Search results for: multimedia learning tools

Authors: Fharia Tilat Loba

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Studies show that there is a certain group of students who are more vulnerable to bullying due to their physical appearance, disability, sexual preference, race, and lack of social and behavioral skills. Students with autism spectrum disorders (ASD) are one of the most vulnerable groups among these at-risk groups. Researchers suggest that focusing on vulnerable groups of students who can be the target of bullying helps to understand the causes and patterns of aggression, which ultimately helps in structuring intervention programs to reduce bullying. Since Australia ratified the United Nations Convention on the Rights of Persons with Disabilities in 2006, it has been committed to providing an inclusive, safe, and effective learning environment for all children. In addition, the 2005 Disability Standards for Education seeks to ensure that students with disabilities can access and participate in education on the same basis as other students, covering all aspects of education, including harassment and victimization. However, bullying hinders students’ ability to fully participate in schooling. The proposed study aims to synthesize the notions of traditional bullying and cyberbullying and attempts to understand the experiences of students with ASD who are experiencing bullying in their schools. The proposed study will primarily focus on identifying the gaps between policy and practice related to bullying, and it will also attempt to understand the experiences of parents of students with ASD and professionals who have experience dealing with bullying at the school level in Australia. This study is expected to contribute to the theoretical knowledge of the bullying phenomenon and provide a reference for advocacy at the school, organization, and government levels.

Keywords: education policy, bullying, Australia, neurodiversity

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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: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

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In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

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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: Catherine Begin, Jeanne Berthod, Manon Truchon

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In Quebec, there are more than 8,000 community organizations throughout the province, representing more than 72,000 jobs. Working in a community setting involves several particularities (e.g., contact with the suffering of users, feelings of powerlessness, institutional pressure, unstable funding, etc.), which can put workers at risk of fatigue, burnout, and psychological distress. A 2007 study shows that 52% of community workers surveyed have a high psychological distress index. The Ricochet project, founded in 2019, is an initiative aimed at providing various care and services to community workers in the Quebec City region, with a global health approach. Within this program, mindful self-compassion training (MSC) is offered at a low cost. MSC is one of the effective strategies proposed in the literature to help prevent and reduce burnout. Self-compassion is the recognition that suffering, failure, and inadequacies are inherent in the human experience and that everyone, including oneself, deserves compassion. MSC training targets several behavioral, cognitive, and emotional learnings (e.g., motivating oneself with caring, better managing difficult emotions, promoting resilience, etc.). A mixed-method evaluation was conducted with the participants in order to explore the effects of the training on community workers in the Quebec City region. The participants were community workers (management or caregiver). 15 participants completed satisfaction and perceived impact surveys, and 30 participated in structured interviews. Quantitative results showed that participants were generally completely satisfied or satisfied with the training (94%) and perceived that the training allowed them to develop new strategies for dealing with stress (87%). Participants perceived effects on their mood (93%), their contact with others (80%), and their stress level (67%). Some of the barriers raised were scheduling constraints, length of training, and guilt about taking time for oneself. The qualitative results show that individuals experienced long-term benefits, as they were able to apply the tools they received during the training in their daily lives. Some barriers were noted, such as difficulty in getting away from work or problems with the employer, which prevented enrollment. Overall, the results of this evaluation support the use of MSC (mindful self-compassion) training among community workers. Future research could support this evaluation by using a rigorous design and developing innovative ways to overcome the barriers raised.

Keywords: mindful self-compassion, community workers, work stres, burnout, wellbeing at work

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Authors: Bunindro Nameirakpam, Sonia Sougrapakam, Shannon B. Olsson, Rajashekar Yallappa

