Search results for: communal practice network

Authors: Tamara Tallman

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Collaboration is a powerful tool for professional development and central for creating opportunities for teachers to reflect on their practice. However, school districts continue to have difficulty both implementing and sustaining collaboration. The purpose of this research was to investigate the experience of the teacher in a creative, instructional collaboration. The teachers in this study found that teacher-initiated collaboration offered them trust and they were more open with their partners. An interpretative phenomenological analysis was used for this study as it told the story of the teacher’s experience. Interpretative Phenomenological Analysis was chosen for this study to capture the complex and contextual nature of the teacher experience from a creative, instructional collaborative experience. This study sought to answer the question of how teachers in a private, faith-based school experience collaboration. In particular, the researcher engaged the study’s participants in interviews where they shared their unique perspectives on their experiences in relation to this phenomenon. Through the use of interpretative phenomenological analysis, the researcher interpreted the experiences of each participant in an attempt to gain deeper insight into how teachers made sense of their understanding of collaboration. In addition to the researcher’s interpreting the meaning of this construct for each research participant, this study gave a voice to the individual experiences and positionality of each participant at the research site. Moreover, the key findings presented in this study shed light on how teachers within this particular context participated in and made sense of their experience of creating an instructional collaborative. The research presented the findings that speak to the meaning that each research participant experienced in their relation to participating in building a collaborative culture and its effect on professional and personal growth. The researcher provided recommendations for future practice and research possibilities. The research findings demonstrated the unique experiences of each participant as well as a connection to the literature within the field of teacher professional development. The results also supported the claim that teacher collaboration can facilitate school reform. Participating teachers felt less isolation and developed more teacher knowledge.

Keywords: collaboration, personal grwoth, professional development, teachers

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Authors: Merih Welay Welesilassie

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Language is a potent instrument that does not only serve the purpose of communication but also plays a pivotal role in shaping our cultural practices and identities. The right to choose one's language is a fundamental human right that helps to safeguard the integrity of both personal and communal identities. Language holds immense significance in Ethiopia, a nation with a diverse linguistic landscape that extends beyond mere communication to delineate administrative boundaries. Consequently, depriving Ethiopians of their linguistic rights represents a multifaceted punishment, more complex than food embargoes. In the aftermath of the civil war that shook Ethiopia in November 2020, displacing millions and resulting in the loss of hundreds of thousands of lives, concerns have been raised about the preservation of the indigenous Tigrayan language and culture. This is particularly true following the annexation of western Tigray into the Amhara region and the implementation of an Amharic-only language and culture education policy. This scholarly inquiry explores the intricacies surrounding the Amhara regional state's prohibition of Tigrayans' indigenous language and culture and the subsequent adoption of a monolingual and monocultural Amhara language and culture in western Tigray. The study adopts the linguistic genocide conceptual framework as an analytical tool to gain a deeper insight into the factors that contributed to and facilitated this significant linguistic and cultural shift. The research was conducted by interviewing ten teachers selected through a snowball sampling. Additionally, document analysis was performed to support the findings. The findings revealed that the push for linguistic and cultural assimilation was driven by various political and economic factors and the desire to promote a single language and culture policy. This process, often referred to as ‘Amharanization,’ aimed to homogenize the culture and language of the society. The Amhara authorities have enacted several measures in pursuit of their objectives, including the outlawing of the Tigrigna language, punishment for speaking Tigrigna, imposition of the Amhara language and culture, mandatory relocation, and even committing heinous acts that have inflicted immense physical and emotional suffering upon members of the Tigrayan community. Upon conducting a comprehensive analysis of the contextual factors, actions, intentions, and consequences, it has been posited that there may be instances of linguistic genocide taking place in the Western Tigray region. The present study sheds light on the severe consequences that could arise because of implementing monolingual and monocultural policies in multilingual areas. Through thoroughly scrutinizing the implications of such policies, this study provides insightful recommendations and directions for future research in this critical area.

