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Authors: Mahvish Anjum

Abstract:

India is a land of craftsmen and a hub of many popular embroidery clusters. Chikankari is the name given to the delicate art of hand embroidery, traditionally practiced in the city of Lucknow and its environs. Chikankari not only provide employment to 250,000 artisans of different crafts but people from non-craft base also earn their livelihood by associating themselves with this craft. People working in this sector are exploited in term of working hours, low and irregular income, unsatisfactory work conditions, no legal protection and exposed to occupational health hazards. The present paper is an attempt to analyse occupational profile of workers engaged in Chikan embroidery industry. Being an empirical study, the entire work is based upon primary sources of data which have collected through field survey. Purposive random sampling has used for selection of data. Total 150 workers have surveyed through questionnaire technique in Lucknow city during October-November, 2017. For analysis of data Z-score, ANOVA, and Pearson correlation techniques are used. The result of present study indicates that artisans are exploited by the middle man and face the problem of late payment and long working hours because they are not directly associated with the manufacturers. Work conditions of the workers are quite poor such as improper ventilation, poor light and unhygienic conditions that adversely affect the health of workers.

Keywords: artisans, socio-economic status, unorganized industry, work condition

Procedia PDF Downloads 156

Authors: Hassan Wajid

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Architecture design studio with all its accouterments, especially pedagogies, has been committed to awakening the students to the true meaning of the concept of Dwelling. The real task is how to make them unlearn the associations of “dwelling as a rented or owned accommodation by the road with a car parked in front of a garage door and replace it by the fundamental experiential-phenomenological manifestations of Light, Space, Gravity and Time through assigned readings and small theoretical challenges resulting in drawings and models. The primary challenge for teachers remained the introduction of the act or desire of ‘Dwelling’ philosophically. The academic link had been offered by Albert Hofstadter's Poetry, Language, through which Martin Heidegger’s fourfold concept of ‘Building Dwelling, Thinking’ primarily served to guide us through this trajectory in helping to build an intellectual framework as justification of the term “dwelling” in its various meanings. Gaston Bachelard’s Poetics of Space and Merleau-Ponti’s Phenomenology of Perception also got assigned as reading. Four fictional characters created by two master short story writers G Maupassant, and O Henry were introduced as DwellersClients in search of their respective dwellings as drawn imaginations in the studio four-fold of Light, Space, Gravity, and Time and at the same time aspire to understand thoroughly Heidegger’s Four-Fold of Earth, Sky, Divinities and Mortals. asserting its place in the corresponding story and its unique character as the Dweller.

Keywords: dwelling, imagination, architectural manifestation, phenomenological

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Pamir Gogoi, Ratree Wayland

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This study investigates the acoustic measures of breathiness when coarticulated with nasality. The acoustic correlates of breathiness and nasality that has already been well established after years of empirical research. Some of these acoustic parameters - like low frequency peaks and wider bandwidths- are common for both nasal and breathy voice. Therefore, it is likely that these parameters interact when a sound is coarticulated with breathiness and nasality. This leads to the hypothesis that the acoustic parameters, which usually act as robust cues in differentiating between breathy and modal voice, might not be reliable cues for differentiating between breathy and modal voice when breathiness is coarticulated with nasality. The effect of nasality on the perception of breathiness has been explored in earlier studies using synthesized speech. The results showed that perceptually, nasality and breathiness do interact. The current study investigates if a similar pattern is observed in natural speech. The study is conducted on Marathi, an Indo-Aryan language which has a three-way contrast between nasality and breathiness. That is, there is a phonemic distinction between nasals, breathy voice and breathy-nasals. Voice quality parameters like – H1-H2 (Difference between the amplitude of first and second harmonic), H1-A3 (Difference between the amplitude of first harmonic and third formant, CPP (Cepstral Peak Prominence), HNR (Harmonics to Noise ratio) and B1 (Bandwidth of first formant) were extracted. Statistical models like linear mixed effects regression and Random Forest classifiers show that measures that capture the noise component in the signal- like CPP and HNR- can classify breathy voice from modal voice better than spectral measures when breathy voice is coarticulated with nasality.

