Search results for: on-line analytical processing

Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: Alireza Ansariyar, Mansoureh Jeihani

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Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition

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Authors: Wern Lin Yeo, Choo Kim Tan, Sook Ling Lew

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Mathematics anxiety refers to the feeling of anxious when one having difficulties in solving mathematical problem. Mathematics anxiety is the most common type of anxiety among other types of anxiety which occurs among the students. However, level of anxiety among males and females are different. There were few past study were conducted to determine the relationship of anxiety and gender but there were still did not have an exact results. Hence, the purpose of this study is to determine the relationship of anxiety level between male and female undergraduates at a private university in Malaysia. Convenient sampling method used in this study in which the students were selected based on the grouping assigned by the faculty. There were 214 undergraduates who registered the probability courses had participated in this study. Mathematics Anxiety Rating Scale (MARS) was the instrument used in study which used to determine students’ anxiety level towards probability. Reliability and validity of instrument was done before the major study was conducted. In the major study, students were given briefing about the study conducted. Participation of this study were voluntary. Students were given consent form to determine whether they agree to participate in the study. Duration of two weeks were given for students to complete the given online questionnaire. The data collected will be analyzed using Statistical Package for the Social Sciences (SPSS) to determine the level of anxiety. There were three anxiety level, i.e., low, average and high. Students’ anxiety level were determined based on their scores obtained compared with the mean and standard deviation. If the scores obtained were below mean and standard deviation, the anxiety level was low. If the scores were at below and above the mean and between one standard deviation, the anxiety level was average. If the scores were above the mean and greater than one standard deviation, the anxiety level was high. Results showed that both of the gender were having average anxiety level. Males having high frequency of three anxiety level which were low, average and high anxiety level as compared to females. Hence, the mean values obtained for males (M = 3.62) was higher than females (M = 3.42). In order to be significant of anxiety level among the gender, the p-value should be less than .05. The p-value obtained in this study was .117. However, this value was greater than .05. Thus, there was no significant difference of anxiety level among the gender. In other words, there was no relationship of anxiety level with the gender.

Keywords: anxiety level, gender, mathematics anxiety, probability and statistics

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Authors: Lulu Liao, Huijing Chen, Yinan Zhao, Hongting Ning, Hui Feng

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Urinary tract infection rate is an important index of care quality in nursing homes. The aim of the study is to understand the nursing assistant's current knowledge and attitudes of urinary incontinence and to explore related stakeholders' viewpoint about urinary incontinence training. This explanatory sequential study used Knowledge, Practice, and Attitude Model (KAP) and Adult Learning Theories, as the conceptual framework. The researchers collected data from 509 nursing assistants in sixteen nursing homes in Hunan province in China. The questionnaire survey was to assess the knowledge and attitude of urinary incontinence of nursing assistants. On the basis of quantitative research and combined with focus group, training demands were identified, which nurse managers should adopt to improve nursing assistants’ professional practice ability in urinary incontinence. Most nursing assistants held the poor knowledge (14.0 ± 4.18) but had positive attitudes (35.5 ± 3.19) toward urinary incontinence. There was a significant positive correlation between urinary incontinence knowledge and nursing assistants' year of work and educational level, urinary incontinence attitude, and education level (p < 0.001). Despite a general awareness of the importance of prevention of urinary tract infections, not all nurse managers fully valued the training in urinary incontinence compared with daily care training. And the nursing assistants required simple education resources to equip them with skills to address problem about urinary incontinence. The variety of learning methods also highlighted the need for educational materials, and nursing assistants had shown a strong interest in online learning. Related education material should be developed to meet the learning need of nurse assistants and provide suitable training method for planned quality improvement in urinary incontinence.

Keywords: mixed methods, nursing assistants, nursing homes, urinary incontinence

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Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

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The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

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Authors: Malaiphan Pansap, Surasit Vithayarat

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The purpose of this study was to study the relationship between internal organization communications’ effectiveness and employee’s performance of Faculty of Management Science, Suan Sunandha Rajabhat University. Study on solutions of communication were carried out within the organization. Questionnaire was used to collect information from 136 people of staff and instructor and data were analyzed by using frequency, percentage, mean and standard deviation and then data processing statistic programs. The result found that organization communication that affects their employee’s performance is sender which lack the skills for speaking and writing to convince audiences ready before taking message and the message which organizations are not always informed. The employees believe the behavior of good organization communication has a positive impact on the development of organization because the employees feel involved and be a part of the organization, by the cooperation in working to achieve the goal, the employees can work in the same direction and meet goal quickly.

