Search results for: classification of people

Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: M. Khaled Abduesslam, Mohammed Ali, Basher H. Alsdai, Muhammad Nizam Inayati

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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New-England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.

Keywords: IEEE 39 bus, least squares support vector machine, learning vector quantization, voltage collapse

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Authors: Excellent Hansda

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Over the past years, a lot of research has been on the ethnic enclaves from historical, sociological and economic point of view. However there exist a research gap in the built environment and spatial layout of these areas. When immigrants (People) assimilate in a different place, they struggle to preserve their original identity to maintain their heritage. Then there is the Place, which is the physical manifestation of the heritage, shown through streetscape and architecture. Together 'People and Place' form a relationship with the authenticity of the enclave. As immigrants come in the host country, they try to bring their culture into the place, but at the same time, the culture of the host country also affects the immigrants. This creates conflicts not only in the lifestyle and culture of the immigrants, but also the built characteristics of the place. In the midst of such conflicts, one may easily question the authenticity of an ethnic enclave. In Malaysia, a number of ethnic enclaves emerged due to trade during the medieval times. Little India is one among the other ethnic enclaves present in Chulia Street in Malaysia. The study investigates the factors of 'Place and People', affecting the authenticity of a little India, in the context of an evolving state of Penang in Malaysia. The study is carried through extensive literature review of existing data, followed by observations drawn by visual analysis, discussions and interviews with the stakeholders of the study area. The findings of this research suggest the contribution of 'people and places' in the process of place making in an ethnic enclave. The findings are essential for conservation and further development of ethnic enclaves.

Keywords: conservation, ethnic enclaves, heritage, identity

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Gianne Bianca P. Manalo, Ernesto A. Martin, Vanessa V. Velasco

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The laying performance, egg quality, egg classification, and income over feed cost of Improved Philippine Mallard duck (Itik Pinas) were examined as influenced by garlic powder in drinking water. A total of 48 ducks (42 females and 6 males) were used in the study. The ducks were allocated into two treatments - with garlic powder (GP) and without garlic powder (control) in drinking water. Each treatment had three replicates with eight ducks (7 females and 1 male) per replication. The results showed that there was a significant (P = 0.03) difference in average egg weight where higher values were attained by ducks with GP (77.67 g ± 0.64) than the control (75.64 g ± 0.43). The supplementation of garlic powder in drinking water, however, did not affect the egg production, feed intake, FCR, egg mass, livability, egg quality and egg classification. The Itik Pinas with GP in drinking water had numerically higher income over feed cost than those without. GP in drinking water can be considered in raising Itik Pinas. Further studies on increasing level of GP and long feeding duration also merit consideration to substantiate the findings.

Keywords: phytogenic, garlic powder, Itik-Pinas, egg weight, egg production

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Authors: Ahmadu Maidorawa, Idrissa Djibo, Muhammad Tella

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This paper presents a method for detecting flow chart and figure plagiarism based on shape of image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets. Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offense that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide these checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts result in look holes that people can take advantage. That means people can plagiarize figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts.

Keywords: flowchart, multimedia retrieval, figures similarity, image comparison, figure retrieval

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Authors: Damian Czubak

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The Białowieża Forest is a very valuable natural area, included in the World Natural Heritage at UNESCO, where, due to infestation by the bark beetle (Ips typographus), norway spruce (Picea abies) have deteriorated. This catastrophic scenario led to an increase in fire danger. This was due to the occurrence of large amounts of dead wood and grass cover, as light penetrated to the bottom of the stands. These factors in a dry state are materials that favour the possibility of fire and the rapid spread of fire. One of the objectives of the study was to monitor the quantitative and qualitative changes of combustible material on the permanent decay plots of spruce stands from 2012-2022. In addition, the size of the area with highly flammable vegetation was monitored and a classification of the stands of the Białowieża Forest by flammability classes was made. The key factor that determines the potential fire hazard of a forest is combustible material. Primarily its type, quantity, moisture content, size and spatial structure. Based on the inventory data on the areas of forest districts in the Białowieża Forest, the average fire load and its changes over the years were calculated. The analysis was carried out taking into account the changes in the health status of the stands and sanitary operations. The quantitative and qualitative assessment of fallen timber and fire load of ground cover used the results of the 2019 and 2021 inventories. Approximately 9,000 circular plots were used for the study. An assessment was made of the amount of potential fuel, understood as ground cover vegetation and dead wood debris. In addition, monitoring of areas with vegetation that poses a high fire risk was conducted using data from 2019 and 2021. All sub-areas were inventoried where vegetation posing a specific fire hazard represented at least 10% of the area with species characteristic of that cover. In addition to the size of the area with fire-prone vegetation, a very important element is the size of the fire load on the indicated plots. On representative plots, the biomass of the land cover was measured on an area of 10 m2 and then the amount of biomass of each component was determined. The resulting element of variability of ground covers in stands was their flammability classification. The classification developed made it possible to track changes in the flammability classes of stands over the period covered by the measurements.

