Search results for: learning society

Authors: Zahra Mohagheghian, Fatema Agharebparast

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Professional ethic is a subject that has been an issue today, so most of the businesses, including the teaching profession, understand the need and importance of it. So they need to develop a code of professional ethics for their own. In this regard, this study seeks to answer the question, with respect to the integrity of the Qur'an (Nahl / 89), is it possible to contemplate the divine teachers conduct to extract the divine pattern for teaching and training? In the code of conduct for divine teachers what are the most important moral obligations and duties of the teaching professionals? The results of this study show that the teaching of Khidr, according to the Quran’s verses, Abundant and subtle hints emphasized that it can be as comprehensive and divine pattern used in teaching and in the drafting of the charter of professional ethics of teachers used it. Also, the results show that in there have been many ethical principles in prophet Khidr’s teaching pattern.The most important ethical principles include: Student assessment, using objective and not subjective examples, assessment during teaching, flexibility, and others. According to each of these principles can help teachers achieve their educational goals and lead human being in their path toward spiritual evaluation.

Keywords: professional ethics, teaching-learning process, teacher, student, Quran

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Siti Aisyah

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This article discusses character education which is a very basic education for early childhood with the aim of instilling moral values to prevent unacceptable behaviours. Children can absorb good character when they are in a supportive environment, for that schools should understand and implement character education in the learning process. In the school environment, good character education and habituation can be developed. All parties in the school should be involved, especially the teachers. This research discusses how teachers apply characters on the values of responsibility, honesty, discipline, love and compassion, caring, courage, independence, hard work, mutual cooperation, courtesy, justice, self-control and tolerance. The respondents of this study were teachers involving 200 children from all over Indonesia. The methodology used was a survey method with the result that more than 80% of teachers have been able to exhibit the expected behaviours. The survey was conducted based on observations, types of tasks and assessed performance. The character values can be optimally taught in the school environment based on the teacher's ability to implement them. Through the character education in schools, children can also instil a positive outlook on life.

Keywords: teachers, character strengthening, early childhood, behavior

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Authors: Joanna Konstantinou

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The study is about the challenges faced by entrepreneurs in a crisis context and in turbulent economies. The scope is to determine which factors, if any, are related to the success of a new business venture, such as innovation, access to funding and capital, enhanced digital skills, employment relations and organizational culture as well as a company’s strategic orientation towards international markets. The crisis context has been recorded to have affected the number of SMEs in the Greek economy, the number of people employed as well as the volume of the output produced. Although not all SMEs have been equally impacted by the crisis, which has been identified to affect certain sectors more than others, and although research is not exhaustive in that end, employment relations and patterns, firm’s age, and innovation practices in relation to employees’ learning curve seem to have a positive correlation with the successful survival and resilience of the firm. The aim is to identify important factors that can contribute positively to the success of a startup business, and that will allow businesses to acquire resilience and survive economic adversities, and it will focus on businesses of the Greek economy, the country with the longer lasting economic crisis and the findings will be lessons to learn for other economies.

Keywords: entrepreneurship, innovation, crisis, challenges

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Authors: Mamta M. Barapatre, V. N. Sahare

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Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Yosra Ben Salah, Wang Li Jun, Salem Bellil

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The village Hammem Zriba is a lost little paradise in the middle of a beautiful landscape that captures the eyes of every visitor. The village alone is a rich expression of different elements such as urban, architecture, technical and vernacular elements, as well as sociological, spiritual and religious behaviors. This heritage is in degrading conditions and is threatened by disappearing soon; thus, actions have to be taken as soon as possible to preserve this heritage, record, analyze and learn from its traditional ways of construction. The strategy of this study is to examine the architecture within the Berber society over a period of time and influenced by a certain location and its relationship to the social and cultural aspects; this research will focus on historical, environmental, social and cultural aspects influencing architecture. The contents of this paper should mainly be constructed by three successive layouts of historical view, a cultural view and an architectural view that will include the urban and domestic scale. This research relies on the integration of both theoretical and empirical investigations. On the theoretical level: A documentary analysis of secondary data is used. Documentary analysis means content analysis of the relevant documents that include books, journals, magazines, archival data, and field survey and observations. On the empirical level: analysis of these traditional ways of planning and house building will be carried out. Through the Analysis, three techniques will be employed to collect primary data. These techniques are; systematic analysis of the architectural drawings, quantitative analysis to the houses statistics, and a direct observation. Through this research, the technical, architectural and urban achievements of the Berber people who represent a part of the general history and architectural history will be emphasized. And on a second point the potential for the sustainability present in this traditional urban planning and housing to be used to formulate guidelines for modern urban and housing development.