Keywords: linguistic genocide, linguistic human right, mother tongue, Western Tigray

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Henry Okechukwu Onyeiwu

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Nigeria, with its rich tapestry of ethnicities, cultures, and religions, serves as a critical case study in understanding how law influences and shapes collective identities. This abstract delves into the historical context of legal systems in Nigeria, examining the colonial legacies that have influenced contemporary laws and how these laws interact with traditional practices and beliefs. This study examines the critical role of law in shaping and transforming collective identities in Nigeria, a nation characterized by its rich tapestry of ethnicities, cultures, and religions. The legal framework in Nigeria has evolved in response to historical, social, and political dynamics, influencing the way communities perceive themselves and interact with one another. This research highlights the interplay between law and collective identity, exploring how legal instruments, such as constitutions, statutes, and judicial rulings, have contributed to the formation, negotiation, and reformation of group identities over time. Moreover, contemporary legal debates surrounding issues such as citizenship, resource allocation, and communal conflicts further illustrate the law's role in identity formation. The legal recognition of different ethnic groups fosters a sense of belonging and collective identity among these groups, yet it simultaneously raises questions about inclusivity and equality. Laws concerning indigenous rights and affirmative action are essential in this discourse, as they reflect the necessity of balancing majority rule with minority rights—a challenge that Nigeria continues to navigate. By employing a multidisciplinary approach that integrates legal studies, sociology, and anthropology, the study analyses key historical milestones, such as colonial legal legacies, post-independence constitutional developments, and ongoing debates surrounding federalism and ethnic rights. It also investigates how laws affect social cohesion and conflict among Nigeria's diverse ethnic groups, as well as the role of law in promoting inclusivity and recognizing minority rights. Case studies are utilized to illustrate practical examples of legal transformations and their impact on collective identities in various Nigerian contexts, including land rights, religious freedoms, and ethnic representation in government. The findings reveal that while the law has the potential to unify disparate groups under a national identity, it can also exacerbate divisions when applied inequitably or favouring particular groups over others. Ultimately, this study aims to shed light on the dual nature of law as both a tool for transformation and a potential source of conflict in the evolution of collective identities in Nigeria. By understanding these dynamics, policymakers and legal practitioners can develop strategies to foster unity and respect for diversity in a complex societal landscape.

Keywords: law, collective identity, Nigeria, ethnicity, conflict, inclusion, legal framework, transformation

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

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Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: Kalpana Goel

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Australian social work schools are finding it difficult to find appropriate placements for the increasing number of international students enrolled in their Master of Social Work qualifying (MSWQ) programs. Anecdotally, it has been noticed that fewer social work students are ready to work with older people whose numbers are rising globally. An innovative and unique placement for international students enrolled in the MSWQ at one Australian university was organised in partnership with a community-based service working with older clients to meet two objectives: increasing the number of suitable placements for international students and preparing social work students to work with older people. Creative activities and projects were designed to provide meaningful engagement and experience in working with older people in the community. Students participated in a number of projects that were matched with their interest and capability in a 500-hour placement. The students were asked to complete an online survey after all work for the placement had been completed. The areas of assessment were: self-perceived change in perception towards age and older people, valued field placement experiences including reflective practice, knowledge and skill development, and constraints and challenges experienced in the placement. Findings revealed students’ increased level of confidence in applying social work theory to practice, developing effective communication and interpersonal skills, and use of innovation and creativity in preparing well-being plans with older adults. Challenges and constraints related to their limited English language ability and lack of cultural knowledge of the host society. It was recognised that extra support for these students and more planning in the beginning phase of placement are vital to placement success. Caution in matching students with clients of similar cultural background must be exercised to ensure that there is equity in task allocation and opportunities for wider experiences.