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Natural sources for new pesticidal compounds hold promise in view of their eco-friendly nature, selectivity and mammalian safety. Despite a large number of plants that show insecticidal activity and diversity of natural chemistry with inherent eco-friendly nature, newer classes of insecticides have eluded discovery. Artemisia vulgaris, known as Mugwort, is a universal herb used for folk medicine and religious purposes throughout the ancient world. In India, the essential oils of Artemisia vulgaris are used for its insecticidal, anti parasiticidal and antimicrobial properties. Traditionally, the dried leaves of Artemisia vulgaris are used to repel insects as well as rats in and around the granaries in the North-East India. Artemisia vulgaris collected during November from different ecological sites were studied for the bio-pesticidal utility against the stored grain pests. The insecticidal activities were found in the crude extracts of n-hexane and methanol from the samples collected in Sikkim and Manipur respectively. Using silica gel column chromatography protocol, we have isolated one novel bioactive molecule from the aerial parts of Artemisia vulgaris L based on various physical-chemical and spectroscopic techniques (IR, 1H NMR, 13C NMR and mass). The novel bioactive molecule is highly toxic and very low concentration (4.35 µg/l) is needed to control the stored product insects. In additional experiment results clearly showed the involvement of sodium pumps inhibition in the insecticidal action of purified compound in the Sitophilus oryzae. The knockdown activity of the purified compound is concomitant with the in vivo inhibition of Na+/ K+- ATPase. Further, our study showed insignificant differences in the seed germination of control and the treated grains. The lack of adverse effect of the novel bioactive molecule on the seed germination is highly desirable for seed/grain protectant and showing the potential to be developed as possible natural fumigants for the control of stored grain pests. The novel bioactive molecule is selective insecticide with a high margin of safety to mammals and showed promise as novel biopesticide candidate for grain protection. It is believed that Bio-pesticides can serve as the most important pest management tools as far as global safety is concerned.

Keywords: Indian traditional plant, Artemisia vulgaris, bio-pesticides, Na+/ K+- ATPase, seed germination

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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: 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: Joana Mourão

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Transition to a low carbon economy requires changes in consumption and production patterns, including the improvement of existing buildings’ environmental performance. Urban rehabilitation is a top policy priority in Europe, creating an opportunity to increase this performance. However, urban rehabilitation comprises different typologies of interventions with distinct levels of consideration for cultural urban heritage values and for environmental values, thus with different impacts. Cities rely on both material and non-material forms of heritage that are deep-rooted and resilient. One of the most relevant parts of that urban heritage is the historical pre-industrial housing stock, with an extensive presence in many European cities, as Lisbon. This stock is rehabilitated and transformed at the framework of urban management and local governance traditions, as well as the framework of the global economy, and in that context, faces opportunities and threats that need evaluation and control. The scope of this article is to define methodological bases and research lines for the assessment of impacts that urban rehabilitation initiatives set on the vulnerable and historical pre-industrial urban housing stock, considering it as an environmental and cultural unreplaceable material value and resource. As a framework, this article reviews the concepts of urban regeneration, urban renewal, current buildings conservation and refurbishment, and energy refurbishment of buildings, seeking to define key typologies of urban rehabilitation that represent different approaches to the urban fabric, in terms of scope, actors, and priorities. Moreover, main types of interventions - basing on a case-study in a XVIII century neighborhood in Lisbon - are defined and analyzed in terms of the elements lost in each type of intervention, and relating those to urbanistic, architectonic and constructive values of urban heritage, as well as to environmental and energy efficiency. Further, the article overviews environmental cultural heritage assessment and life-cycle assessment tools, selecting relevant and feasible impact assessment criteria for urban buildings rehabilitation regulation, focusing on multi-level urban heritage integrity. Urbanistic, architectonic, constructive and energetic integrity are studied as criteria for impact assessment and specific indicators are proposed. The role of these criteria in sustainable urban management is discussed. Throughout this article, the key challenges for urban rehabilitation planning and management, concerning urban built heritage as a resource for sustainability, are discussed and clarified.

Keywords: urban rehabilitation, impact assessment criteria, buildings integrity, embodied energy

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Authors: Alok Madan, Ashok Gupta, Arshad K. Hashmi

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Non-linear dynamic time history analysis is considered as the most advanced and comprehensive analytical method for evaluating the seismic response and performance of multi-degree-of-freedom building structures under the influence of earthquake ground motions. However, effective and accurate application of the method requires the implementation of advanced hysteretic constitutive models of the various structural components including masonry infill panels. Sophisticated computational research tools that incorporate realistic hysteresis models for non-linear dynamic time-history analysis are not popular among the professional engineers as they are not only difficult to access but also complex and time-consuming to use. And, commercial computer programs for structural analysis and design that are acceptable to practicing engineers do not generally integrate advanced hysteretic models which can accurately simulate the hysteresis behavior of structural elements with a realistic representation of strength degradation, stiffness deterioration, energy dissipation and ‘pinching’ under cyclic load reversals in the inelastic range of behavior. In this scenario, push-over or non-linear static analysis methods have gained significant popularity, as they can be employed to assess the seismic performance of building structures while avoiding the complexities and difficulties associated with non-linear dynamic time-history analysis. “Push-over” or non-linear static analysis offers a practical and efficient alternative to non-linear dynamic time-history analysis for rationally evaluating the seismic demands. The present paper is based on the analytical investigation of the effect of distribution of masonry infill panels over the elevation of planar masonry infilled reinforced concrete (R/C) frames on the seismic demands using the capacity spectrum procedures implementing nonlinear static analysis (pushover analysis) in conjunction with the response spectrum concept. An important objective of the present study is to numerically evaluate the adequacy of the capacity spectrum method using pushover analysis for performance based design of masonry infilled R/C frames for near-field earthquake ground motions.