Keywords: classification, combustible material, flammable vegetation, Norway spruce

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Authors: Da Kuang

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Resilience is a hotly debated topic in many research fields (e.g., engineering, ecology, society, psychology). In flood management studies, we are experiencing the paradigm shift from flood resistance to flood resilience. Flood resilience refers to tolerate flooding through adaptation or transformation. It is increasingly argued that our city as a social-ecological system holds the ability to learn from experience and adapt to flood rather than simply resist it. This research aims to investigate what kinds of adaptation knowledge the frequently flooded village learned from past experience and its advantages and limitations in coping with floods. The study area – Xinnongcun village, located in the west of Wuhan city, is a linear village and continuously suffered from both flash flood and drainage flood during the past 30 years. We have a field trip to the site in June 2017 and conducted semi-structured interviews with local residents. Our research summarizes two types of adaptation knowledge that people learned from the past floods. Firstly, at the village scale, it has formed a collective urban form which could help people live during both flood and dry season. All houses and front yards were elevated about 2m higher than the road. All the front yards in the village are linked and there is no barrier. During flooding time, people walk to neighbors through houses yards and boat to outside village on the lower road. Secondly, at individual scale, local people learned tacit knowledge of preparedness and emergency response to flood. Regarding the advantages and limitations, the adaptation knowledge could effectively help people to live with flood and reduce the chances of getting injuries. However, it cannot reduce local farmers’ losses on their agricultural land. After flood, it is impossible for local people to recover to the pre-disaster state as flood emerges during June and July will result in no harvest. Therefore, we argue that learning from past flood experience could increase people’s adaptive capacity. However, once the adaptive capacity cannot reduce people’s losses, it requires a transformation to a better regime.

Keywords: adaptation, flood resilience, tacit knowledge, transformation

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

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National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

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Authors: Naeemeh Silvari

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The phenomenon of the spread and epidemic of the corona virus caused many aspects of the social life of the people of the world to face various challenges. In this regard, and in order to improve the living conditions of the people, the World Health Organization has tried to publish the necessary instructions for its contacts in the world in the form of its media capacities. Considering the importance of cultural differences in the discussion of health communication and the distinct needs of people in different societies, some production contents were produced and published exclusively. This research has studied six videos published on the official page of the World Health Organization in Iran as a case study. The published content has the least semantic affinity with Iranian culture, and it has been tried to show a uniform image of the Middle East with the predominance of the image of the culture of the developing Arab countries.

Keywords: corona, representation, semiotics, instagram, health communication

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Authors: Toledo-Fernandez Aldebaran

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Introduction: One of the least explored cognitive functions in relation with depression is the one related to musical stimuli. Music perception and memory can become impaired as well. The term amusia is used to define a type of agnosia caused by damage to basic processes that creates a general inability to perceive music. Therefore, the main objective is to explore performance-based and self-report deficits in music perception and memory on people with major depressive disorder (MDD). Method: Data was collected through April-October 2021 recruiting people who met the eligibility criteria and using the Montreal Battery of Evaluation of Amusia (MBEA) to evaluate performance-based music perception and memory, along with the module for depression of the Mini International Neuropsychiatric Interview, and the Amusic Dysfunction Inventory (ADI) which evaluates the participants’ self-report concerning their abilities in music perception. Results: 64 participants were evaluated. The main study, referring to analyzing the differences between people with MDD and the control group, only showed one statistical difference on the Interval subtest of the MBEA. No difference was found in the dimensions assessed by the ADI. Conclusion: Deficits in interval perception can be explained by mental fatigue, to which people with depression are more vulnerable, rather than by specific deficits in musical perception and memory associated with depressive disorder. Additionally, significant associations were found between musical deficits as observed by performance-based evidence and music dysfunction according to self-report, which could suggest that some people with depression are capable of detecting these deficits in themselves.

