Search results for: hierarchical tree inference.

Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: Lexicon of disasters, modelling, Petri nets, text annotation, social disasters.

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Authors: Yung-Chien Sun, O. Grant Clark

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In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: Phusit Phukamchanoad, Chutchai Ditchareon, Suwaree Yordchim

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This research was to study on background and social and cultural context of Kamchanoad community for sustainable tourism management. All data was collected through in-depth interview with village headmen, community committees, teacher, monks, Kamchanoad forest field officers and respected senior citizen above 60 years old in the community who have lived there for more than 40 years. Altogether there were 30 participants for this research. After analyzing the data, content from interview and discussion, Kamchanoad has both high land and low land in the region as well as swamps that are very capable of freshwater animals’ conservation. Kamchanoad is also good for agriculture and animal farming. 80% of Kamchanoad’s land are forest, freshwater and rice farms. Kamchanoad was officially set up as community in 1994 as “Baan Nonmuang”. Inhabitants in Kamchanoad make a living by farming based on sufficiency economy. They have rice farm, eucalyptus farm, cassava farm and rubber tree farm. Local people in Kamchanoad still believe in the myth of Srisutto Naga. They are still religious and love to preserve their traditional way of life. In order to understand how to create successful tourism business in Kamchanoad, we have to study closely on local culture and traditions. Outstanding event in Kamchanoad is the worship of Grand Srisutto, which is on the fullmoon day of 6th month or Visakhabucha Day. Other big events are also celebration at the end of Buddhist lent, Naga firework, New Year celebration, Boon Mahachart, Songkran, Buddhist Lent, Boon Katin and Loy Kratong. Buddhism is the main religion in Kamchanoad. The promotion of tourism in Kamchanoad is expected to help spreading more income for this region. More infrastructures will be provided for local people as well as funding for youth support and people activities.

Keywords: Social and Culture Area, Tourism Management, Kamchanoad Community.

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Authors: Chiung-Hui Chen

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Traditional service channel is losing its edge due to emerging service technology. To establish interaction with the clients, the service industry is using effective mechanism to give clients direct access to services with emerging technologies. Thus, as service science receives attention, special and unique consumption pattern evolves; henceforth, leading to new market mechanism and influencing attitudes toward life and consumption patterns. The market demand for customized services is thus valued due to the emphasis of personal value, and is gradually changing the demand and supply relationship in the traditional industry. In respect of interior design service, in the process of traditional interior design, a designer converts to a concrete form the concept generated from the ideas and needs dictated by a user (client), by using his/her professional knowledge and drawing tool. The final product is generated through iterations of communication and modification, which is a very time-consuming process. Although this process has been accelerated with the help of computer graphics software today, repeated discussions and confirmations with users are still required to complete the task. In consideration of what is addressed above a space user’s life model is analyzed with visualization technique to create an interaction system modeled after interior design knowledge. The space user document intuitively personal life experience in a model requirement chart, allowing a researcher to analyze interrelation between analysis documents, identify the logic and the substance of data conversion. The repeated data which is documented are then transformed into design information for reuse and sharing. A professional interior designer may sort out the correlation among user’s preference, life pattern and design specification, thus deciding the critical design elements in the process of service design.

Keywords: Information Design, Life Model-Based, Aesthetic Computing, Communication.

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Authors: Selvam M, Natarajan. A M, Thangarajan R

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Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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Authors: Japhet N. Mwambusi

