Search results for: school based support program

Authors: Jun-Yong Lee, Hyoung-Gook Kim

Abstract:

In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

Procedia PDF Downloads 422

Authors: Dammar Bahadur Adhikari

Abstract:

Community forestry in Nepal has got disproportionately high level of support from government and other actors in forestry sector. Even though master plan for forestry sector (1989) has highlighted community and private forestry as one component, the government policies and other intervention deliberately left out private forestry in its structure and programs. The study aimed at providing the pathway for formulating appropriate policies to address need of different kind of forest management regimes in Rautahat district, Nepal. The key areas the research focused were assessment of current status of private forestry, community forest users' understanding on private forestry; criteria for choosing species of private forestry and factors affecting establishment of private forestry in the area. Qualitative and quantitative data were collected employing questionnaire survey, rapid forest assessment and key informant interview. The study found out that forest policies are imposed due to intense pressure of exogenous forces than due to endogenous demand. Most of the local people opine that their traditional knowledge and skills are not sufficient for private forestry and hence need training on the matter. Likewise, local use, market value and rotation dictate the choice of species for plantation in private forests. Currently district forest office is the only government institution working in the area of private forestry all other governmental and non-governmental organizations have condoned. private forestry. Similarly, only permanent settlers in the area are found to establish private forests other forest users such as migrants and forest encroachers follow opportunistic behavior to meet their forest product need from community and national forests. In this regard, the study recommends taking appropriate step to support other forest management system including private forestry provide community forestry the benefits of competition as suggested by Darwin in 18th century, one and half century back and to help alleviate poverty by channelizing benefits to household level.

Keywords: community forest, forest management, poverty, private forest, users’ group

Procedia PDF Downloads 335

Authors: Alaa Osman, Sara Elgazzar, Breksal Elmiligy

Abstract:

The Supply Chain Operation Reference (SCOR) model is considered one of the most widely implemented supply chain performance measurement systems (SCPMSs). Several studies have been proposed on the SCOR model adaptation in developed countries context; while there is a limited availability of previous work on the SCPMSs application generally and the SCOR model specifically in developing nations. This paper presents a research agenda on the SCOR model adaptation in the developing countries. It aims at investigating the challenges of adapting the SCOR model to manage and measure supply chain performance in developing countries. The research will exemplify the system in the Egyptian automotive sector to gain a comprehensive understanding of how the application of the SCOR model can affect the performance of automotive companies in Egypt, with a necessary understanding of challenges and obstacles faced the adaptation of the model in the Egyptian supply chain context. An empirical study was conducted on the Egyptian automotive sector in three companies considering three different classes: BMW, Hyundai and Brilliance. First, in-depth interviews were carried out to gain an insight into the implementation and the relevance of the concepts of supply chain management and performance measurement in the Egyptian automotive industry. Then, a formal survey was designed based on the SCOR model five main processes (plan, source, make, deliver and return) and best practices to investigate the challenges and obstacles faced the adaptation of the SCOR model in the Egyptian automotive supply chain. Finally, based on the survey results, the appropriate best practices for each process were identified in order to overcome the SCOR model adaptation challenges. The results showed that the implementation of the SCOR model faced different challenges and unavailability of the required enablers. The survey highlighted the low integration of end-to-end supply chain, lacks commitment for the innovative ideas and technologies, financial constraints and lack of practical training and support as the main challenges faced the adaptation of the SCOR model in the Egyptian automotive supply chain. The research provides an original contribution to knowledge by proposing a procedure to identify challenges encountered during the process of SCOR model adoption which can pave a way for further research in the area of SCPMSs adaptation, particularly in the developing countries. The research can help managers and organizations to identify obstacles and difficulties of the SCOR model adaptation, subsequently this can facilitate measuring the improved performance or changes in the organizational performance.

Keywords: automotive sector, developing countries, SCOR model, supply chain performance

Procedia PDF Downloads 364

Authors: Irtaza M. Syed, Kaameran Raahemifar

Abstract:

This paper presents comparative analysis of photovoltaic systems (PVS) and proposes practical techniques to improve operational efficiency of the PVS. The best engineering and construction practices for PVS are identified and field oriented recommendation are made. Comparative analysis of central and string inverter based, as well as 600 and 1000 VDC PVS are performed. In addition, direct current (DC) and alternating current (AC) photovoltaic (PV) module based systems are compared. Comparison shows that 1000 V DC String Inverters based PVS is the best choice.

