Search results for: marketing intelligence

Authors: Nyong Princely Awazi, Gadinga Walter Forje, Barnabas Neba Nfornkah, Ndzifon Jude Kimengsi

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Ecotourism is documented as a sustainable measure of bridging conservation goals and livelihood sustenance around protected areas, due to its ability of not just providing alternative livelihood, but also in providing the necessary resources that can help finance conservation initiatives. In Cameroon, all ecotourism activities around national parks are aimed at generating revenue through the conservation service while providing sustainable livelihood options to the local population. There exists an information lacuna regarding the contribution of ecotourism finances to conservation efforts in the country. This study was aimed at establishing the contribution of ecotourism finances to conservation initiatives in and around the Campo Ma’an National Park (CMNP). Data were collected through the administering of 120 structured questionnaires to ecotourism actors and 15 key/expert interviews with tourism and conservation actors in the Campo Ma’an landscape. Chi-square test, Spearman’s rank correlation and regressions were used for data analysis. The study revealed that the main sources of ecotourism financing to the park service are through entrance fees, cameras and vehicle fees paid by tourists as well as ecotourism project financing through NGOs. Calculations from the tourism register of the park showed that the park was able to raise as much as 1,576,000 FCFA (US$ 3,152) annually. It was further established that ecotourism revenue has not greatly supported conservation, with 54% of respondents perceiving ecotourism not contributing to biodiversity conservation. Chi Square test results highlighted poor ecotourism governance, low level of ecotourism development, corruption from park management staff, obsolete nature of the current finance law on the management of protected area revenue as key factors hindering ecotourism financing in conservation. For ecotourism financing to contribute to biodiversity conservation in the CMNP and in Cameroon’s protected areas, the government needs to revise the finance law on the management of revenue generated from protected areas, improve park governance to fight corruption and enhance transparency, invest in the development and marketing of the Campo Ma’an national park as a tourism destination in the country.

Keywords: Cameroon, Campo Ma’an National Park, conservation, ecotourism, ecotourism financing

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Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: Suantak Demkhosei Vaiphei

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Mental illness is still considered as an illness not to be treated, resulting India becoming the most depressed country in the world. At present, 150 million Indians are suffering from mental illness and desperately in need of immediate care assessment for their mental health condition. However, only 0.06 per cent of India’s health budget is devoted to mental health treatment, in which the available data suggests that the state of spending the sanctioned budget in this regard is abysmal. Lack of awareness, ignorance, social stigma, and discriminations becomes the underlying factors for worsening the individual mental health conditions. Unfortunately, India becomes the most depressed country in the world, which is hugely affected by anxiety, schizophrenia, and bipolar disorder followed by China and USA as per the latest World Health Organization report. The National Care of Medical Health stated that at least 6.5 per cent of the Indian populations are under serious mental disorder both in the rural and the urban areas’Mental health is the integral part of health and can be affected by a range of psychosocial-economic factors that need comprehensive strategically approach for promotion, prevention, treatment, and recovery. In a low- and middle-income country like India, the advance progress in mental health service is visible consistently slow and minimal. Some of the major barriers can be seen in the existing public health priorities and its influence on funding; challenges to delivery of basic mental health care in the primary care settings; the minimal numbers of well-trained professionals in the area of mental health care; and lack of mental health perspective in public-health leadership. The existing barriers according to WHO (2007) are; lack of funding for mental health services is the core barrier in implementing quality mental health services, including inadequate coordinated and consensus based national mental health advocacy and plans, the absence of mental health in major donor priorities, marketing of expensive pharmaceuticals by industry, cost-effectiveness information on mental health services that is unknown to senior decision-makers and social stigma among others. Moreover, lack of strong mental health advocacy in countries to increase resources for mental health services and the role of social stigma and the view that mental health is a private responsibility are also the two barriers to mental health.

Keywords: mental health, depression, stigma, barriers

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Authors: Trevor R. Higgins, Ben Lopez