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High tropical forests deforestation for solid wood furniture industry is among of climate change contributing agents. This pressure indirectly is caused by furniture joints failure due to poor gluing technology based on improper use of different glues to different wood species which lead to low quality and weak wood-glue joints. This study was carried in order to run performance tests of wood glues on different wood species used in wood workshops: Morogoro Tanzania whereby three popular wood species of C. lusitanica, T. glandis and E. maidenii were tested against five glues of Woodfix, Bullbond, Ponal, Fevicol and Coral found in the market. The findings were necessary on developing a guideline for proper glue selection for a particular wood species joining. Random sampling was employed to interview carpenters while conducting a survey on the background of carpenters like their education level and to determine factors that influence their glues choice. Monsanto Tensiometer was used to determine bonding strength of identified wood glues to different wood species in use under British Standard of testing wood shear strength (BS EN 205) procedures. Data obtained from interviewing carpenters were analyzed through Statistical Package of Social Science software (SPSS) to allow the comparison of different data while laboratory data were compiled, related and compared by the use of MS Excel worksheet software as well as Analysis of Variance (ANOVA). Results revealed that among all five wood glues tested in the laboratory to three different wood species, Coral performed much better with the average shear strength 4.18 N/mm², 3.23 N/mm² and 5.42 N/mm² for Cypress, Teak and Eucalyptus respectively. This displays that for a strong joint to be formed to all tree wood species for soft wood and hard wood, Coral has a first priority in use. The developed table of guideline from this research can be useful to carpenters on proper glue selection to a particular wood species so as to meet glue-bond strength. This will secure furniture market as well as reduce pressure to the forests for furniture production because of the strong existing furniture due to their strong joints. Indeed, this can be a good strategy on reducing climate change speed in tropics which result from high deforestation of trees for furniture production.

Keywords: Climate change, deforestation, gluing technology, joint failure, wood-glue, wood species.

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Authors: G. Feletti, D. Tedesco, P. Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of a first phase of revision of the technical-scientific literature concerning the indicators currently in use for the performance measurement of EMS. It emerges that current studies focus on two distinct areas and independent objectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). Conversely, the perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal covers the end-to-end healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid even to EMS aspects that in current literature tend to be neglected or underestimated. In particular, the integration of the two processes enables to evaluate the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering, besides the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating firstly the ones not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draw us to exclude additional indicators due to unavailability of data required for their computation. The final dashboard, that was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness on EDs accessibility in real time. The association of each KPI to the EMS phase it refers to enabled the design of a well-balanced dashboard, covering both efficiency and effectiveness performance objectives of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient care are covered by traditional KPIs. Future developments could be directed to building a hierarchical dashboard, composed by a high-level minimal set of KPIs for measuring the basic performance of the EMS system, at an aggregate level, and lower levels of KPIs that bring additional and more detailed information on specific performance dimensions or EMS phases.

Keywords: Emergency Medical Services, Key Performance Indicators, Dashboard, Decision Support.

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Authors: Süleyman Hakan Yılmaz, Yasemin Gülşen Yılmaz

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The Gezi Park protests of 2013 have significantly changed the Turkish agenda and its effects have been felt historically. The protests, which rapidly spread throughout the country, were triggered by the proposal to recreate the Ottoman Army Barracks to function as a shopping mall on Gezi Park located in Istanbul’s Taksim neighbourhood despite the oppositions of several NGOs and when trees were cut in the park for this purpose. Once the news that the construction vehicles entered the park on May 27 spread on social media, activists moved into the park to stop the demolition, against whom the police used disproportioned force. With this police intervention and the then prime-minister Tayyip Erdoğan's insistent statements about the construction plans, the protests turned into anti- government demonstrations, which then spread to the rest of the country, mainly in big cities like Ankara and Izmir. According to the Ministry of Internal Affairs’ June 23rd reports, 2.5 million people joined the demonstrations in 79 provinces, that is all of them, except for the provinces of Bayburt and Bingöl, while even more people shared their opinions via social networks. As a result of these events, 8 civilians and 2 security personnel lost their lives, namely police chief Mustafa Sarı, police officer Ahmet Küçükdağ, citizens Mehmet Ayvalıtaş, Abdullah Cömert, Ethem Sarısülük, Ali İsmail Korkmaz, Ahmet Atakan, Berkin Elvan, Burak Can Karamanoğlu, Mehmet İstif, and Elif Çermik, and 8163 more were injured. Besides being a turning point in Turkish history, the Gezi Park protests also had broad repercussions in both in Turkish and in global media, which focused on Turkey throughout the events. Our study conducts content analysis of three Turkish reporting newspapers with varying ideological standpoints, Hürriyet, Cumhuriyet ve Yeni Şafak, in order to reveal their basic approach to news casting in context of the Gezi Park protests. Headlines, news segments, and news content relating to the Gezi protests were treated and analysed for this purpose. The aim of this study is to understand the social effects of the Gezi Park protests through media samples with varying political attitudes towards news casting.

Keywords: Gezi Park, media, news casting, tree.