Keywords: depression, amusia, music, perception, memory

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Authors: Valentina Piric, Maja Martinovic, Zoran Barac

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The application of marketing to the domain of politics has become relevant in recent times. With this article the authors wanted to explore the issue of the current political engagement among young people in Croatia. The question is what makes young people (age 18-30) politically active in young democracies such as that of the Republic of Croatia. Therefore, the objective of this study was to discover the real or hidden motivations behind the decision to actively participate in politics among young members of the two largest political parties in the country – the Croatian Democratic Union and the Social Democratic Party of Croatia. The study expected to find that the motivation for political engagement of young people is often connected with a possible achievement of individual goals and egoistic needs such as: self-acceptance, social success, financial success, prestige, reputation, status, recognition from the others etc. It was also expected that, due to the poor economic and social situation in the country, young people feel an increasing disconnection from politics. Additionally, the authors expected to find that there is a huge potential to engage young people in the political life of the country through a proper and more interactive use of marketing communication campaigns and social media platforms, with an emphasis on highly ethical motives of political activity and their benefits to society. All respondents included in the quantitative survey (sample size [N=100]) are active in one of the two largest political parties in Croatia. The sampling and distribution of the survey occurred in the field in September 2016. The results of the survey demonstrate that in Croatia, the way young people feel about politics and act accordingly, are in fact similar to what the theory describes. The research findings reveal that young people are politically active; however, the challenge is to find a way to motivate even more young people in Croatia to actively participate in the political and democratic processes in the country and to encourage them to see additional benefits out of this practice, not only related to their individual motives, but related more to the well-being of Croatia as a country and of every member of society. The research also discovered a huge potential for political marketing communication possibilities, especially related to interactive social media. It is possible that the social media channels have a stronger influence on the decision-making process among young people when compared to groups of reference. The level of interest in politics among young Croatians varies; some of them are almost indifferent, whilst others express a serious interest in different ways to actively contribute to the political life of the country, defining a participation in the political life of their country almost as their moral obligation. However, additional observations and further research need to be conducted to get a clearer and more precise picture about the interest in politics among young people in Croatia and their social potential.

Keywords: Croatia, marketing communication, motivation, politics, young people

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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Authors: Alberto Piatto, Zaza Nadja Lee Hansen, Peter Jacobsen

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This paper examines the quantitative and qualitative factors influencing the buyer-supplier relationship. Understanding and acting on the right factors influencing supplier relationship management is crucial when a company outsource an important part of its business as it can be for engineering to order (ETO) company executing only the designing part in-house. Acting on these factors increase the quality of the relationship obtaining for both parties what they want and expect from an improved relationship. Best practices in supplier relationship management are considered and a case study of a large global company, called Cement A/S, operating in the cement business is carried out. One study is conducted including a large international company and hundreds of its suppliers. Data from the company is collected using semi-structured interviews and data from the suppliers is collected using a survey. Based on these inputs and an extensive literature review a classification of factors influencing the relationship buyer-supplier is presented and discussed. The results show that different managers among the company are assessing supplier from various perspectives, a standard approach to measure the performance of suppliers does not exist. The factors used nowadays in the company to measure performances of the suppliers are mostly related to time and cost. Quality is a key factor, but it has not been addressed properly since no data are available in the system. From a practical perspective, managers can learn from this paper which factors to consider when applying best practices of Supplier Relationship Management. Furthermore, from a theoretical perspective, this paper contributes with new knowledge in the area as limited research in collaboration with the company has been conducted. For this reason, a company, its suppliers and few studies for this type of industry have been conducted. For further research, it is suggested to define the correlation of factors to the profitability of the company and calculate its impact. When conducting this analysis it is important to focus on the efficient and effective use of factors that can be measurable and accepted from the supplier.