Keywords: field placement, international students, older people, social work

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Eyasu Markos Woldesemayat, Paolo Vincenzo Genovese

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In recent years with an increase in the concentration of Green House Gases (GHG), Climate Change (CC) externalities are mounting, regardless of governments, are scrambling to implement mitigation and adaptation measures. With multiple social, economic and environmental benefits, Green Infrastructure (GI) has evolved as a highly valuable policy tool to promote sustainable development and smart growth by meeting multiple objectives towards quality of life. However, despite the wide range of benefits, it's uptake in African cities such as Addis Ababa is very low due to several constraining factors. This study, through content analysis and key informant interviews, examined barriers for the uptake of GI among spatial planners in Addis Ababa. Added to this, the study has revealed that the spatial planners had insufficient knowledge about GI planning principles such as multi-functionality, integration, and connectivity, and multiscale. The practice of implementing these holistic principles in urban spatial planning is phenomenally nonexistent. The findings also revealed 20 barriers categorized under four themes, i.e., institutional, socio-cultural, resource, and cognitive barriers. Similarly, it was identified that institutional barriers (0.756), socio-cultural barriers (0.730), cognitive barriers (0.700) and resource barriers (0.642), respectively, are the foremost impending factors for the promotion of GI in Addis Ababa. It was realized that resource barriers were the least constraining factor for enshrining the GI uptake in the city. Strategies to hasten the adoption of GI in the city mainly focus on improving political will, harmonization sectorial plans, improve spatial planning and implementation practice, prioritization of GI in all planning activities, enforcement of environmental laws, introducing collaborative GI governance, creating strong and stable institutions and raising awareness on the need to conserve environment and CC externalities through education and outreach mechanisms.

Keywords: Addis Ababa, climate change, green infrastructure, spatial planning, spatial planners

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Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

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Authors: Jianwei Qian, Rob Law

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With the expansion of globalization and the increment of market competition, the festival, especially the traditional one, has demonstrated its vitality under the new context. As a new tourist attraction, festivals play a critically important role in promoting the tourism economy, because the organization of a festival can engage more tourists, generate more revenues and win a wider media concern. However, in the current stage of China, traditional festivals as a way to disseminate national culture are undergoing the challenge of foreign festivals and the related culture. Different from those special events created solely for developing economy, traditional festivals have their own culture and connotation. Therefore, it is necessary to conduct a study on not only protecting the tradition, but promoting its development as well. This study conducts a comparative study of the development of China’s Valentine’s Day and Western Valentine’s Day under the Chinese context and centers on newspaper reports in China from 2000 to 2016. Based on the literature, two main research focuses can be established: one is concerned about the festival’s impact and the other is about tourists’ motivation to engage in a festival. Newspaper reports serve as the research discourse and can help cover the two focal points. With the assistance of content mining techniques, semantic networks for both Days are constructed separately to help depict the status quo of these two festivals in China. Based on the networks, two models are established to show the key component system of traditional festivals in the hope of perfecting the positive role festival tourism plays in the promotion of economy and culture. According to the semantic networks, newspaper reports on both festivals have similarities and differences. The difference is mainly reflected in its cultural connotation, because westerners and Chinese may show their love in different ways. Nevertheless, they share more common points in terms of economy, tourism, and society. They also have a similar living environment and stakeholders. Thus, they can be promoted together to revitalize some traditions in China. Three strategies are proposed to realize the aforementioned aim. Firstly, localize international festivals to suit the Chinese context to make it function better. Secondly, facilitate the internationalization process of traditional Chinese festivals to receive more recognition worldwide. Finally, allow traditional festivals to compete with foreign ones to help them learn from each other and elucidate the development of other festivals. It is believed that if all these can be realized, not only the traditional Chinese festivals can obtain a more promising future, but foreign ones are the same as well. Accordingly, the paper can contribute to the theoretical construction of festival images by the presentation of the semantic network. Meanwhile, the identified features and issues of festivals from two different cultures can enlighten the organization and marketing of festivals as a vital tourism activity. In the long run, the study can enhance the festival as a key attraction to keep the sustainable development of both the economy and the society.