Keywords: culture, history, traditional architecture, values

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Lystra Huggins

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The COVID-19 pandemic affected all facets of life, including pedagogical strategies and perceptual experiences for both instructors and students. While there have also been many challenges and advantages to the online teaching and learning environment, when students’ cameras are on, the daily experiences of students’ lives have been magnified during synchronous online instruction and have served to humanize them in the classroom. This means that students’ everyday experiences, now often on display on ZOOM, allow instructors to see the realities of students. They include children running, spouses walking by parents cooking or sitting on the sofa following the lecture, students at their place of employment or driving from work, or having their classroom engagement interrupted by a delivery. Students’ backgrounds and spaces create unique dynamics during synchronous instruction, which offers a holistic view of them outside academia. This research explores whether witnessing students’ daily experiences leads to empathy from their instructors and whether it results in a greater understanding of students’ challenges and circumstances. Ultimately, it will amplify instructors’ stance on the advantages of students having their cameras on during synchronous online classes to develop a connection with the instructor and a more cohesive classroom environment.

Keywords: instructor’s empathy, synchronous class, asynchronous class, online environment

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Authors: Jakia Rajoana

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The aim of this paper is to examine the role of women entrepreneurs in bringing about sustainable rural tourism (SRT) development in Sundarbans area of Bangladesh. Theoretically, it draws upon empowerment and entrepreneurial marketing concepts. Women entrepreneurship development and lack of empowered women as role models is an important issue for developing economies in South Asia. Despite the substantial role women play in rural economy of Sundarbans, their contribution remains overlooked as enterprises led by them are run on an informal basis and their business acumen is not taken seriously both by their families and society at large. Studies on SRT fail to engage in sufficient depth with the term applied in this paper as ‘invisible women on the margins’ who run their enterprises with no formal training or societal/familial support. Moreover, the link between their (non) tourism enterprise and their empowerment remains under-theorized. Thus empirically, this research seeks to fill a significant gap by focusing on a considerably under-researched Sundarbans region. Methodologically, this study follows a qualitative research design using visual ethnographic approach. Participant observation, semi-structured interviews, and documentation are the primary data collection instruments in three coastal communities – Munshigonj, Burigoalini and Gabura – in the Sundarbans area. By focusing on the narratives of these under-investigated women, this work aims to provide in-depth and nuanced insights into salient issues on marginal communities experience from rural women’s perspectives. Initial findings illustrate that the Sundarbans women have low income due to no or little education. In addition, socio-cultural and religious factors also restrict the scope of their extensive contribution to workplace. In addition, physical and social violence which is a common occurrence for these women inhibits their agency and contributes to their disempowerment.

Keywords: gender, empowerment, entrepreneurial marketing, sustainable rural tourism, Sundarbans

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Authors: Muhammad Afief Maruf