Keywords: employee’s performance, faculty of management science, internal organization communications’ effectiveness, management accounting, Suan Sunandha Rajabhat University

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Authors: Mohammad Rahim Rahimi, Yuji Hoshino

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Building Information Management (BIM) at recent years has widespread consideration on the Architecture, Engineering and Construction (AEC). BIM has been bringing innovation in AEC industry and has the ability to improve the construction industry with high quality, reduction time and budget of project. Meanwhile, BIM support model and process in AEC industry, the process include the project time cycle, estimating, delivery and generally the way of management of project but not limited to those. This research carried the BIM advantages, adaptation and challenges of implementation in Kabul region. Capital Region Independence Development Authority (CRIDA) have responsibilities to implement the development projects in Kabul region. The method of study were considers on advantages and reasons of BIM performance in Afghanistan based on online survey and data. Besides that, five projects were studied, the reason of consideration were many times design revises and changes. Although, most of the projects had problems regard to designing and implementation stage, hence in canal project was discussed in detail with the main reason of problems. Which were many time changes and revises due to the lack of information, planning, and management. In addition, two projects based on BIM utilization in Japan were also discussed. The Shinsuizenji Station and Oita River dam projects. Those are implemented and implementing consequently according to the BIM requirements. The investigation focused on BIM usage, project implementation process. Eventually, the projects were the comparison with CRIDA and BIM utilization in Japan. The comparison will focus on the using of the model and the way of solving the problems based upon on the BIM. In conclusion, that BIM had the capacity to prevent many times design changes and revises. On behalf of achieving those objectives are required to focus on data management and sharing, BIM training and using new technology.

Keywords: construction information management, implementation and adaptation of BIM, project management, developing countries

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Manju Kanu, Subrata Sinha, Surabhi Johari

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Viral proteins of Ebola viruses belong to one of the best studied viruses; however no effective prevention against EBOV has been developed. Epitope-based vaccines provide a new strategy for prophylactic and therapeutic application of pathogen-specific immunity. A critical requirement of this strategy is the identification and selection of T-cell epitopes that act as vaccine targets. This study describes current methodologies for the selection process, with Ebola virus as a model system. Hence great challenge in the field of ebola virus research is to design universal vaccine. A combination of publicly available bioinformatics algorithms and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertypes Human Leukocyte Antigen (HLA) alleles. MUSCLE and MOTIF tools were used to find out most conserved peptide sequences of viral proteins. Immunoinformatics tools were used for prediction of immunogenic peptides of viral proteins in zaire strains of Ebola virus. Putative epitopes for viral proteins (VP) were predicted from conserved peptide sequences of VP. Three tools NetCTL 1.2, BIMAS and Syfpeithi were used to predict the Class I putative epitopes while three tools, ProPred, IEDB-SMM-align and NetMHCII 2.2 were used to predict the Class II putative epitopes. B cell epitopes were predicted by BCPREDS 1.0. Immunogenic peptides were identified and selected manually by putative epitopes predicted from online tools individually for both MHC classes. Finally sequences of predicted peptides for both MHC classes were looked for common region which was selected as common immunogenic peptide. The immunogenic peptides were found for viral proteins of Ebola virus: epitopes FLESGAVKY, SSLAKHGEY. These predicted peptides could be promising candidates to be used as target for vaccine design.

Keywords: epitope, b cell, immunogenicity, ebola

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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: Marianna Ciaccia, Gennaro Agrimi, Isabella Pisano, Maurizio Bettiga, Silvia Rapacioli, Giulia Mensa, Monica Marzagalli

