Search results for: stochastic reward net

Authors: P. Selyshchev

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We consider fluctuations of defects density taking into account their interaction. Stochastic field of displacement generation rate gives random defect distribution. We determinate statistical characteristics (mean and dispersion) of random field of point defect distribution as function of defect generation parameters, temperature and properties of irradiated crystal.

Keywords: irradiation, primary defects, interaction, fluctuations

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Authors: Shiao-Wei Chu

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In order to enhance the ability of their graduates to compete in an increasingly globalized economy, the majority of universities in Taiwan require students to pass Freshman English in order to earn a bachelor's degree. However, many college students show low motivation in English class for several important reasons, including exam-oriented lessons, unengaging classroom activities, a lack of opportunities to use English in authentic contexts, and low levels of confidence in using English. Students’ lack of motivation in English classes is evidenced when students doze off, work on assignments from other classes, or use their phones to chat with others, play video games or watch online shows. Cooperative learning aims to address these problems by encouraging language learners to use the target language to share individual experiences, cooperatively complete tasks, and to build a supportive classroom learning community whereby students take responsibility for one another’s learning. This study includes approximately 50 student participants in a low-proficiency Freshman English class. Each week, participants will work together in groups of between 3 and 4 students to complete various in-class interactive tasks. The instructor will employ a reward system that incentivizes students to be responsible for their own as well as their group mates’ learning. The rewards will be based on points that team members earn through formal assessment scores as well as assessment of their participation in weekly in-class discussions. The instructor will record each team’s week-by-week improvement. Once a team meets or exceeds its own earlier performance, the team’s members will each receive a reward from the instructor. This cooperative learning approach aims to stimulate EFL freshmen’s learning motivation by creating a supportive, low-pressure learning environment that is meant to build learners’ self-confidence. Students will practice all four language skills; however, the present study focuses primarily on the learners’ reading comprehension. Data sources include in-class discussion notes, instructor field notes, one-on-one interviews, students’ midterm and final written reflections, and reading scores. Triangulation is used to determine themes and concerns, and an instructor-colleague analyzes the qualitative data to build interrater reliability. Findings are presented through the researcher’s detailed description. The instructor-researcher has developed this approach in the classroom over several terms, and its apparent success at motivating students inspires this research. The aims of this study are twofold: first, to examine the possible benefits of this cooperative approach in terms of students’ learning outcomes; and second, to help other educators to adapt a more cooperative approach to their classrooms.

Keywords: freshman English, cooperative language learning, EFL learners, learning motivation, zone of proximal development

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Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis

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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.

Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics

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Authors: Danielle Katrina Santos, Koji Shimada

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Environmentally-friendly agriculture has been promoted for over two decades as a response to the environmental challenges brought by climate change and biological loss. Located above the equator, it is possible that Japan may benefit from future climate change, yet Japan is also a rarely developed country located in the Asian Monsoon climate region, making it vulnerable to the impacts of climate change. In this regard, the Japanese government has initiated policies to adapt to the adverse effects of climate change through the promotion and popularization of environmentally-friendly farming practices. This study aims to determine profit efficiency among environmentally-friendly rice farmers in Shiga Prefecture using the Stochastic Frontier Approach. A cross-sectional survey was conducted among 66 farmers from top rice-producing cities through a structured questionnaire. Results showed that the gross farm income of environmentally-friendly rice farmers was higher by JPY 316,223.00/ha. Production costs were also found to be higher among environmentally-friendly rice farmers, especially on labor costs, which accounted for 32% of the total rice production cost. The resulting net farm income of environmentally-friendly rice farmers was only higher by JPY 18,044/ha. Results from the stochastic frontier analysis further showed that the profit efficiency of conventional farmers was only 69% as compared to environmentally-friendly rice farmers who had a profit efficiency of 76%. Furthermore, environmentally-friendly agriculture participation, other types of subsidy, educational level, and farm size were significant factors positively influencing profit efficiency. The study concluded that substitution of environmentally-friendly agriculture for conventional rice farming would result in an increased profit efficiency due to the direct payment subsidy and price premium received. The direct government policies that would strengthen the popularization of environmentally-friendly agriculture to increase the production of environmentally-friendly products and reduce pollution load to the Lake Biwa ecosystem.