Keywords: breathiness, marathi, nasality, voice quality

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Authors: Kavita Bodke

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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.

Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification

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Authors: Feng Tao, Han Ye, Shaoyi Liao

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City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.

Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Asmae Tafraouti, Yasmina Layouni, Pascal Kleimann

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The growing market for Microsystems (MST) and Micro-Electromechanical Systems (MEMS) is driving the research for alternative manufacturing techniques to microelectronics-based technologies, which are generally expensive and time-consuming. Hot-embossing and micro-injection modeling of thermoplastics appear to be industrially viable processes. However, both require the use of master models, usually made in hard materials such as steel. These master models cannot be fabricated using standard microelectronics processes. Thus, other micromachining processes are used, such as laser machining or micro-electrical discharge machining (µEDM). In this work, µEDM has been used. The principle of µEDM is based on the use of a thin cylindrical micro-tool that erodes the workpiece surface. The two electrodes are immersed in a dielectric with a distance of a few micrometers (gap). When an electrical voltage is applied between the two electrodes, electrical discharges are generated, which cause material machining. In order to produce master models with high resolution and smooth surfaces, it is necessary to well control the discharge mechanism. However, several problems are encountered, such as a random electrical discharge process, the fluctuation of the discharge energy, the electrodes' polarity inversion, and the wear of the micro-tool. The effect of different parameters, such as the applied voltage, the working capacitor, the micro-tool diameter, and the initial gap, has been studied. This analysis helps to improve the machining performances, such as the workpiece surface condition and the lateral crater's gap.

Keywords: craters, electrical discharges, micro-electrical discharge machining, microsystems

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Authors: Juliza Hidayati, Sukardi, Ani Suryani, Sugiharto, Anas M. Fauzi

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The idea of making North Sumatera as a barometer of national oil palm industry requires efforts commodities and agro-industry development of oil palm. One effort that can be done is by successful execution plantation revitalization. The plantation Revitalization is an effort to accelerate the development of smallholder plantations, through expansion and replanting by help of palm Estate Company as business partner and bank financed plantation revitalization fund. Business partner agreement obliged and bound to make at least the same smallholder plantation productivity with business partners, so that the refund rate to banks become larger and prosperous people as a plantation owner. Generally low productivity of smallholder plantations under normal potential caused a lot of old and damaged plants with plant material at random. The purpose of revitalizing oil palm plantations is which are to increase their competitiveness through increased farm productivity. The research aims to identify potential criteria in influencing plantation productivity improvement priorities to be observed and followed up in order to improve the competitiveness of destinations and make North Sumatera barometer of national palm oil can be achieved. Research conducted with Analytical Network Process (ANP), to find the effect of dependency relationships between factors or criteria with the knowledge of the experts in order to produce an objective opinion and relevant depict the actual situation.

Keywords: palm barometer, acceleration of plantation development, productivity, revitalization

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Authors: Mark Anthony A. Catiil

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Teachers are the principal actors in the delivery of quality education to the learners. Unfortunately, as time goes by, some of them got low motivation at work. Absenteeism, tardiness, under time, and non-compliance to school policies are some of the end results. There is, therefore, a need to review the different human resource management practices of the school that contribute to teachers’ work satisfaction and motivation. Hence, this study determined the level of satisfaction of teachers on the human resource management practices of Gingoog City Comprehensive National High School. This mixed-methodology research was focused on the 45 teachers chosen using a stratified random sampling technique. Reliability-tested questionnaires, interviews, and focus group discussions were used to gather the data. Results revealed that the majority of the respondents are female, Teacher I, with MA units and have served for 11-20 years. Likewise, among the human resource management practices of the school, the respondents rated the lowest satisfaction on recruitment and selection (mean=2.15; n=45). This could mean that most of the recruitment and selection practices of the school are not well communicated, disseminated, and implemented. On the other hand, retirement practices of the school were rated with the highest satisfaction among the respondents (mean=2.73; n=45). This could mean that most of the retirement practices of the school are communicated, disseminated, implemented, and functional. It was recommended that the existing human resource management practices on recruitment and selection be reviewed to find out its deficiencies and possible improvement. Moreover, future researchers may also conduct a study between private and public schools in Gingoog City on the same topic for comparison.

