Abstract: This cross-sectional study aims to explore the differences among adults with somatic symptom disorder (SSD) versus adults without SSD, in terms of attachment and emotion regulation strategies. A total sample of 80 participants (40 people with SSD and 40 healthy controls), aged 20-57 years old (M = 31.69, SD = 10.55), were recruited from institutions and online groups. They completed the Romanian version of the Experiences in Close Relationships Scale – Short Form (ECR-S), Regulation of Emotion Systems Survey (RESS), Patient Health Questionnaire-15 (PHQ-15) and Somatic Symptom Disorder – B Criteria Scale (SSD-12). The results indicate significant differences between the two groups in terms of attachment and emotion regulation strategies. Adults with SSD have a higher level of attachment anxiety and avoidance compared to the nonclinical group. Moreover, people with SSD are more prone to use rumination and suppression and less prone to use reevaluation compared to healthy people. Implications for SSD prevention and treatment are discussed.
Abstract: The wellbeing of urban dwellers is strongly associated with the quality and quantity of green infrastructure. Nevertheless, urban green infrastructure is still lagging in many Arab cities, and Jordan is no exception. The capital city of Jordan, Amman, is becoming more urban dense with limited green spaces. The unplanned urban growth in Amman has caused several environmental problems such as urban heat islands, air pollution and lack of green spaces. This study aims to investigate the most suitable drivers to leverage the implementation of urban green infrastructure in Jordan through qualitative and quantitative analysis. The qualitative research includes an extensive literature review to discuss the most common drivers used internationally to promote urban green infrastructure implementation in the literature. The quantitative study employs a questionnaire survey to rank the suitability of each driver. Consultants, contractors and policymakers were invited to fill the research questionnaire according to their judgments and opinions. Relative Importance Index has been used to calculate the weighted average of all drivers and the Kruskal-Wallis test to check the degree of agreement among groups. This study finds that research participants agreed that indirect financial incentives (i.e., tax reductions, reduction in stormwater utility fee, reduction of interest rate, density bonus etc.) are the most effective incentive policy whilst granting sustainability certificate policy is the least effective driver to ensure widespread of UGI is elements in Jordan.
Abstract: With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.
Abstract: In March 2020, in Spain, a sanitary and unexpected crisis caused by COVID-19 was declared. All of a sudden, all degrees, classes and evaluation tests and projects had to be transformed into online activities. However, the chaotic situation generated by a complex operation like that, executed without any well-established procedure, led to very different experiences and, finally, results. In this paper, we are describing three experiences in two different Universities in Madrid. On the one hand, the Technical University of Madrid, a public university with little experience in online education was considered. On the other hand, Alfonso X el Sabio University, a private university with more than five years of experience in online teaching was involved. All analyzed subjects were related to computer engineering. Professors and students answered a survey and personal interviews were also carried out. Besides, the professors’ workload and the students’ academic results were also compared. From the comparative analysis of all these experiences, we are extracting the most successful strategies, methodologies, and activities. The recommendations in this paper will be useful for courses during the next months when the sanitary situation is still affecting an educational organization. While, at the same time, they will be considered as input for the upcoming digitalization process of higher education.
Abstract: Continuous improvement activities are becoming a key organizational success factor; those improvement activities include but are not limited to kaizen, six sigma, lean production, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This research aims at proposing a measuring system for kaizen activities from a sustainable balanced scorecard perspective. A survey was developed and disseminated among kaizen experts in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five sustainable balanced scorecard perspectives. This research contributes to the extant literature by presenting a kaizen measurement of both kaizen process and results that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation across various sectors and industries. Thus, grasping the full benefits of kaizen implementation will contribute to the spread of kaizen understanding and practice. Also, this research provides insights on the social and cultural differences that would influence the kaizen success. Determining the combination of the proper kaizen measures could be used by any industry, whether service or manufacturing for better kaizen activities measurement. The comparison between Japanese implementation of kaizen, as the pioneers of continuous improvement, and Egyptian implementation will help recommending better practices of kaizen in Egypt and contributing to the 2030 sustainable development goals. The study results reveal that there is no significant difference in allocating kaizen benefits between Egypt and Japan. However, with regard to the critical success factors some differences appeared reflecting the social differences and understanding between both countries, a single integrated measurement was reached between the Egyptian and Japanese allocation highlighting the Japanese experts’ opinion as the ultimate criterion for selection.