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

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

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Daniel Puciato, Piotr Oleśniewicz, Julita Markiewicz-Patkowska, Krzysztof Widawski, Michał Rozpara, Władysław Mynarski, Agnieszka Gawlik, Małgorzata Dębska, Soňa Jandová

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Physical activity as a part of people’s everyday life reduces the risk of many diseases, including those induced by lifestyle, e.g. obesity, type 2 diabetes, osteoporosis, coronary heart disease, degenerative arthritis, and certain types of cancer. That refers particularly to professionally active people, including the early senior group working on non-manual positions. The aim of the study is to evaluate the relationship between physical activity and the socio-economic status of non-manual workers from Wroclaw—one of the biggest cities in Poland, a model setting for such investigations in this part of Europe. The crucial problem in the research is to find out the percentage of respondents who meet the health-related recommendations of the World Health Organization (WHO) concerning the volume, frequency, and intensity of physical activity, as well as to establish if the most important socio-economic factors, such as gender, age, education, marital status, per capita income, savings and debt, determine the compliance with the WHO physical activity recommendations. During the research, conducted in 2013, 1,170 people (611 women and 559 men) aged 21–60 years were examined. A diagnostic poll method was applied to collect the data. Physical activity was measured with the use of the short form of the International Physical Activity Questionnaire with extended socio-demographic questions, i.e. concerning gender, age, education, marital status, income, savings or debts. To evaluate the relationship between physical activity and selected socio-economic factors, logistic regression was used (odds ratio statistics). Statistical inference was conducted on the adopted ex ante probability level of p<0.05. The majority of respondents met the volume of physical effort recommended for health benefits. It was particularly noticeable in the case of the examined men. The probability of compliance with the WHO physical activity recommendations was highest for workers aged 21–30 years with secondary or higher education who were single, received highest incomes and had savings. The results indicate the relations between physical activity and socio-economic status in the examined women and men. People with lower socio-economic status (e.g. manual workers) are physically active primarily at work, whereas those better educated and wealthier implement physical effort primarily in their leisure time. Among the investigated subjects, the youngest group of non-manual workers have the best chances to meet the WHO standards of physical activity. The study also confirms that secondary education has a positive effect on the public awareness on the role of physical activity in human life. In general, the analysis of the research indicates that there is a relationship between physical activity and some socio-economic factors of the respondents, such as gender, age, education, marital status, income per capita, and the possession of savings. Although the obtained results cannot be applied for the general population, they show some important trends that will be verified in subsequent studies conducted by the authors of the paper.

Keywords: International physical activity questionnaire, non-manual workers, physical activity, socio-economic factors, WHO.

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Authors: Mohammad Abdollahi

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Tomato (Lycopersicon esculentum Mill.) is one of the most popular, widely grown and the second most important vegetable crop, after potatoes. Nematodes have been identified as one of the major pests affecting tomato production throughout the world. The most destructive nematodes are the genus Meloidogyne. Most widespread and devastating species of this genus are M. incognita, M. javanica, and M. arenaria. These species can cause complete crop loss under adverse growing conditions. There are several potential methods for management of the root knot nematodes. Although the chemicals are widely used against the phytonematodes, because of hazardous effects of these compounds on non-target organisms and on the environment, there is a need to develop other control strategies. Nowadays, non-chemical measures are widely used to control the plant parasitic nematodes. Biocontrol of phytonematodes is an important method among environment-friendly measures of nematode management. There are some soil-inhabiting fungi that have biocontrol potential on phytonematodes, which can be used in nematode management program. The fungus Metarhizium anisopliae, originally is an entomopathogenic bioagent. Biocontrol potential of this fungus on some phytonematodes has been reported earlier. Recently, use of organic soil amendments as well as the use of bioagents is under special attention in sustainable agriculture. This research aimed to reduce the pesticide use in control of root-knot nematode, Meloidogyne javanica in tomato. The effects of M. anisopliae IMI 330189 and different levels of oak tree debris on M. javanica were determined. The combination effect of the fungus as well as the different rates of soil amendments was determined. Pots were filled with steam pasteurized soil mixture and the six leaf tomato seedlings were inoculated with 3000 second stage larvae of M. javanica/kg of soil. After eight weeks, plant growth parameters and nematode reproduction factors were compared. Based on the results of our experiment, combination of M. anisopliae IMI 330189 and oak debris caused more than 90% reduction in reproduction factor of nematode, at the rates of 100 and 150 g/kg soil (P ≤ 0.05). As compared to control, the reduction in number of galls was 76%. It was 86% for nematode reproduction factor, showing the significance of combined effect of both tested agents. Our results showed that plant debris can increase the biological activity of the tested bioagent. It was also proved that there was no adverse effect of oak debris, which potentially has antimicrobial activity, on antagonistic power of applied bioagent.