Keywords: Chinese context, comparative study, festival tourism, semantic network analysis, valentine’s day

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Authors: Abu Samah Abdul Khalim, Hamzah Khali Aziz

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Tropical forests in Malaysia safeguard enormous biological diversity while providing crucial benefits and services for the sustainable development of human communities. They are highly significant globally, both for their diverse and threatened species and as representative unique ecosystems. In order to promote the conservation and sustainable management of forest in this country, the Forestry Department (FD) is using ITTO guidelines on managing the forest under the Sustainable Forest Management practice (SFM). The fundamental principles of SFM are the sustained provision of products, goods and services; economic viability, social acceptability and the minimization of environmental/ecological impacts. With increased awareness and recognition of the importance of tropical forests and biodiversity in the global environment, efforts have been made to classify forests and natural areas with unique values or properties in a universally accepted scale. In line with that the concept of High Conservation Value Forest (HCVF) first used by the Forest Stewardship Council (FSC) in 1999, has been adopted and included as Principle ‘9’ in the Malaysia Criteria and Indicators for Forest Management Certification (MC&I 2002). The MC&I 2002 is a standard used for assessing forest management practices of the Forest Management Unit (FMU) level for purpose of certification. The key to the concept of HCVF is identification of HCVs of the forest. This paper highlighted initiative taken by the Forestry Department Peninsular Malaysia in establishing and managing HCVF areas within the Permanent Forest Reserves (PFE). To date almost all states forestry department in Peninsular Malaysia have established HCVFs in their respective states under different categories. Among others, the establishments of HCVF in this country are related to the importance of conserving biological diversity of the flora in the natural forest in particular endemic and threatened species such as Shorea bentongensis. As such it is anticipated that by taking this important initiatives, it will promote the conservation of biological diversity in the PFE of Peninsular Malaysia in line with the Sustainable Forest Management practice.

Keywords: high conservation value forest, sustainable forest management, forest management certification, Peninsular Malaysia

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Authors: Karen Koellner, Nanette Seago, Jennifer Jacobs, Helen Garnier

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Although studies of teacher professional development (PD) are prevalent, surprisingly most have only produced incremental shifts in teachers’ learning and their impact on students. There is a critical need to understand what teachers take up and use in their classroom practice after attending PD and why we often do not see greater changes in learning and practice. This paper is based on a mixed methods efficacy study of the Learning and Teaching Geometry (LTG) video-based mathematics professional development materials. The extent to which the materials produce a beneficial impact on teachers’ mathematics knowledge, classroom practices, and their students’ knowledge in the domain of geometry through a group-randomized experimental design are considered. In this study, we examine a small group of teachers to better understand their interpretations of the workshops and their classroom uptake. The participants included 103 secondary mathematics teachers serving grades 6-12 from two states in different regions. Randomization was conducted at the school level, with 23 schools and 49 teachers assigned to the treatment group and 18 schools and 54 teachers assigned to the comparison group. The case study examination included twelve treatment teachers. PD workshops for treatment teachers began in Summer 2016. Nine full days of professional development were offered to teachers, beginning with the one-week institute (Summer 2016) and four days of PD throughout the academic year. The same facilitator-led all of the workshops, after completing a facilitator preparation process that included a multi-faceted assessment of fidelity. The overall impact of the LTG PD program was assessed from multiple sources: two teacher content assessments, two PD embedded assessments, pre-post-post videotaped classroom observations, and student assessments. Additional data was collected from the case study teachers including additional videotaped classroom observations and interviews. Repeated measures ANOVA analyses were used to detect patterns of change in the treatment teachers’ content knowledge before and after completion of the LTG PD, relative to the comparison group. No significant effects were found across the two groups of teachers on the two teacher content assessments. Teachers were rated on the quality of their mathematics instruction captured in videotaped classroom observations using the Math in Common Observation Protocol. On average, teachers who attended the LTG PD intervention improved their ability to engage students in mathematical reasoning and to provide accurate, coherent, and well-justified mathematical content. In addition, the LTG PD intervention and instruction that engaged students in mathematical practices both positively and significantly predicted greater student knowledge gains. Teacher knowledge was not a significant predictor. Twelve treatment teachers were self-selected to serve as case study teachers to provide additional videotapes in which they felt they were using something from the PD they learned and experienced. Project staff analyzed the videos, compared them to previous videos and interviewed the teachers regarding their uptake of the PD related to content knowledge, pedagogical knowledge and resources used.