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Objective: Untargeted metabolomic analysis of extracellular metabolites is a powerful approach that focuses on comprehensively profiling in the extracellular space. In this study, we applied extracellular metabolomic analysis to investigate the metabolism of two probiotic microorganisms with health benefits that extend far beyond the digestive tract and the immune system. Methods: Analytical techniques employed in extracellular metabolomic analysis encompass various technologies, including mass spectrometry (MS), which enables the identification of metabolites present in the fermentation media, as well as the comparison of metabolic profiles under different experimental conditions. Multivariate statistical analysis techniques like principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) play a crucial role in uncovering metabolic signatures and understanding the dynamics of metabolic networks. Results: Different types of supernatants from fermentation processes, such as dairy-free, not dairy-free media and media with no cells or pasteurized, were subjected to metabolite profiling, which contained a complex mixture of metabolites, including substrates, intermediates, and end-products. This profiling provided insights into the metabolic activity of the microorganisms. The integration of advanced software tools has facilitated the identification and characterization of metabolites in different fermentation conditions and microorganism strains. Conclusions: In conclusion, untargeted extracellular metabolomic analysis, combined with software tools, allowed the study of the metabolites consumed and produced during the fermentation processes of probiotic microorganisms. Ongoing advancements in data analysis methods will further enhance the application of extracellular metabolomic analysis in fermentation research, leading to improved bioproduction and the advancement of sustainable manufacturing processes.

Keywords: biotechnology, metabolomics, lactic bacteria, probiotics, postbiotics

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Kalaashini Ramachandran, Maznah Dahlui, Nik Daliana Nik Farid

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WHO recommends all babies to be exclusively breastfed and donor milk is the next best alternative in the absence of mother’s own milk. The establishment of a human milk bank (HMB) is still being debated due to religious concerns in Malaysia leading to informal milk sharing practices, but little is known on the knowledge, attitude and perception of women towards HMB and its benefits. This study hypothesizes that there is no association between knowledge and attitude and the acceptance towards the establishment of human milk bank among Malaysian women and healthcare providers. The aim of this study is to determine the drivers and barriers among Malaysian towards the acceptance of an HMB. A cross-sectional study with 367 participants was enrolled within a period of 3 months to answer an online self-administered questionnaire. Data on sociodemographic, knowledge on breastfeeding benefits, knowledge and attitude on HMB and its specific issues were analyzed in terms of frequency and then proceed to multiple logistic regression. Majority of the respondents are of Islamis religion (73.3%), have succeesfully completed their tertiary education (82.8%), and are employed (70.8%). Only 55.9% of respondents have heard of an HMB stating internet as their main source of information but a higher prevalence is agreeable to the establishment of a human milk bank (67.8%). Most respondents have a good score on knowledge of breastfeeding benefits and on HMB specific issues (70% and 54.2% respectively) while 63.8% of them have a positive attitude towards HMB. In the multivariate analysis, mothers with a good score on general knowledge of breastfeeding (AOR: 1.715) were more likely to accept the establishment of an HMB while Islamic religion was negatively associated with its establishment (AOR:0.113). This study has found a high prevalence rate of mothers who are willing to accept the establishment of an HMB. This action can be potentially shaped by educating mothers on the benefits of breastfeeding as well as addressing their religious concerns so the establishment of a religiously abiding HMB in Malaysia may be accepted without compromising their belief or the health benefit of donor milk.

Keywords: acceptability, attitude, human milk bank, knowledge

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Authors: Mokhtar Nikgoo

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Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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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: Wang Jie

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This article advances the reform of Chinese migration law through an analysis of the updated and former versions of the Chinese migration law, specifically for the Exit-Entry Administration Law of the People’s Republic of China and Regulations on Foreigners’ Permanent Residence in the People’s Republic of China(Exposure Draft), which was most recently issued in 2012 and 2020 respectively. After a fundamental reform of China’s migration law, China’s immigration legal framework has become relatively well developed compared with the previous one. Immigration procedures are available online and these procedures have become relatively simple. Comparative research for the Chinese migration laws has been done during the past several years for its legislation, legal reference for western countries and its preliminary implementation. Some results show that the reform is a superficial one and may not have a practical effect on China’s current immigration legal framework. However, complete results cannot be obtained only through the comparative research of legal definitions. Some practical case studies will also be required to analyze in detail to demonstrate the reasons that some reforms still remain at the superficial level and what further progress is required in China's immigration legal framework. This is a perspective that has been overlooked in most comparative law studies. In the first part, this article will conduct a simple comparative study of the reform of Chinese migration law and use cases studies to illustrate the reform of Chinese migration law. In the second part, this article will point out another perspective that is easily overlooked, that is, how do the Chinese nationals treat the reform: whether it is a legislative advance or a failure, and whether it deepens social tensions between nationals and immigrants. In the third part, the article will discuss Chinese migration law through China’s international law perspective with international organizations, such as International Organization for Migration and International Labour Organization will also be discussed to dialectically judge the reform of Chinese migration law. This article will adopt case and comparative studies to conduct overall research based on the reform of Chinese migration law and try to put forward more constructive advice for China’s immigration legal framework.