Keywords: Biological control, nematode management, organic soil, Quercus branti, root knot nematode, soil amendment.

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Authors: Larysa Novak-Kalyayeva, Aleksander Kuczabski, Orystlava Sydorchuk, Nataliia Fersman, Tatyana Zemlinskaia

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The article presents the results of the creative analysis and comparison of trends in the development of the theory of public administration during the period from the second half of the 20^th to the beginning of the 21^st century. The process of conceptualization of the priorities of public administration in the dynamics of reforming was held under the influence of such factors as globalization, integration, information and technological changes and human rights is examined. The priorities of the social state in the concepts of the second half of the 20^th century are studied. Peculiar approaches to determining the priorities of public administration in the countries of "Soviet dictatorship" in Central and Eastern Europe in the same period are outlined. Particular attention is paid to the priorities of public administration regarding the interaction between public power and society and the development of conceptual foundations for the modern managerial process. There is a thought that the dynamics of the formation of concepts of the European governance is characterized by the sequence of priorities: from socio-economic and moral-ethical to organizational-procedural and non-hierarchical ones. The priorities of the "welfare state" were focused on the decent level of material wellbeing of population. At the same time, the conception of "minimal state" emphasized priorities of human responsibility for their own fate under the conditions of minimal state protection. Later on, the emphasis was placed on horizontal ties and redistribution of powers and competences of "effective state" with its developed procedures and limits of responsibility at all levels of government and in close cooperation with the civil society. The priorities of the contemporary period are concentrated on human rights in the concepts of "good governance" and all the following ones, which recognize the absolute priority of public administration with compliance, provision and protection of human rights. There is a proved point of view that civilizational changes taking place under the influence of information and technological imperatives also stipulate changes in priorities, redistribution of emphases and update principles of managerial concepts on the basis of publicity, transparency, departure from traditional forms of hierarchy and control in favor of interactivity and inter-sectoral interaction, decentralization and humanization of managerial processes. The necessity to permanently carry out the reorganization, by establishing the interaction between different participants of public power and social relations, to establish a balance between political forces and social interests on the basis of mutual trust and mutual understanding determines changes of social, political, economic and humanitarian paradigms of public administration and their theoretical comprehension. The further studies of theoretical foundations of modern public administration in interdisciplinary discourse in the context of ambiguous consequences of the globalizational and integrational processes of modern European state-building would be advisable. This is especially true during the period of political transformations and economic crises which are the characteristic of the contemporary Europe, especially for democratic transition countries.

Keywords: Concepts of public administration, democratic transition countries, human rights, the priorities of public administration, theory of public administration.

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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Authors: Duan Huanyun, Xu Rui, Li Jianchang, Yuan Yage, Wang Qiuxia, Nomana Intekhab Hadi

