Search results for: social media networks (SN

Authors: Oluwaseun Amusa

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The online space has continued to be a platform for not only private and mundane discussions but also a tribune for voicing critical political and national opinions. Nigerians and the international community have employed the online media, as well as other media platforms to articulate their thoughts on the claims which favour possibilities of the demise of the incumbent president of Nigeria, President Muhammadu Buhari, after a prolonged illness in year 2007 and the ploy of a Jubril of Sudan clone in his place. This study thus examines the pragmatic strategies employed in the online articles on the national dilemma caused by the Buhari/Jubril claims and refutals, in response to the lacuna in the literature on such analytical investigations on the subject. Two online articles titled, 'Buhari: The real, the fake and the dead' and 'Taking the Buhari/Jubril story seriously', authored by two Nigerian writers, Tunde Odesola and Abimbola Adelakun, respectively and retrieved online from 360nobs.com and Nairaland blogs, on December 3, 2018, and December 7, 2018, respectively, served as data for the study. The data were analysed using the Stance Theory and the Pragmatic Act Theory. Findings showed that the writers employed stance acts, rhetorical questions, metaphors, histo-political allusions, name-calling, and derogatives, in achieving the pragmeme of disabusing. This results in a pragmatic reconstruction of readers' views on the issue.

Keywords: Buhari/Jubril claims, online articles, pragmatic strategies, stance theory

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Authors: Jacques C. Duvenhage

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The use of emoticons or so-called ‘emojis’ has gained much attention, not only in the daily use thereof with friends or family but also within the workplace amongst co-workers and employers. Even though emojis may be seen as a way to express feelings or even ideas, it may present legal challenges in the workplace. With new emojis being created on a daily basis, communicating through emojis, whether via phone, email or social media platforms, can become convoluted, especially within the working environment. The question to be addressed is how and/or whether Australian legislators will regulate the use of emojis (as a form of technology) in the workplace to prevent harassment, discrimination and other forms of prejudice. The emojis sent to co-workers may be interpreted by employees and even employers in different ways depending on their age, sexual orientation, and cultural background. Therefore, Australian courts will need to interpret an emoji’s meaning on a case-by-case basis. This paper will explore the use of emojis in the workplace (drawing on a desktop study), the impact emojis have on the employer-employee relationship as well as co-worker relationships, its legal application through case studies and whether a legal framework should be adopted by Australian legislators on this issue. Furthermore, this paper will reflect on the legal framework and application of emojis in the workplace considering foreign jurisdictions such as the United Kingdom and the United States of America and whether Australia should adopt similar legal approaches to these jurisdictions.

Keywords: emoticons, legal approaches, regulation, workplace

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Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Arian Amirnia, Atena Taheri, Mohammadreza Arabi, Mahmud Fotuhi-Firuzabad

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Ferroresonance effects cause overvoltage in medium voltage transformers and isolators used in electrical networks. Ferroresonance effects are nonlinear and occur between the network capacitor and the nonlinear inductance of the voltage transformer during saturation. This phenomenon is unwanted for transformers since it causes overheating, introduction of high dynamic forces in primary coils, and rise of voltage in primary coils for the voltage transformer. Furthermore, it results in electrical and thermal failure of the transformer. Expansion of distribution lines, design of the transformer in smaller sizes, and the increase of harmonics in distribution networks result in an increase of ferroresonance. There is limited literature available to improve the effects of ferroresonance; therefore, optimizing its effects for voltage transformers is of great importance. In this study, comprehensive modeling of a medium voltage block-type voltage transformer is performed. In addition, a recent model is proposed to improve the performance of voltage transformers during the occurrence of ferroresonance using damping oscillations. Also, transformer design optimization is presented in this study to show further improvements in the performance of the voltage transformer. The recently proposed model is experimentally tested and verified on a medium voltage transformer in the laboratory, and simulation results show a large reduction of the effects of ferroresonance.