Keywords: Chinese migration law, reform, foreigners, immigration legal framework

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Authors: Zana Llonçari Osmani, Nita Llonçari

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In Kosovo, public rhetoric and popular sentiment position the War of 1998-99 (the war) as central to the formation of contemporary Kosovo's national identity. This period was marked by the forced massive displacement of Kosovo Albanians, the destruction of entire settlements, the loss of family members, and the profound emotional trauma experienced by civilians, particularly those who actively participated in the war as members of the Kosovo Liberation Army (KLA). Amidst these profound experiences, the Prekaz Massacre (The Massacre) is widely regarded as the defining event that preceded the final struggles of 1999 and the long-awaited attainment of independence. This study aims to explore how different visitors perceive the dominant discourse at The Memorial, a site dedicated to commemorating the Prekaz Massacre, and to identify the factors that influence their perceptions. The research employs a comprehensive mixed-method approach, combining online surveys, critical discourse analysis of visitor impressions, and content analysis of media representations. The findings of the study highlight the significant role played by original material remains in shaping visitor perceptions of The Memorial in comparison to the curated symbols and figurative representations interspersed throughout the landscape. While the design elements and physical layout of the memorial undeniably hold significance in conveying the memoryscape, there are notable shortcomings in enhancing the overall visitor experience. Visitors are still primarily influenced by the tangible remnants of the war, suggesting that there is room for improvement in how design elements can more effectively contribute to the memorial's narrative and the collective memory of the Prekaz Massacre.

Keywords: critical discourse analysis, memorialisation, national discourse, public rhetoric, war tourism

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Authors: Karish Thavabalan, Alistair Ovenell, Aman Sutaria, Annabelle Parkhouse, Numan Baydemir, Theodore Lally

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Background: Open discussions surrounding menopause are often associated with stigma, with many women feeling uncomfortable to engage in them with friends, colleagues, and healthcare professionals. Though the barriers regarding safe discussions of symptom management experienced by menopausal women are well documented, existing research offers little insight into whether these were shared by pre-menopausal women. This study aimed to explore the barriers regarding safe discussions about menopausal symptom management as perceived or experienced by pre-menopausal and menopausal women. Methods: This qualitative study was conducted over a 2-month period (March 2022 - April 2022) under the auspices of Imperial College Business School, London, UK. Snowball sampling was used to recruit both menopausal (age 45-70) and pre-menopausal participants (age <45), and sampling continued until data saturation was achieved. 16 semi-structured online interviews were conducted, and transcripts were thematically analyzed following Braun and Clarke’s six-step methodology. Results: A total of 7 higher themes regarding safe discussion of menopausal symptom management were identified by both pre-menopausal and menopausal women, including: “ineffective coping mechanisms”, “perceived onus to self-endure”, “lack of workplace support”, “poor knowledge of management approaches”, “poor healthcare infrastructure”, “poor support from friends and family”, “lack of knowledge and interest from a young age”. Conclusion: Identifying the barriers regarding safe discussion helped to highlight which areas require most significant intervention. Alongside tackling the barriers, menopausal women face, ultimately, there is a pertinent need to and address the lack of insight into menopause from a younger age and to encourage earlier discussions so as to not propagate the cycle of stigma.

Keywords: menopause, stigma, safe discussions, symptom management

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Authors: Anusha Edirisinghe

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Sexual Gender based violence is a most common social phenomenon in higher education institutions. It has become a hidden crime of the Universities. Masculinities norms and attitudes are more influential and serve as key drivers and risk for ragging and SGBV. This research will reveal that in Sri Lankan universities, SGBV takes from the violence and murder of women students, assault and battery coerced sex, sexual harassment including harassment via information technology. This study focus is to prevention of ragging and SGBV in University system. Main objective of this paper describes and critically analyses of plight of ragging and SGBV in higher education institutions and legal and national level policy implementation to prevent these crimes in society. This paper is with special reference to ragging case from University of Kelaniya 2016. University Grant commission introduced an Act for the prevention of Ragging and gender standing committee established in Sri Lanka in 2016. And each university has been involved in the prevention of SGBV and ragging in higher education institutions. Case study from first year female student, reported sexual harassment was reported to the police station in May in 2016. After this case, the university has been implementing emergency action plan, short term and long term action plan. Ragging and SGBV task force was established and online complaint center opened to all students and academic and non- academics. Under these circumstances student complained to SGBV and other harassment to the university. University security system was strong support with police and marshals, and vigilant committees including lecturers. After this case all universities start to several programmes to stop violence in university