Keywords: buyer-supplier relationship, cement industry, classification of factors, ETO

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Authors: Naser Kazemi Eilaki, Ilona Heldal, Carolyn Ahmer, Bjarne Christian Hagen

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Elderly people and people with disabilities are recognized as at-risk groups when it comes to egress and travel from hazard zone to a safe place. One's disability can negatively influence her or his escape time, and this becomes even more important when people from this target group live alone. While earlier studies have frequently addressed quantitative measurements regarding at-risk groups' physical characteristics (e.g., their speed of travel), this paper considers the influence of at-risk groups’ characteristics on their decision and determining better escape routes. Most of evacuation models are based on mapping people's movement and their behaviour to summation times for common activity types on a timeline. Usually, timeline models estimate required safe egress time (RSET) as a sum of four timespans: detection, alarm, premovement, and movement time, and compare this with the available safe egress time (ASET) to determine what is influencing the margin of safety.This paper presents a cross-sectional study for identifying the most critical items on RSET and people's decision-making and with possibilities to include safety knowledge regarding people with physical or cognitive functional impairments. The result will contribute to increased knowledge on considering at-risk groups and disabilities for designing and developing safe escape routes. The expected results can be an asset to predict the probabilistic behavioural pattern of at-risk groups and necessary components for defining a framework for understanding how stakeholders can consider various disabilities when determining the margin of safety for a safe escape route.

Keywords: fire safety, evacuation, decision-making, at-risk groups

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Authors: Pablo Martinez, Emad Mohamed, Osama Mohsen, Yasser Mohamed

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Highway and bridge agencies, such as the Ministry of Transportation in Ontario, use the Bridge Condition Index (BCI) which is defined as the weighted condition of all bridge elements to determine the rehabilitation priorities for its bridges. Therefore, accurate forecasting of BCI is essential for bridge rehabilitation budgeting planning. The large amount of data available in regard to bridge conditions for several years dictate utilizing traditional mathematical models as infeasible analysis methods. This research study focuses on investigating different classification models that are developed to predict the bridge condition index in the province of Ontario, Canada based on the publicly available data for 2800 bridges over a period of more than 10 years. The data preparation is a key factor to develop acceptable classification models even with the simplest one, the k-NN model. All the models were tested, compared and statistically validated via cross validation and t-test. A simple k-NN model showed reasonable results (within 0.5% relative error) when predicting the bridge condition in an incoming year.

Keywords: asset management, bridge condition index, data mining, forecasting, infrastructure, knowledge discovery in databases, maintenance, predictive models

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Authors: Jinali Chaklasiya

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The importance of face masks, gloves, sanitizer, face shield Were only Applied for Doctor Amenities, and because of the outbreak of coronavirus, everybody has to wear Personal Protective Equipment (PPE) for health measures. . The main focus of this research paper is in the area of how doctor amenities changed the importance of gloves, face masks, sanitizer, face shield in day to day life of people. For this research, we have collected data from a quantitative survey. A questionnaire survey was conducted to note down the user point of view in doctor amenities and why is it important. The result of the questionnaire survey has helped to design parameters which were used to ideate new protective products. Thus, it is concluded to keep in mind that these protective devices can be used in day-to-day life by people across the globe. In the coming future, the protective device can make a difference and protect us from other common viruses.

Keywords: equpiment, coronavirus, products, protective, environment

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Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

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A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Layla Mujahed

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COVID-19 is an exam for all the city’s systems. It shows many gaps in the systems such as healthcare, economic, social, and environment. This pandemic is paving for a new era, an era of technology and it has changed people’s lives, such as physical, and emotional changes, and converting communication into digitalized. The effect of COVID-19 has covered all urban city parts. COVID-19 will not be the last pandemic our cities will face. For that, more researches focus on enhancing the quality of the urban environment. This pandemic encourages a rethinking of the environment’s role, especially in cities. Cities are trying to provide the best suitable strategies and regulations to prevent the spread of COVID-19, and an example of that is Amman city. Amman has a high increment in the number of COVID-19 infected people, while it has controlled the situation for months. For that, this paper studies the relation between COVID-19 and urban environmental studies cases about cities around the world, and learns from their models to face COVID-19. In Amman, people’s behavior has changed towards public transportation and public green spaces. N­ew governmental regulations focus on increasing people’s mental awareness, supporting local businesses, and enhancing neighborhood planning that can help Amman to face any future pandemics.