Keywords: optimization, voltage transformer, ferroresonance, modeling, damper

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Authors: Arash Khosravi, Mohamad Nazir Ahmad

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Today’s economy is a knowledge-based economy in which knowledge is a crucial facilitator to individuals, as well as being an instigator of success. Due to the impact of globalization, universities face new challenges and opportunities. Accordingly, they ought to be more innovative and have their own competitive advantages. One of the most important goals of universities is the promotion of students as professional knowledge workers. Therefore, knowledge sharing and transferring at tertiary level between students and supervisors is vital in universities, as it decreases the budget and provides an affordable way of doing research. Knowledge-sharing impact factors can be categorized into three groups, namely: organizational, individual and technical factors. There are some individual barriers to knowledge sharing, namely: lack of time and trust, lack of communication skills and social networks. IT systems such as e-learning, blogs and portals can increase knowledge sharing capability. However, it must be stated that IT systems are only tools and not solutions. Individuals are still responsible for sharing information and knowledge. This paper proposes new research model to examine the effect of individual factors and organisational factors, namely: learning strategy, trust culture, supervisory support, as well as technological factor on knowledge sharing in a research supervision process at the University of Technology Malaysia.

Keywords: knowledge management, knowledge sharing, research supervision, knowledge transferring

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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Authors: Mobina Bagherianlemraski, Parastoo Namdar

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Background: The ongoing coronavirus disease has affected most countries. This virus has high transmission power. Due to the closure of most dental clinics, millions of orthodontic patients missed their appointments during the COVID-19 pandemic. Methods: A questionnaire was developed and sent to patients receiving orthodontic treatment at a public or private clinic. Results: A total of 200 responses were analyzed: These included 153 women (76.5%) and 47 men (23.5%). The mean and standard deviation of their age was 18.92±7.23 years, with an age range of 8 to 40 years. One hundred eighty-nine patients (94.5%) had fixed appliances, and 11 patients (5.5%) had removable appliances. Of all participants, 35% (70) missed their appointments. The highest and lowest reasons for stopping appointments were concerned about the spread of COVID-19 with 28 cases (40%) and the closure of the clinic with 15 cases (21.4%). Of the 53 patients who contacted their orthodontists, 86.8 % (46) communicated via office phone and 5.7% (3) through social media. Conclusion: This study determined that the coronavirus pandemic and quarantine have had an important impact on orthodontic treatments. The greatest concern of orthodontic patients was increasing in treatment duration. Patients who used fixed appliances reported missing dental appointments more than others. Therefore, during COVID 19 Pandemic, orthodontists should prepare patients to solve their problems linked to orthodontic appliances when possible.

Keywords: orthodontic patients, coronavirus pandemic, appointments, COVID-19

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Authors: Tariq Ahamad, Mohammed S. Al-Kahtani, Taisir Eldos

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Optical communications technology has made enormous and steady progress for several decades, providing the key resource in our increasingly information-driven society and economy. Much of this progress has been in finding innovative ways to increase the data carrying capacity of a single optical fiber. In this research article we have explored basic issues in terms of security and reliability for secure and reliable information transfer through the fiber infrastructure. Conspicuously, one potentially enormous source of improvement has however been left untapped in these systems: fibers can easily support hundreds of spatial modes, but today’s commercial systems (single-mode or multi-mode) make no attempt to use these as parallel channels for independent signals. Bandwidth, performance, reliability, cost efficiency, resiliency, redundancy, and security are some of the demands placed on telecommunications today. Since its initial development, fiber optic systems have had the advantage of most of these requirements over copper-based and wireless telecommunications solutions. The largest obstacle preventing most businesses from implementing fiber optic systems was cost. With the recent advancements in fiber optic technology and the ever-growing demand for more bandwidth, the cost of installing and maintaining fiber optic systems has been reduced dramatically. With so many advantages, including cost efficiency, there will continue to be an increase of fiber optic systems replacing copper-based communications. This will also lead to an increase in the expertise and the technology needed to tap into fiber optic networks by intruders. As ever before, all technologies have been subject to hacking and criminal manipulation, fiber optics is no exception. Researching fiber optic security vulnerabilities suggests that not everyone who is responsible for their networks security is aware of the different methods that intruders use to hack virtually undetected into fiber optic cables. With millions of miles of fiber optic cables stretching across the globe and carrying information including but certainly not limited to government, military, and personal information, such as, medical records, banking information, driving records, and credit card information; being aware of fiber optic security vulnerabilities is essential and critical. Many articles and research still suggest that fiber optics is expensive, impractical and hard to tap. Others argue that it is not only easily done, but also inexpensive. This paper will briefly discuss the history of fiber optics, explain the basics of fiber optic technologies and then discuss the vulnerabilities in fiber optic systems and how they can be better protected. Knowing the security risks and knowing the options available may save a company a lot embarrassment, time, and most importantly money.