Keywords: photovoltaic module, photovoltaic systems, operational efficiency improvement, comparative analysis

Procedia PDF Downloads 477

Authors: Dawit Hoyiso, Abinet Arega, Terefe Markos

Abstract:

Background: - In spite of all the various programs and strategies to promote the use of research finding there is still gap between theory and practice. Difference in outcomes, health inequalities, and poorly performing health service continue to present a challenge to all nurses. A number of studies from various countries have reported that nurses’ experience of evidence-based practice is low. In Ethiopia there is an information gap on the extent of evidence based nursing practice and its associated factors. Objective: - the study aims to assess the implementation of evidence based nursing practice and associated factors among nurses in Jimma zone public hospitals. Method: - Institution based cross-sectional study was conducted from March 1-30/2015. A total of 333 sampled nurses for quantitative and 8 in-depth interview of key informants were involved in the study. Semi-structured questionnaire was adapted from funk’s BARRIER scale and Friedman’s test. Multivariable Linear regression was used to determine significance of association between dependent and independent variables. Pretest was done on 17 nurses of Bedele hospital. Ethical issue was secured. Result:-Of 333 distributed questionnaires 302 were completed, giving 90.6% response rate. Of 302 participants 245 were involved in EBP activities to different level (from seldom to often). About forty five(18.4%) of the respondents had implemented evidence based practice to low level (sometimes), one hundred three (42 %) of respondents had implemented evidence based practice to medium level and ninety seven (39.6 %) of respondents had implemented evidence based practice to high level(often). The first greatest perceived barrier was setting characteristic (mean score=26.60±7.08). Knowledge about research evidence was positively associated with implementation of evidence based nursing practice (β=0.76, P=0.008). Similarly, Place where the respondent graduated was positively associated with implementation of evidence based nursing practice (β=2.270, P=0.047). Also availability of information resources was positively associated with implementation of evidence based practice (β=0.67, P= 0.006). Conclusion: -Even though larger portion of nurses in this study were involved in evidence-based practice whereas small number of participants had implemented frequently. Evidence-based nursing practice was positively associated with knowledge of research, place where respondents graduated, and the availability of information resources. Organizational factors were found to be the greatest perceived barrier. Intervention programs on awareness creation, training, resource provision, and curriculum issues to improve implementation of evidence based nursing practice by stakeholders are recommended.

Keywords: evidence based practice, nursing practice, research utilization, Ethiopia

Procedia PDF Downloads 86

Authors: Thao Thi Vu, Libby Lee-Hammond, Andrew McConney

Abstract:

In Vietnam, the Vietnamese language is normally used as the language of instruction. The dominance of this language places children who have a different first language such as Indigenous children at a disadvantage when commencing school. This study explores preschool teachers’ beliefs about second language acquisition in Lai Chau provinces where is typical of highland provinces of Vietnam and the proportion of Indigenous minority groups in high. Data were collected from surveys with both closed-end questions and opened-end questions. The participants in this study were more than 200 public preschool teachers who come from eight different districts in Lai Chau. An analysis of quantitative data survey is presented to indicate several practical implications, such as the connection between teachers’ knowledge background that gained from their pre-service and in-service teacher education programs regarding second language teaching for Indigenous children and their practice. It also explains some factors that influence teachers’ beliefs and perspective about Indigenous children and pedagogies in their classes.

Keywords: indigenous children, learning Vietnamese, preschool, teachers’ beliefs

Procedia PDF Downloads 415

Authors: Camille Rault, Mark Bahr

Abstract:

The aim of the present study was to develop a contemporaneous instrument measuring adolescent’s subjective well-being (SWB). The instrument development underwent a three-phase pilot study. Phase one (N = 31) used a qualitative approach to generate domains of SWB relevant to adolescents. During the second phase (N = 22), items were tested targeting these domains. Finally, the third phase (N = 22) assisted in addition, deletion and refinement according to the first two phases of the pilot. A total of 49 items were retained for the final version of the instrument. The Contemporary Adolescent Well-Being Scale (CAWBS) was administered to 1071 school children (599 girls) aged between ten to 18 years old (M = 14,70; SD = 1.45) from Queensland, Australia. Results confirmed the seven-factor construct hypothesized and explained 45% of the variance. The questionnaire pertained to seven domains of adolescent’s SWB, namely; Overall life satisfaction; Bullying; Body image; Social connectedness; Activities; Control appraisal; and Negative feelings. Reliability was shown to be acceptable with Cronbach’s alpha ranging from .58 to .89. Future research should refine the CAWBS and investigate the psychometric properties of this instrument.

