Search results for: traditional knowledge resources classification

Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Alif Nur Irvan, M. Varaby Wahyu

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Indonesia is a country that have a lot of natural resources and as one of the most populous people in the world. In the last few years, the world economic is growing rapid, and then Indonesia must be able to develop his economy like the other country. The number of graduates in Indonesia always increase every year and the employment in Indonesia is getting decreased, this situation leads to rise unemployment in Indonesia. Limited employment makes people look for the ways to live decently. From this situation, entrepreneurs become an alternative in Indonesia to develop the economy. Being an entrepreneur means being able to find opportunities to utilize existing resources to take advantage of these opportunities. With the increasing number of entrepreneurs in Indonesia can increase employment, improve the quality of life, income distribution, utilize and mobilize resources to improve national productivity, and improve the welfare of government. The main sources for economic growth are the investments that improve the quality of capital or human resources, which in turn managed to increase the quantity of productive resources and can raise the productivity of all resources through new discoveries, innovations, creativity and technological progress. This paper is talking about the topic, discussions, and it offers the solutions to support entrepreneurs in Indonesia, and also talk about entrepreneurial problems that occurred in Indonesia, and the right solution to solve the problems of entrepreneurship in Indonesia and also discusses the role of government to support entrepreneurship to encourage the economy in Indonesia.

Keywords: entrepreneurship, economy, employment, government

Procedia PDF Downloads 282

Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Levent Taylan Ozgur Yildirim, Qihao Qian, John Yilin Wang

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A critical review of assessments of geological carbon dioxide (CO2) storage resources in Pennsylvania and the surrounding region was completed with a focus on the studies of Midwest Regional Carbon Sequestration Partnership (MRCSP), United States Department of Energy (US-DOE), and United States Geological Survey (USGS). Pennsylvania Geological Survey participated in the MRCSP Phase I research to characterize potential storage formations in Pennsylvania. The MRCSP’s volumetric method estimated ~89 gigatonnes (Gt) of total CO2 storage resources in deep saline formations, depleted oil and gas reservoirs, coals, and shales in Pennsylvania. Meanwhile, the US-DOE calculated storage efficiency factors using log-odds normal distribution and Monte Carlo sampling, revealing contingent storage resources of ~18 Gt to ~20 Gt in deep saline formations, depleted oil and gas reservoirs, and coals in Pennsylvania. Additionally, the USGS employed Beta-PERT distribution and Monte Carlo sampling to determine buoyant and residual storage efficiency factors, resulting in 20 Gt of contingent storage resources across four storage assessment units in Appalachian Basin. However, few studies have explored CO2 storage resources in shales in the region, yielding inconclusive findings. This article provides a critical and most up to date review and analysis of geological CO2 storage resources in Pennsylvania and the region.

Keywords: carbon capture and storage, geological CO2 storage, pennsylvania, appalachian basin

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Authors: A. Deswal, N. S. Deora, H. N. Mishra

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The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyse spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modelling by class analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable counts showed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20 hours and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Keywords: electronic-nose, bacteriological, shelf-life, classification

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Authors: Babar Khan, Wang Zhijie

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Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric.

Keywords: automatic classification, texture descriptor, colour descriptor, opponent colour channel

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Authors: Eugen Neagoe, Victor Balanica

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A Smart Building Controller (SBC) is a server software that offers secured access to a pool of building specific resources, executes monitoring tasks and performs automatic administration of a building, thus optimizing the exploitation cost and maximizing comfort. This paper brings to discussion the issues that arise with the secure exploitation of the SBC administered resources and proposes a technical solution to implement a robust secure access system based on roles, individual rights and privileges (special rights).

Keywords: smart building controller, software security, access rights, access authorization

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Reza Shakoori

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This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.

Keywords: Arabic, chain code normalization, OCR systems, image processing

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Authors: Shahnaz Bashir, Abel Usoro, Imran Khan

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Hofstede’s culture model is an important model to study culture between different societies. He collected data from world-wide and performed a comprehensive study. Hofstede’s cultural model is widely accepted and has been used to study cross cultural influences in different areas like cross-cultural psychology, cross cultural management, information technology, and intercultural communication. This study investigates the societal cultural aspects of knowledge sharing in virtual communities.