Keywords: higher Education, ragging, sexual gender-based violence, Sri Lanka

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Authors: Bernard Bladergroen, David Vlotman, Bradley Cerff

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The agricultural sector is one which requires and consumes large amounts of water globally. Commercial wine production, in particular, uses extensive volumes of fresh water and generates significant volumes of wastewater through various processes. The wastewater produced by wineries typically exhibits elevated levels of chemical oxygen demand (COD), total suspended solids (TSS), total dissolved solids (TDS), acidic pH and varying salinity and nutrient contents. This study investigates the performance of a shear-enhanced flotation separation (SEFS) pilot plant as a primary treatment stage during winery wastewater processing by modifying a conventional Dissolved Air Flotation (DAF) system. The SEFS pilot plant achieved a 99% reduction in both turbidity and TSS in comparison to the 97% achieved with the conventional DAF system. The COD was reduced by 66% and 51% for the SEFS and DAF systems, respectively. SEFS shows the advantages of hydrodynamic shear to enhance the coagulation and subsequent flocculation processes with a significant reduction of coagulant and flocculant (36% and 31%, respectively).

Keywords: shear enhanced flotation, suspended solids, primary wastewater treatment, zeta potential

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Authors: Olanike A. Ojo, Akindele M. Ojo, Jacob H. Tsado, Ramatu U. Kutigi

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The study was carried out on analysis of the effect of farmers’ socio-economic factors on the net farm income of catfish farmers in Kwara State, Nigeria. Primary data were collected from selected catfish farmers with the aid of well-structured questionnaire and a multistage sampling technique was used to select 102 catfish farmers in the area. The analytical techniques involved the use of descriptive statistics and multiple regression analysis. The findings of the analysis of socio-economic characteristics of catfish farmers reveal that 60% of the catfish farmers in the study area were male gender which implied the existence of gender inequality in the area. The mean age of 47 years was an indication that they were at their economically productive age and could contribute positively to increased production of catfish in the area. Also, the mean household size was five while the mean year of experience was five. The latter implied that the farmers were experienced in fishing techniques, breeding and fish culture which would assist in generating more revenue, reduce cost of production and eventual increase in profit levels of the farmers. The result also revealed that stock capacity (X3), accessibility to credit (X7) and labour (X4) were the main determinants of catfish production in the area. In addition, farmer’s sex, household size, no of ponds, distance of the farm from market, access to credit were the main socio-economic factors influencing the net farm income of the catfish farmers in the area. The most serious constraints militating against catfish production in the study area were high mortality rate, insufficient market, inadequate credit facilities/ finance and inadequate skilled labour needed for daily production routine. Based on the findings, it is therefore recommended that, to reduce the mortality rate of catfish extension agents should organize training workshops on improved methods and techniques of raising catfish right from juvenile to market size.

Keywords: credit, income, stock, mortality

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Authors: Ashraf Ward

Abstract:

Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

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Authors: Wei-Ting Hung

Abstract:

Inbound tourist expenditure might not only have influenced by individual tourist characteristics but may also be affected by nationality characteristics. The cross national distance effects on tourist consumption behavior should be incorporated in the analytical framework. Additionally, the often used factor analysis, cluster analysis and regression analysis overlook the hierarchical tourist consumption data structure and may lead to misleading results. The objectives of the present study were twofold. First, we propose a multilevel model that takes individual and cross-national differences into account under a hierarchical framework. Second, we further sought to determine the types of cross-national differences affecting tourist expenditure. Thus, this study incorporates the individual tourist effects and cross national distance effects simultaneously, uses the data of 2010 Annual Survey Report on Visitors’ Expenditure and Trends in Taiwan to investigate the determinants of inbound tourist expenditure. Multilevel analysis was used to investigate the influence of individual tourist effects and cross national distance effects on inbound tourist expenditure. The empirical results show that cross national distance plays a crucial role in tourist consumption behavior. Our findings also indicate age and income have positive influence on tourism expenditure., whereas education and gender do not have significant impact. Regarding macro-level factors, geographic and cultural differences exhibited significant positive relationships on tourism expenditure, while economic differences did not. Based on the above empirical results, it is suggested that tour operators should take tourists’ individual attributes, particularly their income and age, into consideration when arranging tours. In addition, nationality holds sway over tourists’ consumption behavior, of which geographic and cultural differences are the two major factors at play. The empirical results of this study serve as practical suggestions for tourism marketing strategies and policy implications for government policies.

