Search results for: resource and task allocation

Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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Authors: Trapond Hiransalee

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The technology of mobile devices has changed our daily lives. Since smartphone have become a multi-functional device, many people spend unnecessary time on them, and could be interrupted by inappropriate notifications such as unimportant messages from social media. Notifications from smartphone could draw people’s attention and distract them from their priorities and current tasks. This research investigated that if the users were notified by their surroundings instead of smartphone, would it create less distraction and keep their focus on the present task. The experiment was a simulation of a lamp and door notification. Notifications related to work will be embedded in the lamp such as an email from a colleague. A notification that is useful when going outside such as weather information, traffic information, and schedule reminder will be embedded in the door. The experiment was conducted by sending notifications to the participant while he or she was working on a primary task and the working performance was measured. The results show that the lamp notification had fewer interruption effects than the smartphone. For the door notification, it was simulated in order to gain opinions and insights on ambient notifications from participants. Many participants agreed that the ambient notifications are useful and being informed by them could lessen the usage of their smartphone. The results and insights from this research could be used to guide the design process of ambient notifications.

Keywords: HCI, Interaction, Interaction design, Usability testing.

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: Algorithm recommendation, meta-learning, bioinformatics, hierarchical classification.

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: Brain activity, EEG, information processing model, model human processor.

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Authors: F. Keller, G. Reinhart

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The efficient and economic allocation of resources is one main goal in the field of production planning and control. Nowadays, a new variable gains in importance throughout the planning process: Energy. Energy-efficiency has already been widely discussed in literature, but with a strong focus on reducing the overall amount of energy used in production. This paper provides a brief systematic approach, how energy-supply-orientation can be used for an energy-cost-efficient production planning and thus combining the idea of energy-efficiency and energy-flexibility.

Keywords: Production planning and control, energy, efficiency, flexibility.

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Authors: Somnath Dey, Debasis Samanta

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Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.

Keywords: Iris recognition, iris localization, biometrics, image processing.

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Authors: Mehaiguene Madjid, Touhari Fadhila, Meddi Mohamed

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The Cheliff basin offers a good hydrological example for the possibility of studying the problem which elucidated in the future, because of the unclearity in several aspects and hydraulic installation. Thus, our study of the Cheliff basin is divided into two principal parts: The spatial evaluation of the precipitation: also, the understanding of the modes of the reconstitution of the resource in water supposes a good knowledge of the structuring of the precipitation fields in the studied space. In the goal of a good knowledge of revitalizes them in water and their management integrated one judged necessary to establish a precipitation card of the Cheliff basin for a good understanding of the evolution of the resource in water in the basin and that goes will serve as basis for all study of hydraulic planning in the Cheliff basin. Then, the establishment of the precipitation card of the Cheliff basin answered a direct need of setting to the disposition of the researchers for the region and a document of reference that will be completed therefore and actualized. The hydrological study, based on the statistical hydrometric data processing will lead us to specify the hydrological terms of the assessment hydrological and to clarify the fundamental aspects of the annual flow, seasonal, extreme and thus of their variability and resources surface water.

Keywords: Hydrological assessment, surface water resources, Cheliff, Algeria.

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

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Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Keywords: Distillation, neural networks, software tools, identification, control.

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Authors: W. Mughees, M. Al-Ahmad, M. Naeem

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This research involves the design and analysis of pinch-based water/wastewater networks to minimize water utility in the petrochemical and petroleum industries. A study has been done on Tehran Oil Refinery to analyze feasibilities of regeneration, reuse and recycling of water network. COD is considered as a single key contaminant. Amount of freshwater was reduced about 149m3/h (43.8%) regarding COD. Re-design (or retrofitting) of water allocation in the networks was undertaken. The results were analyzed through graphical method and mathematical programming technique which clearly demonstrated that amount of required water would be determined by mass transfer of COD.

Keywords: Minimization, Water Pinch, Water Management, Pollution Prevention.

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Authors: B. E. Narkhede, S. K. Mahajan, B. T. Patil, R. D. Raut

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Information quality is a major performance measure for an Enterprise Resource Planning (ERP) system of any firm. This study identifies various critical success factors of information quality. The effect of various critical success factors like project management, reengineering efforts and interdepartmental communications on information quality is analyzed using a multiple regression model. Here quantitative data are collected from respondents from various firms through structured questionnaire for assessment of the information quality, project management, reengineering efforts and interdepartmental communications. The validity and reliability of the data are ensured using techniques like factor analysis, computing of Cronbach’s alpha. This study gives relative importance of each of the critical success factors. The findings suggest that among the various factors influencing information quality careful reengineering efforts are the most influencing factor. This paper gives clear insight to managers and practitioners regarding the relative importance of critical success factors influencing information quality so that they can formulate a strategy at the beginning of ERP system implementation.

Keywords: Enterprise resource planning, information systems, multiple regression, information quality.

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Authors: Daniel A. Montoya, Marta L. Tostes

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This investigation aims at analyzing and determining the relation between two very important variables in the human resource management: The organizational climate and the performance assessment. This study aims at contributing with knowledge in the search of the relation between the mentioned variables because the literature still does not provide solid evidence to this respect and the cases revised are incipient to reach conclusions enabling a typology about this relation.To this regard, a correlational and cross-sectional perspective was adopted in which quantitative and qualitative techniques were chosen with the total of the workers of the tourist service company PTS Peru. In order to measure the organizational climate, the OCQ (Organization Climate Questionnaire) from was used; it has 50 items and measures 9 dimensions of the Organizational Climate. Also, to assess performance, a questionnaire with 21 items and 6 dimensions was designed. As a means of assessment, a focus group was prepared and was applied to a worker in every area of the company. Additionally, interviews to human resources experts were conducted. The results of the investigation show a clear relation between the organizational climate and the personnel performance assessment as well as a relation between the nine dimensions of the organizational climate and the work performance in general and with some of its dimensions.