Keywords: education, human resource management practices, satisfaction, teachers

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Modupe Beatrice Adeyinka

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French, as a foreign language in Nigeria, is pronounced to be the second official language and a compulsory subject in the primary school level; hence, colleges of education across the nation are saddled with the responsibility of training teachers for the subject. However, it has been observed that this policy has not been fully implemented, for French teachers in training, do face many challenges, of which translation is chief. In a bid to investigate the major cause of the perceived translation problem, this study examined French translation problems of pre-service teachers in selected colleges of education in the southwest, Nigeria. This study adopted a descriptive survey research design. The simple random sampling technique was used to select four colleges of education in the southwest, where 100 French students were randomly selected by selecting 25 from each school. The pre-service teachers’ French translation problems’ questionnaire (PTFTPQ) was used as an instrument while four research questions were answered and three null hypotheses were tested. Among others, the findings revealed that students do have problems with false friends, though mainly with its interpretation when attempting French-English translation and vice versa; majority of the students make use of French dictionary as a way out and found the material very useful for their understanding of false friends. Teachers were, therefore, urged to attend in-service training where they would be exposed to new and emerging strategies, approaches and methodologies of French language teaching that will make students overcome the challenge of translation in learning French.

Keywords: false friends, French language, pre-service teachers, source language, target language, translation

Procedia PDF Downloads 155

Authors: Ali S. Al-Aufi, Ibrahim S. Al-Harthi, Yousuf S. AlHinai, Ali H.S. Al-Badi, Zahran S. Al-Salti

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Social media tools have currently been leading a major change in the flow and use of information for different life aspects within people and between people and their governments. They represent powerful channels for direct exchanges of information, ideas, and suggestions for purposes of civic participation. The current study aims at investigating Omani citizens’ perceptions, expectations, and motivations of their uses of social media tools to interact with the government for civic participation. A quantitative methodology was used to collect data through self-administered questionnaires from a random sample of university students and staff drawn from Sultan Qaboos University, considering them as well-informed and typically active users of social media. The literature was comprehensively reviewed to retrieve relevant empirical studies that particularly investigated the use of social media for civic engagement which provided a basis for the construct of the questionnaire; taken into consideration the delineated dimensions of perceptions, expectations, and motivations. The findings of the study offer practical and useful recommendations for governmental units in Oman and similar contexts in the region to inform better and efficient use of social media tools to interact with citizens in issues related to civic engagement; particularly to make best use of these tools for improving services and developing existing and newer initiatives, and hence, encouraging and strengthening citizens’ involvement for civic engagement.

Keywords: social media, social networking sites, web 2.0, civic engagement, civic participation, oman

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Authors: Che Jusoh, Mohd Rahimi, Toby Mundel

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This study was designed to investigate the physiological and performance effects of a local Malaysian native starch (Metroxylin sago) on cycling in a hot (30°C) and humid (78% RH) environment. Eight male, non-heat acclimated, well-trained club cyclists (VO2max 65 ± 10 ml kg-1 min-1, peak aerobic power 397 ± 71 W) completed one familiarization and three experimental trials in our laboratory simulating cycling in environmental conditions of heat and humidity. Each trial consisted of 45 minutes at a fixed workload (55% VO2max) followed by a 15 minute time-trial (~75% VO2max). Sago in porridge form was consumed 1h before exercise (Pre), in gel form during exercise (Dur) and compared to a control trial (Con), using a random, cross-over design. Plasma glucose concentration did not differ between trials (P = 0.06) with an increase from 4.1 ± 0.6 to 6.1 ± 1.6 mmol-1 (Con), 4.8 ± 1.7 to 5.7 ± 0.4 mmol-1 (Pre) and 4.7 ± 0.8 to 6.9 ± 1.4 mmol-1 (Dur) from start to end of exercise. Plasma lactate increased (P = 0.02) from 1.6 ± 0.3 to 7.6 ± 2.2 mmol-1 (Con), 1.7 ± 0.5 to 7.3 ± 2.9 mmol-1 (Pre) and 1.6 ± 0.2 to 7.3 ± 1.8 mmol-1 (Dur) with no effect of trial (P = 0.74). No differences were found between trials for RER (P = 0.328) with values of 0.93 ± 0.05 (Con), 0.94 ± 0.04 (Pre) and 0.92 ± 0.04 (Dur). There were no differences between trials in rectal (P = 0.64) and skin (P = 0.56) temperatures; values reaching 39.1 ± 0.5°C (Con), 38.9 ± 0.4°C (Pre) and 39.1 ± 0.4°C (Dur) for rectal and 32.7 ± 1.2°C (Con), 32.8 ± 1.4°C (Pre) and 32.8 ± 1.8°C (Dur) for skin temperature, respectively. Heart rate (P = 0.07) also did not differ between trials but reached maximal values by the end of time-trial for all trials. Performance was unaffected by trial (P = 0.98) with the average work completed in 15 minutes being 221 ± 33 kJ (Con), 222 ± 31 kJ (Pre) and 219 ± 32 kJ (Dur), respectively. Therefore, the results of this investigation do not support consumption of sago, either before or during exercise, in altering the thermoregulatory, metabolic or performance responses in a hot and humid environment.