Keywords: in-house networks, fiber optics, security risk, money

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Authors: Pius Akindele Adeniyi

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Developing countries including Nigeria are greatly saddled with problems emanating from environmental deterioration. These problems are glaringly threatening the existence of mankind. A wide range of factors contribute to environmental problems and prominent among these are: increase in human population, deforestation, industrialization, urbanization, ignorance and socio-economic activities. The economic function of the forest has for quite a long time played a major role in the economic life of the people of Nigeria while the social function such as the recreational use of the forest has until today play very little role in the cultural development of the country. Recreation forest ameliorates the environment, reduces psychological stress, and broadens individual outlook and horizon. Unfortunately domestic tourism of recreational forest is not developed and almost unknown due to poverty and non existence of recreational facilities. Social forestry is seen as a sustainable means of combating ecological problems especially in third world countries such as Nigeria. The programme also provides social and economic benefits to the rural people. As a rural-based activity, people's participation is crucial for its success. There is need to create awareness on recreational forestry and social forestry as well as harness their resources for the country .This paper therefore highlights the constraints in the practice of social and recreational forestry in developing countries and suggests ways to motivate the rural people to participate in the programme. . Attempt has been made to trace the causes and consequences of Nigerian environmental deterioration, while suggestions on possible solutions are proffered .

Keywords: recreational, social, deteriorating, forestry

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Authors: Milton Jusu, Moses Koroma

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Efforts by the Ministry of Fisheries and Marine Resources and its development partners to introduce “modern” aquaculture in Sierra Leone since the 1970s have not been successful. A number of reasons have been hypothesized, including the suggestion that the market infrastructure and demand for farmed fish were inadequate to stimulate large-scale and widespread aquaculture production in the country. We have assessed the size, structure, networks and opportunities in fish markets using a combination of Participatory Rural Appraisals (PRAs) and questionnaire surveys conducted in a sample of 29 markets (urban, weekly, wholesale and retail) and two hundred traders. The study showed that the local fish markets were dynamic, with very high variations in demand and supply. The markets sampled supplied between 135.2 and 9947.6 tonnes/year. Mean prices for fresh fish varied between US$1.12 and US$3.89/kg depending on species, with smoked catfish and shrimps commanding prices as high as US$7.4/kg. It is unlikely that marine capture fisheries can increase their current production levels, and these may, in fact, already be over-exploited and declining. Marine fish supplies are particularly low between July and September. More careful attention to the timing of harvests (rainy season, not dry season) and to species (catfish, not tilapia) (could help in the successful adoption of aquaculture.