Abstract: Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization were only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the Hydrocarbon Spectra Slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven different hydrocarbon oils (crude and refined oil) taken on 10 different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).
Abstract: The study deals with the presentation of the results of quantitatively oriented research. The research was conducted as part of a questionnaire survey with the aim to find out what are the attitudes of parents to compulsory preschool education in the Czech Republic. This research presents results from the area of importance of compulsory pre-school education from the parents’ perspective. The research method was a questionnaire, which was distributed to respondents through an online platform. The research involved 107 parents, who answered a total of 36 questions that found out their attitudes to last year’s compulsory preschool attendance. The results show that compulsory pre-school attendance has increased the importance of pre-school education. However, the results also show that the compulsory last year of preschool education is not more important according to parents than in previous years. Most participants consider compulsory pre-school attendance to be important and are happy that their child attends it. The results reveal the fact that the introduction of compulsory pre-school attendance has contributed to the importance of parents’ perceptions of pre-primary education.
Abstract: In light of the tense relationship between Saudi Arabia and Iran, this research paper sheds some light on Saudi-owned television network, Al-Arabiya’s reporting of the Coronavirus in the Gulf region. Particularly because most of the cases in the beginning were coming from Iran, some programs of this Saudi channel embraced a conspiracy theory. Hate speech has been used in the talking and discussions about the topic. The results of these discussions will be detailed in this paper in percentages with regard to the research sample, which includes five programs on the Al-Arabiya channel: ‘DNA’, ‘Marraya’ (Mirrors), ‘Panorama’, ‘Tafaolcom’ (Your Interaction) and ‘Diplomatic Street’, in the period between January 19, that is, the date of the first case in Iran, and April 10, 2020. The research shows the use of a conspiracy theory in the programs, in addition to some professional violations. The surveyed sample also shows that the matter receded due to the Arab Gulf states' preoccupation with the successively increasing cases that have appeared there since the start of the pandemic. The results indicate that hate speech was present in the sample at a rate of 98.1%, and that most of the programs that dealt with the Iranian issue under the Coronavirus pandemic on Al Arabiya used the conspiracy theory at a rate of 75.5%.
Abstract: A lot of children under the age of five spend their daytime hours away from their home, in a kindergarten. Caring for children is a serious subject, and their safety in case of earthquake is the first priority. Being aware of earthquakes helps to prioritize the needs and take the appropriate actions to limit the effects. Earthquakes occurring anywhere at any time require emergency planning. Earthquake planning is a cooperative effort and childcare providers have unique roles and responsibilities. Greece has high seismicity and Ionian Islands Region has the highest seismic activity of the country. Earthquake Planning and Protection Organization (EPPO) is a national organization in Greece. The mission of EPPO is the seismic risk reduction by designing an earthquake management program of mitigation and preparedness. Among other actions EPPO has analyzed the needs and requirements of kindergartens on earthquake protection issues and has designed specific activities to familiarize the day care centers staff being prepared for earthquakes. This research presents the results of a survey that detects the level of earthquake preparedness of kindergartens in all over the country and Ionian Islands too. A closed-form questionnaire of 20 main questions was developed for the survey in order to detect the aspects of participants concerning the earthquake preparedness actions at individual, family and day care environment level. 2668 questionnaires were gathered from March 2014 to May 2019, and analyzed by EPPO’s Department of Education. Moreover, this paper presents the EPPO’s educational activities targeted to the Ionian Islands Region that implemented in the framework of “Telemachus” Project. To provide safe environment for children to learn, and staff to work is the foremost goal of any State, community and kindergarten. This project is funded under the Priority Axis “Environmental Protection and Sustainable Development” of Operational Plan “Ionian Islands 2014-2020”. It is increasingly accepted that emergency preparedness should be thought of as an ongoing process rather than a one-time activity. Creating an earthquake safe daycare environment that facilitates learning is a challenging task. Training, drills, and update of emergency plan should take place throughout the year at kindergartens to identify any gaps and to ensure the emergency procedures. EPPO will continue to work closely with regional and local authorities to actively address the needs of children and kindergartens before, during and after earthquakes.