Keywords: profit efficiency, environmentally-friendly agriculture, rice farmers, direct payment subsidies

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Authors: Shaibu Baanni Azumah, William Adzawla

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Rice is an important staple crop, with current demand higher than the domestic supply in Ghana. This has led to a high and unfavourable import bill. Therefore, recent policies and interventions in the agricultural sub-sector aim at promoting various improved agricultural technologies in order to improve domestic production and reduce the importation of rice. In this study, we examined the effect of the adoption of Urea Deep Placement (UDP) technology by rice farmers on the position of the production frontier. This involved 200 farmers selected through a multi stage sampling technique in the Northern region of Ghana. A Cobb-Douglas stochastic frontier model was fitted. The result showed that the adoption of UDP technology shifts the output frontier outward and also move the farmers closer to the frontier. Farmers were also operating under diminishing returns to scale which calls for redress. Other factors that significantly influenced rice production were farm size, labour, use of certified seeds and NPK fertilizer. Although there was an opportunity for improvement, the farmers were highly efficient (92%), compared to previous studies. Farmers’ efficiency was improved through increased education, household size, experience, access to credit, and lack of extension service provision by MoFA. The study recommends the revision of Ghana’s agricultural policy to include the UDP technology. Agricultural Extension officers of the Ministry of Food and Agriculture (MoFA) should be trained on the UDP technology to support IFDC’s drive to improve adoption by rice farmers. Rice farmers are also encouraged to expand their farm lands, improve plant population, and also increase the usage of fertilizer to improve yields. Mechanisms through which credit can be made easily accessible and effectively utilised should be identified and promoted.

Keywords: efficiency, rice farmers, stochastic frontier, UDP technology

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Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Amin Alvani

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Multiple sclerosis (MS) is a chronic, often disabling disease in which the immune system attacks the myelin sheath of neurons in the central nervous system. The present study aimed to investigate the Relationship between behavioral inhibition/approach system (BIS-BAS) and perceived stress (PS) whit control white blood cell (WBC). 60 MS patients (male=36.7, female=63.3%; age range=15-65 participated in the study and completed the demographic questionnaire, the count blood cell (CBC) test, the behavioral Activation and behavioral inhibition scale (BIS-BAS), and the perceived stress Questionnaire (PSS-14). The results revealed that Between of BAS-reward responsiveness (BAS-DR) subscale and PS, in more than MS patient (BIS), there are increase WBC.

Keywords: behavioral inhibition/approach system, perceived stress, white blood cell, multiple sclerosis

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Authors: Engy A. Mohamed, Y. G. Hegazy

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This paper presents a novel algorithm for modeling photovoltaic based distributed generators for the purpose of optimal planning of distribution networks. The proposed algorithm utilizes sequential Monte Carlo method in order to accurately consider the stochastic nature of photovoltaic based distributed generators. The proposed algorithm is implemented in MATLAB environment and the results obtained are presented and discussed.

Keywords: comulative distribution function, distributed generation, Monte Carlo

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Authors: Felipe Henao, Yeny Rodriguez, Juan P. Viteri, Isaac Dyner

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Colombia is rich in natural resources and greatly focuses on the exploitation of water for hydroelectricity purposes. Alternative cleaner energy sources, such as solar and wind power, have been largely neglected despite: a) its abundance, b) the complementarities between hydro, solar and wind power, and c) the cost competitiveness of renewable technologies. The current limited mix of energy sources creates considerable weaknesses for the system, particularly when facing extreme dry weather conditions, such as El Niño event. In the past, El Niño have exposed the truly consequences of a system heavily dependent on hydropower, i.e. loss of power supply, high energy production costs, and loss of overall competitiveness for the country. Nonetheless, it is expected that the participation of hydroelectricity will increase in the near future. In this context, this paper proposes a stochastic lineal programming model to optimize the insertion of renewable energy systems (RES) into the Colombian electricity sector. The model considers cost-based generation competition between traditional energy technologies and alternative RES. This work evaluates the financial, environmental, and technical implications of different combinations of technologies. Various scenarios regarding the future evolution of costs of the technologies are considered to conduct sensitivity analysis of the solutions – to assess the extent of the participation of the RES in the Colombian power sector. Optimization results indicate that, even in the worst case scenario, where costs remain constant, the Colombian power sector should diversify its portfolio of technologies and invest strongly in solar and wind power technologies. The diversification through RES will contribute to make the system less vulnerable to extreme weather conditions, reduce the overall system costs, cut CO2 emissions, and decrease the chances of having national blackout events in the future. In contrast, the business as usual scenario indicates that the system will turn more costly and less reliable.