Keywords: cross national distance, inbound tourist, multilevel analysis, tourist expenditure

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Authors: P. Senthil Kumari

Abstract:

Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Julien Baillet

Abstract:

In light of 30 years of scientific research, InCorporer Method was created in 2019 as a new approach to heal traumatic, developmental, and dissociative injuries. Following natural nervous system functions, InCorporer aims to heal, develop, and update the different defensive mammalian subsystems: fight, flight, freeze, feign death, cry for help, & energy regulator. The dimensions taken into account are: (i) Heal the traumatic injuries who are still bleeding, (ii) Develop the systems that never received the security, attention, and affection they needed. (iii) Update the parts that stayed stuck in the past, ignoring for too long that they are out of danger now. Through the Present Part and its caregiving skills, InCorporer method enables a balanced, soothed, and collaborative personality system. To be as integrative as possible, InCorporer method has been designed according to several fields of research, such as structural dissociation theory, attachment theory, and information processing theory. In this paper, the author presents how the internal caregiver is developed and trained to heal all the different parts/subsystems of our clients through mindful attention and reflex movement integration.

Keywords: PTSD, attachment, dissociation, part work

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Authors: Reyhan Özdoğan, Özgür Ceylan, Mehmet Arif Kaya, Mithat Çelebi

Abstract:

Food packaging is important for the food industry. Bioplastics have been used as food packaging materials. According to the European Bioplastics organization, bioplastics can be defined as plastics based on renewable resources (bio-based) or as plastics which are biodegradable and/or compostable. Poly(lactic acid) (PLA) has an industrially importance of bioplastic polymers. PLA is a family of biodegradable thermoplastic polyester made from renewable resources. It is produced by conversion of corn, or other carbohydrate sources, into dextrose, followed by fermentation into lactic acid through direct polycondensation of lactic acid monomers or through ring-opening polymerization of lactide. The processing possibilities of this transparent material are very wide, ranging from injection molding and extrusion over cast film extrusion to blow molding and thermoforming. In this study, PLA films were prepared by solution casting method. PLAs which are different molecular weights were plasticized with glycerol and the morphology of films was monitored by optical microscopy. Properties of mechanical and film of PLA were researched with the mechanical testing machine.

Keywords: biodegradable, bioplastics, morphology, solution casting, poly(lactic acid)

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Authors: Amit Syal, Madeline Grade, Alister Martin

Abstract:

Background: Cross-sectional and longitudinal studies demonstrate an association between health and voting. Furthermore, voting enables populations to support policies that impact their health via social determinants like income, education, housing, and healthcare access. Unfortunately, many barriers exist which disproportionately affect the civic participation of certain minority groups. Health professionals have an important role to play in addressing the civic health of all patients and empowering underrepresented communities. Description: Vot-ER is a non-partisan, nonprofit organization that aims to reduce barriers to civic participation by helping patients register to vote while in healthcare settings. The initial approach involved iPad-based kiosks in the emergency department waiting rooms, allowing patients to register themselves while waiting. After the COVID-19 pandemic began, Vot-ER expanded its touchless digital approaches. Vot-ER provides healthcare workers across the country with “Healthy Democracy Kits” consisting of badge backers, posters, discharge paperwork, and other resources. These contain QR and text codes that direct users to an online platform for registering to vote or requesting a mail-in ballot, available in English or Spanish. Outcomes: From May to November 2020, Vot-ER helped prepare 46,320 people to vote. 13,192 individual healthcare providers across all 50 states signed up for and received Healthy Democracy Kits. 80 medical schools participated in the Healthy Democracy Campaign competition. Over 500 institutions ordered site-based materials. Conclusions: A healthy democracy is one in which all individuals in a community have equal and fair opportunities for their voices to be heard. Healthcare settings, such as hospitals, are appropriate and effective venues for increasing both voter registration and education.

Keywords: civic health, enfranchisement, physician, voting

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Authors: Hatim Laalej, Jon Stammers

Abstract:

In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.

Keywords: machining, manufacturing, tool wear, signal processing

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

Abstract:

The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

Procedia PDF Downloads 503