Search results for: Goal Programming

Authors: Kjersti Engan, Thor Ole Gulsrud, Karl Fredrik Fretheim, Barbro Furebotten Iversen, Liv Eriksen

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Clusters of microcalcifications in mammograms are an important sign of breast cancer. This paper presents a complete Computer Aided Detection (CAD) scheme for automatic detection of clustered microcalcifications in digital mammograms. The proposed system, MammoScan μCaD, consists of three main steps. Firstly all potential microcalcifications are detected using a a method for feature extraction, VarMet, and adaptive thresholding. This will also give a number of false detections. The goal of the second step, Classifier level 1, is to remove everything but microcalcifications. The last step, Classifier level 2, uses learned dictionaries and sparse representations as a texture classification technique to distinguish single, benign microcalcifications from clustered microcalcifications, in addition to remove some remaining false detections. The system is trained and tested on true digital data from Stavanger University Hospital, and the results are evaluated by radiologists. The overall results are promising, with a sensitivity > 90 % and a low false detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).

Keywords: mammogram, microcalcifications, detection, CAD, MammoScan μCaD, VarMet, dictionary learning, texture, FTCM, classification, adaptive thresholding

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Authors: Manuela Nayantara Jeyaraj

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Green IT is a term that refers to the collective strategic and tactical practices that unswervingly condense the carbon footprint to a diminished proportion in an establishment’s computing procedures. This concept has been tightly knit with IT related organizations; hence it has been precluded to be applied within non-IT organizations in Sri Lanka. With the turn of the century, computing technologies have taken over commonplace activities in every nook and corner in Sri Lanka, which is still on the verge of moving forth in its march towards being a developed country. Hence, it needs to be recursively proven that non-IT industries are well-bound to adhere to ‘Green IT’ practices as well, in order to reduce their carbon footprint and move towards considering the practicality of implementing Green-IT practices within their work-arounds. There are several spheres that need to be taken into account in creating awareness of ‘Green IT’, such as the economic breach, technologies available, legislative bounds, community mind-set and many more. This paper tends to reconnoiter causes that currently restrain non-IT organizations from considering Green IT concepts. By doing so, it is expected to prove the beneficial providence gained by implementing this concept within the organization. The ultimate goal is to propose feasible ‘Green IT’ practices that could be implemented within the context of Sri Lankan non-IT sectors in order to ensure that organization’s sustainable growth towards a long term existence.

Keywords: Computing practices, green IT, non-IT industries, Sri Lanka, sustainability.

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Authors: Kritsada Moonpa, Kannipa Motanated, Weerapan Srichan

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Hong Hoi Formation is a Middle Triassic deep marine succession presented in outcrops throughout the Lampang Basin of northern Thailand. The primary goal of this research is to diagnose the paleoenvironment, petrographic compositions, and sedimentary sources of the Hong Hoi Formation in Ban Huat, Ngao District. The Triassic Hong Hoi Formation is chosen because the outcrops are continuous and fossils are greatly exposed and abundant. Depositional environment is reconstructed through sedimentological studies along with facies analysis. The Hong Hoi Formation is petrographically divided into two major facies, they are: sandstones with mudstone interbeds, and mudstones or shale with sandstone interbeds. Sandstone beds are lithic arenite and lithic greywacke, volcanic lithic fragments are dominated. Sedimentary structures, paleocurrent data and lithofacies arrangement indicate that the formation deposited in a part of deep marine abyssal plain environment. The sedimentological and petrographic features suggest that during the deposition the Hong Hoi Formation received sediment supply from nearby volcanic arc. This suggested that the intensive volcanic activity within the Sukhothai Arc during the Middle Triassic is the main sediment source.

Keywords: Sukhothai Zone, petrography, Hong Hoi Formation, Lampang, Triassic.

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.

Keywords: Integral differential equations, L-stable methods, pricing European options, Jump–diffusion model.