Keywords: hot and humid, physiology, time trial performance, thermoregulatory

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: M. F. Amado, A. Amado, F. Poggi, J. Correia de Freitas

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Today it is widely understood that global energy consumption patterns are directly related to the ongoing urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals. In this paper, a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities, economic development, and the local and global environment while safeguarding fairness in the energy sector.

Keywords: solar urban planning, solar smart city, urban development, energy efficiency

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Authors: Siu-Siu Guo, Qingxuan Shi

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In this paper, single-degree-of-freedom (SDOF) systems to white noise and colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis.

Keywords: filtered noise, narrow-banded noise, nonlinear dynamic, random vibration

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Authors: Phillip Thebe

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African traders in China have generated magnanimous attention from scholars because of their choices to take short-term trips to Guangzhou and other places in search of cheaper products taking advantage of the status of China as a "global manufacturing hub". Nevertheless, their activities only gained traction at the turn of the millennium, with their presence in China incrementally dwindling over the next two decades. Now, with the devastating effects of COVID-19, their journeys have had to be totally cut short by unending lockdowns and stiff migration rules due to China's zero-tolerance of COVID-19 policy. This unfortunate yet untimely occurrence has left many scholars wondering if this marks the end of African traders in China and, indeed, the end of their business careers. Between March and September 2022, 20 traders were followed back to Africa, Zimbabwe, to find out what they are doing after having been shut out of China. Data was collected through ethnographic immersion and purposive in-depth interviewing in and around the city of Bulawayo. Snowballing was employed to reach out to the traders until a saturation point was reached and interview transcripts were filed for analysis. The findings revealed that some still trading online in China, report different opinions and feelings about doing business during COVID-19. Others have left the Chinese marketplace, now pursuing European industries in Turkey and other places. Others are still getting Chinese goods but in African countries such as Tanzania, Mozambique, South Africa, and Botswana. Some are now into the second-hand clothing trade, whereas others have stopped doing business to pursue other life-course interests. These and other issues are addressed in this paper from the anthropology of migration and globalization perspectives.

Keywords: entrepreneurship, African traders, China, COVID-19, Africans in China

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Authors: Ororho Maureen Ekpelezie

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This study investigates language educators' perceptions and experiences regarding AI-driven personalized teacher training modules in Awka South, Anambra State, Nigeria. Utilizing a stratified random sampling technique, 25 schools across various educational levels were selected to ensure a representative sample. A total of 1000 questionnaires were distributed among language teachers in these schools, focusing on assessing their perceptions and experiences related to AI-driven personalized teacher training. With an impressive response rate of 99.1%, the study garnered valuable insights into language teachers' attitudes towards AI-driven personalized teacher training and its effectiveness in enhancing language teaching competence. The quantitative analysis revealed predominantly positive perceptions towards AI-driven personalized training modules, indicating their efficacy in addressing individual learning needs. However, challenges were identified in the long-term retention and transfer of AI-enhanced skills, underscoring the necessity for further refinement of personalized training approaches. Recommendations stemming from these findings emphasize the need for continued refinement of training methodologies and the development of tailored professional development programs to alleviate educators' concerns. Overall, this research enriches discussions on the integration of AI technology in teacher training and professional development, with the aim of bolstering language teaching competence and effectiveness in educational settings.