Keywords: nonlinear analysis, capacity spectrum method, response spectrum, seismic demand, near-field earthquakes

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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: 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: 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: Shivani Yadav

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The Study of terrorism lends itself to the constructivist framework as constructivism focuses on the importance of ideas and norms in shaping interests and identities. Constructivism is pertinent to understand the phenomenon of a terrorist organization like the Islamic State (IS), which opportunistically utilizes radical ideas and norms to shape its ‘politics of identity’. This ‘identity’, which is at the helm of preferences and interests of actors, in turn, shapes actions. The paper argues that an effective counter-terrorism policy must recognize the importance of ideas in order to counter the threat arising from acts of radicalism and terrorism. Traditional theories of international relations, with an emphasis on state-centric security problematic, exhibit several limitations and problems in interpreting the phenomena of terrorism. With the changing global order, these theories have failed to adapt to the changing dimensions of terrorism, especially ‘newer’ actors like the Islamic State (IS). The paper observes that IS distinguishes itself from other terrorist organizations in the way that it recruits and spreads its propaganda. Not only are its methods different, but also its tools (like social media) are new. Traditionally, too, force alone has rarely been sufficient to counter terrorism, but it seems especially impossible to completely root out an organization like IS. Time is ripe to change the discourse around terrorism and counter-terrorism strategies. The counter-terrorism measures adopted by states, which primarily focus on mitigating threats to the national security of the state, are preoccupied with statist objectives of the continuance of state institutions and maintenance of order. This limitation prevents these theories from addressing the questions of justice and the ‘human’ aspects of ideas and identity. These counter-terrorism strategies adopt a problem-solving approach that attempts to treat the symptoms without diagnosing the disease. Hence, these restrictive strategies fail to look beyond calculated retaliation against violent actions in order to address the underlying causes of discontent pertaining to ‘why’ actors turn violent in the first place. What traditional theories also overlook is that overt acts of violence may have several causal factors behind them, some of which are rooted in the structural state system. Exploring these root causes through the constructivist framework helps to decipher the process of ‘construction of terror’ and to move beyond the ‘what’ in theorization in order to describe ‘why’, ‘how’ and ‘when’ terrorism occurs. Study of terrorism would much benefit from a constructivist analysis in order to explore non-military options while countering the ideology propagated by the IS.

Keywords: constructivism, counter terrorism, Islamic State, politics of identity

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: Orit Shamir Balderman, Shamir Michal

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Israel often deals with crisis situations, but most have been characterized as security crises (e.g., war). This is the first time that the Israel has dealt with a health and social emergency as part of a global crisis. The crisis began in January 2020 with the emergence of the novel coronavirus (Covid-19), which was defined as a pandemic (World Health Organization, 2020) and arrived in Israel in early March 2020. This study examined how single mothers by choice (SMBC) experience state anxiety (SA), social support, work–family conflict (WFC), and happiness. This group has not been studied in the context of crises in general or a global crisis. Using a snowball sample, 386 SMBCanswered an online questionnaire. The findings show a negative relationship between income and level of state anxiety. State anxiety was also negatively associated with social support, level of happiness, and WFC. Finally, a stepwise regression analysis indicated that happiness explained 34% of the variance in SA. We also found that most of the women did not turn to formal support agencies such as social workers, other Government Ministries, or municipal welfare. A positive and strong correlations was also found between SA and WFC. The findings of the study reinforce the understanding that although these women made a conscious and informed decision regarding the choice of their family cell, their situation is more complex in the absence of a spouse support. Therefore, this study, as other future studies in the field of SMBC, may contribute to the improvement of their social status and the understanding that they are a unique group. Although SMBC are a growing sector of society in the past few years, there are still special needs and special attention that is needed from the formal and informal supports systems. A comparative study of these two groups and in different countries would shed light on SA among mothers in general, regardless of their relationship status and location.Researchers should expand this study by comparing mothers in relationships and exploring how SMBC coped in other countries. In summary, the findings of the study contribute knowledge on three levels: (a) knowledge about SMBC in general and during crisis situations; (b) examination of social support using tools assessing receipt of assistance and support, some of which were developed for the present study; and (c) insights regarding counseling, accompaniment, and guidance of welfare mechanisms.