Keywords: teacher learning, professional development, pedagogical content knowledge, geometry

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Authors: Pablo De Macedo Silveira Vallejos

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This article aims to observe autobiographical and visual narrative practices among users on Instagram. In this way, the work proposes to reflect on how image resources are used to develop edited representations of the self in that social network. The research aims to explore the uses of editing and the degrees of fictionalization present on Instagram.

Keywords: autobiography, visual narratives, representation, fiction, social media

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Zainab Idrees Ahmad, Mahjabeen Qureshi, Zainab Hussain

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Standard precautions are a set of infection control practices used to prevent the transmission of diseases that can be acquired by contact with body fluids, non-intact skin, and mucous membranes. Lack of practice of SPs can result in a considerable increase in morbidity and mortality rates. Medical students (the future physicians) should have the highest knowledge of standard precautions to prevent the spread of nosocomial infections and ensure their safety as well. This study was designed. To assess the knowledge of medical students regarding standard precautions. And explore the attitude of medical students of MBBS in the third, fourth and final year towards standard precautions.: A descriptive cross-sectional study was conducted in the setting of Rawalpindi Medical University, Pakistan including the students of MBBS in their 3rd, 4th and final years. The study duration was from October 2022 to February 2023. The sample size calculated was 282 with a confidence interval of 95%. A questionnaire was structured utilizing the WHO guidelines on SPs assessing knowledge and attitude regarding hand hygiene, needle stick injury, use of gloves and mask, and sharp disposal. A total of 300 responses were received utilizing the technique of non-random convenience sampling. Data was analyzed using the latest version of SPSS.:Knowledge score regarding components of SPs, hand hygiene, and moments of hand hygiene was satisfactory. However, score regarding the use of PPE, needle stick injury, and sharp disposal was low. Almost all the students were compliant with the proper washing of hands but the observation of recommended time length was lacking. Compliance with the use of correct PPE and informing the supervisor upon getting a needle stick injury was low. This study signifies that medical students lack knowledge regarding standard precautions. This is alarming as this can be the vehicle for the spread of nosocomial infections. Proper training should be given to medical students to prevent the spread of hospital-acquired infections.

Keywords: attitude, knowledge, medical students, standard precautions

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: healthcare, settlement strategy, urban health, rural

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Ahmed Eid, Amita Gupta

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Abstract: Background: Background Medical gases are estimated to contribute to 5% of the carbon footprints produced by hospitals, Desflurane has the largest impact, but all increase significantly when used with N2O admixture. Climate Change Act 2008, we must reduce our carbon emission by 80% of the 1990 baseline by 2050.NHS carbon emissions have reduced by 18.5% (2007-2017). The NHS Long Term Plan has outlined measures to achieve this objective, including a 2% reduction by transforming anaesthetic practices. FGF is an important variable that determines the utilization of inhalational agents and can be tightly controlled by the anaesthetist. Aims and Objectives Environmental safety, Identification of areas of high N20 and different anaesthetic agents used across the St Helier operating theatres and consider improvising on the current practice. Methods: Data was collected from St Helier operating theatres and retrieved daily from Care Station 650 anaesthetic machines. 60 cases were included in the sample. Collected data (average flow rate, amount and type of agent used, duration of surgery, type of surgery, duration, and the total amount of Air, O2 and N2O used. AAGBI impact anaesthesia calculator was used to identify the amount of CO2 produced and also the cost per hour for every pt. Communication via reminder emails to staff emphasized the significance of low-flow anaesthesia and departmental meeting presentations aimed at heightening awareness of LFA, Distribution of AAGBI calculator QR codes in all theatres enables the calculation of volatile anaesthetic consumption and CO2e post each case, facilitating informed environmental impact assessment. Results: A significant reduction in the flow rate use in the 2nd sample was observed, flow rate usage between 0-1L was 60% which means a great reduction of the consumption of volatile anaesthetics and also Co2e. By using LFA we can save money but most importantly we can make our lives much greener and save the planet.