Keywords: COVID-19, urban environment, urban planning, urban resilience

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Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

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Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

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Authors: Iliya Ibrahim Gimba

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Human beings or groups over the world have a traditional and cultural practices which guide and direct their ways of life. They value and promote these practices not minding the attitude of others towards them. In spite of the place of culture which is an embodiment of these practices in every human society some people still reduce the understanding of culture to idolatry and other archaic and anachronistic arts good perhaps only for the museum. Others consider culture to be just drumming and dancing. Whether a culture is “good” or “bad”, civilized or barbaric, it can be reformed for the betterment of the society. Hence, this paper focuses on reforming traditional and cultural practices in Nigeria for enhancing development in the 21st century using the Jukun people as a case study. Relevant literatures from journals, reports, published books among others will be consulted.

Keywords: Jukun, traditional and cultural practices, sustainable development, human

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Authors: Barbara Klimek

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Wolves are one of the most misrepresented species in literature and the media. They’re often portrayed as vicious, man-eating beasts whose main life goal is to hunt and kill people. Many movie directors use wolves as their main characters in different types of films, especially horror, thriller and science fiction movies to create gore and fear. This, in turn, results in people being afraid of wolves and wanting to destroy them. Such cultural creations caused wolves being stalked, abused and killed by people and in many areas they were completely destroyed. This paper analyzes the representations of wolves in the chosen films in the four main portrayed aspects: 1. the overall picture – true versus false, positive versus negative, based on stereotypes or realistic, displaying wolf behavior typical of the species or fake 2. subjectivity – how humans treat and talk about the animals – as subjects or as objects 3. animal welfare – how humans treat wolves and nature, are the human – animal relations positive and appropriate or negative and abusive 4. empathy – are human characters shown to co-feel the suffering with the wolves, do they display signs of empathy towards the animals, do the animals empathize with humans? The detailed analysis of the text and pictures presented in the chosen films concludes that wolves are especially misrepresented in the movies. Their behavior is shown as fake and negative, based on stereotypes and myths, the human – animal relations are shown mainly as negative where people fear the animals and hunt them and wolves stalk, follow, attack and kill humans. It shows that people do not understand the needs of these animals and are unable to show empathy towards them. The article will discuss the above-mentioned study results in detail and will present many examples. Animal representations in cultural creations, including film have a great impact on how people treat particular species of animals. The media shape people’s attitudes, what in turn results in people either respecting and protecting the animals or fearing, disliking and destroying the particular species.

Keywords: film, movies, representations, wolves

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Stephanie Hewitt, Leila Sheldrick, Weston Baxter

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Multidisciplinary by nature, design research brings together varying research fields to answer globally significant questions. Emotional design, a field which helps us create products that influence people’s behaviour, and sports psychology, containing a growing field of recent research which focuses on understanding the emotions experienced through sport and the effects this has on our health and wellbeing, are two research fields that can be combined through design research to tackle global physical inactivity. The combination of these research fields presents an opportunity to build new tools and methods that could help designers create new interventions to promote positive behaviour change in the form of physical activity uptake, ultimately improving people’s health and wellbeing. This paper proposes a framework that can be used to develop new products and services that focus on not only improving the uptake and upkeep of physical activity but also helping people have a healthy emotional relationship with exercise. To develop this framework, a set of comprehensive maps exploring the relationship between human emotions and physical activity across a range of factors was created. These maps were then further evolved through in-depth interviews, which analysed the reasons behind the emotions felt, how physical activity fits into the daily routine and how important regular exercise is to people. Finally, to progress these findings into a design framework, a longitudinal study was carried out to explore further the emotional relationship people of varying sporting abilities have overtime with physical activity. This framework can be used to design more successful interventions that help people to not only become more active initially but implement long term changes to ensure they stay active.

