Search results for: random features

Authors: Lenka Mynaříková, Hedvika Boukalová

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The study looks at the ability to detect nonverbal deception among police officers and management students in the Czech Republic. Respondents from police departments (n=197) and university students of human resources (n=161) completed a deception detection task and evaluated veracity of the statements of suspects in 21 video clips from real crime investigations. Their evaluations were based on nonverbal behavior. Voices in the video clips were modified so that words were not recognizable, yet paraverbal voice characteristics were preserved. Results suggest that respondents have a tendency to lie bias based on their profession. In the evaluation of video clips, stereotypes also played a significant role. The statements of suspects of a different ethnicity, younger age or specific visual features were considered deceitful more often. Research might be beneficial for training in professions that are in need of deception detection techniques.

Keywords: deception detection, police officers, human resources, forensic psychology, forensic studies, organizational psychology

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Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

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In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

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Authors: Fuming Yang, Telma Sousa Almeida, Xinyu Li, Yunxi Deng, Heying Zhang, Michael E. Lamb

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Twenty-seven children aged 6-15 years with autism spectrum disorder (ASD) and 32 typically developing children were questioned about their participation in a set of activities after a two-week delay and again after a two-month delay, using a best-practice interview protocol. This paper assessed the narrative coherence of children’s reports based on key story grammar elements and temporal features included in their accounts of the event. Results indicated that, over time, both children with ASD and typically developing (TD) children decreased their narrative coherence. Children with ASD were no different from TD peers with regards to story length and syntactic complexity. However, they showed significantly less coherence than TD children. They were less likely to use the gist of the story to organize their narrative coherence. Interviewer prompts influenced children’s narrative coherence. The findings indicated that children with ASD could provide meaningful and reliable testimony about an event they personally experienced, but the narrative coherence of their reports deteriorates over time and is affected by interviewer prompts.

Keywords: autism spectrum disorders, delay, eyewitness testimony, narrative coherence

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Olufemi Samuel Shola, Oladapo Adenike Adesola

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Inadequate dietary intake has increased the susceptibility of under five children to malnutrition and infections. This study, therefore, assessed the feeding practices of children of 0-23 months of age among mothers in urban areas of Akure, Ondo State, Nigeria. Simple random sampling technique was used to select four hundred (400) mothers out of 710 mothers from 7 primary health care centres in Akure metropolis for the study. Data were collected using modified WHO 2003 Questionnaire on child feeding practices. Data were analyzed using descriptive statistics, while chi-square was used to determine the association between variables. Results showed that 52.0% of the children were males, with 47.5% in the 6-8 months age group. More than half (57.0%) of the mothers were between the ages of 20-29 years, and 45.0% had secondary education. Majority (94.3%) of the mothers breastfed their children in the last 24 hours preceding the survey. The feeding practices history of mothers showed that 28.0% and 53.7% of the mothers initiated breastfeeding less than 30 minutes and between 30 minutes to 1 hour after delivery, respectively. Also, 52.0% of mothers practiced exclusive breastfeeding for six months, while 26.2% breastfed from 6 months up to 2 years of age. Dietary diversity of the children age 6-23 months revealed that 68.7% of the children attained the minimum dietary diversity by consuming 4 or more food groups in the last 24 hours. There was a significant association (P < 0.05) between mothers’ education (n=180), occupation(n=41) and dietary diversity (n= 150) and meal frequency (n=209). Therefore, the study concluded that the duration of breastfeeding and time of introduction of complementary food did not meet WHO recommended guidelines. There is urgent need to launching more programmes.

Keywords: breastfeeding, mothers, child feeding, urban areas, ondo state, nigeria

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Authors: Seyyed Farzad Motevalli-Haghi, Javad Rafinejad, Mahboobeh Hosseni, Jamshid Yazdani-Charati, Behzad Parsi

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Background and purpose: Pediculosis is a worldwide public health concern. This descriptive study was performed on primary-school-aged children to determine the prevalence of pediculosis and its risk factors in Mazandaran Province, Iran, on basis of geographic information system (GIS). Materials and methods: A random sampling method was used to select 45237 school-aged children from Sari to Ramsar cities during September 2012 to June 2013. Data were collected from the selected schools by five trained nursing inspectors. A detailed questionnaire was filled for each child prior to hair examination following which examination was carried out to detect head lice as well as eggs/nits. Data were analyzed chi-square test. Finally, the GIS map was obtained in province informational chart. Results: 823 primary-school children (of 45237) were infected with lice in Mazandaran Province. The mean infection prevalence was 1.4% in cities 5.64% in rural area from Sari to Ramsar. There were significant relationships between pediculosis and some factors (P<0.05). GIS map revealed that the contamination was less in west than in east and central regions. Conclusion: Increasing awareness and training of teachers and parents, as well as improving standards of personal health can significantly reduce the prevalence of pediculosis.