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BioEnergy is an archetypal appropriate technology and alternate source of energy in rural areas of China, and can meet the basic need for cooking fuel in rural areas. The paper introduces with an alternate mean of research that can accelerate the biogas energy production. Tithonia diversifolia or the Tree marigold can be hailed as mesophillic anaerobic digestion to increase the production of more Bioenergy. Tithonia diversifolia is very native to Mexico and Central America, which can be served as ornamental plants- green manure and can prevent soil erosion. Tithonia diversifolia is widely grown and known to Asia, Africa, America and Australia as well. Nowadays, Considering China’s geographical condition it is found that Tithonia diversifolia is widely growing plant in the many tropical and subtropical regions of southern Yunnan- which can have great usage in accelerating and increasing the Bioenergy production technology. The paper discussed aiming at proving possibility that Tithonia diversifolia can be applied in biogas fermentation and its biogas production potential, the research carried experiment on Tithonia diversifolia biogas fermentation under the mesophilic condition (35 Celsius Degree). The result revealed that Tithonia diversifolia can be used as biogas fermentative material, and 6% concentration can get the best biogas production, with the TS biogas production rate 656mL/g and VS biogas production rate 801mL/g. It is well addressed that Tithonia diversifolia grows wildly in 53 Counties and 9 cities of Yunnan Province, which mainly grows in form of the road side plants, the edge of the field, countryside, forest edge, open space; of which demersum-natures can form dense monospecific beds -causing serious harm to agricultural production landforms threatening the ecological system as a potentially harmful exotic plant. There are also found the three types of invasive daisy alien plants -Eupatorium adenophorum, Eupatorium Odorata and Tithonia diversifolia in Yunnan Province of China-among them the Tithonia diversifolia is responsible for causing serious harm to agricultural production. In this paper we have designed the experimental explanation of Biogas energy production that requires anaerobic environment and some microbes; Tithonia diversifolia plant has been taken into consideration while carrying experiments and with successful resulting of generating more BioEnergy emphasizing on the practical applications of Tithonia diversifolia. This paper aims at- to find a new mechanism to provide a more scientific basis for the development of this plant herbicides in Biogas energy and to improve the utilization throughout the world as well.

Keywords: Biogas Energy Production, Tithonia diversifolia, Energy Development, Ecological Agriculture, Eupatorium adenophorum, Eupatorium odorata, Anaerobic Fermentation, Biogas Production Potential, Mesopilic Fermentation.

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Authors: A. Appe, B. Poluparthi, L. Kasivajjula, U. Mv, S. Bagadi, P. Modi, A. Singh, H. Gunupudi, S. Troiano, J. Paul, J. Stovall, J. Yamamoto

Abstract:

The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data are considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP (SHapley Additive exPlanations), to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since it is data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for e.g., quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP, a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: Competition, DAGs, hospital, healthcare, machine learning, market share, random forest, SHAP.

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Authors: R. G. Ariyawansa, M. A. N. R. M. Perera

Abstract:

“House” is a powerful symbol of socio-economic background of individuals and families. In fact, housing provides all types of needs/wants from basic needs to self-actualization needs. This phenomenon can be realized only having analyzed hidden motives of buyers and sellers of the housing market. Hence, the aim of this study is to examine the socio-economic insight of the secondary housing market in Colombo suburbs. This broader aim was achieved via analyzing the general pattern of the secondary housing market, identifying socio-economic motives of sellers of the secondary housing market, and reviewing sellers’ experience of buyer behavior. A purposive sample of 50 sellers from popular residential areas in Colombo such as Maharagama, Kottawa, Piliyandala, Punnipitiya, and Nugegoda was used to collect primary data instead of relevant secondary data from published and unpublished reports. The sample was limited to selling price ranging from Rs15 million to Rs25 million, which apparently falls into middle and upper-middle income houses in the context. Participatory observation and semi-structured interviews were adopted as key data collection tools. Data were descriptively analyzed. This study found that the market is mainly handled by informal agents who are unqualified and unorganized. People such as taxi/tree-wheel drivers, boutique venders, security personals etc. are engaged in housing brokerage as a part time career. Few fulltime and formally organized agents were found but they were also not professionally qualified. As far as housing quality is concerned, it was observed that 90% of houses was poorly maintained and illegally modified. They are situated in poorly maintained neighborhoods as well. Among the observed houses, 2% was moderately maintained and 8% was well maintained and modified. Major socio-economic motives of sellers were “migrating foreign countries for education and employment” (80% and 10% respectively), “family problems” (4%), and “social status” (3%). Other motives were “health” and “environmental/neighborhood problems” (3%). This study further noted that the secondary middle income housing market in the area directly related with the migrants who motivated for education in foreign countries, mainly Australia, UK and USA. As per the literature, families motivated for education tend to migrate Colombo suburbs from remote areas of the country. They are seeking temporary accommodation in lower middle income housing. However, the secondary middle income housing market relates with the migration from Colombo to major global cities. Therefore, final transaction price of this market may depend on migration related dates such as university deadlines, visa and other agreements. Hence, it creates a buyers’ market lowering the selling price. Also it was revealed that the buyers tend to trust more on this market as far as the quality of construction of houses is concerned than brand new houses which are built for selling purpose.

Keywords: Informal housing market, hidden motives of buyers and sellers, secondary housing market, socio-economic insight.

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