Keywords: adolescence, construct validity, instrument, subjective well-being

Procedia PDF Downloads 263

Authors: Harsh Thakkar, Ganesh Iyer

Abstract:

In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

Procedia PDF Downloads 314

Authors: Suha Alawadhi, Malak Alrasheed

Abstract:

In the recent past, public participation in governments has been declined to a great extent, as citizens have been isolated from community life and their ability to articulate demands for good government has been noticeably decreased. However, the Internet has introduced new forms of interaction that could enhance different types of relationships, including government-public relationship. In fact, technology-enabled government has become a catalyst for enabling social inclusion. This exploratory study seeks to investigate public perceptions in Kuwait regarding the use of social media networks in government where social capital is built to achieve social inclusion. Social capital has been defined as social networks and connections amongst individuals, that are based on shared trust, ideas and norms, enable participants of a network to act effectively to pursue a shared objective. The quantitative method was used to generate empirical evidence. A questionnaire was designed to address the research objective and reflect the identified constructs: social capital dimensions (bridging, bonding and maintaining social capital), social inclusion, and social equality. In this pilot study, data was collected from a random sample of 61 subjects. The results indicate that all participants have a positive attitude towards the dimensions of social capital (bridging, bonding and maintaining), social inclusion and social equality constructs. Tests of identified constructs against demographic characteristics indicate that there are significant differences between male and female as they perceived bonding and maintaining social capital, social inclusion and social equality whereas no difference was identified in their perceptions of bridging social capital. Also, those who are aged 26-30 perceived bonding and maintaining social capital, social inclusion and social equality negatively compared to those aged 20-25, 31-35, and 40-above whose perceptions were positive. With regard to education, the results also show that those holding high school, university degree and diploma perceived maintaining social capital positively higher than with those who hold graduate degrees. Moreover, a regression model is proposed to study the effect of bridging, bonding, and maintaining social capital on social inclusion via social equality as a mediator. This exploratory study is necessary for testing the validity and reliability of the questionnaire which will be used in the main study that aims to investigate the perceptions of individuals towards building social capital to achieve social inclusion.

Keywords: government, social capital, social inclusion, social networks

Procedia PDF Downloads 319

Authors: Maged Assem Soliman Mossallam

Abstract:

Thermal vacuum testing target is to qualify the space system and ensure its operability under harsh space environment. The functionality of the cubesat was checked at extreme orbit conditions. Test was performed for operational and nonoperational modes. Analysis is done to simulate the cubesat thermal cycling inside thermal vacuum chamber. Comsol Multiphysics finite element is used to solve three dimensional problem for the cubesat inside TVAC. Three dimensional CAD model is done using Autodesk Inventor program. The boundary conditions were applied from the actual shroud temperature. The input heat load variation with time is considered to solve the transient three dimensional problem. Results show that the simulated temperature profiles are within an acceptable range from the real testing data.

Keywords: cubesat, thermal vacuum test, testing simulation, finite element analysis

Procedia PDF Downloads 138

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

Abstract:

Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

Procedia PDF Downloads 112

Authors: Z. Zerdoumi, D. Benatia, , D. Chicouche

Abstract:

This paper investigates the application of artificial neural network to the problem of nonlinear channel equalization. The difficulties caused by channel distortions such as inter symbol interference (ISI) and nonlinearity can overcome by nonlinear equalizers employing neural networks. It has been shown that multilayer perceptron based equalizer outperform significantly linear equalizers. We present a multilayer perceptron based equalizer with decision feedback (MLP-DFE) trained with the back propagation algorithm. The capacity of the MLP-DFE to deal with nonlinear channels is evaluated. From simulation results it can be noted that the MLP based DFE improves significantly the restored signal quality, the steady state mean square error (MSE), and minimum Bit Error Rate (BER), when comparing with its conventional counterpart.