Keywords: fisheries and aquaculture, fish market, marine fish supplies, harvests

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Authors: Ilaria Manca, Ilaria Manca, Francesca Pettinau, Ignazia Mocci, Elisabetta M. Usai, Barbara Pittau

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Lamotrigine is a phenyltriazine used in the treatment of epilepsy and bipolar disorder type I. The purpose of this study was to test and compare various solid forms of immediate release (IR) lamotrigine products, at different strenghts, in order to study their disaggregation and dissolution behavior. IR products are designed to release their active substance promptly after administration. Concentration of hydrochloric acid in gastric juice is about 0.1-0.001 M, so FDA (Food and Drug Administration) recommends, for lamotrigine regular tablets, dissolution tests in HCl 0.1 M.Toinvestigate the pH dependency of drug release in the entire gastrointestinal tract, we worked at two additional media with different pH values (4.5 and 6.8), that reflect conditions in it. To afford acceptable dissolution rates, tablets must disintegrate. Disaggregation of constituent particles increases the surface area and substantially increases the dissolution rate. For this reason availability of an active substance from tablets depends on its ability to disintegrate fast in dissolution media. pH of gastrointestinal fluid affects drug absorption by conditioning its solubility and dissolution, but also tablet disintegration may be influenced by it. To obtain information about the quantitative relationship between different mixture components, Nuclear Magnetic Resonance (NMR) spectroscopy was used. We also investigate tablet hardness. The investigation carried out confirms pH 1.2 as the ideal environment for the immediate availability of the active substance.

Keywords: dissolution, disaggregation, Lamotrigine, bioequivalence

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Authors: Md. Abu Yousuf

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Islamic social financing (ISF) refers to the fair distribution of wealth and financial dealings and prevents economic exploitation at all levels. ISF instruments include Islamic institutions Zakat (obligatory charity), Sadaqah (voluntary charity) and Waqf (endowment) based on philanthropy such and Qard-al Hasan (beautiful loan), micro takaful (insurance) and social investments through Sukuk (bonds) based on cooperation. ISF contributes to socio-economic development, end poverty, protects environmental sustainability, promotes education, equality, social justice and above all, establishes social well-being since the birth of Islam. ISF tools are instrumental towards achieving sustainable development goals (SDGs) set by United Nations (UN). The present study will explore the scope of ISF for community development in Bangladesh and examine the challenges in implementing ISF tools and will provide the most practical model of ISF. The study will adopt a mixed-method (MM) design in the process of data collection and analysis. The researcher will consider all issues related to ethics, reliability, validity and feasibility while conducting the study.

Keywords: Islamic social financing, sustainable development goals, poverty eradication, zakat, waqf, sadaqah, Islamic microfinance

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Drazen Simlesa, Jelena Pudjak, Anita Tonkovic Busljeta

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Regarding social economy (SE), Croatia is, on general level, considered as ex-communist country with good tradition, bad performance in second part of 20th Century because of political control in the business sector, which has in transition period (1990-1999) became a problem of ignorance in public administration (policy level). Today, social economy in Croatia is trying to catch up with other EU states on all important levels of SE sector: legislative and institutional framework, financial infrastructure, education and capacity building, and visibility. All four are integral parts of Strategy for the Development of Social Entrepreneurship in the Republic of Croatia for the period of 2015 – 2020. Within iPRESENT project, funded by Croatian Science Foundation, we have mapped social economy actors and after many years there is a clear and up to date social economy base. At the ICSE 2016 we will present main outcomes and results of this process. In the second year of the project we conducted a field research across Croatia carried out 19 focus groups with most influential, innovative and inspirational social economy actors. We divided interview questions in four themes: laws on social economy and public policies, definition/ideology of social economy and cooperation on SE scene, the level of democracy and working conditions, motivation and existence of intrinsic values. The data that are gathered through focus group interviews has been analysed via qualitative data analysis software (Atlas ti.). Major finding that will be presented in ICSA 2016 are: Social economy actors are mostly unsatisfied with legislative and institutional framework in Croatia and consider it as unsupportive and confusing. Social economy actors consider SE to be in the line with WISE model and as a tool for community development. The SE actors that are more active express satisfaction with cooperation amongst SE actors and other partners and stakeholders, but the ones that are in more isolated conditions (spatially) express need for more cooperation and networking. Social economy actors expressed their praise for democratic atmosphere in their organisations and fair working conditions. And finally, they expressed high motivation to continue to work in the social economy and are dedicated to the concept, including even those that were at the beginning interested just in getting a quick job. It means that we can detect intrinsic values for employees in social economy organisations. This research enabled us to describe for the first time in Croatia the view from the inside, attitudes and opinion of employees of social economy organisations.