Keywords: knowledge management, knowledge sharing, societal culture, virtual communities

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Authors: Manisha Ohlan, Manju Dahiya

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The present study was conducted in Karnal, Rohtak, and Jhajjar districts of Haryana state, covering 360 respondents. Results showed that 42.78 percent of the respondents had above average knowledge at the preparation stage followed by 48.33 percent of the respondents who had high knowledge at the production stage, and 37.22 percent of the respondents had average knowledge at the processing stage regarding the usage of digital technologies. Nearly half of the respondents (47.50%) agreed with the usage of digital technologies, followed by strongly agreed (19.45%) and strongly disagreed (14.45%). A significant and positive relationship was found between independent variables and knowledge and of digital technologies at 5 percent level of significance. Therefore, the null hypothesis cannot be rejected. All the dependent variables, including knowledge and attitude, had a significant and positive relationship with z value at 5 percent level of significance, which showed that it is between -1.96 to +1.96; therefore, the data falls between the acceptance region, that’s why the null hypothesis is accepted.

Keywords: knowledge, attitude, digital technologies, significant, positive relationship

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

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This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: Jasna Milošević Đorđević, Jelisaveta Blagojević, Jovana Timotijević, Alison Mckinley

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Young people in Serbia, have grown up in turbulent times during the Balkan wars, in a cultural and economic isolation without adequate education on (ethnic, gender, social,..) equality. They often have very strong patriarchal gender stereotypes. The perception of gender in Serbia is still heavily influenced by traditional worldview and young people have little opportunity in traditional educational system to challenge it, receiving no formal sex education. Educational policies have addressed achieving gender equality as one of the goals, supporting all young people to gain better educational opportunities, but there are obvious shortcomings of the official education system in implementation of those goals. Therefore new approaches should be implemented. We evaluate the impact of non traditional approach, such as participatory theatre performance with strong transformative potential, especially in relation to gender issues. Theatre based intervention (TBI) was created to provoke the young people to become aware of their gender constructs. Engaging young people in modern form of education such as transformative gender intervention through participatory theatre could have positive impact on their sex knowledge and understanding gender roles. The transformative process in TBI happens on two levels – the affective and the cognitive. The founding agency of the project and evaluation is IPPF. The most important aim of this survey is evaluation of the transformative TBI, as a new educational approach related to better understanding gender as social construct. To reach this goal, we have measured attitude change in three indicators: a) gender identity/ perception of feminine identity, perception of masculine identity, importance of gender for personal identity, b) gender roles on the labor market, c) Gender equality in partnership & sexual behavior. Our main hypothesis is that participatory theatre-based intervention can have a transformational potential in challenging traditional gender knowledge and attitudes among youth in Serbia. To evaluate the impact of TB intervention, we implement: online baseline and end-line survey with nonparticipants of the TBI on the representative sample in targeted towns (control group). Additionally we conducted testing the experimental group twice: pretest at the beginning of each TBI and post testing of participants after the play. A sample of 500 respondents aged 18-30 years, from 9 towns in Serbia responded to online questionnaire in September 2017, in a baseline research. Pre and post measurement of all tested variables among participants in nine towns would be performed. End-line survey with 500 respondents would be conducted at the end of the project (early year 2018). After the first TBI (60 participants) no impact was detected on measured indicators: perception of desirable characteristics of man F(1,59)= 1.291, p=.260; perception of desirable characteristics of women F(1,55)=1.386, p= .244; gender identity importance F(1,63)= .050, p=.824; sex related behavior F(1,61)=1,145, p=.289; gender equality on labor market F(1,63)=.076, p=.783; gender equality in partnership F(1,61)=.201, p=.656; However, we hope that following intervention would bring more data showing that participatory theatre intervention explaining gender as a social construct could have additional positive impact in traditional educational system.

