mandarin Chinese that had been learning Portuguese in College for almost a year. They named pictured objects and their oral productions were recorded and phonetically transcribed. The selection of the objects to name took into account some linguistic variables (e.g. stress pattern, syllable structure, presence of the Portuguese oral vowels in different word positions according to stress location). The results are analysed in two ways: the impact of linguistic variables on the success rate in the vowels' production; the replacement strategies used in the non-target productions. Both analyses show that the Chinese learners of Portuguese (i) have significantly more difficulties with the mid vowels as well as the high central vowel and (ii) do not master the vowel height feature. These findings contribute to define the phonetic profile of these learners in terms of oral vowel production. Besides, they have important didactic implications for the pronunciation teaching to these specific learners. Those implications are discussed and exemplified.

Keywords: Chinese learners, learners’ phonetic profile, linguistic variables, Portuguese as foreign language, production data, pronunciation teaching, oral vowels

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Authors: Markandeya Kunchi

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Usability testing (UT) is one of the vital steps in the User-centred design (UCD) process when designing a product. In an e-commerce ecosystem, UT becomes primary as new products, features, and services are launched very frequently. And, there are losses attached to the company if an unusable and inefficient product is put out to market and is rejected by customers. This paper tries to answer why UT is important in the product life-cycle of an E-commerce ecosystem. Secondary user research was conducted to find out work patterns, development methods, type of stakeholders, and technology constraints, etc. of a typical E-commerce company. Qualitative user interviews were conducted with product managers and designers to find out the structure, project planning, product management method and role of the design team in a mid-level company. The paper tries to address the usual apprehensions of the company to inculcate UT within the team. As well, it stresses upon factors like monetary resources, lack of usability expert, narrow timelines, and lack of understanding of higher management as some primary reasons. Outsourcing UT to vendors is also very prevalent with mid-level e-commerce companies, but it has its own severe repercussions like very little team involvement, huge cost, misinterpretation of the findings, elongated timelines, and lack of empathy towards the customer, etc. The shortfalls of the unavailability of a UT process in place within the team and conducting UT through vendors are bad user experiences for customers while interacting with the product, badly designed products which are neither useful and nor utilitarian. As a result, companies see dipping conversions rates in apps and websites, huge bounce rates and increased uninstall rates. Thus, there was a need for a more lean UT system in place which could solve all these issues for the company. This paper highlights on optimizing the UT process with a collaborative method. The degree of optimization and structure of collaborative method is the highlight of this paper. Collaborative method of UT is one in which the centralised design team of the company takes for conducting and analysing the UT. The UT is usually a formative kind where designers take findings into account and uses in the ideation process. The success of collaborative method of UT is due to its ability to sync with the product management method employed by the company or team. The collaborative methods focus on engaging various teams (design, marketing, product, administration, IT, etc.) each with its own defined roles and responsibility in conducting a smooth UT with users In-house. The paper finally highlights the positive results of collaborative UT method after conducting more than 100 In-lab interviews with users across the different lines of businesses. Some of which are the improvement of interaction between stakeholders and the design team, empathy towards users, improved design iteration, better sanity check of design solutions, optimization of time and money, effective and efficient design solution. The future scope of collaborative UT is to make this method leaner, by reducing the number of days to complete the entire project starting from planning between teams to publishing the UT report.

Keywords: collaborative method, e-commerce, product management method, usability testing

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Maria L. McLeod

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This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers –The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, ten from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting repeated use of specific metaphors and tropes while charting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals with university affiliations, that emphasizes an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. Thus, the use of anecdotal evidence presented in patient narratives could be perceived as being in conflict with this evidence-based model, as the patient stories are not an accurate representation of scientific outcomes related to developing cancer, cancer reoccurrence, or cancer outcomes. The representative patient narratives tend to exclude or downplay adverse responses to treatment, survival rates, integrative and/or complementary cancer treatments, cancer prevention and causes, and barriers to treatment, such as the limitation of insurance plans, costs of treatment, and/or other issues related to access, potentially contributing to false narratives and inaccurate notions of cancer prevention, cancer care treatment and the potential for a cure. Both quantitative and qualitative findings demonstrate that cancer patient stories featured on the blogsites of the nation’s top cancer care centers deemphasize patient agency and, instead, emphasize deference and gratitude toward the institutions where the featured patients received treatment. Along these lines, language choices reflect positive framing of the cancer experience. Accompanying portrait photos of healthy appearing subjects as well as positive-framed headlines, subheads, and pull quotes function similarly, reflecting hopeful, transformative experiences and outcomes over hardship and suffering. Although patient narratives include real, factual scientific details and descriptions of actual events, the stories lack references to more negative realities of cancer diagnosis and treatment. Instead, they emphasize the triumph of survival by which the cancer care center, in the savior/hero role, enables the patient’s success, represented as a cathartic medical journey.

Keywords: cancer framing, cancer stories, medical gaze, patient narratives

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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