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Australian football fans have a tendency to indulge in foreign football clubs, often assigning a greater value to foreign clubs, in preference to the Australian National football competition; the A-League. There currently exists a gap in the knowledge available in relation to football fans in Australia, their engagement with foreign football teams and the impact that this may have with their engagement with A-League. The purpose of this study was to compare the engagement of the members of the Manchester United Supporters Club - Australia (MUSC-Aus) with Manchester United and the A-League. An online survey was implemented to gather the relevant data from members of the MUSC-Aus. Results from completed surveys were collected, and analyzed in relation to engagement levels with Manchester United and the A-League. Members of MUSC-Aus who responded to the survey were predominantly male (94%) and born in Australia (46%), England (25%), Ireland (7%), were greatly influenced in their choice of Manchester United by family (43%) and team history (16%), whereas location was the overwhelming influence in supporting the A-League (88%). Importantly, there was a reduced level of engagement in the A-League on two accounts. Firstly, only 64% of MUSC-Aus engaged with the A-League, reporting perceptions of low standard as the major reason (50%). Secondly, MUSC-Aus members who engaged in the A-League reported reduced engagement in the A-League, identified through spending patterns. MUSC-Aus members’ expenditure on Manchester United engagement was 400% greater than expenditure on A-League engagement. Furthermore, additional survey responses indicated that the level of commitment towards the A-League overall was less than Manchester United. The greatest impact on fan engagement in the A-League by MUSC-Aus can be attributed to several primary factors; family support, team history and perceptions to on-field performance and quality of players. Currently, there is little that can be done in regards to enhancing family and history as the A-League is still in its infancy. Therefore, perceptions of on-field performances and player quality should be addressed. Introducing short-term international marquee contracts to A-League rosters, across the entire competition, may provide the platform to raise the perception of the A-League player quality with minimal impact on local player development. In addition, a national marketing campaign promoting the success of A-League clubs in the ACL, as well as promoting the skill on display in the A-League may address the negative association with the standard of the A-League competition.

Keywords: engagement, football, perceptions of performance, team

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Authors: Chia-Ying Lin

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This paper explains how to enhance doctor-patient communication and nurse-patient communication through multiple intelligence signing methods and user-centered. It is hoped that through the implementation of the "electronic consent", the problems faced by the paper consent can be solved: storage methods, resource utilization, convenience, correctness of information, integrated management, statistical analysis and other related issues. Make better use and allocation of resources to provide better medical quality. First, invite the ｍedical records department to assist in the inventory of paper consent in the hospital: organising, classifying, merging, coding, and setting. Second, plan the electronic consent configuration file: set the form number, consent form group, fields and templates, and the corresponding doctor's order code. Next, Summarize four types of rapid methods of electronic consent: according to the doctor's order, according to the medical behavior, according to the schedule, and manually generate the consent form. Finally, system promotion and adjustment: form an "electronic consent promotion team" to improve, follow five major processes: planning, development, testing, release, and feedback, and invite clinical units to raise the difficulties faced in the promotion, and make improvements to the problems. The electronic signature rate of the whole hospital will increase from 4% in January 2022 to 79% in November 2022. Use the saved resources more effectively, including: reduce paper usage (reduce carbon footprint), reduce the cost of ink cartridges, re-plan and use the space for paper medical records, and save human resources to provide better services. Through the introduction of information technology and technology, the main spirit of "lean management" is implemented. Transforming and reengineering the process to eliminate unnecessary waste is also the highest purpose of this project.

Keywords: smart signature, electronic consent, electronic medical records, user-centered, doctor-patient communication, nurse-patient communication

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Authors: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: Elachouri Mostafa, Fakchich Jamila, Lazaar Jamila, Elmadmad Mohammed, Marhom Mostafa

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Of course, there has been a great growth in scientific information about medicinal plants in recent decades, but in many ways this has proved poor compensation, because such information is accessible, in practice, only to a very few people and anyway, rather little of it is relevant to problems of management and utilization, as encountered in the field. Active compounds are used in most traditional medicines and play an important role in advancing sustainable rural livelihoods through their conservation, cultivation, propagation, marketing and commercialization. Medicinal herbs are great resources for various pharmaceutical compounds and urgent measures are required to protect these plant species from their natural destruction and disappearance. Indeed, there is a real danger of indigenous Arab medicinal practices and knowledge disappearing altogether, further weakening traditional Arab culture and creating more insecurity, as well as forsaking a resource of inestimable economic and health care importance. As scientific approach, the ethnopharmacological investigation remains the principal way to improve, evaluate, and increase the odds of finding of biologically active compounds derived from medicinal plants. As developing country, belonging to the Mediterranean basin, Morocco country is endowed with resources of medicinal and aromatic plants. These plants have been used over the millennia for human welfare, even today. Besides, Morocco has a large plant biodiversity, in fact, its medicinal flora account more than 4200 species growing on various bioclimatic zones from subhumide to arid and Saharan. Nevertheless, the human and animal pressure resulting from the increase of rural population needs has led to degradation of this patrimony. In this paper, we focus our attention on ethnopharmacological studies carried out in Morocco. The goal of this work is to clarify the importance of herbs as platform for drugs discovery and further development, to highlight the importance of ethnopharmacological study as approach on discovery of natural products in the health care field, and to discuss the limit of ethnopharmacological investigation of drug discovery in Morocco.