Keywords: Artificial Neural Network, signal restoration, Nonlinear Channel equalization, equalization

Procedia PDF Downloads 491

Authors: Ahmed Tarek, Ahmed Alveed

Abstract:

Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

Procedia PDF Downloads 143

Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

Abstract:

Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometer long pipe with 7.9 kilometers as pumping main and 5.1 kilometers as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

Procedia PDF Downloads 360

Authors: Hitesh Tahbildar

Abstract:

The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

Procedia PDF Downloads 397

Authors: Mohamed Majrashi, Patricia Connolly, Terry Gourlay

Abstract:

Cardiopulmonary bypass is known to cause inflammatory response during open heart surgery. It includes the initiation of different cascades such as coagulation, complement system and cytokines. Although the immune system is body’s key defense mechanism against external assault, when overexpressed, it can be injurious to the patient, particularly in a cohort of patients in which there is a heightened and uncontrolled response. The inflammatory response develops in these patients to an exaggerated level resulting in an autoimmune injury and may lead to poor postoperative outcomes (systemic inflammatory response syndrome and multi-organs failure). Previous studies by this group have suggested a correlation between the level of IL6 measured in patient’s blood before surgery and after polymeric activation and the observed inflammatory response during surgery. Based upon these findings, the present work is aimed at using this response to develop a test which can be used prior to the open heart surgery to identify the high-risk patients before their operation. The work will be accomplished via three main clinical phases including some pilot in-vitro studies, device development and clinical investigation. Current findings from studies using animal blood, employing DEHP and DEHP plasticized PVC materials as the activator, support the earlier results in patient samples. Having established this relationship, ongoing work will focus on developing an activated lateral flow strip technology as a screening device for heightened inflammatory propensity.

Keywords: cardiopulmonary bypass, cytokines, inflammatory response, overexpression

Procedia PDF Downloads 278

Authors: Marcelo Sifuentes López

Abstract:

Strategic performance definition and follow-up processes have to be clear in order to provide value in today’s competitive world. Customer expectations must be linked to internal organization strategic objectives leading to profitability and supported by visibility and flexibility among others.By taking a whole picture of the supply chain, the executive, and its team will define the current supply chain situation and an insight into potential opportunities to improve processes and provide value to main stakeholders. A systematic performance evaluation process based on operational and financial indicators defined by customer requirements needs to be implemented and periodically reviewed in order to mitigate costs and risks on time.Supplier long term relationship and collaboration plays a key role using resources available, real-time communication, innovation and new ways to capitalize global opportunities like emerging markets; efforts have to focus on the reduction of uncertainties in supply and demand. Leadership has to promote consistency of communication and execution involving suppliers, customers, and the entire organization through the support of a strategic sourcing methodology that assure the targeted competitive strategy and sustainable growth. As customer requirements and expectations are met, results could be captured in a casual picture like a “selfie”; where outcomes could be perceived from any desired angle by them; or like most “selfies”, can be taken with a camera held at arm's length by a third party company rather than using a self-timer.

Keywords: supply chain management, competitive advantage, value creation, collaboration and innovation, global marketplace

Procedia PDF Downloads 434

Authors: Yanchun Zuo, Yingao Liu, Wei Liu, Le Yu, Run Huang, Lixin Guo

Abstract:

Electric field detection is important in many application scenarios. The traditional strategy is measuring the electric field with a man walking around in the area under test. This strategy cannot provide a satisfactory measurement accuracy. To solve the mentioned problem, an autopilot measurement system is divided. A mini-car is produced, which can travel in the area under test according to respect to the program within the CPU. The electric field measurement platform (EFMP) carries a central computer, two horn antennas, and a vector network analyzer. The mini-car stop at the sampling points according to the preset. When the car stops, the EFMP probes the electric field and stores data on the hard disk. After all the sampling points are traversed, an electric field map can be plotted. The proposed system can give an accurate field distribution description of the chamber.

Keywords: autopilot mini-car measurement system, electric field detection, field map, static zone measurement

Procedia PDF Downloads 96

Authors: María José Bugueño, Natalia Jaime, Cristian Castro, Diego Naranjo, Guido Trautmann, Mario Pérez-Won, Vilbett Briones-Labarca

Abstract:

Proteins play a crucial role in various prepared foods, including dairy products, drinks, emulsions, and ready meals. These food proteins are naturally present in food waste and byproducts. The alkaline extraction and acid precipitation method is commonly used to extract proteins from plants and animals due to its product stability, cost-effectiveness, and ease of use. This study aimed to investigate the impact of pH-shifting storage at two different pH levels on the conformational changes affecting the physicochemical and functional properties of quinoa protein isolate (QPI) and yellow shrimp byproduct protein isolate (YSPI). The QPI and YSPI were extracted using the alkaline extraction-isoelectric precipitation method. The dispersions were adjusted to pH 4 or 12, stirred for 2 hours at 20°C to achieve a uniform dispersion, and then freeze-dried. Various analyses were conducted, including flexibility (F), free sulfhydryl content (Ho), emulsifying activity (EA), emulsifying capacity (EC), water holding capacity (WHC), oil holding capacity (OHC), intrinsic fluorescence, ultraviolet spectroscopy, differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FTIR) to assess the properties of the protein isolates. pH-shifting at pH 11 and 12 for QPI and YSPI, respectively, significantly improved protein properties, while property modification of the samples treated under acidic conditions was less pronounced. Additionally, the pH 11 and 12 treatments significantly improved F, Ho, EA, WHC, OHC, intrinsic fluorescence, ultraviolet spectroscopy, DSC, and FTIR. The increase in Ho was due to disulfide bond disruption, which produced more protein sub-units than other treatments for both proteins. This study provides theoretical support for comprehensively elucidating the functional properties of protein isolates, promoting the application of plant proteins and marine byproducts. The pH-shifting process effectively improves the emulsifying property and stability of QPI and YSPI, which can be considered potential plant-based or marine byproduct-based emulsifiers for use in the food industry.

Keywords: quinoa protein, yellow shrimp by-product protein, physicochemical properties, structural properties

Procedia PDF Downloads 27

Authors: Xingyu Gao, Qiang Wu

Abstract:

Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

Procedia PDF Downloads 38

Authors: Aadita Chaudhury

Abstract:

Since at least the early 2000s, DNA profiling has achieved a preeminent status in forensic investigations into criminal acts. While the criminal justice system has a long history of using forensic evidence and testing them through establish technoscientific means, the primacy of DNA in establishing 'truth' or reconstructing a series of events is unparalleled in the history of forensic science. This paper seeks to elucidate the ways in which DNA profiling has become the most authoritative instrument of 'truth' in criminal investigations, and how it is used in the legal process to ascertain culpability, create the notion of infallible evidence, and advance the search for justice. It is argued that DNA profiling has created a paradigm shift in how the legal system and the general public understands crime and culpability, but not without limitations. There are indications that even trace amounts of DNA evidence can point to causal links in a criminal investigation, however, there still remains many rooms to create confusion and doubt from empirical evidence within the narrative of crimes. Many of the shortcomings of DNA-based forensic investigations are explored and evaluated with regards to claims of the authority of biological evidence and implications for the public understanding of the elusive concepts of truth and justice in the present era. Public misinformation about the forensic analysis processes could produce doubt or faith in the judgements rooted in them, depending on other variables presented at the trial. A positivist understanding of forensic science that is shared by the majority of the population does not take into consideration that DNA evidence is far from definitive, and can be used to support any theories of culpability, to create doubt and to deflect blame.

Keywords: DNA profiling, epistemology of forensic science, philosophy of forensic science, sociology of scientific knowledge

Procedia PDF Downloads 199

Authors: Maryam Meftahi, Yashar Hamidzadeh

Abstract:

In recent decades, the amount of solid waste production has been rising. In the meantime, plastic waste is one of the major parts of urban solid waste, so, recycling plastic waste from water bottles has become a serious challenge in the whole world. The experimental program includes the study of the effect of waste plastic fibers on maximum dry density (MDD), optimum moisture content (OMC) with different sizes and contents. Also, one dimensional consolidation tests were carried out to evaluate the benefit of utilizing randomly distributed waste plastics fiber to improve the engineering behavior of a tested soils. Silty soil specimens were prepared and tested at five different percentages of plastic waste content (i.e. 0.25%, 0.50%, 0.75%, 1% and 1.25% by weight of the parent soil). The size of plastic chips used, are 4 mm, 8 mm and 12 mm long and 4 mm in width. The results show that with the addition of waste plastic fibers, the MDD and OMC and also the compressibility of soil decrease significantly.