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Authors: H. W. Corley

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A scalar equilibrium (SE) is an alternative type of equilibrium in pure strategies for an n-person normal-form game G. It is defined using optimization techniques to obtain a pure strategy for each player of G by maximizing an appropriate utility function over the acceptable joint actions. The players’ actions are determined by the choice of the utility function. Such a utility function could be agreed upon by the players or chosen by an arbitrator. An SE is an equilibrium since no players of G can increase the value of this utility function by changing their strategies. SEs are formally defined, and examples are given. In a greedy SE, the goal is to assign actions to the players giving them the largest individual payoffs jointly possible. In a weighted SE, each player is assigned weights modeling the degree to which he helps every player, including himself, achieve as large a payoff as jointly possible. In a compromise SE, each player wants a fair payoff for a reasonable interpretation of fairness. In a parity SE, the players want their payoffs to be as nearly equal as jointly possible. Finally, a satisficing SE achieves a personal target payoff value for each player. The vector payoffs associated with each of these SEs are shown to be Pareto optimal among all such acceptable vectors, as well as computationally tractable.

Keywords: Compromise equilibrium, greedy equilibrium, normal-form game, parity equilibrium, pure strategies, satisficing equilibrium, scalar equilibria, utility function, weighted equilibrium.

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Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel

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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.

Keywords: Firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics.

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Authors: Kumar Padmanabh, Rajarshi Roy

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In this paper a special kind of buffer management policy is studied where the packet are preempted even when sufficient space is available in the buffer for incoming packets. This is done to congestion for future incoming packets to improve QoS for certain type of packets. This type of study has been done in past for ATM type of scenario. We extend the same for heterogeneous traffic where data rate and size of the packets are very versatile in nature. Typical example of this scenario is the buffer management in Differentiated Service Router. There are two aspects that are of interest. First is the packet size: whether all packets have same or different sizes. Second aspect is the value or space priority of the packets, do all packets have the same space priority or different packets have different space priorities. We present two types of policies to achieve QoS goals for packets with different priorities: the push out scheme and the expelling scheme. For this work the scenario of packets of variable length is considered with two space priorities and main goal is to minimize the total weighted packet loss. Simulation and analytical studies show that, expelling policies can outperform the push out policies when it comes to offering variable QoS for packets of two different priorities and expelling policies also help improve the amount of admissible load. Some other comparisons of push out and expelling policies are also presented using simulations.

Keywords: Buffer Management Policy, Diffserv, ATM, Pushout Policy, Expeling Policy.

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Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: Clique, clan, electronic health records, physician collaboration.

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Authors: Raluca Ionela Maxim

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Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: Design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models.

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Authors: Bibhya Sharma, Jito Vanualailai, Ravindra Rai

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This research paper designs a unique motion planner of multiple platoons of nonholonomic car-like robots as a feasible solution to the lane changing/merging maneuvers. The decentralized planner with a leaderless approach and a path-guidance principle derived from the Lyapunov-based control scheme generates collision free avoidance and safe merging maneuvers from multiple lanes to a single lane by deploying a split/merge strategy. The fixed obstacles are the markings and boundaries of the road lanes, while the moving obstacles are the robots themselves. Real and virtual road lane markings and the boundaries of road lanes are incorporated into a workspace to achieve the desired formation and configuration of the robots. Convergence of the robots to goal configurations and the repulsion of the robots from specified obstacles are achieved by suitable attractive and repulsive potential field functions, respectively. The results can be viewed as a significant contribution to the avoidance algorithm of the intelligent vehicle systems (IVS). Computer simulations highlight the effectiveness of the split/merge strategy and the acceleration-based controllers.

Keywords: Lane merging, Lyapunov-based control scheme, path-guidance principle, split/merge strategy.

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Authors: Kanika Sood, Sijie Shang

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A fundamental goal of education includes preparing students to become a part of the global workforce by making beneficial contributions to society. In this paper, we analyze student performance for multiple courses that involve different teaching pedagogies: a cooperative learning technique and an inquiry-based learning strategy. Student performance includes student engagement, grades, and attendance records. We perform this study in the Computer Science department for online and in-person courses for 450 students. We will perform correlation analysis to study the relationship between student scores and other parameters such as gender, mode of learning. We use natural language processing and machine learning to analyze student feedback data and performance data. We assess the learning outcomes of two teaching pedagogies for undergraduate and graduate courses to showcase the impact of pedagogical adoption and learning outcome as determinants of academic achievement. Early findings suggest that when using the specified pedagogies, students become experts on their topics and illustrate enhanced engagement with peers.