Keywords: Morocco, medicinal plants, ethnopharmacology, natural products, drug-discovery

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Authors: Uche Lucy Onyekwelu, Uche B. Ugwuanyi

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Suffice to say that socio-economic disruptions of any form is likely to affect the wellbeing of the citizenry. The upsurge of social disequilibrium caused by the incessant disruptive tendencies exhibited by youths and some others in Nigeria are not helping matters. In Nigeria the social unrest has caused different forms of draw backs in Socio Economic Development. This study has empirically evaluated the impact of insecurity and insurgency on the Economic Development of Nigeria. The paper noted that the different forms of insecurity in Nigeria are namely: Insurgency and Banditry as witnessed in Northern Nigeria; Militancy: Niger Delta area and self-determination groups pursuing various forms of agenda such as Sit –at- Home Syndrome in the South Eastern Nigeria and other secessionist movements. All these have in one way or the other hampered Economic development in Nigeria. Data for this study were collected through primary and secondary sources using questionnaire and some existing documentations. Cost of investment in different aspects of security outfits in Nigeria represents the independent variable while the differentials in the Gross Domestic Product(GDP) and Human Development Index(HDI) are the measures of the dependent variable. Descriptive statistics and Simple Linear Regression analytical tool were employed in the data analysis. The result revealed that Insurgency/Insecurity negatively affect the economic development of the different parts of Nigeria. Following the findings, a model to analyse the effect of insecurity and insurgency was developed, named INSECUREDEVNIG. It implies that the economic development of Nigeria will continue to deteriorate if insurgency and insecurity continue. The study therefore recommends that the government should do all it could to nurture its human capital, adequately fund the state security apparatus and employ individuals of high integrity to manage the various security outfits in Nigeria. The government should also as a matter of urgency train the security personnel in intelligence cum Information and Communications Technology to enable them ensure the effectiveness of implementation of security policies needed to sustain Gross Domestic Product and Human Capital Index of Nigeria.

Keywords: insecurity, insurgency, gross domestic product, human development index, Nigeria

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: G. Scremin, I. Y. Suh, S. Doukas

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Spectators follow their favorite sports teams for different reasons. While some attend a sporting event simply for its entertainment value, others do so because of the personal sense of achievement and accomplishment their connection with a sports team creates. Moreover, the level of identity spectators feel toward their favorite sports team falls in a broad continuum. Some are mere spectators. For those spectators, their association to a sports team has little impact on their self-image. Others are die-hard fans who are proud of their association with their team and whose connection with that team is an important reflection of who they are. Several motives for sports consumption can be used to explain the level of spectator support in a variety of sports. Those motives can also be used to explain the variance in the identification, attachment, and loyalty spectators feel toward their favorite sports team. Motives for sports consumption can be used to discriminate the degree of identification spectators have with their favorite sports team. In this study, motives for sports consumption was used to discriminate the level of identity spectators feel toward their sports team. It was hypothesized that spectators with a strong level of team identity would report higher rates of interest in player, interest in sports, and interest in team than spectators with a low level of team identity. And spectators with a low level of team identity would report higher rates for entertainment value, bonding with friends or family, and wholesome environment. Football spectators in the United States and England were surveyed about their motives for football consumption and their level of identification with their favorite football team. To assess if the motives of sports fans differed by level of team identity and allegiance to an American or English football team, a Multivariate Analysis of Variance (MANOVA) under the General Linear Model (GLM) procedure found in SPSS was performed. The independent variables were level of team identity and allegiance to an American or English football team, and the dependent variables were the sport fan motives. A tripartite split (low, moderate, high) was used on a composite measure for team identity. Preliminary results show that effect of team identity is statistically significant (p < .001) for at least nine of the 17 motives for sports consumption assessed in this investigation. These results indicate that the motives of spectators with a strong level of team identity differ significantly from spectators with a low level of team identity. Those differences can be used to discriminate the degree of identification spectators have with their favorite sports team. Sports marketers can use these methods and results to develop identity profiles of spectators and create marketing strategies specifically designed to attract those spectators based on their unique motives for consumption and their level of team identification.

Keywords: fan identification, market segmentation of sports fans, motives for sports consumption, team identity

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Authors: Samar Swaid

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Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.