Keywords: educational impact, gender identity, gender role, participatory theatre based intervention

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Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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The proliferation of mobile devices in society enables the media to disseminate information and knowledge more rapidly. Higher education students access these contents and share them with each other, in the most diverse platforms, allowing the ubiquity in access to information. This article presents the results and respective quantitative analysis of a survey applied to communication students of two higher education institutions: one in Portugal and another in Spain. The results show that, in this sample, higher education students regularly access news content believing traditional news sources to be more credible. Regarding online sources, it was verified that the access was mostly to free news contents. This study intends to promote the knowledge about the changes that occur in the relationship of higher education students with the media, characterizing how news consumption is processed by these students, considering the resulting effects of the digital media evolution. It is intended to present not only the news sources they use, but also to know some of their habits and relationship with the news media.

Keywords: students' perceptions, communication design, mass media, higher education, digital media

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Authors: Salman Ali Nisar, Koshi Suzuki

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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.

Keywords: construction project management, critical path method, project scheduling, precedence diagram method

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

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Authors: Tatyana Gavrilova, Vadim Onufriev

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Knowledge-based systems’ design requires the developer’s owning the advanced analytical skills. The efficient development of that skills within university courses needs a deep understanding of main pitfalls and drawbacks, which students usually make during their analytical work in form of visual modeling. Thus, it was necessary to hold an analysis of 5-th year students’ learning exercises within courses of 'Intelligent systems' and 'Knowledge engineering' in Saint-Petersburg Polytechnic University. The analysis shows that both lack of system thinking skills and methodological mistakes in course design cause the errors that are discussed in the paper. The conclusion contains an exploration of the issues and topics necessary and sufficient for the implementation of the improved practices in educational design for future curricula of teaching programs.

Keywords: knowledge based systems, knowledge engineering, students’ errors, visual modeling

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Authors: Prabha Rohatgi

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To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Abdulnasser Ahmed Haza’a, Marzoq Ali Odhah, Saddam Ahmed Al-Ahdal, Abdulfatah Saleh Al-Jaradi, Gamil Ghaleb Alrubaiee

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Patient safety in hospitals is an essential professional indicator that should be noticed. The threat of fires is potentially the most dangerous risk that could harm patients and personnel. The aim of the study is to assess the knowledge of operating room (OR) staff toward prevention and control sources of fires. Between March 1 and March 30, 2022, data collection was done. A descriptive cross-sectional study was conducted. The sample of the study consisted of 89 OR staff from different governmental hospitals. Convenient sampling was applied to select the sample size. Official approvals were obtained from selected settings for start collection data. Data were collected using a close-ended questionnaire and tested for knowledge. This study was conducted in four governmental hospitals in Sana'a, Yemen. Most of the OR staff were male. Of these, 50.6% of them were operation technician professionals. More than two-thirds of OR staff have less than ten years of experience; 93% of OR staff had inadequate knowledge of sources of fires, and inadequate knowledge of them toward controls and prevention of fires (73%, 79.8%), respectively; 77.5% of OR staff had inadequate knowledge of prevention and control sources of fires. The study concluded that most of OR staff had inadequate knowledge of sources, controls, and prevention of fires, while 22.5% of them had adequate knowledge of prevention and control sources of fires. We recommended the implementation of training programs toward sources, controls, and prevention of fires or related workshops in their educational planning for OR staff of hospitals.

Keywords: knowledge, operation rooms staff, fires, prevention

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Authors: Abdelmessih Malak Sadek Labib