Keywords: Bag-of-words, cooperative learning, education, inquiry-based learning, in-person learning, Natural Language Processing, online learning, sentiment analysis, teaching pedagogy.

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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Authors: Fernando Augusto Ullmann Tobe, Moacyr Amaral Domingues, Figueiredo, Stephany Rie Yamamoto Gushiken

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The purpose of this paper is to present the process of elaborating the layout of an assembly line of a welding industry using the principles of lean manufacturing as the main driver. The objective of this paper is relevant since the current layout of the assembly line causes non-productive times for operators, being related to the lean waste of unnecessary movements. The methodology used for the project development was Project-based Learning (PBL), which is an active way of learning focused on real problems. The process of selecting the methodology for layout planning was developed considering three criteria to evaluate the most relevant one for this paper's goal. As a result of this evaluation, Systematic Layout Planning was selected, and three steps were added to it – Value Stream Mapping for the current situation and after layout changed and the definition of lean tools and layout type. This inclusion was to consider lean manufacturing in the layout redesign of the industry. The layout change resulted in an increase in the value-adding time of operations carried out in the sector, reduction in movement times between previous and final assemblies, and in cost savings regarding the man-hour value of the employees, which can be invested in productive hours instead of movement times.

Keywords: Assembly line, layout, lean manufacturing, systematic layout planning.

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Authors: A. F. Ali, D. M. Shawky

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Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.

Keywords: Bioinformatics, Artificial Neural Networks, Protein Sequence Analysis, Feature Extraction.

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Authors: Asma Rabaoui, Zied Lachiri, Noureddine Ellouze

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Discrimination between different classes of environmental sounds is the goal of our work. The use of a sound recognition system can offer concrete potentialities for surveillance and security applications. The first paper contribution to this research field is represented by a thorough investigation of the applicability of state-of-the-art audio features in the domain of environmental sound recognition. Additionally, a set of novel features obtained by combining the basic parameters is introduced. The quality of the features investigated is evaluated by a HMM-based classifier to which a great interest was done. In fact, we propose to use a Multi-Style training system based on HMMs: one recognizer is trained on a database including different levels of background noises and is used as a universal recognizer for every environment. In order to enhance the system robustness by reducing the environmental variability, we explore different adaptation algorithms including Maximum Likelihood Linear Regression (MLLR), Maximum A Posteriori (MAP) and the MAP/MLLR algorithm that combines MAP and MLLR. Experimental evaluation shows that a rather good recognition rate can be reached, even under important noise degradation conditions when the system is fed by the convenient set of features.

Keywords: Sounds recognition, HMM classifier, Multi-style training, Environmental Adaptation, Feature combinations.

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent’s attributes. Also, the influence of social networks in the developing of agents interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: Artificial stock markets, agent based simulation, bounded rationality, behavioral finance, artificial neural network, interaction, scale-free networks.

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Authors: Saowapa Phaithayawat

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The purposes of this study are 1) to study the impact of the 3-community-core model: House (H), Temple (T), and School (S) with the co-operation of official departments on community development to ASEAN economic community involvement and 2) to study the procedures and extension of the model. The research which is a qualitative research is based on the formal and informal interviews. Local people in a community are observed. Group interview is, also, operated by executors and cooperators in the school in the community. In terms of social and cultural dimension, the 3-community-core model consisting of house, temple and school is the base of Thai cultures bringing about understanding, happiness and unity to the community. The result of this research is that the official departments in accompanied with this model developers cooperatively work together in the community to support such factors as budget, plan, activities. Moreover, the need of community, and the continual result to sustain the community are satisfied by the model implementation. In terms of the procedures of the model implementation, executors and co-operators can work, coordinate, think, and launch their public relation altogether. Concerning the model development, this enables the community to achieve its goal to prepare the community’s readiness for ASEAN Economic Community involvement.

Keywords: ASEAN Economic Community, Community Development.