Keywords: energy policy and planning, stochastic programming, sustainable development, water management

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Authors: Bella Llego

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This study aims to investigate the relationships between human resource management and entrepreneurship in the view of owner-managers and employees, and among employees with in the SME in Thailand. The research method used a qualitative method to confirm the phenomenology interest with top management position which women are regarding their career path by using purposive sampling method. The results showed that human resources management has positive relate with the corporate entrepreneurship are including the recruitment process, training worker, professional career development and reward system impact to entrepreneur’s knowledge and innovation of corporate entrepreneurship in respectively to bring a very reliable way. Then, the key informant suggested that women’s career experiences predisposed them to find an alternative route for entrepreneurship, despite having achieved top management. The understanding factors that successfully contribute to the development of women entrepreneurs from career development perspective are critical endeavours for any type of organization as well.

Keywords: entrepreneurship, firm performance, human resource management, work efficiency

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Authors: Hannes Koester

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Driven by difficult market conditions and increasing regulations, many banks are making the strategic decision to restructure their portfolio by divesting several business segments. Using a unique dataset of 727 portfolio restructuring announcements by 161 international listed banks over the period 1999 to 2015, we investigate the impact of restructuring measurements on the stock performance as well as on the banks’ profitability and risk. Employing the event study methodology, we detect positive stock market reactions on the announcement of restructuring measurements. These positive stock market reactions indicate that shareholders reward banks’ specialization activities. However, the results of the system GMM regressions show a negative relation between restructuring measurements and banks’ return on assets and a positive relation towards the individual and systemic risk of banks. These empirical results indicate that there is no guarantee that portfolio restructurings will result in a more profitable and less risky institution.

Keywords: bank performance, bank risk, divestiture, restructuring, systemic risk

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Authors: Mami Miyasaka, Kaichi Yanaoka

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Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity; symptoms often manifest during childhood. In children with ADHD, the development of inhibitory processes is impaired. Inhibitory control allows people to avoid processing unnecessary stimuli and to behave appropriately in various situations; thus, people with ADHD require interventions to improve inhibitory control. Positive or negative reinforcements (i.e., reward or punishment) help improve the performance of children with such difficulties. However, in order to optimize impact, reward and punishment must be presented immediately following the relevant behavior. In regular elementary school classrooms, such supports are uncommon; hence, an alternative practical intervention method is required. One potential intervention involves setting goals to keep children motivated to perform tasks. This study examined whether goal setting improved inhibitory performances, especially for children with severe ADHD-related symptoms. We also focused on giving feedback on children's task performances. We expected that giving children feedback would help them set reasonable goals and monitor their performance. Feedback can be especially effective for children with severe ADHD-related symptoms because they have difficulty monitoring their own performance, perceiving their errors, and correcting their behavior. Our prediction was that goal setting by itself would be effective for children with mild ADHD-related symptoms, and goal setting based on feedback would be effective for children with severe ADHD-related symptoms. Japanese elementary school children and their parents were the sample for this study. Children performed two kinds of go/no-go tasks, and parents completed a checklist about their children's ADHD symptoms, the ADHD Rating Scale-IV, and the Conners 3rd edition. The go/no-go task is a cognitive task to measure inhibitory performance. Children were asked to press a key on the keyboard when a particular symbol appeared on the screen (go stimulus) and to refrain from doing so when another symbol was displayed (no-go stimulus). Errors obtained in response to a no-go stimulus indicated inhibitory impairment. To examine the effect of goal-setting on inhibitory control, 37 children (Mage = 9.49 ± 0.51) were required to set a performance goal, and 34 children (Mage = 9.44 ± 0.50) were not. Further, to manipulate the presence of feedback, in one go/no-go task, no information about children’s scores was provided; however, scores were revealed for the other type of go/no-go tasks. The results revealed a significant interaction between goal setting and feedback. However, three-way interaction between ADHD-related inattention, feedback, and goal setting was not significant. These results indicated that goal setting was effective for improving the performance of the go/no-go task only with feedback, regardless of ADHD severity. Furthermore, we found an interaction between ADHD-related inattention and feedback, indicating that informing inattentive children of their scores made them unexpectedly more impulsive. Taken together, giving feedback was, unexpectedly, too demanding for children with severe ADHD-related symptoms, but the combination of goal setting with feedback was effective for improving their inhibitory control. We discuss effective interventions for children with ADHD from the perspective of goal setting and feedback. This work was supported by the 14th Hakuho Research Grant for Child Education of the Hakuho Foundation.