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Kacapuri foundation is the traditional shallow foundation of building which has been used since long by traditional communities in Borneo, Indonesia. Kacapuri foundation is a foundation that uses a combination of ironwood (eusideroxylon zwageri) as a column and truss and softwood (Melaleuca leucadendra syn. M. leucadendron) as a raft. In today's modern era, ironwood happened to be a rare item, and it is protected by the Indonesian government. This condition then triggers the idea to maintain the shape of the traditional foundation by modifying the material. The suggestion is replacing the ironwood column with reinforced concrete column. In addition, the number of stem softwood is added to sustain the burden of replacing the column material. Although this modified form of Kacapuri foundation is currently still not been tested in applications in society, some research on the modified Kacapuri foundation has been conducted by some researchers and government unit. This paper will try to give an overview of the theoretical foundation bearing capacity Kacapuri modifications applied to the soft alluvial soil located in Borneo, Indonesia, where the original form of Kacapuri is implemented this whole time. The foundation is modeled buried depth in 2m below the ground surface and also below the ground water level. The calculation of the theoretical bearing capacity and then is calculated based on the bearing capacity equation suggested Skempton, Terzaghi and Ohsuki using the data of soft alluvial soil in Borneo. The result will then compared with the bearing capacity of the Kacapuri foundation original design from some previous research. The results show that the ultimate bearing capacity of the Modified Kacapuri foundation using Skempton equation amounted to 329,26 kN, Terzaghi for 456,804kN, and according Ohsaki amounted to 491,972 kN. The ultimate bearing capacity of the original Kacapuri foundation model based on Skempton equation is 18,23 kN. This result shows that the modification added the ultimate bearing capacity of the foundation, although the replacement of ironwood to reinforced concrete will also add some dead load to the total load itself.

Keywords: bearing capacity, Kacapuri, modified foundation, shallow foundation

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Authors: Rendani Mercy Makhwathana

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This paper intends to explore teachers' encounters when teaching English First Additional Language in rural public schools. Teachers are pillars of any education system around the globe. Educational transformations hinge on them as critical role players in the education system. Thus, teachers' encounters are worth consideration, for they impact learners' learning and the well-being of education in general. An exploratory qualitative approach was used in this paper. The population for this paper comprised all Foundation Phase teachers in the district. A purposive sample of 15 Foundation Phase teachers from five rural-based schools was used. Data were collected through classroom observation and individual face-to-face interviews. Data were categorized, analyzed, and interpreted. Amongst the revealed teachers' encounters are learners' inability to read and write and learners' lack of English language background and learners' lack of the vocabulary to express themselves. This paper recommends the provision of relevant resources and support to effectively teach English First Additional Language to enable learners' engagement and effective use of the English language.

Keywords: first additional language, english second language, medium of instruction, teacher professional development

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Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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Authors: Ibrahim Mohammed

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Background: Diabetes mellitus is a chronic disease that can cause devastating secondary complications, reducing the quality and length of life as well as increasing medical costs for the patient and society. The guidelines recommend both clinical and preventive strategies for diabetes management and are regularly updated. The aim of the study is to assess the level of adherence of physicians to American Diabetes Association Guidelines. Method: Observational multicenter retrospective study will be conducted among different hospitals in the central region. Patient data will be collected from the records of the last three years (2017- 2020). Records will be selected randomly after a complete randomized design. The study focuses on the management of type 2 according to ADA not changed in the last three updating; those standards; all patients should be taking Metformin 1500 to 2000 mg/day as recommended dose and should be received a high dose of statin if the high risk to ASCVD or moderate statin if not at risk, patients with hypertension and diabetes should taking ACE or ARBS. Result: The study aimed to evaluate the commitment of physicians in the central region to the ADA. Out of the 153 selected patients, only 17 % were able to control their diabetes with an average A1c below 7. ADA stated that to reach the minimum benefit of using Metformin, the daily dose should be between 1500 and 2000 mg. Results showed that 110 patients were on Metformin, where 68% of them were on the recommended dose. ADA recommended the intake of high statin for diabetic patients with ASCVD risk, while diabetic patients without ASCVD risk should be on a moderate statin. Results showed that 61.5% of patients with ASCVD risk were at high statin while only 36% of patients without ASCVD risk were at moderate statin. Results showed that 89 patients have hypertension, and 80% of them are getting ACE/ARBs as recommended by the ADA. Recommendation: It is necessary to implement periodic training courses for some physicians to enhance and update their knowledge.