Keywords: single mothers by choice, state anxiety, social support, happiness, work–family conflict

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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: Noor Ayuni Che Zakaria, Takashi Komeda, Cheng Yee Low, Kaoru Inoue, Fazah Akhtar Hanapiah

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Previous studies have shown that there are arguments regarding the reliability and validity of the Ashworth and Modified Ashworth Scale towards evaluating patients diagnosed with upper limb disorders. These evaluations depended on the raters’ experiences. This initiated us to develop an upper limb disorder part-task trainer that is able to simulate consistent upper limb disorders, such as spasticity and rigidity signs, based on the Modified Ashworth Scale to improve the variability occurring between raters and intra-raters themselves. By providing consistent signs, novice therapists would be able to increase training frequency and exposure towards various levels of signs. A total of 22 physiotherapists and occupational therapists participated in the study. The majority of the therapists agreed that with current therapy education, they still face problems with inter-raters and intra-raters variability (strongly agree 54%; n = 12/22, agree 27%; n = 6/22) in evaluating patients’ conditions. The therapists strongly agreed (72%; n = 16/22) that therapy trainees needed to increase their frequency of training; therefore believe that our initiative to develop an upper limb disorder training tool will help in improving the clinical education field (strongly agree and agree 63%; n = 14/22).

Keywords: upper limb disorder, clinical education tool, inter/intra-raters variability, spasticity, modified Ashworth scale

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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: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

Procedia PDF Downloads 150

Authors: Indhumathi Gopal

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Undergraduate research is well documented in Science, Technology, Engineering, and Mathematics (STEM), neurosciences, and microbiology disciplines, though it is hardly part of a physical fitness & wellness discipline. However, students need experiential learning opportunities, like internships and research assistantships, to get ahead with graduate schools and be gainfully employed. The first step towards this goal is to have students do a simple research project in a semester-long course. The value of research experiences and how to integrate research activity in a physical fitness & wellness course are discussed. The investigator looks into a mini research project, “Awareness of Obesity among College Students” and explains how to guide students through the research process, including journal search, data collection, and basic statistics. Besides, students will be introduced to the statistical package program SPSS 22.0 to assist with data evaluation. The lab component of the combined lecture-physical activity course could include the measurement of student’s weight with respect to their height to obtain body mass index (BMI). Students could categorize themselves in accordance with the World Health Organization’s guidelines. Results obtained after completing the data analysis help students be aware of their own potential health risks associated with overweight and obesity. Overweight and obesity are risk factors for hypertension, hypercholesterolemia, heart disease, stroke, diabetes, and certain types of cancer. It is hoped that this experience will get students interested in scientific studies, gain confidence, think critically, and develop problem-solving and good communication skills.

Keywords: physical fitness, undergraduate research experience, obesity, BMI

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Ayman Al Yaari, Montaha Al Yaari, Adham Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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Background & Aims: Audio-visual aids and computer-aided language instruction (CALI) have been documented to improve receptive skills, namely listening skills, in normal students. The increased listening has been attributed to the understanding of other interlocutors' speech, but recent experiments have suggested that audio-visual aids and CALI should be tested against the listening of students of special needs to see the effects of the former in the latter. This investigation described the effect of audio-visual aids and CALI on the performance of these students. Methods: Pre-and-posttests were administered to 40 students of special needs of both sexes at al-Malādh school for students of special needs aged between 8 and 18 years old. A comparison was held between this group of students and another similar group (control group). Whereas the former group underwent a listening course using audio-visual aids and CALI, the latter studied the same course with the same speech language therapist (SLT) with the classical method. The outcomes of the two tests for the two groups were qualitatively and quantitatively analyzed. Results: Significant improvement in the performance was found in the first group (treatment group) (posttest= 72.45% vs. pre-test= 25.55%) in comparison to the second (control) (posttest= 25.55% vs. pre-test= 23.72%). In comparison to the males’ scores, the scores of females are higher (1487 scores vs. 1411 scores). Suggested results support the necessity of the use of audio-visual aids and CALI in teaching listening at the schools of students of special needs.