Keywords: data science, design thinking, AI, currculum, transformation

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Authors: Ubon Asuquo Essien, Okwudili Bismark Ibeagwa, Daberechi Peace Ubabuko

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The Broiler Poultry subsector is dominated by small scale production with low aggregate output. The high cost of inputs currently experienced in Nigeria tends to aggravate the situation; hence many broiler farmers struggle to break-even. This study was designed to examine income and input factors in small scale deep liter broiler production in Imo state, Nigeria. Specifically, the study examined; socio-economic characteristics of small scale deep liter broiler producing Poultry farmers; estimate cost and returns of broiler production in the area; analyze input factors in broiler production in the area and examined marketability, age and profitability of the enterprise. A multi-stage sampling technique was adopted in selecting 60 small scale broiler farmers who use deep liter system from 6 communities through the use of structured questionnaire. The socioeconomic characteristics of the broiler farmers and the profitability/ marketability age of the birds were described using descriptive statistical tools such as frequencies, means and percentages. Gross margin analysis was used to analyze the cost and returns to broiler production, while Cobb Douglas production function was employed to analyze input factors in broiler production. The result of the study revealed that the cost of feed (P<0.1), deep liter material (P<0.05) and medication (P<0.05) had a significant positive relationship with the gross return of broiler farmers in the study area, while cost of labour, fuel and day old chicks were not significant. Furthermore, Gross profit margin of the farmers who market their broiler at the 8th week of rearing was 80.7%; and 78.7% and 60.8% for farmers who market at the 10th week and 12th week of rearing, respectively. The business is, therefore, profitable but at varying degree. Government and Development partners should make deliberate efforts to curb the current rise in the prices of poultry feeds, drugs and timber materials used as bedding so as to widen the profit margin and encourage more farmers to go into the business. The farmers equally need more technical assistance from extension agents with regards to timely and profitable marketing.

Keywords: broilers, factor analysis, income, small scale

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Authors: Berie Abebe Getahun

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The tourism sector has been identified by the Ethiopian government as one of the priority economic sectors and planned to make Ethiopia among the top five African destinations by 2020. It is obvious international tourism demand for Ethiopia lags behind other African countries like South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival to Ethiopia increases continuously. The main purpose of this study was to find out potentials, challenges, and opportunities of Ethiopian Cultural Center for tourism product development. Therefore, an attempt has been made to identify potentials over which tourism product development can be enhanced, and opportunities that promote tourism product development in Ethiopia. To achieve this objective, data have been collected by using observation, interview and focus group discussion with selected informants working the ministry of tourism and culture. The collected data has been analyzed by transcribing materials, and by using thematic analysis method based on the research objective. Likewise, the analyzed data has been discussed in the context of prevailing literature. As revealed in finding, Ethiopian cultural center has untapped potential for tourism product development that includes: meetings, incentives, conferences, events, availability of concerned stakeholders and demand of visitors. On the other hand, lack of awareness about tourism product development, financial constraints, skilled manpower, absence of tour guiding service and interpretation of heritages have been identified as the major challenges that hindering tourism product development in the cultural center. Moreover, the growth of domestic tourism, distinctive presence and rich culture of Ethiopia, and policy of Ethiopia that promotes the growth and preservation of indigenous cultures are deemed important opportunities for tourism product development in the country. And lastly, conducting a research based on tourism product development, reviewing the existing marketing and promotion strategies, training manpower, working harmoniously with the concerned stakeholders, and a careful examination of opportunities present in order to best utilize resources were implications drawn for future intervention.

Keywords: challenges and opportunities of tourism, Ethiopian tourism potential, tourism product, tourism product development

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Authors: Lufungula Osembe

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The field of education has witnessed advances in technology and digital transformation. The methods of teaching have undergone significant changes in recent years, resulting in effects on various areas such as pedagogies, curriculum design, personalized teaching, gamification, data analytics, cloud-based learning applications, artificial intelligence tools, advanced plug-ins in LMS, and the emergence of multimedia creation and design. The field of education has not been immune to the changes brought about by digital innovation in recent years, similar to other fields such as engineering, health, science, and technology. There is a need to look at the variables/elements that digital innovation brings to education and develop a framework for higher institutions of learning to assess their readiness to create a viable environment for digital innovation to be successfully adopted. Given the potential benefits of digital innovation in education, it is essential to develop a framework that can assist academics and policymakers in higher institutions of learning to evaluate the effectiveness of adopting and adapting to the evolving landscape of digital innovation in education. The primary research question addressed in this study is to establish the preparedness of higher institutions of learning to adopt and adapt to the evolving landscape of digital innovation. This study follows a Design Science Research (DSR) paradigm to develop a framework for academics and policymakers in higher institutions of learning to evaluate the readiness of their institutions to adopt digital innovation in education. The Design Science Research paradigm is proposed to aid in developing a readiness framework for digital innovation in education. This study intends to follow the Design Science Research (DSR) methodology, which includes problem awareness, suggestion, development, evaluation, and conclusion. One of the major contributions of this study will be the development of the framework for digital innovation in education. Given the various opportunities offered by digital innovation in recent years, the need to create a readiness framework for digital innovation will play a crucial role in guiding academics and policymakers in their quest to align with emerging technologies facilitated by digital innovation in education.