Abstract: In Nigeria, enormous efforts/resources had, over the years, been expended on promoting financial inclusion (FI); however, it is seemingly discouraging that many of its self-declared targets on FI remained unachieved, especially amongst the Rural Dwellers and Actors in the Informal Sectors (RDAIS). Expectedly, many reasons had been earmarked for these failures: low literacy level, huge informal/rural sectors etc. This study posits that in spite of these truly-debilitating factors, these FI policy failures could have been avoided or mitigated if the principles of active and better-managed citizens’ participation had been strictly followed in the (re)design/implementation of its FI policies. In other words, in a bid to mitigate the prevalent financial exclusion (FE) in Nigeria, this study hypothesizes the significant positive impact of involving the RDAIS in policy-wide decision making in the FI domain, backed by a preliminary empirical validation. Also, the study introduces the RDAIS-focused Participatory Financial Inclusion Policy (PFIP) as a major FI policy regeneration/improvement tool. The three categories of respondents that served as research subjects are FI experts in Nigeria (n = 72), RDAIS from the very rural/remote village of Unguwar Dogo in Northern Nigeria (n = 43) and RDAIS from another rural village of Sekere (n = 56) in the Southern region of Nigeria. Using survey design (5-point Likert scale questionnaires), random/stratified sampling, and descriptive/inferential statistics, the study often recorded independent consensus (amongst these three categories of respondents) that RDAIS’s active participation in iterative FI policy initiation, (re)design, implementation, (re)evaluation could indeed give improved FI outcomes. However, few questionnaire items also recorded divergent opinions and various statistically (in)significant differences on the mean scores of these three categories. The PFIP (or any customized version of it) should then be carefully integrated into the NFIS of Nigeria (and possibly in the NFIS of other developing countries) to truly/fully provide FI policy integration for these excluded RDAIS and arrest the prevalence of FE.
Abstract: A great number of children in mainstream schools across Libya is currently living with emotional, behavioural difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioural difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Libya find classroom behaviour problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom, 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with EBD. The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.
Abstract: Since the beginning of the 21st century, we have been observing in some seaside resorts aging demography, combined with an increase in second homes. These seaside resorts are said to have become places undergoing profound changes, leading to hybridization of functions (personal services, health, residential, etc.) and practices. All of these issues are part of the challenges of silver tourism, which stems from the silver economy. The Hauts-de-France region is made up of numerous seaside resorts that have a significant proportion of second homes in their real estate stock. The seaside resorts have tourist offers based on sports and leisure activities. They also offer a suitable environment for the installation of this category of the population. This set of attractive criteria in the choice of installation in seaside resorts is likely to be replaced by personal and health services due to the advanced age of the population. The resorts of Le Touquet Paris-Plage, Bray-Dunes, Neufchâtel-Hardelot and Le Crotoy seem to be evolving towards other functions of residential resorts, as opposed to seaside resorts This paper will be an opportunity to present the results of the surveys we conducted in 4 seaside resorts in the Hauts-de-France region, where more than 420 retired secondary residents were questioned. The results show that nearly 90% of retirees spend their time in their second home at any time of the year. The criteria that lead them there are school vacations and the weather. More than 40% of them have been living there for more than 20 years. The reasons for the installations are the living environment (83%) and the quality of life (79%). Their activities are walking and strolling, as well as sports. More than 99% of the respondents do not take into account the health service offers. Personal services are also little taken into account - around 60% of respondents say they do not know whether personal services exist in the resort. 80% of respondents answer that their grandchildren benefit from activities organized by the commune and the tourist offices during their stay. To conclude, the influx of retired secondary residents will not lead to a change in the functions of the seaside resorts. Their classic tourist offers - leisure and sports activities, the environment - will remain the attractive criteria of the seaside resorts. The results of the study prove that personal services and health services are not the first choice criteria in the installation of retired secondary residents, quite the contrary. We can even complete that retirees in secondary residences are demanding and concerned about living in a calm, safe and clean environment and quality of life.
Abstract: During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.