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Authors: S. Moshaf, Z. Hamidi-Esfahani, M. H. Azizi

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Xanthan gum is one of the major commercial biopolymers. Due to its excellent rheological properties xanthan gum is used in many applications, mainly in food industry. Commercial production of xanthan gum uses glucose as the carbon substrate; consequently the price of xanthan production is high. One of the ways to decrease xanthan price, is using cheaper substrate like agricultural wastes. Iran is one of the biggest date producer countries. However approximately 50% of date production is wasted annually. The goal of this study is to produce xanthan gum from waste date using Xanthomonas campestris PTCC1473 by submerged fermentation. In this study the effect of three variables including phosphor and nitrogen amount and agitation rate in three levels using response surface methodology (RSM) has been studied. Results achieved from statistical analysis Design Expert 7.0.0 software showed that xanthan increased with increasing level of phosphor. Low level of nitrogen leaded to higher xanthan production. Xanthan amount, increasing agitation had positive influence. The statistical model identified the optimum conditions nitrogen amount=3.15g/l, phosphor amount=5.03 g/l and agitation=394.8 rpm for xanthan. To model validation, experiments in optimum conditions for xanthan gum were carried out. The mean of result for xanthan was 6.72±0.26. The result was closed to the predicted value by using RSM.

Keywords: Optimization, RSM, Waste date, Xanthan gum, Xanthomonas Campestris

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Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.

Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.

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Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

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Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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Authors: H. Bentarzi, A. Zitouni

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The reliability of the power grid depends on the successful operation of thousands of protective relays. The failure of one relay to operate as intended may lead the entire power grid to blackout. In fact, major power system failures during transient disturbances may be caused by unnecessary protective relay tripping rather than by the failure of a relay to operate. Adequate relay testing provides a first defense against false trips of the relay and hence improves power grid stability and prevents catastrophic bulk power system failures. The goal of this research project is to design and enhance the relay tester using a technology such as Field Programmable Gate Array (FPGA) card NI 7851. A PC based tester framework has been developed using Simulink power system model for generating signals under different conditions (faults or transient disturbances) and LabVIEW for developing the graphical user interface and configuring the FPGA. Besides, the interface system has been developed for outputting and amplifying the signals without distortion. These signals should be like the generated ones by the real power system and large enough for testing the relay’s functionality. The signals generated that have been displayed on the scope are satisfactory. Furthermore, the proposed testing system can be used for improving the performance of protective relay.

Keywords: Amplifier class D, FPGA, protective relay, tester.

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Authors: Ehi E. Aimiuwu

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As of 2017, many researchers in educational journals are still wondering if students are effectively and efficiently engaged in active learning in the online learning environment. The goal of this qualitative single case study and narrative research is to explore if students are actively engaged in their online learning. Seven online students in the United States from LinkedIn and residencies were interviewed for this study. Eleven online learning techniques from research were used as a framework.  Data collection tools were used for the study that included a digital audiotape, observation sheet, interview protocol, transcription, and NVivo 12 Plus qualitative software.  Data analysis process, member checking, and key themes were used to reach saturation. About 85.7% of students preferred individual grading. About 71.4% of students valued professor’s interacting 2-3 times weekly, participating through posts and responses, having good internet access, and using email.  Also, about 57.1% said students log in 2-3 times weekly to daily, professor’s social presence helps, regular punctuality in work submission, and prefer assessments style of research, essay, and case study.  About 42.9% appreciated syllabus usefulness and professor’s expertise.

Keywords: Class facilitation, course management, online teaching, online education, student engagement.

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Authors: García López

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The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: Emotions in tweets emotion detection in text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content.