Keywords: digital innovation, DSR, education, opportunities, research

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Eteri Kharaishvili

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Introduction. The paper analyzes the main indicators of export and import of Georgian agri-food products; identifies positive and negative trends under the pandemic; based on the revealed problemssubstantiates the need formodernization ofin agri-food sector. It is argued that low production and productivity rates of food products negatively impact achieving the optimal export-to-import ratio; therefore, it leads toincreaseddependence on other countries andreduces the level of food security. Research objectives. The objective of the research is to identify the key challenges based on the analysis of export-import indicators of Georgian food products during the pandemic period and develop recommendations on the possibilities of post-pandemic perspectives. Research methods. Various theoretical and methodological research tools are used in the paper; in particular, a desk research is carried out on the research topic; endogenous and exogenous variables affecting export and import are determined through factor analysis; SWOT and PESTEL analysis are used to identify development opportunities; selection and groupingof data, identification of similarities and differences is carried outby using analysis, synthesis, sampling, induction and other methods; a qualitative study is conducted based on a survey of agri-food experts and exporters for clarifying the factors that impede export-import flows. Contributions. The factors that impede the export of Georgian agri-food products in the short run under COVID-19 pandemic are identified. These are: reduced income of farmers, delays in the supply of raw materials and supplies to the agri-food sectorfrom the neighboring industries, as well as in harvesting, processing, marketing, transportation, and other sectors; increased indirect costs, etc. The factors that impede the export in the long run areas follows loss of public confidence in the industry, risk of losing positions in traditional markets, etc. Conclusions are made on the problems in the field of export and import of Georgian agri-food products in terms of the pandemic; development opportunities are evaluated based on the analysis of the agri-food sector potential. Recommendations on the development opportunities for export and import of Georgian agri-food products in the post-pandemic period are proposed.

Keywords: agri-food products, export, and import, pandemic period, hindering factor, development potential

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Authors: Kishor Prasad Bhatta, Suman Ghimire, Durga Prasad Joshi

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Invasive Alien Species (IAS) are considered waste forest resources in Nepal. The rapid expansion of IAS is one of the nine main drivers of forest degradation, though the extent and distribution of this species are not well known. Further, the knowledge of the impact of IAS removal on forest plant diversity is hardly known, and the possibilities of income generation from them at the grass-root communities are rarely documented. Systematic sampling of 1% with nested circular plots of 500 square meters was performed in IAS removed and non-removed area, each of 30 hectares in Udayapur Community Forest User Group (CFUG), Chitwan, central Nepal to observe whether the removal of IAS contributed to an increase in plant diversity. In addition, ten entrepreneurs of Udaypur CFUG, involved in the charcoal production, briquette making and marketing were interviewed and interacted as well as their record keeping booklets were reviewed to understand if the charcoal production contributed to their income and employment. The average annual precipitation and temperature of the study area is 2100 mm and 34 degree Celsius respectively with Shorea robusta as main tree species and Eupatorium odoratum as dominant IAS. All the interviewed households were from the ̔below-poverty-line’ category as per Community Forestry Guidelines. A higher Shannon-Weiner plant diversity index at regeneration level was observed in IAS removed areas (2.43) than in control site (1.95). Furthermore, the number of tree seedlings and saplings in the IAS harvested blocks were significantly higher (p < 0.005) compared to the unharvested one. The sale of charcoal produced through the pyrolysis of IAS in ̔ Bio-energy kilns’ contributed for an average increased income of 30.95 % (Nepalese rupees 31,000) of the involved households. Despite above factors, some operational policy hurdles related to charcoal transport and taxation existed at field level. This study suggests that plant diversity could be increased through the removal of IAS, and considerable economic benefits could be achieved if charcoal is substantially produced and utilized.

Keywords: briquette, economic benefits, pyrolysis, regeneration

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Authors: Mahdi Allaoua Seklab, Süleyman BaşTürk

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In the quest to enhance coastal environmental health, this study introduces a fully autonomous beach cleaning machine, a breakthrough in leveraging green energy and advanced artificial intelligence for ecological preservation. Designed to operate independently, the machine is propelled by a solar-powered system, underscoring a commitment to sustainability and the use of renewable energy in autonomous robotics. The vehicle's autonomous navigation is achieved through a sophisticated integration of LIDAR and a camera system, utilizing an SSD MobileNet V2 object detection model for accurate and real-time trash identification. The SSD framework, renowned for its efficiency in detecting objects in various scenarios, is coupled with the lightweight and precise highly MobileNet V2 architecture, making it particularly suited for the computational constraints of on-board processing in mobile robotics. Training of the SSD MobileNet V2 model was conducted on Google Colab, harnessing cloud-based GPU resources to facilitate a rapid and cost-effective learning process. The model was refined with an extensive dataset of annotated beach debris, optimizing the parameters using the Adam optimizer and a cross-entropy loss function to achieve high-precision trash detection. This capability allows the machine to intelligently categorize and target waste, leading to more effective cleaning operations. This paper details the design and functionality of the beach cleaning machine, emphasizing its autonomous operational capabilities and the novel application of AI in environmental robotics. The results showcase the potential of such technology to fill existing gaps in beach maintenance, offering a scalable and eco-friendly solution to the growing problem of coastal pollution. The deployment of this machine represents a significant advancement in the field, setting a new standard for the integration of autonomous systems in the service of environmental stewardship.