Keywords: listening, receptive skills, audio-visual aids, CALI, special needs

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Authors: Benjamin Mugisha Bugingo

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Healthcare staffhas been considered as asignificant pillar to the health care system. However, the contest of human resources for health in terms of the turnover of health workers in Uganda has been more distinct in the latest years. The objective of the paper, therefore, were to investigate the influence Role Human resource management functions in on employeeperformance of professional health workers in public district hospitals in Kampala. The study objectives were: to establish the effect of performance management function, financialincentives, non-financial incentives, participation, and involvement in the decision-making on the employee performance of professional health workers in public district hospitals in Kampala. The study was devised in the social exchange theory and the equity theory. This study adopted a descriptive research design using quantitative approaches. The study used a cross-sectional research design with a mixed-methods approach. With a population of 402 individuals, the study considered a sample of 252 respondents, including doctors, nurses, midwives, pharmacists, and dentists from 3 district hospitals. The study instruments entailed a questionnaire as a quantitative data collection tool and interviews and focus group discussions as qualitative data gathering tools. To analyze quantitative data, descriptive statistics were used to assess the perceived status of Human resource management functions and the magnitude of intentions to stay, and inferential statistics were used to show the effect of predictors on the outcome variable by plotting a multiple linear regression. Qualitative data were analyzed in themes and reported in narrative and verbatim quotes and were used to complement descriptive findings for a better understanding of the magnitude of the study variables. The findings of this study showed a significant and positive effect of performance management function, financialincentives, non-financial incentives, and participation and involvement in decision-making on employee performance of professional health workers in public district hospitals in Kampala. This study is expected to be a major contributor for the improvement of the health system in the country and other similar settings as it has provided the insights for strategic orientation in the area of human resources for health, especially for enhanced employee performance in relation with the integrated human resource management approach

Keywords: human resource functions, employee performance, employee wellness, profecial workers

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Authors: Jialin Ma, Jia Meng

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Genomic features, the genome-based coordinates, are commonly used for the representation of biological features such as genes, RNA transcripts and transcription factor binding sites. For the analysis of RNA-related genomic features, such as RNA modification sites, a common task is to correlate these features with transcript components (5'UTR, CDS, 3'UTR) to explore their distribution characteristics in terms of transcriptomic coordinates, e.g., to examine whether a specific type of biological feature is enriched near transcription start sites. Existing approaches for performing these tasks involve the manipulation of a gene database, conversion from genome-based coordinate to transcript-based coordinate, and visualization methods that are capable of showing RNA transcript components and distribution of the features. These steps are complicated and time consuming, and this is especially true for researchers who are not familiar with relevant tools. To overcome this obstacle, we develop a dedicated web app TARF, which represents web toolkit for annotating RNA-related genomic features. TARF web tool intends to provide a web-based way to easily annotate and visualize RNA-related genomic features. Once a user has uploaded the features with BED format and specified a built-in transcript database or uploaded a customized gene database with GTF format, the tool could fulfill its three main functions. First, it adds annotation on gene and RNA transcript components. For every features provided by the user, the overlapping with RNA transcript components are identified, and the information is combined in one table which is available for copy and download. Summary statistics about ambiguous belongings are also carried out. Second, the tool provides a convenient visualization method of the features on single gene/transcript level. For the selected gene, the tool shows the features with gene model on genome-based view, and also maps the features to transcript-based coordinate and show the distribution against one single spliced RNA transcript. Third, a global transcriptomic view of the genomic features is generated utilizing the Guitar R/Bioconductor package. The distribution of features on RNA transcripts are normalized with respect to RNA transcript landmarks and the enrichment of the features on different RNA transcript components is demonstrated. We tested the newly developed TARF toolkit with 3 different types of genomics features related to chromatin H3K4me3, RNA N6-methyladenosine (m6A) and RNA 5-methylcytosine (m5C), which are obtained from ChIP-Seq, MeRIP-Seq and RNA BS-Seq data, respectively. TARF successfully revealed their respective distribution characteristics, i.e. H3K4me3, m6A and m5C are enriched near transcription starting sites, stop codons and 5’UTRs, respectively. Overall, TARF is a useful web toolkit for annotation and visualization of RNA-related genomic features, and should help simplify the analysis of various RNA-related genomic features, especially those related RNA modifications.

Keywords: RNA-related genomic features, annotation, visualization, web server

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Authors: Xue Wang, Li-Wei Fan

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The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

Procedia PDF Downloads 56