Keywords: pediculosis capitis, primary school children, epidemiology, geographic information system (GIS), Mazandaran, Iran

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Authors: Parveen Kundu, Zile Singh, Kunika Kundu, Swaran Kaur

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Context: Tuberculous osteomyelitis is a relatively uncommon condition that can present with various clinical and radiological features, often mimicking bone tumors or tumor-like lesions. In endemic countries like India, tuberculosis should be considered as a potential differential diagnosis for lytic bone lesions. This study aimed to highlight the different presentations of tuberculosis that can mimic tumors or tumor-like lesions in bone and emphasize the successful outcome of antitubercular therapy (ATT) in treating these cases. Research Aim: The main objective of this research was to explore the varied presentations of tuberculosis that mimic bone tumors or tumor-like lesions both clinically and radiologically, focusing on different bones. The study aimed to raise awareness among clinicians about this possibility and highlight the importance of histopathological confirmation before initiating treatment for lytic bone lesions. Methodology: This study utilized a retrospective review of 22 patients with suspected lytic bone lesions, who were subsequently diagnosed with tuberculous osteomyelitis through histopathological examination. The cases were collected over a period of ten years. Eleven cases required curettage for extensive lesions with sequestrations, while all 22 patients received 12 months of antitubercular therapy. Findings: The study included 14 male and 8 female patients, ranging in age from 3 to 61 years, with an average age of 22.05. The clinical and radiological presentations varied, with examples including bone cysts in the metaphyseal area of long bones, lesions resembling chondroblastomas, giant cell tumors, and osteoid osteoma, as well as multifocal lytic lesions resembling metastasis or multiple myeloma. One patient had lesions in both the clavicle and hand. Lesions mimicking chondromas were also observed in the phalanges of the hand and foot metatarsal. All patients showed resolution of the lesions and no residual disability following ATT. Theoretical Importance: This study highlights the importance of considering tuberculosis as a potential differential diagnosis for lytic bone lesions, particularly in endemic regions. It emphasizes the need for histopathological confirmation to accurately diagnose tuberculous osteomyelitis, as this is considered the gold standard. Data Collection and Analysis Procedures: Data for this study were collected retrospectively from medical records and radiological images of the 22 patients. The cases were analyzed based on clinical presentation, radiological findings, and histopathological confirmation. The outcomes of antitubercular therapy were also assessed. The data were summarized and presented descriptively. Question Addressed: This study aimed to address the question of how tuberculosis can mimic different bone tumors and tumor-like lesions clinically and radiologically. It also aimed to assess the successful outcome of antitubercular therapy in treating these cases. Conclusion: Tuberculous osteomyelitis can present with varied clinical and radiological features, often mimicking bone tumors or tumor-like lesions. Clinicians should consider tuberculosis as a potential diagnosis for lytic bone lesions, especially in endemic areas. Histopathological confirmation is essential for accurate diagnosis. Antitubercular therapy is an effective treatment for tuberculous osteomyelitis, leading to the resolution of the lesions with no residual disability.

Keywords: tuberculosis, tumor, curettage, bone

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Authors: Takanori Tanaka, Daisuke Kitao, Daisuke Ikeda

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The aurora is an attractive phenomenon but it is difficult to understand the whole mechanism of it. An approach of data-intensive science might be an effective approach to elucidate such a difficult phenomenon. To do that we need labeled data, which shows when and what types of auroras, have appeared. In this paper, we propose an image retrieval system for auroral all-sky images, some of which include discrete and diffuse aurora, and the other do not any aurora. The proposed system retrieves images which are similar to the query image by using a popular image recognition method. Using 300 all-sky images obtained at Tromso Norway, we evaluate two methods of image recognition methods with or without our original color filtering method. The best performance is achieved when SIFT with the color filtering is used and its accuracy is 81.7% for discrete auroras and 86.7% for diffuse auroras.