Keywords: autonomous beach cleaning machine, renewable energy systems, coastal management, environmental robotics

Procedia PDF Downloads 27

Authors: Lucas Berrini

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Academic libraries have always struggled with engaging with students and faculty. Striking the balance between what the community needs and what the library can afford has also been a point of contention for libraries. As academia begins to return to a new normal after COVID, library staff are rethinking how remind patrons that the library is open and ready for business. NC Wesleyan, a small liberal arts school in eastern North Carolina, decided to be proactive and reach out to the academic community. After shutting down in 2020 for COVID, the campus library saw a marked decrease in in-person attendance. For a small school whose operational budget was tied directly to tuition payments, it was imperative for the library to remind faculty and staff that they were open for business. At the beginning of the Summer 2022 term and continuing into the fall, the reference team created a marketing plan using email, physical meetings, and virtual events targeted at students and faculty as well as community members who utilized the facilities prior to COVID. The email blasts were gentle reminders that the building was open and available for use The target audiences were the community at large. Several of the emails contained reminders of previous events in the library that were student centered. The next phase of the email campaign centers on reminding the community about the libraries physical and electronic resources, including the makerspace lab. Language will indicate that student voices are needed, and a QR code is included for students to leave feedback as to what they want to see in the library. The final phase of the email blasts were faculty focused and invited them to connect with library reference staff for an in-person consultation on their research needs. While this phase is ongoing, the response has been positive, and staff are compiling data in hopes of working with administration to implement some of the requested services and materials. These email blasts will be followed up by in-person meetings with faculty and students who responded to the QR codes. This research is ongoing. This type of targeted outreach is new for Wesleyan. It is the hope of the library that by the end of Fall 2022, there will be a plan in place to address the needs and concerns of the students and faculty. Furthermore, the staff hopes to create a new sense of community for the students and staff of the university.

Keywords: academic, education, libraries, outreach

Procedia PDF Downloads 94

Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

Procedia PDF Downloads 273

Authors: Orit Wolf

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Classical music confronts a crucial challenge: updating cherished concert traditions for the digital age. This paper is a journey, and a quest to make classical concerts resonate with a new generation. It's not just about asking questions; it's about exploring the future of classical concerts and their potential to captivate and connect with today's audience in an era defined by change. The younger generation, known for their love of diversity, interactive experiences, and multi-sensory immersion, cannot be overlooked. This paper explores innovative strategies that forge deep connections with audiences whose relationship with classical music differs from the past. The urgency of this challenge drives the transformation of classical concerts. Examining classical concerts is necessary to understand how they can harmonize with contemporary sensibilities. New dimensions in audiovisual experiences that enchant the emerging generation are sought. Classical music must embrace the technological era while staying open to fusion and cross-cultural collaboration possibilities. The role of technology and Artificial Intelligence (AI) in reshaping classical concerts is under research. The fusion of classical music with digital experiences and dynamic interdisciplinary collaborations breathes new life into the concert experience. It aligns classical music with the expectations of modern audiences, making it more relevant and engaging. Exploration extends to the structure of classical concerts. Conventions are challenged, and ways to make classical concerts more accessible and captivating are sought. Inspired by innovative artistic collaborations, musical genres and styles are redefined, transforming the relationship between performers and the audience. This paper, therefore, aims to be a catalyst for dialogue and a beacon of innovation. A set of critical inquiries integral to reshaping classical concerts for the digital age is presented. As the world embraces digital transformation, classical music seeks resonance with contemporary audiences, redefining the concert experience while remaining true to its roots and embracing revolutions in the digital age.