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Ceramic materials are known for their stability in harsh environments and excellent electrical, mechanical, and thermal properties. They have been widely used in various applications despite the emergence of new materials such as plastics and composites. However, ceramics are often brittle, which can lead to catastrophic failure. The fragility of ceramics and the mechanisms behind their failure have been a topic of extensive research, particularly in load-bearing applications like veneers. Porcelain, a type of traditional pottery, is commonly used in such applications. Traditional pottery consists of clay, silica, and feldspar, and the presence of quartz in the ceramic body can lead to microcracks and stress concentrations. The mullite hypothesis suggests that the strength of porcelain can be improved by increasing the interlocking of mullite needles in the ceramic body. However, there is a lack of reports on Young's moduli in the literature, leading to erroneous conclusions about the mechanical behavior of porcelain. This project aims to investigate the role of quartz and mullite on the mechanical strength of various porcelains while considering factors such as particle size, flexural strength, and fractographic forces. Research Aim: The aim of this research project is to assess the role of quartz and mullite in enhancing the mechanical strength of different porcelains. The project will also explore the effect of reducing particle size on the properties of porcelain, as well as investigate flexural strength and fractographic techniques. Methodology: The methodology for this project involves using scientific expressions and a mix of modern English to ensure the understanding of all attendees. It will include the measurement of Young's modulus and the evaluation of the mechanical behavior of porcelains through various experimental techniques. Findings: The findings of this study will provide a realistic assessment of the role of quartz and mullite in strengthening and reducing the fragility of porcelain. The research will also contribute to a better understanding of the mechanical behavior of ceramics, specifically in load-bearing applications. Theoretical Importance: The theoretical importance of this research lies in its contribution to the understanding of the factors influencing the mechanical strength and fragility of ceramics, particularly porcelain. By investigating the interplay between quartz, mullite, and other variables, this study will enhance our knowledge of the properties and behavior of traditional ceramics. Data Collection and Analysis Procedures: Data for this research will be collected through experiments involving the measurement of Young's modulus and other mechanical properties of porcelains. The effects of quartz, mullite, particle size, flexural strength, and fractographic forces will be examined and analyzed using appropriate statistical techniques and fractographic analysis. Questions Addressed: This research project aims to address the following questions: (1) How does the presence of quartz and mullite affect the mechanical strength of porcelain? (2) What is the impact of reducing particle size on the properties of porcelain? (3) How do flexural strength and fractographic forces influence the behavior of porcelains? Conclusion: In conclusion, this research project aims to enhance the understanding of the role of quartz and mullite in strengthening and reducing the fragility of porcelain. By investigating the mechanical properties of porcelains and considering factors such as particle size, flexural strength, and fractographic forces, this study will contribute to the knowledge of traditional ceramics and their potential applications. The findings will have practical implications for the use of ceramics in various fields.

Keywords: stability, harsh environments, electrical, techniques, mechanical disadvantages, materials

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Authors: Zahra A. Barzegar, Maryam B. Golboo

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In this paper, the manner of obtaining hierarchies and privacy entry of traditional houses in providing a safe place in the city of Shiraz will be evaluated by qualitative–descriptive methods and 6 old houses are the case study. The houses of Shiraz, as the houses in other cities in Iran are a response to climate and physical features. The old part of Shiraz has a compressed and dense texture in which the houses are in narrow and tight alleys. In this regard, the principles of traditional house entrance design have been introduced. The results show that every house has a private entrance. Direction of the entry of most houses is toward the south and with a turn to the South-East side. Entrance to yard path in all the cases is not straight, and this had been done by using 90 degrees rotates of the corridor leading to the yard. Vestibule provides a private place for the house and entrance stairway to the rooftop is located inside it.

Keywords: entrance, components of entrance, hierarchy, frontage, Shiraz houses

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Authors: Farouk Shehu Abdulwahab

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The concept of farmer-farmer knowledge sharing was introduced to bridge the extension worker-farmer ratio gap in developing countries. However, the idea was poorly accepted, especially in typical agrarian communities. Therefore, the study explores the concept of a farmer-to-farmer knowledge-sharing network to enhance extension service delivery. The study collected data from 80 farmers randomly selected through a series of multiple stages. The Data was analysed using a 5-point Likert scale and descriptive statistics. The Likert scale results revealed that 62.5% of the farmers are satisfied with farmer-to-farmer knowledge-sharing networks. Moreover, descriptive statistics show that lack of capacity building and low level of education are the most significant problems affecting farmer-farmer sharing networks. The major implication of these findings is that the concept of farmer-farmer knowledge-sharing networks can work better for farmers in developing countries as it was perceived by them as a reliable alternative for information sharing. Therefore, the study recommends introducing incentives into the concept of farmer-farmer knowledge-sharing networks and enhancing the capabilities of farmers who are opinion leaders in the farmer-farmer concept of knowledge-sharing to make it more sustainable.