Keywords: low flow anesthesia, sustainability project, N₂0, Co2e

Procedia PDF Downloads 68

Authors: Tunde Ope-Davies

Abstract:

Transmediality and platformization as online content-sharing protocols have continued to accentuate the growing impact of the unprecedented digital revolution across the world. The rapid transformation across all sectors as a result of this revolution has continued to spotlight the increasing importance of new media technologies in redefining and reshaping the rhythm and dynamics of our private and public discursive practices. Equally, social and political activities are being impacted daily through the creation and transmission of political discourse content through multi-channel platforms such as mobile telephone communication, social media networks and the internet. It has been observed that digital platforms have become central to the production, processing, and distribution of multimodal social data and cultural content. The platformization paradigm thus underpins our understanding of how digital platforms enhance the production and heterogenous distribution of media and cultural content through these platforms and how this process facilitates socioeconomic and political activities. The use of multiple digital platforms to share and transmit political discourse material synchronously and asynchronously has gained some exciting momentum in the last few years. Nigeria’s 2023 general elections amplified the usage of social media and other online platforms as tools for electioneering campaigns, socio-political mobilizations and civic engagement. The study, therefore, focuses on transmedia and platformed political discourse as a new strategy to promote political candidates and their manifesto in order to mobilize support and woo voters. This innovative transmedia digital discourse model involves a constellation of online texts and images transmitted through different online platforms almost simultaneously. The data for the study was extracted from the 2023 general elections campaigns in Nigeria between January- March 2023 through media monitoring, manual download and the use of software to harvest the online electioneering campaign material. I adopted a discursive-analytic qualitative technique with toolkits drawn from a computer-mediated multimodal discourse paradigm. The study maps the progressive development of digital political discourse in this young democracy. The findings also demonstrate the inevitable transformation of modern democratic practice through platform-dependent and transmedia political discourse. Political actors and media practitioners now deploy layers of social media network platforms to convey messages and mobilize supporters in order to aggregate and maximize the impact of their media campaign projects and audience reach.

Keywords: social media, digital humanities, political discourse, platformized discourse, multimodal discourse

Procedia PDF Downloads 85

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of cross-linked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: redox enzyme, nanomaterials, biosensors, electrical communication

Procedia PDF Downloads 454

Authors: Chalise Kiran

Abstract:

The prime idea of inclusive education is to mainstream every child in education. However, it will be challenging for implementation when there are policy and practice gaps. It will be even more challenging when children have disabilities. Generally, the focus will be on the policy gap, but the problem may not always be with policy. The proper practice could be a challenge in the countries like Nepal. In determining practice, the teachers’ perceptions toward inclusive will play a vital role. Nepal has categorized disability in 7 types (physical, visual, hearing, vision/hearing, speech, mental, and multiple). Out of these, hearing impairment is the study realm. In the context of a limited number of researches on children with disabilities and rare researches on CWHI and their education in Nepal, this study is a pioneering effort in knowing basically the problems and challenges of CWHI focused on inclusive education in the schools including gaps and barriers in its proper implementation. Philosophically, the paradigm of the study is post-positivism. In the post-positivist worldview, the quantitative approach with the description of the situation and inferential relationship are revealed out in the study. This is related to the natural model of objective reality. The data were collected from an individual survey with the teachers and head teachers of 35 schools in Nepal. The survey questionnaire was prepared and filled by the respondents from the schools where the CWHI study in 7 provincial 20 districts of Nepal. Through these considerations, the perceptions of CWHI focused inclusive education were explored in the study. The data were analyzed using both descriptive and inferential tools on which the Likert scale-based analysis was done for descriptive analysis, and chi-square mathematical tool was used to know the significant relationship between dependent variables and independent variables. The descriptive analysis showed that the majority of teachers have positive perceptions toward implementing CWHI focused inclusive education, and the majority of them have positive perceptions toward CWHI focused inclusive education, though there are some problems and challenges. The study has found out the major challenges and problems categorically. Some of them are: a large number of students in a single class; availability of generic textbooks for CWHI and no availability of textbooks to all students; less opportunity for teachers to acquire knowledge on CWHI; not adequate teachers in the schools; no flexibility in the curriculum; less information system in schools; no availability of educational consular; disaster-prone students; no child abuse control strategy; no disabled-friendly schools; no free health check-up facility; no participation of the students in school activities and in child clubs and so on. By and large, it is found that teachers’ age, gender, years of experience, position, employment status, and disability with him or her show no statistically significant relation to successfully implement CWHI focused inclusive education and perceptions to CWHI focused inclusive education in schools. However, in some of the cases, the set null hypothesis was rejected, and some are completely retained. The study has suggested policy implications, implications for educational authority, and implications for teachers and parents categorically.