Keywords: silty soil, waste plastic, compaction, consolidation, reinforcement

Procedia PDF Downloads 167

Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

Abstract:

Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

Procedia PDF Downloads 41

Authors: Amber Hatch, Eric Wright, Feihong Wang

Abstract:

Research suggests that attachment in close relationships affects one’s emotional processes, mindfulness, conflict-management behaviors, and interpersonal interactions. Attachment insecurity is often associated with maladaptive social interactions and suboptimal relationship qualities. Past studies have considered how the nature of emotion regulation and mindfulness in teachers may be related to student or classroom outcomes. Still, no research has examined how the relationship between such internal experiences and classroom management outcomes may also be related to teachers’ attachment insecurity. This study examined the interrelationships between teachers’ attachment insecurity, mindfulness tendencies, emotion regulation abilities, and classroom management efficacy as indexed by students’ classroom behavior and teachers’ response effectiveness. Teachers’ attachment insecurity was evaluated using the global ECRS-SF, which measures both attachment anxiety and avoidance. The present study includes a convenient sample of 357 American elementary school teachers who responded to a survey regarding their classroom management efficacy, attachment in/security, dispositional mindfulness, emotion regulation strategies, and difficulties in emotion regulation, primarily assessed via pre-existing instruments. Good construct validity was demonstrated for all scales used in the survey. Sample demographics, including gender (94% female), race (92% White), age (M = 41.9 yrs.), years of teaching experience (M = 15.2 yrs.), and education level were similar to the population from which it was drawn, (i.e., American elementary school teachers). However, white women were slightly overrepresented in our sample. Correlational results suggest that teacher attachment insecurity is associated with poorer classroom management efficacy as indexed by students’ disruptive behavior and teachers’ response effectiveness. Attachment anxiety was a much stronger predictor of adverse student behaviors and ineffective teacher responses to adverse behaviors than attachment avoidance. Mindfulness, emotion regulation abilities, and years of teaching experience predicted positive classroom management outcomes. Attachment insecurity and mindfulness were more strongly related to frequent adverse student behaviors, while emotion regulation abilities were more strongly related to teachers’ response effectiveness. The teaching experience was negatively related to attachment insecurity and positively related to mindfulness and emotion regulation abilities. Although the data were cross-sectional, path analyses revealed that attachment insecurity is directly related to classroom management efficacy. Through two routes, this relationship is further mediated by emotion regulation and mindfulness in teachers. The first route of indirect effect suggests double mediation by teacher’s emotion regulation and then teacher mindfulness in the relationship between teacher attachment insecurity and classroom management efficacy. The second indirect effect suggests mindfulness directly mediated the relationship between attachment insecurity and classroom management efficacy, resulting in improved model fit statistics. However, this indirect effect is much smaller than the double mediation route through emotion regulation and mindfulness in teachers. Given the significant predication of teacher attachment insecurity, mindfulness, and emotion regulation on teachers’ classroom management efficacy both directly and indirectly, the authors recommend improving teachers’ classroom management efficacy via a three-pronged approach aiming at enhancing teachers’ secure attachment and supporting their learning adaptive emotion regulation strategies and mindfulness techniques.

Keywords: Classroom management efficacy, student behavior, teacher attachment, teacher emotion regulation, teacher mindfulness

Procedia PDF Downloads 80

Authors: Gi-Beom Park, Hyong-Gi Park, Seong-Yong Lee, Jaeho Choi, Seok Hong Min, Tae Kwon Ha

Abstract:

The Nb silicide-based alloy has the excellent high-temperature strength and relatively lower density than the Ni-based superalloy; therefore, it has been receiving a lot of attention for the next generation high-temperature material. To enhance the high temperature creep property and oxidation resistance, Si was added to the Nb-based alloy, resulting in a multi-phase microstructure with metal solid solution and silicide phase. Since the silicide phase has a low machinability due to its brittle nature, it is necessary to fabricate components using the powder metallurgy. However, powder manufacturing techniques for the alloys have not yet been developed. In this study, we tried to fabricate Nb-based alloy powder by the hydrogenation-dehydrogenation reaction. The Nb-based alloy ingot was prepared by vacuum arc melting and it was annealed in the hydrogen atmosphere for the hydrogenation. After annealing, the hydrogen concentration was increased from 0.004wt% to 1.22wt% and Nb metal phase was transformed to Nb hydride phase. The alloy after hydrogenation could be easily pulverized into powder by ball milling due to its brittleness. For dehydrogenation, the alloy powders were annealed in the vacuum atmosphere. After vacuum annealing, the hydrogen concentration was decreased to 0.003wt% and Nb hydride phase was transformed back to Nb metal phase.