Keywords: agricultural productivity, extension, farmer-to-farmer, livelihood, technology transfer

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Authors: Izdihar Ismail, Alona C. Linatoc, Maryati Mohamed

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The tropical rainforest of Malaysia is known for its rich biological diversity and high endemicity. The potential for these forests to hold the cure for many diseases and illnesses is high and much is yet to be discovered. This study explores the richness of the tropical rainforest of Endau-Rompin National Park in Johor, Malaysia in search of plants traditionally used by the indigenous people in the treatment of malaria and malaria-like symptoms. Seven species of plants were evaluated and tested for antiplasmodial activities. Different plant parts were subjected to methanolic and aqueous extractions. A total of 24 extracts were evaluated by histidine-rich protein II (HRP2) assay against K1 strain of Plasmodium falciparum chloroquine-resistant. Ten extracts showed significant inhibition of the growth of P. falciparum. Phytochemical screening of the same extracts revealed the presence of alkaloids, flavonoids, terpenoids and anthraquinones. This study affirms that tropical rainforests may still hold undiscovered cures for many diseases and illnesses that have inflicted millions of people worldwide. The species studied herein have not known to have been studied elsewhere before.

Keywords: Endau-Rompin, malaria, Malaysia, tropical rainforest, traditional knowledge

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Authors: Abubakar Bello Usman, Alhassan Muhammad Gani, Kolo Ibrahim

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The use of botanical raw materials to produce pharmaceuticals, herbal remedies, teas, spirits, cosmetics, sweets, dietary supplements, special industrial compounds and crude materials constitute an important global resource in terms of healthcare and economy. In Nigeria and other developing countries, the indigenous knowledge on the uses of plants lies with the older generation and the traditional healers. However, these custodians are decreasing in number due to death and other unforeseen occurrences. An Ethno-botanical survey was carried out to obtain information on the ethno medical values of wide range of plants used by the people of Gombe State, North-Eastern Nigeria, in the practice of healing and cure of typhoid (enteric) fever. Oral interviews were conducted so as to consider those with low literacy level who are involved in the practice of traditional medicine and thirty four (34) informants availed themselves for the interview and were consulted. All relevant information obtained from the respondents was recorded. A recent and valid nomenclature, along with local names, family names, part of the plant(s) used, methods of preparation and administration and fifty four (54) plant species belonging to 27 families as well as 7 unidentified species that are commonly used by the people of the state in ethnomedical treatment of the ailment were tabulated. Those interviewed included traditional practitioners, local herb sellers, traditional rulers, hunters, farmers and patients. Specific questions were asked and information supplied by informants was promptly documented. Results showed that the people of Gombe State are knowledgeable on herbal medicine in the treatment of diseases and ailments. Furthermore, the aqueous leaf extracts of Senna siamea, the plant species with the highest PPK (percentage of people who have knowledge about the use of a species for treating typhoid fever) in this ethnobotanical survey, was tested for its activity against clinical isolates of Salmonella typhi using the agar well diffusion method. The aqueous extracts showed some activity (zones of inhibition 11, 9, 7.5, 3.5, 1.3 mm) at 2000, 1800, 1600, 1400, 1200 µg/ml concentrations respectively. Preliminary phytochemical studies of the aqueous leaf extracts of the plant revealed the presence of secondary metabolites such as alkaloids, saponins, tannins, flavonoids and cardiac glycosides. Though a large number of traditionally used plants for the treatment of enteric fever were identified, further scientific validation of the traditional claims of anti-typhoid properties is imperative. This would establish their candidature for any possible future research for active principles and the possible development of new cheaper and more effective anti-typhoid drugs, as well as in the conservation of this rich diversity of medicinal plants.