Keywords: children with hearing impairment, disability, inclusive education, perception

Procedia PDF Downloads 112

Authors: Armando Cuspinera

Abstract:

Humans are nature itself, being with non-human species part of the same ecosystem, but the praxis reflects that not all relations are the same. In fields of design such as Biomimicry, Biodesign, and Biophilic design exist different approaches towards nature, nevertheless, anthropocentric principles such as domination, objectivization, or exploitation are defined in the same as ecocentric principles of inherent importance in life itself. Anthropocentrism has showed humanity with pollution of the earth, water, air, and the destruction of whole ecosystems from monocultures and rampant production of useless objects that life cannot outstand this unaware rhythm of life focused only for the human benefits. Even if by nature the biosphere is resilient, studies showed in the Paris Agreement explain that humanity will perish in an unconscious way of praxis. This is why is important to develop a differentiation between anthropocentric and ecocentricprinciples in the praxis of design, in order to enhance respect, valorization, and positive affectivity towards other life forms is necessary to analyze what principles are reproduced from each practice of design. It is only from the study of immaterial dimensions of design such as symbolism, epistemology, and ontology that the relation towards nature can be redesigned, and in order to do so, it must be studies from the dimensions of ontological design what principles –anthropocentric or ecocentric- through what the objects enhance or focus the perception humans have to its surrounding. The things we design also design us is the principle of ontological design, and in order to develop a way of ecological design in which is possible to consider other species as users, designers or collaborators is important to extend the studies and relation to other living forms from a transdisciplinary perspective of techniques, knowledge, practice, and disciplines in general. Materials, technologies, and any kind of knowledge have the principle of a tool: is not good nor bad, but is in the way of using it the possibilities that exist within them. The collaboration of disciplines and fields of study gives the opportunity to connect principles from other cultures such as Deep Ecology and Environmental Humanities in the development of methodologies of design that study nature, integrates their strategies to our own species, and considers life of other species as important as human life, and is only form the studies of ontological design that material and immaterial dimensions can be analyzed and imbued with structures that already exist in other fields.

Keywords: design, antropocentrism, ecocentrism, ontological design

Procedia PDF Downloads 156

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

Procedia PDF Downloads 329

Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

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Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

Procedia PDF Downloads 183

Authors: Daniela Lamaison Sepulveda

Abstract:

Critical media literacy teaches people to think analytically about the information they receive through the media. It is heavily influenced by Paulo Freire’s critical pedagogy and the necessity of becoming conscious of one’s reality in order to transform it. This qualitative research examines the case of Bolivia, which experienced dramatic political change after the first indigenous president, Evo Morales, was elected in 2006. In 2010, the government passed an education reform — the Avelino Siñani Elizardo Pérez (ASEP) —that draws heavily on decolonial thought and the Freirean notion of critical consciousness. The extent to which these theories were implemented in practice is evaluated in context of a media literacy project, run by an NGO, that trains secondary school teachers from public schools across Bolivia through yearly workshops ranging from producing media to identifying fake news. This context is examined against the backdrop of the highly contested general elections in October 2019. While there is plenty of literature that outlines the benefits of teaching media literacy in the classroom and different ways to apply it, little research has been done analysing implementation at an institutional level and how to best enable teachers who are motivated to teach the subject. Through semi-structured interviews, document analysis and naturalistic observations, this study aims to identify the struggles faced by teachers who are dedicated to teaching critical media literacy in their classrooms and how they navigate educational spaces while being subject to a demanding national curriculum that supposedly also seeks to promote critical thinking. The interplay between the aspirations of teachers and NGOs in contrast to the top-down discourse and policy of governmental institutions provides for a very enlightening case. By exploring these institutional, cultural, sociopolitical and economic barriers the teachers face, this research attempts to contribute to the debate in media literacy theories concerned with implementing the practice in schools.