Keywords: language teacher training, AI-driven personalized learning, professional development, language teaching competence, personalized teacher training

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Authors: L. Paulino Ferreira, M. Gomes Neto, M. Duarte, S. Serra

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Objectives: COVID-19 pandemic has caused older adults to experience a degree of social isolation and loneliness that is unprecedented. Our aim is to review state of the art regarding the consequences of social isolation due to COVID-19 in elderly people. Methods: The authors conducted a search on Medscape and PubMed with the keywords mentioned below, and the most relevant articles were selected. Results: Social isolation leads many elderlies to experience loneliness, anxiety, depression, alcohol abuse, and feelings of abandonment with a perception of being a burden on society. Thus, social isolation has increased the risk for suicide in older people. It is also noteworthy that the exacerbation of psychiatric disorders (such as depression, anxiety, and post-traumatic stress disorder) without correct treatment and follow-up also increases suicide risk. Loneliness is also associated with accelerated cognitive deterioration and dementia. Besides that, during social isolation, it could be more difficult for older people to get medication as well as proper health care. It is also noticed an increase in the risk of falls, poor nutrition, and lack of exercise. All this contributes to weakening elderlies’ immune systems leading to a higher risk of developing infections, cardiovascular events, and cancer, increasing hospitalization and morbimortality. Conclusion: Social isolation in the elderly has a significant impact on physical and mental health, as well as morbimortality and hospitalizations due to non-COVID causes. Nevertheless, further studies will be needed to assess the real dimension of the effects of social isolation due to COVID-19.

Keywords: social isolation, COVID-19, elderly, mental health

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Authors: Hatice Canan Gungor, Ahmet Akdemir

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The fields of engineering and technological sciences are increasing in quality and quantity day by day all over the world. Countries have to follow, implement and adapt these developments in order to economical empowerments. In our era, it's possible to follow the rapidly developing technology and to produce new technologies by inquisitive, curious, numerical thinking individuals who can show several approaches to problem solving. In this case, countries should develop te result oriented and need-focused curriculums in university education. As in the whole world, there are more space studies in our country as well. Universities should undertake the task of supply the need for staff of this technological race. In this context, questions about the purpose, content and learning outcomes of the space sciences and space engineering departments in our country will be researched answers to reveal the characteristic of this section. In this study, it was determined in which universities the space engineering and the departments of basic sciences educate with formal education and the contents of this education, and the universities were compared with each other as of 2017. In our country three universities provide Aeronautical and Aerospace Engineering, two universities provide Space Sciences and Technologies, two universities provide Aerospace Engineering, two universities provide Aeronautics and Astronautics Engineering education. In all universities, specialized courses are taught after basic engineering education. But the question that needs to be answered is, do the lessons benefit in practice? The answer of this question will reveal the quality of the education. This paper suggests that surveys be conducted to search for the answer to this question. It's thought to be the base for the next works.

Keywords: education, space engineering, space science, quality of systems

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Authors: Supriadi Hardianto, Aditya Daniswara

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Today's workplace, flooded by millennial Generation or known also as Generation Y. A common problem that faced by the company towards Gen Y is a high turnover rate, attitudes problem, communication style, and different work style than the older generation. This is common in private sector. The objective of this study is to get a better understanding of the Gen Y Career Attitude at the workplace. The subject of this study is focusing on 430 respondent of Gen Y which age between 20 – 35 years old who works for a private company. The Questionnaire as primary data source captured 9 aspects of career attitude based on Career Attitudes Strategy Inventory (CASI). This Survey distributes randomly among Gen Y in the IT Industry (125 Respondent) and Manufacture Company (305 Respondent). A Random deep interview was conducted to get the better understanding of the etiology of their primary obstacles. The study showed that most of Indonesia Gen Y have a moderate score on Job satisfaction but in the other aspects, Gen Y has the lowest score on Skill Development, Career Worries, Risk-Taking Style, Dominant Style, Work Involvement, Geographical Barrier, Interpersonal Abuse, and Family Commitment. The top 5 obstacles outside that 9 aspects that faced by Gen Y are 1. Lower communication & networking support; 2. Self-confidence issues; 3. Financial Problem; 4. Emotional issues; 5. Age. We also found that parent perspective toward the way they are nurturing their child are not aligned with their child’s real life. This research fundamentally helps the organization and other Gen Y’s Stakeholders to have a better understanding of Gen Y Career Attitude at the workplace.