Keywords: antimicrobial activities, ethnobotany, gombe state, north-eastern Nigeria, phytochemical screening, senna siamea, typhoid fever

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Authors: Ahmed El-Banbi

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Several PVT models exist to represent how PVT properties are handled in sub-surface and surface engineering calculations for oil and gas production. The most commonly used models include black oil, modified black oil (MBO), and compositional models. These models are used in calculations that allow engineers to optimize and forecast well and reservoir performance (e.g., reservoir simulation calculations, material balance, nodal analysis, surface facilities, etc.). The choice of which model is dependent on fluid type and the production process (e.g., depletion, water injection, gas injection, etc.). Based on close to 2,000 reservoir fluid samples collected from different basins and locations, this paper presents some conclusions on the occurrence of reservoir fluids. It also reviews the common methods used to classify reservoir fluid types. Based on new criteria related to the production behavior of different fluids and economic considerations, an updated classification of reservoir fluid types is presented in the paper. Recommendations on the use of different PVT models to simulate the behavior of different reservoir fluid types are discussed. Each PVT model requirement is highlighted. Available methods for the calculation of PVT properties from each model are also discussed. Practical recommendations and tips on how to control the calculations to achieve the most accurate results are given.

Keywords: PVT models, fluid types, PVT properties, fluids classification

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Authors: Nuran Nur Aypar, Merlinda Alus Tokat

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The aim of the study is to determine the knowledge level of pregnant women with Gestational Diabetes Mellitus (GDM) about the disease and affecting factors. The data of this descriptive study were collected from 184 pregnant women who were followed up in Dokuz Eylul University Hospital (n=34), Izmir Ege Maternity Hospital, Gynecology Training and Research Hospital (n=133), and Egepol Private Hospital (n=17). Data collection forms were prepared by the researcher according to the literature. ANOVA test, Kruskal Wallis test, Mann-Whitney U test, Student’s t-test, and Pearson correlation test were used for statistical analyses. Average GDM knowledge score of pregnant women was 40.10±19.56. The GDM knowledge scores were affected by factors such as age, educational level, working status, income status, educational level of the spouse, and the GDM background. It has been shown in our study that the GDM knowledge scores were negatively affected by factors such as young age, low educational level, low-income level, unemployment, having a spouse with low educational level, the absence of the GDM story. It has been identified that 86.4% of the pregnant women were trained about GDM. The education provided in the antenatal period significantly increased GDM knowledge scores of pregnant women (p=0.000, U=515.0). It has been determined that GDM knowledge of the pregnant women with GDM is affected by various factors. These factors must be considered in order to determine new strategies.

Keywords: affecting factors, gestational diabetes mellitus (GDM), knowledge level, nursing, pregnancy

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Roaa Al Sharif, Salsabil Abo Al-Azayem, Nimah Alsomali, Wjoud Alsaeed, Nawal Alshammari, Abdulaziz Alwatban, Yaseen Alrabae, Razan Orfali, Faisal Alqarni, Ahmad Alrasheedi

Abstract:

from various countries have revealed that nurses possess only a basic understanding of the GCS. Regarding this matter, limited knowledge is available about the situation in Saudi Arabia. Overall, the available research suggests that there is room for improvement in the knowledge of the GCS among nurses in Saudi Arabia. Further training and education programs may be beneficial in enhancing nurses' understanding and application of the GCS in clinical practice. Objective: To determine the level of knowledge and competence in assessing the GCS among staff nurses and to identify factors that might influence their knowledge at King Fahd Medical City in Riyadh, Saudi Arabia. Methods: A descriptive, cross-sectional survey involving 199 KFMC staff nurses was conducted. Nurses were provided with a structured questionnaire, and data were collected and analyzed using SPSS version 16, employing descriptive statistics and Chi-square tests. Results: The majority, 81.4% of nurses, had an average level of knowledge in assessing the Glasgow Coma Scale (GCS). The mean score for measuring the level of knowledge among staff nurses in GCS assessment was 8.8 ± 1.826. Overall, 13.6% of respondents demonstrated good knowledge of the GCS, scoring between 11 and 15 points, while only 5% of nurses exhibited poor knowledge of the GCS assessment. There was a significant correlation between knowledge and nurses' departments (χ2(2) = 19.184, p < 0.001). χ2(2) = 19.184," representing a Chi-square statistic with 2 degrees of freedom used to test the association between categorical variables in the data analysis. Conclusion: The findings indicate that knowledge of GCS assessment among staff nurses in a single center in Saudi Arabia is moderate. Therefore, there is a need for continuous education programs to enhance their competence in using this assessment.

Keywords: Glasgow Coma Scale, brain injury, nurses’ knowledge assessment, continuous education programs

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

Procedia PDF Downloads 248