Keywords: media literacy, critical pedagogy, teacher agency, misinformation, education reform, Bolivia

Procedia PDF Downloads 126

Authors: Gadah Alkeniah

Abstract:

Leadership is acknowledged internationally as fundamental to school efficiency and school enhancement nevertheless there are various understandings of what leadership is and how it is realised in practice. There are a number of educational leadership models that are considered important. However, the present study uses a systematic review method to examine and compare five models of the most well-known contemporary models of leadership as well as introduces the dimension of each model. Our results reveal that recently the distributed leadership has grown in popularity within the field of education. The study concludes by suggesting future directions in leadership development and education research.

Keywords: distributed leadership, instructional leadership, leadership models, moral leadership, strategic leadership, transformational leadership

Procedia PDF Downloads 204

Authors: Afnan Al-Romi, Iman Al-Momani

Abstract:

The urge of applying the Software Engineering (SE) processes is both of vital importance and a key feature in critical, complex large-scale systems, for example, safety systems, security service systems, and network systems. Inevitably, associated with this are risks, such as system vulnerabilities and security threats. The probability of those risks increases in unsecured environments, such as wireless networks in general and in Wireless Sensor Networks (WSNs) in particular. WSN is a self-organizing network of sensor nodes connected by wireless links. WSNs consist of hundreds to thousands of low-power, low-cost, multi-function sensor nodes that are small in size and communicate over short-ranges. The distribution of sensor nodes in an open environment that could be unattended in addition to the resource constraints in terms of processing, storage and power, make such networks in stringent limitations such as lifetime (i.e. period of operation) and security. The importance of WSN applications that could be found in many militaries and civilian aspects has drawn the attention of many researchers to consider its security. To address this important issue and overcome one of the main challenges of WSNs, security solution systems have been developed by researchers. Those solutions are software-based network Intrusion Detection Systems (IDSs). However, it has been witnessed, that those developed IDSs are neither secure enough nor accurate to detect all malicious behaviours of attacks. Thus, the problem is the lack of coverage of all malicious behaviours in proposed IDSs, leading to unpleasant results, such as delays in the detection process, low detection accuracy, or even worse, leading to detection failure, as illustrated in the previous studies. Also, another problem is energy consumption in WSNs caused by IDS. So, in other words, not all requirements are implemented then traced. Moreover, neither all requirements are identified nor satisfied, as for some requirements have been compromised. The drawbacks in the current IDS are due to not following structured software development processes by researches and developers when developing IDS. Consequently, they resulted in inadequate requirement management, process, validation, and verification of requirements quality. Unfortunately, WSN and SE research communities have been mostly impermeable to each other. Integrating SE and WSNs is a real subject that will be expanded as technology evolves and spreads in industrial applications. Therefore, this paper will study the importance of Requirement Engineering when developing IDSs. Also, it will study a set of existed IDSs and illustrate the absence of Requirement Engineering and its effect. Then conclusions are drawn in regard of applying requirement engineering to systems to deliver the required functionalities, with respect to operational constraints, within an acceptable level of performance, accuracy and reliability.

Keywords: software engineering, requirement engineering, Intrusion Detection System, IDS, Wireless Sensor Networks, WSN

Procedia PDF Downloads 322

Authors: Jeffrey R. Mueller

Abstract:

This paper expands on the role of the professor by detailing the origins of the profession, adding some of the unique contributions of North American Universities, as well as some of the best practice recommendations, to the unique tripartite role of the professor. It describes current challenges to the profession including the ever-controversial student rating of professors. It continues with the significance of empowerment to the role of the professor. It concludes with a predictive prescription for the future of the professoriate and the role of the university-level educational administrator toward that end.

Keywords: professoriate history, tripartite role, challenges, empowerment, shared governance, administratization

Procedia PDF Downloads 401