Keywords: career attitudes, CASI, Gen Y, career attitude at workplace

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Authors: Ranjitkumar Patil

Abstract:

Age estimation has importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seem to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in the north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’s method and to compare the chronological age and dental age for validation of the Cameriere’s method in the north Indian population. A comparative study of 02-year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with ages ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from institutional ethical committee. The data was obtained based on inclusion and exclusion criteria and was analyzed by software for dental age estimation. Statistical analysis: The student’s t-test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. The regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between males and females, with their dental age assessed by using a Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that Cameriere’s method can be effectively applied to the north Indian population.

Keywords: forensic, dental age, skeletal age, chronological age, Cameriere’s method

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Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

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Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

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Authors: Cromwell F. Gopo, Joy L. Picar

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This study aimed to predict the employability of senior high school graduates for S.Y. 2018- 2019 in the Davao del Norte Division through quantitative research design using the descriptive status and predictive approaches among the indicated parameters, namely gender, school type, academics, academic award recipient, skills, values, and strand. The respondents of the study were the 33 secondary schools offering senior high school programs identified through simple random sampling, which resulted in 1,530 cases of graduates’ secondary data, which were analyzed using frequency, percentage, mean, standard deviation, and binary logistic regression. Results showed that the majority of the senior high school graduates who come from large schools were females. Further, less than half of these graduates received any academic award in any semester. In general, the graduates’ performance in academics, skills, and values were proficient. Moreover, less than half of the graduates were not employed. Then, those who were employed were either contractual, casual, or part-time workers dominated by GAS graduates. Further, the predictors of employability were gender and the Information and Communications Technology (ICT) strand, while the remaining variables did not add significantly to the model. The null hypothesis had been rejected as the coefficients of the predictors in the binary logistic regression equation did not take the value of 0. After utilizing the model, it was concluded that Technical-Vocational-Livelihood (TVL) graduates except ICT had greater estimates of employability.

Keywords: employability, senior high school graduates, Davao del Norte, Philippines

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Authors: Temitope O. Tokosi

Abstract:

Healthcare is a human right. The sensitivity of health issues has necessitated the introduction of Enterprise Content Management (ECM) at district hospitals in the Western Cape Province of South Africa. The objective is understanding clinicians’ perception of ECM at their workplace. It is a descriptive case study design of constructivist paradigm. It employed a phenomenological data analysis method using a pattern matching deductive based analytical procedure. Purposive and s4nowball sampling techniques were applied in selecting participants. Clinicians expressed concerns and frustrations using ECM such as, non-integration with other hospital systems. Inadequate access points to ECM. Incorrect labelling of notes and bar-coding causes more time wasted in finding information. System features and/or functions (such as search and edit) are not possible. Hospital management and clinicians are not constantly interacting and discussing. Information turnaround time is unacceptably lengthy. Resolving these problems would involve a positive working relationship between hospital management and clinicians. In addition, prioritising the problems faced by clinicians in relation to relevance can ensure problem-solving in order to meet clinicians’ expectations and hospitals’ objective. Clinicians’ perception should invoke attention from hospital management with regards technology use. The study’s results can be generalised across clinician groupings exposed to ECM at various district hospitals because of professional and hospital homogeneity.