Abstract: Autonomous vehicles look set to drastically alter the way we move people and goods, in urban as well as rural areas. However, little has been written about Africa with this regard. Moreover, in order for this new technology to be adopted, user acceptance is vital. The current research examines the user acceptance of autonomous minibus shuttles, as a solution for first/last mile public transport in Pretoria, South Africa. Of the respondents surveyed, only 2.31% perceived them as not useful. Respondents showed more interest in using these shuttles in combination with the bus rapid transit system (75.4%) as opposed to other modes of public transportation (40%). The significance of these findings is that they can help ensure that the implementation of autonomous public transport in South Africa is adapted to the local user. Furthermore, these findings could be adapted for other South African cities and other cities across the continent.
Abstract: The balancing of mechanisms is a well-known problem in the field of mechanical engineering because the variable dynamic loads cause vibrations, as well as noise, wear and fatigue of the machines. A mechanical system with unbalance shaking force and shaking moment transmits substantial vibration to the frame. Therefore, the objective of the balancing is to cancel or reduce the variable dynamic reactions transmitted to the frame. The resolution of this problem consists in the balancing of the shaking force and shaking moment. It can be fully or partially, by internal mass redistribution via adding counterweights or by modification of the mechanism's architecture via adding auxiliary structures. The balancing problems are of continue interest to researchers. Several laboratories around the world are very active in this area and new results are published regularly. However, despite its ancient history, mechanism balancing theory continues to be developed and new approaches and solutions are constantly being reported. Various surveys have been published that disclose particularities of balancing methods. The author believes that this is an appropriate moment to present a state of the art of the shaking force balancing studies completed by new research results. This paper presents an overview of methods devoted to the shaking force balancing of mechanisms, as well as the historical aspects of the origins and the evolution of the balancing theory of mechanisms.
Abstract: Machine learning is a new and exciting area of
artificial intelligence nowadays. Machine learning is the most
valuable, time, supervised, and cost-effective approach. It is not a
narrow learning approach; it also includes a wide range of methods
and techniques that can be applied to a wide range of complex realworld
problems and time domains. Biological image classification,
adaptive testing, computer vision, natural language processing, object
detection, cancer detection, face recognition, handwriting
recognition, speech recognition, and many other applications of
machine learning are widely used in research, industry, and
government. Every day, more data are generated, and conventional
machine learning techniques are becoming obsolete as users move to
distributed and real-time operations. By providing fundamental
knowledge of machine learning tools and research opportunities in
the field, the aim of this article is to serve as both a comprehensive
overview and a guide. A diverse set of machine learning resources is
demonstrated and contrasted with the key features in this survey.
Abstract: This paper describes the differences in views on sustainable development between the general public and experts in a developing country, Iraq. This paper will answer the question: How do the views of the public differ from the generally accepted view of experts in the context of sustainable urban development in Iraq? In order to answer this question, the views of both the public and the experts will be analysed. These results are taken from a public survey and a Delphi questionnaire. These will be analysed using statistical methods in order to identify the significant differences. This will enable investigation of the different perceptions between the public perceptions and the experts’ views towards urban sustainable development factors. This is important due to the fact that different viewpoints between policy-makers and the public will impact on the acceptance by the public of any future sustainable development work that is undertaken. The brief findings of the statistical analysis show that the views of both the public and the experts are considered different in most of the variables except six variables show no differences. Those variables are ‘The importance of establishing sustainable cities in Iraq’, ‘Mitigate traffic congestion’, ‘Waste recycling and separating’, ‘Use wastewater recycling’, ‘Parks and green spaces’, and ‘Promote investment’.
Abstract: Based on a convenience sample of 2,092 participants from across all 50 states of the United States, a survey was conducted to explore Americans’ mask-wearing behaviors during COVID-19 according to their political convictions, religious beliefs, and ethnic cultures from late July to early September, 2020. The purpose of the study is to provide evidential support for government policymaking so as to drive up more effective public policies by taking into consideration the variance in these social factors. It was found that the respondents’ party affiliation or preference, religious belief, and ethnicity, in addition to their health condition, gender, level of concern of contracting COVID-19, all affected their mask-wearing habits both in March, the initial coronavirus outbreak stage, and in August, when mask-wearing had been made mandatory by state governments. The study concludes that pandemic awareness campaigns must be run among all citizens, especially among African Americans, Muslims, and Republicans, who have the lowest rates of wearing masks, in order to protect themselves and others. It is recommended that complementary cognitive bias awareness programs should be implemented in non-Black and non-Muslim communities to eliminate social concerns that deter them from wearing masks.
Abstract: Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.
Abstract: Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.