Keywords: data-intensive science, image classification, content-based image retrieval, aurora

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Franco Ceasar Agbalog, Shintaro Yukawa

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Mindfulness is increasingly being used as a method for resolving conflict. However, less is known about how its positive outcome develops. To better understand the underlying effects of mindfulness on conflict resolution strategies, this study examines the potential mediating factors between them. The researchers hypothesized that Emotional Intelligence (EI) mediates the effects of mindfulness on conflict resolution strategies due to its similar components to the benefits of mindfulness, such as awareness and control of one’s emotions, awareness and understanding of other’s emotions, and cultivation of compassion and empathy. Using a random sampling, 157 participants completed three questionnaires: Five Facet Mindfulness Questionnaire (FFMQ), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and Rahim Organizational Conflict Inventory-II (ROCI-II). Utilizing the SPSS Process, results showed a significant relationship between mindfulness and EI. However, among the five approaches to conflict resolution, only the integrating style was significantly related to EI. Following the principle of Mediation Analysis, mindfulness has an indirect effect on integrating style. Moreover, mindfulness and conflict resolution strategies were not significantly related. This is a rather surprising result because research literature has always indicated a positive relationship between the two variables. These findings imply that although integrating style is generally considered the best approach in handling conflict, each style may be appropriate depending on the situation. Mindfulness allows practitioners to have a holistic view of the conflict situation and choose the approach they think best for that specific situation. This could explain why statistically, there is no direct effect of mindfulness on conflict resolution strategies. This work provides basis for the necessity to investigate the factors of conflict instead of the conflict resolution strategies; factors that can be manipulated and may be directly influenced by mindfulness.

Keywords: conflict resolution strategies, emotional intelligence, mindfulness and conflict, ROCI-II integrating style

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Authors: Nicholas Agyepong, Paul Gyan

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Inappropriate prescribing of antibiotic is a common healthcare concern globally resulted in an increased risk of adverse reactions and the emergence of antimicrobial resistance. The wrong antibiotic prescribing habits may lead to ineffective and unsafe treatment, worsening of disease condition, and thus increase in health care costs. The study was to examine the antibiotic prescribing pattern and associated risk factors at Regional Hospital in the Bono region of Ghana. A retrospective cross-sectional study was conducted to describe the current prescribing practices at the Hospital from January 2014 to December, 2021. A systematic random sampling method was used to select the participants for the study. STATA version 16 software was used for data management and analysis. Descriptive statistics and logistic regression analysis were used to analyze the data. Statistical significance set at p<0.05. Antibiotic consumption was equivalent to 11 per 1000 inhabitants consuming 1 DDD per day. Most common prescribed antibiotic was amoxicillin/clavulanic acid (14.39%) followed by erythromycin (11.44%), and ciprofloxacin (11.36%). Antibiotics prescription have been steadily increased over the past eight years (2014: n=59,280 to 2021: n=190,320). Prescribers above the age of 35 were more likely to prescribe antibiotics than those between the ages of 20 and 25 (COR=21.00; 95% CI: 1.78 – 48.10; p=0.016). Prescribers with at least 6 years of experience were also significantly more likely to prescribe antibiotics than those with at most 5 years of experience (COR=14.17; 95% CI: 2.39 – 84.07; p=0.004). Thus, the establishment of an antibiotic stewardship program in the hospitals is imperative, and further studies need to be conducted in other facilities to establish the national antibiotic prescription guideline.

Keywords: antibiotic, antimicrobial resistance, prescription, prescribers

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Authors: Asmaa Shehata

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Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.

Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning

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Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

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A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Muriel Canas-Walker

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The 2012 TV series "The Legend of Zhen Huan" is one of the most popular and influential historical dramas on Chinese television and is regularly discussed on Chinese social media such as Weibo. Set in the Qing dynasty, the 76 episodes series features palace intrigues focused on female characters. In the Forbidden City, concubines must survive the cruelty of an extreme polygamy system, constantly competing against each other. The patriarchal oppression of the women sequestred in the harem relies on fierce female competition and does not leave much room for compassion. Using Michel Foucault’s theory of power, feminist theories, and visual anthropology, this paper analyzes the complex relationships between the female characters, from their rise to power to their fall from grace, from alliances to betrayals, from sorority to sororicide. This analysis aims to understand what makes this series particularly popular with young female audiences in China and explain its importance in Chinese media.