Keywords: employees, focus groups, mapping, social economy

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Authors: Farah Al-Shatti, Elsayed El-Khamisi, Nabel Suleiman

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The study aimed at identifying the relationship between self-injury behavior and social skills among children with mild intellectual disability (ID) in the state of Kuwait. The sample of the study consisted of 65 males and females with ID; their ages ranged between 8 to 12 years. The study used a measure for rating self-injury behavior designed by the researcher; and a measure for rating social skills was designed. The results of the study showed that there was an increase in the percentages of the two dimensions of the self-injury behavior for children with ID; the self-injury behavior by child’s own body was higher than the self-injury behavior by environmental tools, additionally the results showed that there were statistically significant differences between males and females on the dimensions and total scorer of self-injury scale favor the males, and there were statistically significant differences between them on the dimensions of the social skills and total score favor the females, It also indicated that there was statistically significant negative relationship between the dimensions of the self-injury and the dimensions of the social skills for children with intellectual disability.

Keywords: mild intellectual disability, self injury behavior, social skills, state of Kuwait

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Andrew D. Henshaw, James M. Austin

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Introduction: Human trafficking is an increasingly serious transnational criminal enterprise and social security issue. Despite ongoing efforts to mitigate the phenomenon and a significant expansion of security scrutiny over past decades, it is not receding. This is true for many nations in Southeast Asia, widely recognized as the global hub for trafficked persons, including men, women, and children. Clearly, human trafficking is difficult to address because there are numerous drivers, causes, and motivators for it to persist, such as non-military and non-traditional security challenges, i.e., climate change, global warming displacement, and natural disasters. These make displaced persons and refugees particularly vulnerable. The issue is so large conservative estimates put a dollar value at around $150 billion-plus per year (Niethammer, 2020) spanning sexual slavery and exploitation, forced labor, construction, mining and in conflict roles, and forced marriages of girls and women. Coupled with corruption throughout military, police, and civil authorities around the world, and the active hands of powerful transnational criminal organizations, it is likely that such figures are grossly underestimated as human trafficking is misreported, under-detected, and deliberately obfuscated to protect those profiting from it. For example, the 2022 UN report on human trafficking shows a 56% reduction in convictions in that year alone (UNODC, 2022). Our Approach: To better understand this, our research utilizes a bespoke methodology. Applying a JAM (Juxtaposition Assessment Matrix), which we previously developed to detect flows of dark money around the globe (Henshaw, A & Austin, J, 2021), we now focus on the human trafficking paradigm. Indeed, utilizing a JAM methodology has identified key indicators of human trafficking not previously explored in depth. Being a set of structured analytical techniques that provide panoramic interpretations of the subject matter, this iteration of the JAM further incorporates behavioral and driver indicators, including the employment of Open-Source Artificial Intelligence (OS-AI) across multiple collection points. The extracted behavioral data was then applied to identify non-traditional indicators as they contribute to human trafficking. Furthermore, as the JAM OS-AI analyses data from the inverted position, i.e., the viewpoint of the traffickers, it examines the behavioral and physical traits required to succeed. This transposed examination of the requirements of success delivers potential leverage points for exploitation in the fight against human trafficking in a new and novel way. Findings: Our approach identified new innovative datasets that have previously been overlooked or, at best, undervalued. For example, the JAM OS-AI approach identified critical 'dark agent' lynchpins within human trafficking that are difficult to detect and harder to connect to actors and agents within a network. Our preliminary data suggests this is in part due to the fact that ‘dark agents’ in extant research have been difficult to detect and potentially much harder to directly connect to the actors and organizations in human trafficking networks. Our research demonstrates that using new investigative techniques such as OS-AI-aided JAM introduces a powerful toolset to increase understanding of human trafficking and transnational crime and illuminate networks that, to date, avoid global law enforcement scrutiny.