Keywords: American Diabetic Association, diabetes mellitus, atherosclerotic cardiovascular disease, ACE inhibitors

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: Nisha James, Shubha Ranganathan

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Sex trafficking is a type of human trafficking involving prostitution of individuals for sexual exploitation. The stigma and social isolation they face in the society often makes it difficult for them to become rehabilitated from trafficking, due to which many of them continue in prostitution for years after being sex trafficked. Victims are subjected to violations of their fundamental human rights, deprived of basic medical facilities and undergo long-term abuse. This paper focuses on the role of Non-Governmental Organizations (NGOs) in the rescue and rehabilitation of victims of sex trafficking. Semi-structured interviews were conducted with 26 survivors of sex trafficking, five sex workers and 14 non-community staff members of a project running NGO in the city of Chennai in South India. Chennai has a number of NGOs that are involved in HIV/AIDS awareness and prevention programs. In many cases, rehabilitation of sex trafficking victims is also a mandate of these NGOs. This particular NGO was also involved in development activities towards the eradication of HIV/AIDS. For instance, they were engaged in inculcating safe sex practices among high-risk groups such as sex workers or in fighting for sex worker rights. The study found that the NGO’s role in combatting sex trafficking is overrun by the way it approaches these issue related to HIV/AIDS. Further, their activities are dependent solely on funding. Given that gradually, international funding for HIV/AIDS has slowly been withdrawn, there have been problems such as reduction in the salary of the project staff, the outreach workers and peer educators, many of whom were survivors of sex trafficking who have been able to survive on their wages instead of continuing in prostitution. Therefore, till date, the project funding has helped in making them aware of the health and social consequences of continuing in prostitution, and in supporting them socioeconomically, but the lack of funding may also lead the NGO workers into a state of unemployment, poverty and eventually into being re-trafficked. The study concludes by pointing to the need for disengaging anti-trafficking efforts from the HIV/AIDS related programs.

Keywords: non-governmental organization role, non-governmental organization staff, sex trafficking survivors, sex workers

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Authors: Manana Lobzhanidze

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The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

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Authors: P. Hari Prasad Reddy, Shimna Paulose, V. Sai Kumar, C. H. Rama Vara Prasad

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Soil environment gets contaminated due to rapid industrialisation, agricultural-chemical application and improper disposal of waste generated by the society. Unexpected volume changes can occur in soil in the presence of certain contaminants usually after the long duration of interaction. Alkali is one of the major soil contaminant that has a considerable effect on behaviour of soils and capable of inducing swelling potential in soil. Chemical heaving of clayey soils occurs when they are wetted by aqueous solutions of alkalis. Mineralogical composition of the soil is one of the main factors influencing soil- alkali interaction. In the present work, studies are carried out to understand the swell potential of soils due to soil-alkali interaction with different concentrations of NaOH solution. Locally available soil, namely, red earth containing kaolinite which is of non-swelling nature is selected for the study. In addition to this, two commercially available clayey soils, namely ball clay and china clay containing mainly of kaolinite are selected to understand the effect of alkali interaction in various kaolinitic soils. Non-swelling red earth shows maximum swell at lower concentrations of alkali solution (0.1N) and a slightly decreasing trend of swelling with further increase in concentration (1N, 4N, and 8N). Marginal decrease in swell potential with increase in concentration indicates that the increased concentration of alkali solution exists as free solution in case of red earth. China clay and ball clay both falling under kaolinite group of clay minerals, show swelling with alkaline solution. At lower concentrations of alkali solution both the soils shows similar swell behaviour, but at higher concentration of alkali solution ball clay shows high swell potential compared to china clay which may be due to lack of well ordered crystallinity in ball clay compared to china clay. The variations in the results obtained were corroborated by carrying XRD and SEM studies.