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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Authors: Saule Mussabekova, Samal Abzhanova

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The Kazakh Language Fluency Test, based on the IELTS exam, was implemented in 2012 at Nazarbayev University in Astana, Kazakhstan. We would like to share our experience in developing this exam and some exam results with other language instructors. In this paper, we will cover all these peculiarities and their related issues. The Kazakh Language Fluency Test is a young exam. During its development, we faced many difficulties. One of the goals of the university and the country is to encourage fluency in the Kazakh language for all citizens of the Republic. Nazarbayev University has introduced a Kazakh language program to assist in achieving this goal. This policy is one-step in ensuring that NU students have a thorough understanding of the Kazakh language through a fluency test based on the International English Language Testing System (IELTS). The Kazakh Language Fluency Test exam aims to determine student’s knowledge of Kazakh language. The fact is that there are three types of students at Nazarbayev University: Kazakh-speaking heritage learners, Russian-speaking and English-speaking students. Unfortunately, we have Kazakh students who do not speak Kazakh. All students who finished school with Russian language instruction are given Kazakh Language Fluency Test in order to determine their Kazakh level. After the test exam, all students can choose appropriate Kazakh course: Basic Kazakh, Intermediate Kazakh and Upper-Intermediate Kazakh. The Kazakh Language Fluency Test consists of four parts: Listening, Reading, Writing and Speaking. They are taken on the same day in the abovementioned order.

Keywords: Diagnostic language test, Kazakh language, placement test, test result.

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Authors: S. Sieniutycz

Abstract:

This paper unifies power optimization approaches in various energy converters, such as: thermal, solar, chemical, and electrochemical engines, in particular fuel cells. Thermodynamics leads to converter-s efficiency and limiting power. Efficiency equations serve to solve problems of upgrading and downgrading of resources. While optimization of steady systems applies the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. In reacting systems chemical affinity constitutes a prevailing component of an overall efficiency, thus the power is analyzed in terms of an active part of chemical affinity. The main novelty of the present paper in the energy yield context consists in showing that the generalized heat flux Q (involving the traditional heat flux q plus the product of temperature and the sum products of partial entropies and fluxes of species) plays in complex cases (solar, chemical and electrochemical) the same role as the traditional heat q in pure heat engines. The presented methodology is also applied to power limits in fuel cells as to systems which are electrochemical flow engines propelled by chemical reactions. The performance of fuel cells is determined by magnitudes and directions of participating streams and mechanism of electric current generation. Voltage lowering below the reversible voltage is a proper measure of cells imperfection. The voltage losses, called polarization, include the contributions of three main sources: activation, ohmic and concentration. Examples show power maxima in fuel cells and prove the relevance of the extension of the thermal machine theory to chemical and electrochemical systems. The main novelty of the present paper in the FC context consists in introducing an effective or reduced Gibbs free energy change between products p and reactants s which take into account the decrease of voltage and power caused by the incomplete conversion of the overall reaction.

Keywords: Power yield, entropy production, chemical engines, fuel cells, exergy.

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Authors: Lara F. Horani, Shurong Tong

Abstract:

Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.

Keywords: Analytic hierarchy process, green product, customer requirements for green design, importance weights for the customer requirements.

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

Abstract:

The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: Cytokine, saliva, attention deficit hyperactivity disorder, child, biomarker.

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

Abstract:

The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: Brain machine interface, decision-making, local field potentials, mobile robot, navigation, neural network, rat, signal processing.

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Authors: Osuagwu Justine Ugochukwu, Sazali Abd Wahab, Sunday Sunday Akpan

Abstract:

Investigating the effects of transformational and transactional leadership styles on the performance of healthcare employees at the University Teaching Hospital (UNTH) in Enugu, Nigeria, was the goal of the research. The respondents were asked to fill out a structured questionnaire. The respondents were chosen using a straightforward random sampling technique and consisted of 370 health workers at the hospital. The result of the analysis revealed that transactional and transformational leadership style has a positive while ambidextrous leadership has a negative effect on healthcare workers' performance in UNTH, Enugu. Therefore, the management of public hospitals that have the capacity to change their top management approach to leadership styles will gain substantial support from their employees’ thereby increasing organizational commitment and performance among health workers. This will have remarkable social implications, one of which is a change in the work culture and attitude of medical personnel from the seemingly anti-community of patients to friendly engagement and treatment of patients leading to a harmonious coexistence among these individuals in society. Investigating ambidextrous leadership and the use of nonparametric analysis is unique and has brought knowledge to leadership literature.

Keywords: Workers’ performance, transformational leadership, transactional leadership, governance quality, ambidextrous leadership.

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