Keywords: human trafficking, open-source intelligence, transnational crime, human security, international human rights, intelligence analysis, JAM OS-AI, Dark Money

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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Authors: Yvonne A. Unrau

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Social work education is a competency-based curriculum that relies mostly on cognitive frameworks and problem-solving models. Absent from the curriculum is knowledge and skills that draw from an embodiment perspective, especially somatic practice methods. Embodiment broadly encompasses the understanding that biological, political, historical, and social factors impact human development via changes to the nervous system. In the past 20 years, research has well-established that unresolved traumatic events, especially during childhood, negatively impacts long-term health and well-being. Furthermore, traumatic stress compromises cognitive processing and activates reflexive action such as ‘fight’ or ‘flight,’ which are the focus of somatic methods. The main objective of this paper is to show how embodiment perspectives and somatic methods can enhance social work practice overall. Using an exploratory approach, the author shares a decade-long journey that involved creating an education-support program for college students who exited the state foster care system. Personal experience, program outcomes and case study narratives revealed that ‘classical’ social work methods were insufficient to fully address the complex needs of college students who were living with complex traumatic stressors. The paper chronicles select case study scenarios and key program development milestones over a 10-year period to show the benefit of incorporating embodiment perspectives in social work practice. The lessons reveal that there is an immediate need for social work curriculum to include embodiment perspectives so that social workers may be equipped to respond competently to their many clients who live with unresolved trauma.

Keywords: social work practice, social work curriculum, embodiment, traumatic stress

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Authors: Carrollyne Aasen, Laverne Seales

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With increased Latinx communities within the United States, specifically in California, and more universities receiving designations of Hispanic-Serving institutions, Spanish programs have evolved to include more targeted and applicable practical skills. The Spanish program in the Languages and Cultures Department at California Lutheran University incorporated an interdisciplinary project with the Communication Department to create student-generated Spanish-language news inserts, which serve as a sister publication to the English-language student newspaper, The Echo. California Lutheran University is a Hispanic-Serving Institution, meaning it is an accredited undergraduate institution with full-time Hispanic/Latinx students equivalent to at least 25 percent of the total students enrolled. As a Hispanic Serving Institution with growing numbers of bilingual students, faculty, staff, and community members, the need for more information aimed at Hispanic/Latinx communities increased, resulting in the opportunity to reflect topics of interest by community members. This project was developed to fulfill the Spanish program's goals for proficiency by using the American Council on the Teaching of Foreign Languages guidelines and the university's need to support students and the community's voices. This article describes the stages from inception to production and the incorporation of journalism principles into the Spanish curriculum.

Keywords: interdisciplinary, media, foreign languages, HSI

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Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

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Authors: M. Inbar Daeribi, Vara Leoni

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Street Library Movement has been established and started to grow in some cities in Indonesia as a social movement. In the beginning, this movement emerged as a response to Indonesian lack of reading culture. Nevertheless, this study found out that street library movement is not only a literacy movement for developing reading culture. Furthermore, this movement is also a resistance towards education system in Indonesia. Street library movement is a critical consciousness driven by autonomous working group (community) as counter-public form towards Indonesia’s education condition legitimated by the government. This study, conducted in qualitative method with street library movement in Sukabumi, West Java, Indonesia as the object of study, will examine resistance forms of this movement and its social impacts. By studying this paper, it can be explained how street library movement served as an engine for social development.