Keywords: alkali, kaolinite, swell potential, XRD, SEM

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Authors: Annisa Ulfah Pristya, Andi Setiawan

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Indonesia placed in sixth rank total Acute Respiratory Infection (ARI) patient in the world and Riau as one of the province with the highest number of people with respiratory infection in Indonesia reached 37 thousand people. Usually society using a mask as prevention action. Unfortunately the commercial mouth mask only can work maximum for 4 hours and the pores are too large to filter out microorganisms and viruses carried by infectious droplets nucleated 1-5 μm. On the other hand, Indonesia is rich with Titanium dioxide (TiO2) and purple sweet potato anthocyanin pigment. Therefore, offered Bio-nano-mask which is a antimicrobial and antiviral mouth mask with Nano-TiO2 coating and purple sweet potato anthocyanins utilization as an effective solution to high ARI patients in Riau, which has the advantage of the mask surface can’t be attached by infectious droplets, self-cleaning and have anthocyanins biosensors that give visual response can be understood easily by the general public in the form of a mask color change from blue/purple to pink when acid levels increase. Acid level is an indicator of microorganisms accumulation in the mouth and surrounding areas. Bio-nano mask making process begins with the preparation (design, Nano-TiO2 liquid preparation, anthocyanins biosensors manufacture) and then superimposing the Nano-TiO2 on the outer surface of spunbond color using a sprayer, then superimposing anthocyanins biosensors film on the Meltdown surface, making bio nano-mask and it pack. Bio-nano mask has the advantage is effectively preventing pathogenic microorganisms and infectious droplets and has accumulated indicator microorganisms that color changes which easily observed by the common people though.

Keywords: anthocyanins, ARI, nano-TiO2 liquid, self cleaning

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Oluyemi Christianah Ojo

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This study seeks to investigate the quality of ICT provided in the new Caring Heart schools in Ondo State, Nigeria. The population for the study was all caring Heart Mega Schools in Ondo State, Nigeria. Research questions were generated; two instruments CCCMS and TQCUC were used to elicit information from the schools and the teachers. The study adopts descriptive survey approach. The studies revealed and concluded that ICT components were available and adequate in these schools, Charts showing ICT components and other forms of computer devices used as instructional materials were available but were not adequate; teachers teaching computer studies are competent in the delivery of instructions and in handling computer gadgets in the laboratory. The study recommended the provision of steady electricity, uninterrupted internet facilities and provision of adequate ICT components and charts for effective teaching delivery and learning.

Keywords: facilities, information communication technology, mega primary school, primary education

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Authors: Yan Li

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Purpose: There is a lack of suitable recommendation systems to assist engineering teaching. The existing traditional engineering pedagogies lack learning interests for postgraduate students. The knowledge graph-based recommender system aims to enhance postgraduate students’ programming skills, with a focus on programming courses. Design/methodology/approach: The case study will be used as a major research method, and the two case studies will be taken in both two teaching styles of the universities (Zhejiang University and the University of Nottingham Ningbo China), followed by the interviews. Quantitative and qualitative research methods will be combined in this study. Research limitations/implications: The case studies were only focused on two teaching styles universities, which is not comprehensive enough. The subject was limited to postgraduate students. Originality/value: The study collected and analyzed the data from two teaching styles of universities’ perspectives. It explored the challenges of Engineering education and tried to seek potential enhancement.

Keywords: knowledge graph and recommender system, engineering pedagogy, programming skills, postgraduate students

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Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: hearing aids, hearing aids maintenance skill, hearing impaired children, motion graphics

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Authors: P. J. Moore-Jones

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Emirati students studying at the University of the Emirates, one of three major public institutions of higher learning in the United Arab Emirates (UAE), have a wide demographic of faculty members teaching them an equally wide variety of courses. These faculty members bring with them their own cultural assumptions, methods, expectations, educational practices and use of language. The history of multiculturalism in the UAE coupled with the contemporary multiculturalism that exists in higher education Dubai create intriguing phenomena within the classroom. This study seeks to delve into students’ and faculty members’ perceptions of the social stratification that exist in this context. Data were collected via semi-structured interviews with both and analyzed from an interpretive perspective. Findings suggest the social stratification with is deeply-seeded in the multicultural history of the region and country are reflected in the everyday interworkings of education in modern day Dubai. The relevance of this research lies in that these findings can provide valuable insights into not only the attitudes and perceptions of these Emirati students might also be applicable to any of those student populations may exist.