Keywords: clinician, electronic content management, hospital, perception, technology

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Authors: Liesbeth Van Kelst, Jozefiene Jansens

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Background: All care providers within mother and child care are confronted, at some point in their career, with the care for parents who (will) lose or have lost a baby. Obtaining the correct attitude and communicating well during these difficult moments are aspects that many healthcare provides continue to struggle with. Parents still encounter well-intentioned but inappropriate communication from healthcare providers. Aim: To study how communication, both verbal and non-verbal, around the death of a baby during pregnancy, birth, or in the first ten days postnatal was experienced by parents and healthcare providers. Methods: A qualitative study using grounded theory principles was conducted. Data were collected through 22 individual face-to-face in-depth interviews with parents who had lost a baby (n = 12) and intramural caregivers, such as midwives, nurses, gynecologists and neonatologists (n=10). In the first phase, data were analyzed within each group separately (parents and healthcare providers) and in the second phase, findings from both groups were compared and analyzed according to meta-synthesis principles. Results: The themes that emerged from the data demonstrated congruent experiences between the group of the parents and the health care providers. Both strengths and weaknesses in current care were named and suggestions for appropriate communication were formulated. Conclusion: Since most health care providers only occasionally care for parents with a deceased baby, a communication tool can optimize communication between healthcare professionals and parents who lose a baby. This is very important as the words which are said at this difficult period last a lifetime in the heads of parents.

Keywords: communication, death, perinatal loss, stillbirth

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Authors: Pradip Lingfa, L. M. Das, S. N. Naik

Abstract:

In the last three decades the world has been confronting an energy crisis caused by the decreased of fossil resources, and increased of environmental problems. This situation resulted in a search for an alternative fuel. Non-edible vegetable oils are promising sources for producing liquid fuels. In the present experimental investigation, the engine tests were carried out for performance and exhaust emissions on 2.5 L Turbo-charged diesel engine fuelled with 5% biodiesel blend obtained from non-edible vegetable oils such as Jatropha, Karanja, and Castor Seeds. The engine tests were carried out at full throttle position with various engine speeds of 1500, 1750, 2000, 2250, 2750 and 3000 rpm respectively. After test, it was observed that 5% Jatropha biodiesel blend have highest brake power of 46.65 kW and less brake specific fuel consumptions of 225.8 kg/kW-hr compared to other two biodiesel blends of brake power of 45.99 kW, 45.81 kW and brake specific fuel consumption of 234.34, 236.55 kg/kW-hr respectively. The brake specific fuel consumption of biodiesel blends increase at increasing speeds for all biodiesel blends. NOx emissions for biodiesel blends were observed to be higher compared to diesel fuel during the entire range of engine operations. The emission characteristics like CO, HC and smoke were lowered at all engine speed conditions compared to diesel fuel.

Keywords: biodiesel blend, brake power, brake specific fuel consumption, emission, performance

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Authors: Dibyendu Das, Santanu Kumar Pal

Abstract:

Milk protein lactoferrin (Lf) exhibits potent antibacterial activity due to its interaction with Gram-negative bacterial cell membrane component, lipopolysaccharide (LPS). This paper represents fabrication of new Liquid crystals (LCs) based biosensors to explore the interaction between Lf and LPS. LPS self-assembled at aqueous/LCs interface and orients interfacial nematic 4-cyano-4’- pentylbiphenyl (5CB) LCs in a homeotropic fashion (exhibiting dark optical image under polarized optical microscope). Interestingly, on the exposure of Lf on LPS decorated aqueous/LCs interface, an optical image of LCs changed from dark to bright indicating an ordering alteration of interfacial LCs from homeotropic to tilted/planar state. The ordering transition reflects strong binding between Lf and interfacial LPS that, in turn, perturbs the orientation of LCs. With the help of epifluorescence microscopy, we further affirmed the interfacial LPS-Lf binding event by imaging the presence of FITC tagged Lf at the LPS laden aqueous/LCs interface. Finally, we have investigated the conformational behavior of Lf in solution as well as in the presence of LPS using Circular Dichroism (CD) spectroscopy and further reconfirmed with Vibrational Circular Dichroism (VCD) spectroscopy where we found that Lf undergoes alpha-helix to random coil-like structure in the presence of LPS. As a whole the entire results described in this paper establish a robust approach to envisage the interaction between LPS and Lf through the ordering transitions of LCs at aqueous/LCs interface.

Keywords: endotoxin, interface, lactoferrin, lipopolysaccharide

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