Keywords: new concert formats, reception of classical music, interdiscplinary concerts, innovation in the new musical era, mash-up, cross culture, innovative concerts, engaging musical performances

Procedia PDF Downloads 64

Authors: Marisa P. De Brito

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The internet is affecting the way the industry operates and communicates. It is also becoming a customary means for leisure, tourism, and hospitality consumers to seek and exchange information and views on hotels, destinations events and attractions, or to develop social ties with other users. On the one hand, the internet is a rich field to conduct leisure, tourism, and hospitality research; on the other hand, however, there are few researchers formally embracing online methods of research, such as netnography. Within social sciences, netnography falls under the interpretative/ethnographic research methods umbrella. It is an adaptation of anthropological techniques such as participant and non-participant observation, used to study online interactions happening on social media platforms, such as Facebook. It is, therefore, a research method applied to the study of online communities, being the term itself a contraction of the words network (as on internet), and ethnography. It was developed in the context of marketing research in the nineties, and in the last twenty years, it has spread to other contexts such as education, psychology, or urban studies. Since netnography is not universally known, it may discourage researchers and educators from using it. This work offers guidelines for researchers wanting to apply this method in the field of leisure, tourism, and hospitality or for educators wanting to teach about it. This is done by means of a double approach: a content analysis of the literature side-by-side with educational data, on the use of netnography. The content analysis is of the incidental research using netnography in leisure, tourism, and hospitality in the last twenty years. The educational data is the author and her colleagues’ experience in coaching students throughout the process of writing a paper using primary netnographic data - from identifying the phenomenon to be studied, selecting an online community, collecting and analyzing data to writing their findings. In the end, this work puts forward, on the one hand, a research agenda, and on the other hand, an educational roadmap for those wanting to apply netnography in the field or the classroom. The educator’s roadmap will summarise what can be expected from mini-netnographies conducted by students and how to set it up. The research agenda will highlight for which issues and research questions the method is most suitable; what are the most common bottlenecks and drawbacks of the method and of its application, but also where most knowledge opportunities lay.

Keywords: netnography, online research, research agenda, educator's roadmap

Procedia PDF Downloads 182

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

Procedia PDF Downloads 170

Authors: Mariana Damova, Stanko Stankov, Emil Stoyanov, Hristo Hristov, Hermand Pessek, Plamen Chernev

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We will present one of the first use cases on the DestinE platform, a joint initiative of the European Commission, European Space Agency and EUMETSAT, providing access to global earth observation, meteorological and statistical data, and emphasize the good practice of intergovernmental agencies acting in concert. Further, we will discuss the importance of space-bound disruptive solutions for improving the balance between the ever-increasing water-related disasters coming from climate change and minimizing their economic and societal impact. The use case focuses on forecasting floods and estimating the impact of flood events on the urban environment and the ecosystems in the affected areas with the purpose of helping municipal decision-makers to analyze and plan resource needs and to forge human-environment relationships by providing farmers with insightful information for improving their agricultural productivity. For the forecast, we will adopt an EO4AI method of our platform ISME-HYDRO, in which we employ a pipeline of neural networks applied to in-situ measurements and satellite data of meteorological factors influencing the hydrological and hydrodynamic status of rivers and dams, such as precipitations, soil moisture, vegetation index, snow cover to model flood events and their span. ISME-HYDRO platform is an e-infrastructure for water resources management based on linked data, extended with further intelligence that generates forecasts with the method described above, throws alerts, formulates queries, provides superior interactivity and drives communication with the users. It provides synchronized visualization of table views, graphviews and interactive maps. It will be federated with the DestinE platform.

Keywords: flood simulation, AI, Earth observation, e-Infrastructure, flood forecasting, flood areas localization, response planning, resource estimation

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Authors: Payel Saha

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Social media is playing an important role for dissemination of information in society. In 21st century most people have a smart phone and used different social media tools like Facebook, Twitter, Instagram, WhatsApp, Skype etc. in day to day life. It is rapidly growing web-based tool for everyone to share thoughts, ideas and knowledge globally using internet. The study highlights the current use of social media tools for promoting library and information services of Library and Information Professionals of India, which are working in Library. The study was conducted during November, 2017. A structured questionnaire was prepared using google docs and shared using different mailing list, sent to individual email IDs and sharing with other social media tools. Only 90 responses received from the different states of India and analyzed via MS-Excel. The data receive from 17 states and 3 union territories of India; however most of the respondents has come from the states Odisha 23, Himachal Pradesh 14 and Assam 10. The results revealed that out 90 respondents 37 Female and 53 male categories and also majority of respondents 71 have come from academic library followed by special library 15, Public library 3 and corporate library 1 respondent. The study indicates that, out of 90 respondent’s majority of 53 of respondents said that their Library have a social media account while 39 of respondents have not their Library social media account. The study also inform that Facebook, YouTube, Google+, LinkedIn, Twitter and Instagram are using by the LIS professional of India and Facebook 86 was popular social media tool among the other social media tools. Furthermore, respondent reported that they are using social media tools for sharing photos of events and programs of library 72, followed by tips for using different services 64, posting of new arrivals 56, tutorials of database 35 and send brief updates to patrons 32, announcement of library holidays 22. It was also reported by respondents that they are sharing information about scholarships training programs and marketing of library events etc. The study furthermore identify that lack of time is the major problem while using social media with 53 of respondents followed by low speed of internet 35, too many social media tools to learn 17 and some 3 respondents reported that there is no problem while using social media tools. The results also revealed that, majority of the respondents reported that they are using social media tools in daily basis 71 followed by weekly basis 16. It was followed by monthly 1 respondent and other 2 of the respondents. In summary, this study is expected to be useful in further promoting the social media for dissemination of library and information services to the general public.