Keywords: Chinese TV Drama, feminism, popular culture, Theory of Power

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Authors: S. Hosseini, M. Ahmadi Najafabadi, M. Akhlaghi

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The health of the journal bearings is very important in preventing unforeseen breakdowns in rotary machines, and poor lubrication is one of the most important factors for producing the bearing failures. Hydrodynamic lubrication (HL), mixed lubrication (ML), and boundary lubrication (BL) are three regimes of a journal bearing lubrication. This paper uses acoustic emission (AE) measurement technique to correlate features of the AE signals to the three lubrication regimes. The transitions from HL to ML based on operating factors such as rotating speed, load, inlet oil pressure by time domain and time-frequency domain signal analysis techniques are detected, and then metal-to-metal contacts between sliding surfaces of the journal and bearing are identified. It is found that there is a significant difference between theoretical and experimental operating values that are obtained for defining the lubrication regions.

Keywords: acoustic emission technique, pressure fed journal bearing, time and frequency signal analysis, metal-to-metal contact

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Authors: Michael Udey Udam

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Background: This study investigated the impact of cloud resources, a component of cloud computing, on science teachers’ effectiveness in secondary schools in Cross River State. Three (3) research questions and three (3) alternative hypotheses guided the study. Method: The descriptive survey design was adopted for the study. The population of the study comprised 1209 science teachers in public secondary schools of Cross River state. Sample: A sample of 487 teachers was drawn from the population using a stratified random sampling technique. The researcher-made structured questionnaire with 18 was used for data collection for the study. Research question one was answered using the Pearson Product Moment Correlation, while research question two and the hypotheses were answered using the Analysis of Variance (ANOVA) statistics in the Statistical Package for Social Sciences (SPSS) at a 0.05 level of significance. Results: The results of the study revealed that there is a positive correlation between the utilization of cloud resources in teaching and teaching effectiveness among science teachers in secondary schools in Cross River state; there is a negative correlation between gender and utilization of cloud resources among science teachers in secondary schools in Cross River state; and that there is a significant correlation between teaching experience and the utilization of cloud resources among science teachers in secondary schools in Cross River state. Conclusion: The study justifies the effectiveness of the Cross River state government policy of introducing cloud computing into the education sector. The study recommends that the policy should be sustained.

Keywords: cloud resources, science teachers, effectiveness, secondary school

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Authors: Esmaeil Khodadad

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The environment is one of the hotbeds of global politics. It is only necessary to emphasize the human being on this word, and to take it as a serious political-social debate, so as to prevent the collapse of the harmony of the system of nature governing the earth, the landlord and its creatures. Earth, water and humans are three interconnected arms that should be kept in balance and harmony. The collapse of one of these arms disrupts the entire framework of the philosophy of life on earth. Environmental issues were found worldwide in the late 20th century and were given serious attention by experts. At the same time, international environmental issues have brought to the forefront the challenges of international relations. These ideas have introduced environmental issues and some of the main features of the causes and consequences of global environmental change, as well as ways to deal with this change Has been discussed. The objectives of this study are environmental issues in the world and in Iran, and it shows what factors contribute to the formation of spatial systems and its supporting systems, and finally what the goals should be about the ideal state of the future of the global environment and its issues. The information required for this research is a combination of documentary, descriptive-analytical and library methods.

Keywords: environment, environmental issues, flower, oeacen

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Authors: G. Voicu, C. D. Ghitulica, A. Cucuruz, C. Busuioc

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In the field of tissue engineering, the compositional and microstructural features of the employed materials play an important role, with implications on the mechanical and biological behaviour of the medical devices. In this context, the development of calcium phosphate-natural biopolymer composites represents a choice of many scientific groups. Thus, tricalcium phosphate powders were synthesized by a wet method, namely co-precipitation, starting from high purity reagents. Moreover, the substitution of calcium with magnesium have been approached, in the 5-10 wt.% range. Afterwards, the phosphate powders were integrated into two types of composites with chitosan, different from morphological point of view. First, 3D porous scaffolds were obtained by a freeze-drying procedure. Second, uniform compact films were achieved by film casting. The influence of chitosan molecular weight (low, medium and high), as well as phosphate powder to polymer ratio (1:1 and 1:2) on the morphological properties, were analysed in detail. In conclusion, the reported biocomposites, prepared by a straightforward route are suitable for bone substitution or repairing applications.

Keywords: bone reconstruction, chitosan, composite scaffolds, tricalcium phosphate

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Authors: Shreya Asthana

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Testers know that the feature they tested on stage is working perfectly in production only after release went live. Sometimes something breaks in production and testers get to know through the end user’s bug raised. The panic mode starts when your staging test results do not reflect current production behavior. And you started doubting your testing skills when finally the user reported a bug to you. Testers can deploy their confidence on release day by testing on production. Once you start doing testing in production, you will see test result accuracy because it will be running on real time data and execution will be a little faster as compared to staging one due to elimination of bad data. Feature flagging, canary releases, and data cleanup can help to achieve this technique of testing. By this paper it will be easier to understand the steps to achieve production testing before making your feature live, and to modify IT company’s testing procedure, so testers can provide the bug free experience to the end users. This study is beneficial because too many people think that testing should be done in staging but not in production and now this is high time to pull out people from their old mindset of testing into a new testing world. At the end of the day, it all just matters if the features are working in production or not.