Keywords: design research, emotional design, emotions, intervention, physical activity, sport psychology

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Authors: Amin Nakhostin-Ansari, Samaneh Akbarour, Khosro Sadeghniiat Haghighi, Zahra Banafsheh Alemohammad, Farnaz Etesam, Arezu Najafi, Mahnaz Khalafehnilsaz

Abstract:

Introduction: The outbreak of coronavirus disease has considerably burdened the healthcare system in Iran. This study aimed to evaluate the characteristics of insomnia experienced by the general Iranian population during the COVID-19 pandemic. Method: A scale(FCV-19) was used for Fear of COVID-19, Insomnia Severity Index (ISI), Patient Health Questionnaire-2 (PHQ-2), and Generalized Anxiety Disorder Scale-2 (GAD-2) for detailed characterization of insomnia and its patterns Results: In total, 675 people with insomnia with the mean age of 40.28 years (SD=11.15) participated in this study. Prevalence of difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS), and early morning awakening (EMA) were 91.4%, 86.7%, and 77%, respectively. DIS, DMS, and EMA were more common in people with depression and anxiety. FCV-19 score was higher in those with more severe types of DIS, DMS, and EMA (P<0.001). FCV-19 was a risk factor for all patterns of insomnia (OR=1.19, 1.12, 1.02 for DIS, DMS, and EMA, respectively). Conclusion: fear of COVID-19 is a major factor to insomnia patterns. Investigation of COVID-19 fear in people with insomnia and the addition of attributed relieving or management strategies to conventional management of insomnia are reasonable approaches to improve the sleep condition of people in the pandemic.

Keywords: insomnia, difficulty maintaining sleep, COVID-19, Coronavirus

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Authors: Lavina N. Bhaskar, Ashima Tiwari

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In the endeavour of connecting culture to stories, textile to narratives and people to material, authors analyse the impact of narratives in two popular Indian textiles namely - Mata Ni Pachedi and Pabuji Ki Phad. These textiles narrate people’s tale or Folk tale. Each textile has a style or format in which the story is told (and it is visual). Mata Ni Pachedi, when translated into the English language literally means behind the mother goddess. Mata Ni Pachedi is an Indian textile from the province of Gujarat which constitutes an entire temple of the goddess, with the idol herself in it. On the other hand, Pabuji ki Phad is scroll painting of folk deities of Rajasthan, narrated by Bhopas (the Priest singers of Rajasthan). These textiles narrate stories of ordinary people with extraordinary courage, of social reform, and people’s belief in the divine. Authors take to task their years of craft-cluster study conducted in the past and use existing literature to map their journey in the preliminary phase of research. And then carried out an ethnographic study by visiting the origins of these textiles in Rajasthan and Gujrat (in India), met artisans and their families who are still practicing these dying art form, in order to understand the format and impact of textile story-telling. This research paper talks about the narrative in Indian textiles; the stories in them, artisans and their life as metaphorical representations of the People in Mata Ni Pachedi and Pabuji Ki Phad.

Keywords: cultural derivatives, folk-tale, Indo-Narratives, Indology

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Nattapol Pourprasert

Abstract:

This research is to study qualitative research having two objectives: 1. to study comparison of private sector of government to compare with ASEAN Member States, 2. to study trend of private enterprise administration of ASEAN Member States. The results are: (1) Thai people focus on personal resource administrative system, (2) Indonesia focuses on official system by good administrative principles, (3) Malaysia focuses on technology development to service people, (4) Philippines focuses on operation system development, (5) Singapore focuses on public service development, (6) Brunei Darussalam focuses on equality in government service of people, (7) Vietnam focuses on creating government labor base and develop testing and administration of operation test, (8) Myanmar focuses on human resources development, (9) Laos focuses on form of local administration, (10) Cambodia focuses on policy revolution in personal resources. The result of the second part of the study are: (1) Thailand created government personnel to be power under qualitative official structural event, (2) Indonesia has Bureaucracy Reform Roadmap of Bureaucracy Reform and National Development Plan Medium Term, (3) Malaysia has database for people service, (4) Philippines follows up control of units operation by government policy, (5) Singapore created reliability, participation of people to set government policy people’s demand, (6) Brunei Darussalam has social welfare to people, (7) Vietnam revolved testing system and administration including manpower base construction of government effectively, (8) Myanmar creates high rank administrators to develop country, (9) Laos distributes power to locality, and (10) Cambodia revolved personnel resource policy.

Keywords: public administration development, ASEAN member states, private sector, government

Procedia PDF Downloads 238