Keywords: application of social media, India, promoting library services, library professionals

Procedia PDF Downloads 162

Authors: Ya-Mei Chen

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The participatory culture enabled by Web 2.0 technologies has led to the emergence of online translation crowdsourcing, which mainly relies on the collective intelligence of volunteer translators. Due to the fact that many volunteer translators do not have formal translator training, concerns have been raised about the quality of crowdsourced translations. Some empirical research has been done to examine the translation quality of for-profit crowdsourcing initiatives. However, quality assurance of non-profit translation crowdsourcing has rarely been explored in detail. Using the TED Open Translation Project as a case study, this paper investigates how the translation-review-approval method adopted by TED can (1) direct the volunteer translators’ use of translation strategies as well as the reviewers’ adoption of revising strategies and (2) shape the final translation products. To well examine the actual effect of TED’s translation-review-approval method, this paper will focus on its two major quality assurance mechanisms, that is, TED’s style guidelines and quality review. Based on an anonymous questionnaire, this research will first explore whether the volunteer translators and reviewers are aware of the style guidelines and whether their use of translation strategies is similar to that advised in the guidelines. The questionnaire, which will be posted online, will consist of two parts: demographic information and translation strategies. The invitations to complete it will then be distributed through TED Translator Facebook groups. With an aim to investigate if the style guidelines have any substantial impacts on actual subtitling practices, a comparison will be made between the original English subtitles of 20 TED talks (each around 5 to 7 minutes) and their Chinese subtitle translations to identify regularly adopted strategies. Concerning the function of the reviewing stage, a comparative study will be conducted between the drafts of Chinese subtitles for 10 short English talks and the revised versions of these drafts so as to examine the actual revising strategies and their effect on translation quality. According to the results obtained from the questionnaire and textual comparisons, this paper will provide in-depth analysis of quality assurance of the TED Open Translation Project. It is hoped that this research, through a detailed investigation of non-profit translation crowdsourcing, can enable translation researchers and practitioners to have a better understanding of quality control in translation crowdsourcing in the digital age.

Keywords: quality assurance, TED, translation crowdsourcing, volunteer translators

Procedia PDF Downloads 231

Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

Procedia PDF Downloads 187

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 80

Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

Procedia PDF Downloads 361

Authors: Sharmistha Chowdhury, Shuva Chowdhury

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Buying-selling new as well as second-hand goods like tools, furniture, household, electronics, clothing, baby stuff, vehicles, and hobbies through the Facebook marketplace has become a new paradigm for c2c sellers. This phenomenon encourages and empowers decentralised home-oriented sellers. This study adopts Elaboration Likelihood Model (ELM) to explain consumer behaviour on Facebook Marketplace (FM). ELM suggests that consumers process information through the central and peripheral routes, which eventually shape their attitudes towards posts. The central route focuses on information quality, and the peripheral route focuses on cues. Sellers’ FM posts usually include product features, prices, conditions, pictures, and pick-up location. This study uses information relevance and accuracy as central route factors. The post’s attractiveness represents cues and creates positive or negative associations with the product. A post with remarkable pictures increases the attractiveness of the post. So, post aesthetics is used as a peripheral route factor. People influenced via the central or peripheral route forms an attitude that includes multiple processes – response and purchase intention. People respond to FM posts through save, share and chat. Purchase intention reflects a positive image of the product and higher purchase intention. This study proposes trust on sellers as a moderator to test the strength of its influence on consumer attitudes and behaviour. Trust on sellers is assessed whether sellers have badges or not. A sample questionnaire will be developed and distributed among a group of random FM sellers who are selling vehicles on this platform to conduct the study. The chosen product of this study is the vehicle, a high-value purchase item. High-value purchase requires consumers to consider forming their attitude without any sign of impulsiveness seriously. Hence, vehicles are the perfect choice to test the strength of consumers attitudes and behaviour. The findings of the study add to the elaboration likelihood model and online second-hand marketplace literature.

Keywords: consumer behaviour, elaboration likelihood model, facebook marketplace, c2c marketing

Procedia PDF Downloads 138