Keywords: bug free production, new testing mindset, testing strategy, testing approach

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Authors: Jailan Mohamed El Demerdash

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Millennials are a distinctive and dominant consumer group whose behavior, preferences and purchase decisions are broadly explored but not fully understood yet. Making up the largest market segment in the world, and in Egypt, they have the power to reinvent the hospitality industry and contribute to forming prospective demand for green hotels by showing willingness to adopting their environmental-friendly practices. The current study aims to enhance better understanding of Millennials' perception about sustainable initiatives and to increase the prediction power of their intentions regarding green hotel practices in Egypt. In doing so, the study is exploring the relation among different factors; Millennials' environmental awareness, their acceptance of green practices and their willingness to pay more for them. Millennials' profile, their preferences and environmental decision-making process are brought under light to stimulate actions of hospitality decision-makers and hoteliers. Bearing in mind that responsible consumerism is depending on understanding the different influences on consumption. The study questionnaire was composed of four sections and it was distributed to random Egyptian travelers' blogs and Facebook groups, with approximately 8000 members. Analysis of variance test (ANOVA) was used to examine the study variables. The findings indicated that Millennials' environmental awareness will not be a significant factor in their acceptance of hotel green practices, as well as, their willingness to pay more for them. However, Millennials' acceptance of the level of hotel green practices will have an impact on their willingness to pay more. Millennials were found to have a noticeable level of environmental awareness but lack commitment to tolerating hotel green practices and their associated high prices.

Keywords: millennials, environment, awareness, paying more

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Authors: K. Santacruz-Gomez, E. Silva-Campa, S. Álvarez-García, V. Mata-Haro, D. Soto-Puebla, M. Pedroza-Montero

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Blood gamma irradiation is the only available method to prevent transfusion-associated graft versus host disease (TA-GVHD). However, when blood is irradiated, determine blood shelf time is crucial. Non-irradiated blood has a self-time from 21 to 35 days when is preserved with an anticoagulated solution and stored at 4°C. During their storage, red blood cells (RBC) undergo a series of biochemical, biomechanical and molecular changes involving what is known as storage lesion (SL). SL include loss of structural integrity of RBC, a decrease of 2,3-diphosphatidylglyceric acid levels, and an increase of both ion potassium concentration and hemoglobin (Hb). On the other hand, Atomic force Microscopy (AFM) represents a versatile tool for a nano-scale high-resolution topographic analysis in biological systems. In order to evaluate SL in irradiated and non-irradiated blood, RBC topography and morphometric parameters were obtained from an AFM XE-BIO system. Cell viability was followed using flow cytometry. Our results showed that early markers as nanoscale roughness, allow us to evaluate blood quality since another perspective.

Keywords: AFM, blood γ-irradiation, roughness, storage lesion

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

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This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

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Authors: Maria Terezinha Santos Leite Neta, Mônica Silva de Jesus, Hannah Caroline Santos Araujo, Rafael Donizete Dutra Sandes, Raquel Anne Ribeiro Dos Santos, Narendra Narain

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Mango is one of the most consumed and appreciated fruits in the world, mainly due to its peculiar and characteristic aroma. Since the fruit is perishable, it requires conservation methods to prolong its shelf life. Mango cubes were dehydrated at 40°C, 50°C and 60°C and by lyophilization, and the effect of these processes was investigated on the physicochemical characteristics (color and texture) of the products and monitoring of the main volatile compounds for the mango aroma. Volatile compounds were extracted by the SPME technique and analyzed in GC-MS system. Drying temperature at 60°C and lyophilization showed higher efficiency in retention of main volatile compounds, being 63.93% and 60.32% of the total concentration present in the fresh pulp, respectively. The freeze-drying process also presented features closer to the fresh mango in relation to color and texture, which contributes to greater acceptability.