Keywords: attention deficit disorder with hyperactivity, feedback, goal-setting, go/no-go task, inhibitory control

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Authors: Nwobu Obiamaka, Samuel O. Faboyede

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This study examines the factors influencing career choice of undergraduate accounting students in selected Nigerian universities. The manner in which students of accounting perceive the factors that drive them into pursuing a career in accounting is important to the profession. The study made use of primary data collected from undergraduate accounting students in their final year in selected Nigerian universities. The data was collected using a survey instrument (questionnaire), copies of which were made and administered to the respondents (undergraduate accounting students in selected Nigerian universities). The finding suggests that the major factors influencing undergraduate accounting students to opt for a career in accounting include pressure from peers and monetary reward. The findings from the study have crucial policy implications for admission officers in tertiary institutions as well as the accounting profession in Nigeria.

Keywords: accounting, career, choice, undergraduate

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Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: A. Mohammadi, M. Moghimi, S. Mohammadi

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Engineers need computational methods which could provide solutions less sensitive to the environmental effects, so the techniques should be used which take the uncertainty to account to control and minimize the risk associated with design and operation. In order to consider uncertainty in engineering problem, the optimization problem should be solved for a suitable range of the each uncertain input variable instead of just one estimated point. Using deterministic optimization problem, a large computational burden is required to consider every possible and probable combination of uncertain input variables. Several methods have been reported in the literature to deal with problems under uncertainty. In this paper, different methods presented and analyzed.

Keywords: uncertainty, Monte Carlo simulated, stochastic programming, scenario method

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Authors: Satoshi Nishimura

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Although much information has been garnered from the genomes of humans and mice, it remains difficult to extend that information to explain physiological and pathological phenomena. This is because the processes underlying life are by nature stochastic and fluctuate with time. Thus, we developed novel "in vivo molecular imaging" method based on single and two-photon microscopy. We visualized and analyzed many life phenomena, including common adult diseases. We integrated the knowledge obtained, and established new models that will serve as the basis for new minimally invasive therapeutic approaches.

Keywords: two photon microscope, intravital visualization, thrombus, artery

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Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

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Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: sanitation systems, nano-membrane toilet, lca, stochastic uncertainty analysis, Monte Carlo simulations, artificial neural network

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Authors: Arcady Ponosov., Ramazan Kadiev

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The work studies the global moment stability of solutions of systems of nonlinear differential Itô equations with delays. A modified regularization method (W-method) for the analysis of various types of stability of such systems, based on the choice of the auxiliaryequations and applications of the theory of positive invertible matrices, is proposed and justified. Development of this method for deterministic functional differential equations is due to N.V. Azbelev and his students. Sufficient conditions for the moment stability of solutions in terms of the coefficients for sufficiently general as well as specific classes of Itô equations are given.

Keywords: asymptotic stability, delay equations, operator methods, stochastic noise

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Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

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In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Mohammed A. Hajeeh

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This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: repairable models, imperfect, availability, exponential distribution

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Authors: Qiuwen Ma, Sai On Cheung

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Incentive contracting has been developed to push the agent team for extra effort. Generally, there are three types of incentive arrangement, namely incentive/penalty for super performance/underperformance, risk/reward sharing and future business opportunities. It is found that there are significant differences in the use of incentive arrangement in private and public projects. In Hong Kong, very few public projects have used future business as incentivizer whereas private developers often signal repeated business coupled with heavy penalty. This study was conducted to identify various attributes affecting the use of I/D in both private and public engineering sectors of Hong Kong. The diverging preferences were unveiled with reference to a literature review and semi-structured interviews with industry experts. The findings reveal the public/private sectors would consider the implementation issues regarding the various performance targets. The most deterministic factor for the public sector is about accountability. The private sector is in general skeptical about the need to provide extra for the contractors for what they have already contracted to perform.