Keywords: social stratification, intercultural competence, Dubai, United Arab Emirates

Procedia PDF Downloads 233

Authors: Fereshteh Nazeri Bahadori

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In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

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Authors: Aileen O'loughlin

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‘Is Everybody Going WeLL?’ (IEGW?) is a 33-hour classroom-based initiative created to a) explore values and how they impact on well-being, b) encourage adolescents to connect with their community, and c) provide them with the education to encourage and maintain a lifetime love of physical activity (PA) to ensure beneficial effects on their personal well-being. This initiative is also aimed at achieving sustainable education and aligning with the United Nation’s Sustainable Development Goals numbers 3 and 4. The classroom is a unique setting in which adolescents’ PA participation can be positively influenced through fun PA policies and initiatives. The primary purpose of this research is to evaluate a range of psychosocial and PA outcomes following the 33-hour education programme. This research examined the impact of a PA and well-being programme consisting of either a 60minute or 80minute class, depending on the timetable structure of the school, delivered once a week. Participant outcomes were measured using validated questionnaires regarding Self-esteem, Mental Health Literacy (MHL) and Daily Physical Activity Participation. These questionnaires were administered at three separate time points; baseline, mid-intervention, and post intervention. Semi-structured interviews with participating teachers regarding adherence and participants’ attitudes were completed post-intervention. These teachers were randomly selected for interview. This perspective analytical cohort study included 235 post-primary school students between 11-13 years of age (100 boys and 135 girls) from five public Irish post-primary schools. Three schools received the intervention only; a 33hour interactive well-being learning unit, one school formed a control group and one school had participants in both the intervention and control group. Participating schools were a convenience sample. Data presented outlines baseline data collected pre-participation (0 hours completed). N = 18 junior certificate students returned all three questionnaires fully completed for a 56.3% return rate from 1 school, Intervention School #3. 94.4% (n = 17) of participants enjoy taking part in some form of PA, however only 5.5% (n = 1) of the participants took part in PA every day of the previous 7 days and only 5.5% (n = 1) of those surveyed participated in PA every day during a normal week. 55% (n = 11) had a low level of self-esteem, 50% (n = 9) fall within the normal range of self-esteem, and n = 0 surveyed demonstrated a high level of self-esteem. Female participants’ Mean score was higher than their male counterparts when MHL was compared. Correlation analyses revealed a small association between Self-esteem and Happiness (r = 0.549). Positive correlations were also revealed between MHL and Happiness, MHL and Self-esteem and Self-esteem and 60+ minutes of PA completed daily. IEGW? is a classroom-based with simple methods easy to implement, replicate and financially viable to both public and private schools. It’s unique dataset will allow for the evaluation of a societal approach to the psycho-social well-being and PA participation levels of adolescents. This research is a work in progress and future work is required to learn how to best support the implementation of ‘Is Everybody Going WeLL?’ as part of the school curriculum.

Keywords: education, life-long learning, physical activity, psychosocial well-being

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Authors: Ana B. Vivas, Antonia Ypsilanti, Aristea I. Ladas, Angeles F. Estevez

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Mild Cognitive Impairment (MCI) is considered an intermediate stage between normal and pathological aging, as a substantial percentage of people diagnosed with MCI converts later to dementia of the Alzheimer’s type. Memory is of the first cognitive processes to deteriorate in this condition. In the present study we employed the differential outcomes procedure (DOP) to improve visuospatial memory in a group of participants with MCI. The DOP requires the structure of a conditional discriminative learning task in which a correct choice response to a specific stimulus-stimulus association is reinforced with a particular reinforcer or outcome. A group of 10 participants with MCI, and a matched control group had to learn and keep in working memory four target locations out of eight possible locations where a shape could be presented. Results showed that participants with MCI had a statistically significant better terminal accuracy when a unique outcome was paired with a location (76% accuracy) as compared to a non differential outcome condition (64%). This finding suggests that the DOP is useful in improving working memory in MCI patients, which may delay their conversion to dementia.

Keywords: mild cognitive impairment, working memory, differential outcomes, cognitive process

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Authors: Hong Lu, Xiong Xiao

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Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

Procedia PDF Downloads 321