Keywords: mango, freeze drying, convection drying, aroma, GC-MS

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Authors: Rattanan Tippayaphalapholgul, Yasothorn Sapsathiarn

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Composites of piezoelectric materials are widely use in practical applications such as nondestructive testing devices, smart adaptive structures and medical devices. A thorough understanding of coupled electro-elastic response and properties of piezocomposite are crucial for the development and design of piezoelectric composite materials used in advanced applications. The micromechanics analysis is employed in this paper to determine the response and engineering properties of the piezocomposite. A mechanical imperfect interface bonding between piezoelectric inclusion and polymer matrix is taken into consideration in the analysis. The micromechanics analysis is based on the Boundary Element Method (BEM) together with the periodic micro-field micromechanics theory. A selected set of numerical results is presented to investigate the influence of volume ratio and interface bonding condition on effective piezocomposite material coefficients and portray basic features of coupled electroelastic response within the domain of piezocomposite unit cell.

Keywords: effective engineering properties, electroelastic response, imperfect interface, piezocomposite

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Authors: Abdusalam Sharf

Abstract:

In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.

Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall

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Authors: Amir Rashid

Abstract:

Today is the world of innovation and Cloud Computing is becoming a day to day technology with every passing day offering remarkable services and features on the go with rapid elasticity. This platform took business computing into an innovative dimension where clients interact and operate through service provider web portals. Initially, the trust relationship between client and service provider remained a big question but with the invention of several cryptographic paradigms, it is becoming common in everyday business. This research work proposes a solution for building a cloud storage service with respect to Data Security addressing public cloud infrastructure where the trust relationship matters a lot between client and service provider. For the great satisfaction of client regarding high-end Data Security, this research paper propose a layer of cryptographic primitives combining several architectures in order to achieve the goal. A survey has been conducted to determine the benefits for such an architecture would provide to both clients/service providers and recent developments in cryptography specifically by cloud storage.

Keywords: data security in cloud computing, cloud storage architecture, cryptographic developments, token key

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Authors: Olubusayo Asikhia

Abstract:

The purpose of the study was to compare the incidence of indiscipline and guidance and counseling programmes among federal and state-owned tertiary institutions in Lagos State, Southwest, Nigeria. This study was borne out of persistent students’ revolt and unrest in Nigerian tertiary institutions with its concomitant breakdown of law and order, disruption of academic activities, closure of institutions and the disruption of lives and property among others. A sample of 300 students, 270 staff (including academic and non-academic, heads of disciplinary committees, deans of student affairs and counselors) from 6 federal and state-owned tertiary institutions were selected through stratified random sampling. Three structured questionnaires with reliability coefficients that range from 0.78 to 0.91 were used to collect data for the study. The data were tested at 0.05 level of significance and analyzed using descriptive, paired samples statistics and regression analysis. Findings from the four hypotheses generated for the study revealed that student indiscipline occurs more in state colleges of education and polytechnics than in their federal counterparts. It was also higher in federal universities than the state. The study also revealed a significant difference in the causes of indiscipline and assessment of guidance and counseling programmes in state and federal universities and no significant difference in state and federal colleges and polytechnics. It was recommended that the guidance and counseling department in tertiary institutions should create a well-structured program that will enable it to address issues of indiscipline among students and that counselors should use small-group counseling approach and student-focused interventions.

Keywords: colleges of education, guidance and counseling, indiscipline, polytechnics, students and universities

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Dilang Thouk Tharjiath

Abstract:

This study seeks to examine determinants of access to finance: the case of micro and small enterprises in bonga town. It identifies the sector as the key to unlocking the economic potentials of the country. For the achievement of the objective of the study simple random and stratified sampling has been used to select 179 respondents, primary and secondary data were used, primary data were collected through face to face interview and preparing questionnaire and secondary data were collected through reviewing firms record and reports, quantitative research approach were used and the data obtained were analyzed using descriptive research design. Access to finance is one of the key obstacles of MSE’s not only when starting the business project but also when operating. Identifying the major determinants of access to finance is therefore quite crucial. Based on descriptive result the financiers specially formal financiers tend to grant credit easily for enterprises which are located near to town, having operators with higher educational level, experienced and with a positive attitudes towards or fulfill their lending procedures, and a firm having collateralized asset, prepare business plan, maintain accounting practice ,large and old enough. Finally the study recommended that As Educational level of entrepreneurs has significant effect on access to credit from bank and the managers or owners education level is low in Bonga town the concerned bodies of both the government and non-governmental institutions in collaboration with Bonga town MSE development office are recommended to create awareness and facilitate the provision of additional training for those with lower educational level.

Keywords: credit, entrepreneur, enterprise, manager

Procedia PDF Downloads 79