Keywords: street library movement, social movement, resistance, education system

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

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This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: image registration techniques, medical images, neural networks, optimisaztion, transformation

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Authors: Nutthan Inkhong, Sutthiphong Ruangchante

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Chiang Rai province is located at the northern border of Thailand. Most of the geography there is the northern continental highlands, and the population has many types of inhabitants, including Thai people, immigrants and ethnic groups such as Akha, Lahu, Lisu, Yao, etc. Most of these ethnic groups migrated from neighbouring countries such as Myanmar, Laos, China, etc. and settled in the mountains. Each ethnic group has their unique traditions, culture, and ways of life, including the musical culture that the ancestors of each ethnic group brought with them. In the present, the Akha have the largest population in the region and still live together in numerous villages in many districts. Thus, Akha musical culture still appears in the community traditions and cultural events of Chiang Rai province regularly. This article presents the situations of Akha musical culture in the present and the predictions for the future. The study method involves the analysis of music information and the related social contexts, which were collected from the fieldwork of ethnomusicological methodology by in-depth interviews, observations, audio and visual recordings, and related documents. The results found that the important persons who are related with Akha musical culture include (1) a musical instrument maker (lives in Mae Chan district) who produces various Akha musical instruments, including gourd mouth organs, Akha drums, two-way flutes, three-hole flutes, Jew’s harps (the sound of teenage love), buffalo horns (the sound symbol of hunting) and bird call instruments (the imitation of bird sounds), (2) a folk philosopher (lives in Mae Pha Luang district) who can teach music to the new generation of Akha people as well as lecture and demonstrate music to academics and tourists, and (3) a community leader (lives in Mae Chan district) who conserves Akha performances, singing and music through various activities of the students in an informal school. Because of the changes to the social contexts and ways of life of the Akha people, such as the educational system, religion, social media, etc., including the popularity of both Thai and international popular music among the new generation of Akha people, changes to and the fading away of Akha musical culture in the future may likely occur. Therefore, the conservation and inheritance of Akha music is an issue that should be resolved quickly. This primary study leads to the next step of the ethnomusicological work and plays a part in preventing or reducing the problems impacting Akha musical culture survival by the recording of Akha music in all of its dimensions, such as producing musical instruments, playing musical instruments, analysis of tuning systems, recording Akha music as musical notation using symbols, researching related social contexts, etc. and the transcription of this information to create lessons that can be returned to the Akha community.

Keywords: Akha music, Chiang Rai, ethnic music in Thailand, ethnomusicology

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Authors: Tsega Asresa Mengistu, Getahun Tigistu

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Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

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Authors: Nadia Samantha Zuñiga-Peña, Norberto Hernández-Romero, Omar Aguilar-Mejia, Salatiel García-Nava

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Using unmanned aerial vehicles (UAVs) for load transport has gained significant importance in various sectors due to their ability to improve efficiency, reduce costs, and access hard-to-reach areas. Although UAVs offer numerous advantages for load transport, several complications and challenges must be addressed to exploit their potential fully. Complexity relays on UAVs are underactuated, non-linear systems with a high degree of coupling between their variables and are subject to forces with uncertainty. One of the biggest challenges is modeling and controlling the system formed by UAVs carrying a load. In order to solve the controller problem, in this work, a hybridization of Neural Network and Hunger Games Search (HGS) metaheuristic algorithm is developed and implemented to find the parameters of the Super Twisting Sliding Mode Controller for the 8 degrees of freedom model of UAV with payload. The optimized controller successfully tracks the UAV through the three-dimensional desired path, demonstrating the effectiveness of the proposed solution. A comparison of performance shows the superiority of the neural network HGS (NNHGS) over the HGS algorithm, minimizing the tracking error by 57.5 %.

Keywords: neural networks, hunger games search, super twisting sliding mode controller, UAVs.