Keywords: Nb alloy, Nb metal and silicide composite, powder, hydrogenation-dehydrogenation reaction

Procedia PDF Downloads 240

Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

Abstract:

This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

Procedia PDF Downloads 347

Authors: Baldev Setia, Raj Rajeshwari, Maneesh Kumar

Abstract:

Present paper is an analysis of water transmission mains failed due to surge analysis by using basic software known as Surge Analysis Program (SAP). It is a real time failure case study of a pipe laid in Una, Himachal Pradesh. The transmission main is a 13 kilometres long pipe with 7.9 kilometres as pumping main and 5.1 kilometres as gravitational main. The analysis deals with mainly pumping mains. The results are available in two text files. Besides, several files are prepared with specific view to obtain results in a graphical form. These results help to observe the pressure difference and surge occurrence at different locations along the pipe profile, which help to redesign the transmission main with different but suitable safety measures against possible surge. A technically viable and economically feasible design has been provided as per the relevant manual and standard code of practice.

Keywords: surge, water hammer, transmission mains, SAP 2000

Procedia PDF Downloads 396

Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

Abstract:

Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

Procedia PDF Downloads 68

Authors: Georgios Alexandropoulos

Abstract:

The purpose of this study is to examine the historical text of Alexiad by Anna Comnena using computational tools for the extraction of lexical bundles containing the name of her father, Alexius Comnenus. For this reason, in this research we apply corpus linguistics techniques for the automatic extraction of lexical bundles and through them we will draw conclusions about how these lexical bundles serve her support provided to her father.

Keywords: lexical bundles, computational literature, critical discourse analysis, Alexiad

Procedia PDF Downloads 613

Authors: Venkateswara R. Naira, Debasish Das, Soumen K. Maiti

Abstract:

Achieving high cell densities of microalgae under obligatory light-limiting and high light conditions of diurnal (low-high-low variations of daylight intensity) sunlight are further limited by CO₂ supply and dissolved oxygen (DO) accumulation in large-scale photobioreactors. High DO levels cause low growth due to photoinhibition and/or photorespiration. Hence, scalable elevated CO₂ levels (% in air) and their effect on DO accumulation in a 10 L cylindrical membrane photobioreactor (a vertical tubular type) are studied in the present study. The CO₂ elevation strategies; biomass-based, pH control based (types II & I) and diurnal light based, were explored to study the growth of Chlorella sp. FC2 IITG under single-sided LED lighting in the laboratory, mimicking diurnal sunlight. All the experiments were conducted in fed-batch mode by maintaining N and P sources at least 50% of initial concentrations of the optimized BG-11 medium. It was observed that biomass-based (2% - 1st day, 2.5% - 2nd day and 3% - thereafter) and well-known pH control based, type-I (5.8 pH throughout) strategies were found lethal for FC2 growth. In both strategies, the highest peak DO accumulation of 150% air saturation was resulted due to high photosynthetic activity caused by higher CO₂ levels. In the pH control based type-I strategy, automatically resulted CO₂ levels for pH control were recorded so high (beyond the inhibition range, 5%). However, pH control based type-II strategy (5.8 – 2 days, 6.3 – 3 days, 6.7 – thereafter) showed final biomass titer up to 4.45 ± 0.05 g L⁻¹ with peak DO of 122% air saturation; high CO₂ levels beyond 5% (in air) were recorded thereafter. Thus, it became sustainable for obtaining high biomass. Finally, a diurnal light based (2% - low light, 2.5 % - medium light and 3% - high light) strategy was applied on the basis of increasing/decreasing photosynthesis due to increase/decrease in diurnal light intensity. It has resulted in maximum final biomass titer of 5.33 ± 0.12 g L⁻¹, with total biomass productivity of 0.59 ± 0.01 g L⁻¹ day⁻¹. The values are remarkably higher than constant 2% CO₂ level (final biomass titer: 4.26 ± 0.09 g L⁻¹; biomass productivity: 0.27 ± 0.005 g L⁻¹ day⁻¹). However, 135% air saturation of peak DO was observed. Thus, the diurnal light based elevation should be further improved by using CO₂ enriched N₂ instead of air. To the best of knowledge, the light-based CO₂ elevation strategy is not reported elsewhere.

Keywords: Chlorella sp., CO₂ elevation strategy, dissolved oxygen accumulation, diurnal light based CO₂ elevation, high cell density, microalgae, scale-up

Procedia PDF Downloads 121