Keywords: construction incentive, public/private projects, semi-structured interview, hong kong

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Authors: Tomoaki Hashimoto

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Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Muhammad Umair Ahmed, Aftab Shoukat

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Today the global economy has become one of the key strategies in dealing with environmental issues. To allow for a round economy, organizations have begun to work to improve their sustainability management. The contribution of green resource management to the transformation of the global economy has not been investigated. The purpose of the study was to evaluate the effects of green labor management on the global economy, environmental and economic performance, and the organisation's environmental dignity. We strongly evaluate the different roles of the various processes of green personnel management (i.e., green recruitment, training, and engagement green, as well as green performance management and reward) in organizational operations. We are also investigating the leadership role of CEO Ethical. Our outcome will have a positive impact on the performance of the organization. Green Human Resource Management contributes to the evolution of a roundabout economy without the influence of different external factors such as market demand and commitment. Finally, the results of our research will provide a few aspects for future research, both academic and human.

Keywords: sustainability, green human resource management, circular economy, human capital

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Authors: Sun Jin Park, Kyung-Ja Cho

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This study focused on characteristics related to hasty behaviour. To investigate the relation between personal characteristics and hasty behaviour, 601 data were collected, 335 males and 256 females answered their own 'social avoidance and distress’, ‘anxiety’, ‘sensation seeking', 'hope', and ' hasty behaviour. And then 591 data were used for the analysis. The factor analysis resulted hasty behaviour consisted of 5 factors, time pressure, isolation, uncomfortable situation, boring condition, and expectation of reward. The result showed anxiety, sensation seeking, and hope related to hasty behaviour. Specifically, anxiety was involved in every hasty behaviour. This result means that psychological tension and worry are related to hasty behaviour in common. 'Social avoidance and distress', 'sensation seeking' and 'hope' influenced on hasty behaviour under time pressure, in isolation, in expectation of rewards respectively. This means that each factor of hasty behaviour has anxiety as its basis, expressed through a varied nature.

Keywords: hasty behaviour, social avoidance and distress, anxiety, sensation seeking, hope

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Authors: Fakhruddin Esa, Yusri Yusof

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The confirmatory of Total Quality Management (TQM) implementation is most vital in quality management. This paper focuses on employees' perceptions towards TQM implementation in a local automotive company supplier. The objectives of this study are first and foremost to determine the perception of TQM implementation among the staff, and secondly to ascertain the correlation between the variables, and lastly to identify the relative influence of the 10 TQM variables on the cost of poor quality (COPQ). The TQM implementation is perceived to be moderate. All correlation is found to be significant and five variables having positively moderate to high correlation. Out of 10 variables, quality system improvement, reward and recognition and customer focus influence the perceived COPQ. This study extended a discussion on these three variables contribution to TQM in general and the human resource development in the organization. A significant recommendation to lowering costs of internal error, such as trouble shooting and scraps are also discussed. Certain components of further research that would add value to this study have also been suggested and perhaps could be implemented at policy-level initiatives.

Keywords: cost of poor quality (COPQ), correlation, total quality management (TQM), variables

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Authors: Raja Jarray, Imen Zaghbani, Soufiene Bouallègue

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Path planning for Unmanned Aerial Vehicles (UAVs) in dynamic environments poses a significant challenge. Adapting planning algorithms to these complex environments with moving obstacles is a major task in real-world robotics. This article introduces a path-planning strategy based on a Q-learning algorithm, which enables an effective response to avoid moving obstacles while ensuring mission feasibility. A dynamic reward function is introduced, causing the UAV to use the real-time distance between its current position and the destination as training data. The objective of the proposed Q-learning-based path planning algorithm is to guide the drone through an optimal flight itinerary in a dynamic, collision-free environment. The proposed Q-learning-based UAV planner is evaluated considering numerous commonly used performance metrics. Demonstrative results are provided and discussed to show the effectiveness and practicability of such an artificial intelligence-based path planning approach.

Keywords: unmanned aerial vehicles, dynamic path planning, moving obstacles, reinforcement-learning, Q-learning

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

Abstract:

The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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