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Authors: Kailin K. Zhang, Anne W. Thompson

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Electronic learning for continuing professional education (CPE) and interprofessional education (IPE) in healthcare have been shown to improve learners’ satisfaction, attitudes, and performance. Yet, their impact on behavior change in healthcare professionals through continuing interprofessional education (CIPE) is less known. A scoping review of 32 articles from 2010 to 2020 was conducted using the Arksey and O’Malley framework across all healthcare settings. It focused on evaluating the effectiveness of CIPE on behavior change of healthcare professionals, as well as identifying course features of electronic CIPE programs facilitating behavior change. Eight different types of electronic learning methods, including online programs, tele-education, and social media, were identified as interventions. More than 35,542 healthcare professionals participated in the interventions. Electronic learning for CIPE led to positive behavior outcomes in 30 out of 32 studies, especially through a change in patient care practices. The most successful programs provided interactive and authentic learning experiences tailored to learners’ needs while promoting the direct application of what was learned in their clinical settings. Future research should include monitoring of sustained behavior changes and their resultant patient outcomes.

Keywords: behavior change, continuing interprofessional education, distance learning, electronic learning

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Authors: Umair Nadeem, Sidra Umair

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Political behavior of voters and democratic values have been observed an emerging phenomenon in recent years in Pakistan. Privatized TV news channels are taking one sided position on the political issues, corresponding with respective political parties. Since last decade, TV News Channels have undermined this monopoly. Elections 2013 were unique in Pakistan with reference to political behavior and democratic values. Partisan narratives and counter narratives have been witnessed on different TV channels, in last few years. These mediated events seem very important to study the political behavior and democratic values as the country is approaching towards elections 2018. This endeavor is an attempt to capture the framing of the parties, issues in the partisan media culture and framing effects on political behavior of voters. Data for this research come from two data set. Content analysis of selected representative talks shows broadcast on mainstream news channels provide an assessment of the framing while quantitative survey of the discussion program’s viewers from Lahore city provide an evidence of framing effects on political behavior on voters and on democratic values. Regression results help us to argue that the highly partisan shows are strong predictors of polarized views among the audience. Study also grasp the attention of scholars towards the implications of this phenomenon.

Keywords: democratic values, partisan media, polarized views, political behavior

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Authors: Iris Maria Velez Osorio

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There has been in the last decade a concern about the environment, particularly about clean and enough water for human consumption but, some enterprises had some trouble to understand the limited resources in the environment. This research tries to understand how some industries are better oriented to the preservation of the environment through investment for strategic management of scarce resources and try in the best way possible, the contaminants. It was made an industry classification since four different group of theories for Corporate Social Responsibility agree with variables of: investment in environmental care, water protection, and residues treatment finding different levels of commitment with CSR.

Keywords: corporate social responsibility, environment, strategic management, water

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Authors: Jae-Hyung Jin, Kyung-Tae Lee, Yee-Seul So, Eunji Jeong, Yeonseon Lee, Dongpil Lee, Dong-Gi Lee, Yong-Sun Bahn

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Cryptococcus neoformans causes cryptococcal meningoencephalitis mainly in immunocompromised patients as well as immunocompetent people. But therapeutic options are limited to treat cryptococcosis. Some signaling pathways including cyclic AMP pathway, MAPK pathway, and calcineurin pathway play a central role in the regulation of the growth, differentiation, and virulence of C. neoformans. To understand signaling networks regulating the virulence of C. neoformans, we selected the 114 putative phosphatase genes, one of the major components of signaling networks, in the genome of C. neoformans. We identified putative phosphatases based on annotation in C. neoformans var. grubii genome database provided by the Broad Institute and National Center for Biotechnology Information (NCBI) and performed a BLAST search of phosphatases of Saccharomyces cerevisiae, Aspergillus nidulans, Candida albicans and Fusarium graminearum to Cryptococcus neoformans. We classified putative phosphatases into 14 groups based on InterPro phosphatase domain annotation. Here, we constructed 170 signature-tagged gene-deletion strains through homologous recombination methods for 91 putative phosphatases. We examined their phenotypic traits under 30 different in vitro conditions, including growth, differentiation, stress response, antifungal resistance and virulence-factor production.

Keywords: human fungal pathogen, phosphatase, deletion library, functional genomics

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