Keywords: Job performance, human resource management, organization climate, performance assessment.

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Authors: M. Sankari, R. Bremananth, C.Meena

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Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments. 

Keywords: Character segmentation, Connectivity checking, Edge detection, Image analysis, license plate localization, license number recognition, Quality frame selection

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Authors: J. H. Boonzaaier, A. C. Brent

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South Africa, a water scarce country, experiences the phenomenon that its life supporting natural water resources is seriously threatened by the users that are totally dependent on it. South Africa is globally applauded to have of the best and most progressive water laws and policies. There are however growing concerns regarding natural water resource quality deterioration and a critical void in the management of natural resources and compliance to policies due to increasing institutional uncertainties and failures. These are in accordance with concerns of many South African researchers and practitioners that call for a change in paradigm from talk to practice and a more constructive, practical approach to governance challenges in the management of water resources. A qualitative theory-building case study through longitudinal action research was conducted from 2014 to 2017. The research assessed whether a strategic positioned institutional agent can be parlayed to facilitate and execute WRM on catchment level by engaging multiple stakeholders in a polycentric setting. Through a critical realist approach a distinction was made between ex ante self-deterministic human behaviour in the realist realm, and ex post governance-management in the constructivist realm. A congruence analysis, including Toulmin’s method of argumentation analysis, was utilised. The study evaluated the unique case of a self-steering local water management institution, the Impala Water Users Association (WUA) in the Pongola River catchment in the northern part of the KwaZulu-Natal Province of South Africa. Exploiting prevailing water resource threats, it expanded its ancillary functions from 20,000 to 300,000 ha. Embarking on WRM activities, it addressed natural water system quality assessments, social awareness, knowledge support, and threats, such as: soil erosion, waste and effluent into water systems, coal mining, and water security dimensions; through structured engagement with 21 different catchment stakeholders. By implementing a proposed polycentric governance-management model on a catchment scale, the WUA achieved to fill the void. It developed a foundation and capacity to protect the resilience of the natural environment that is critical for freshwater resources to ensure long-term water security of the Pongola River basin. Further work is recommended on appropriate statutory delegations, mechanisms of sustainable funding, sufficient penetration of knowledge to local levels to catalyse behaviour change, incentivised support from professionals, back-to-back expansion of WUAs to alleviate scale and cost burdens, and the creation of catchment data monitoring and compilation centres.

Keywords: Institutional agent, water governance, polycentric water resource management, water resource management.

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Authors: Hiroshi Abe, Minoru Nakayama

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The frontal area in the brain is known to be involved in behavioral judgement. Because a Kanji character can be discriminated visually and linguistically from other characters, in Kanji character discrimination, we hypothesized that frontal event-related potential (ERP) waveforms reflect two discrimination processes in separate time periods: one based on visual analysis and the other based on lexcical access. To examine this hypothesis, we recorded ERPs while performing a Kanji lexical decision task. In this task, either a known Kanji character, an unknown Kanji character or a symbol was presented and the subject had to report if the presented character was a known Kanji character for the subject or not. The same response was required for unknown Kanji trials and symbol trials. As a preprocessing of signals, we examined the performance of a method using independent component analysis for artifact rejection and found it was effective. Therefore we used it. In the ERP results, there were two time periods in which the frontal ERP wavefoms were significantly different betweeen the unknown Kanji trials and the symbol trials: around 170ms and around 300ms after stimulus onset. This result supported our hypothesis. In addition, the result suggests that Kanji character lexical access may be fully completed by around 260ms after stimulus onset.

Keywords: Character discrimination, Event-related Potential, IndependentComponent Analysis, Kanji, Lexical access.

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Authors: Chuang-Hung Lin, Cheng-Yuan Hsu, Jia-Yan Lin

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It is an indispensible strategy to adopt greenery approach on architectural bases so as to improve ecological habitats, decrease heat-island effect, purify air quality, and relieve surface runoff as well as noise pollution, all of which are done in an attempt to achieve sustainable environment. How we can do with plant design to attain the best visual quality and ideal carbon dioxide fixation depends on whether or not we can appropriately make use of greenery according to the nature of architectural bases. To achieve the goal, it is a need that architects and landscape architects should be provided with sufficient local references. Current greenery studies focus mainly on the heat-island effect of urban with large scale. Most of the architects still rely on people with years of expertise regarding the adoption and disposition of plantation in connection with microclimate scale. Therefore, environmental design, which integrates science and aesthetics, requires fundamental research on landscape environment technology divided from building environment technology. By doing so, we can create mutual benefits between green building and the environment. This issue is extremely important for the greening design of the bases of green buildings in cities and various open spaces. The purpose of this study is to establish plant selection and allocation strategies under different building sunshade levels. Initially, with the shading of sunshine on the greening bases as the starting point, the effects of the shades produced by different building types on the greening strategies were analyzed. Then, by measuring the PAR (photosynthetic active radiation), the relative DLI (daily light integral) was calculated, while the DLI Map was established in order to evaluate the effects of the building shading on the established environmental greening, thereby serving as a reference for plant selection and allocation. The discussion results were to be applied in the evaluation of environment greening of greening buildings and establish the “right plant, right place” design strategy of multi-level ecological greening for application in urban design and landscape design development, as well as the greening criteria to feedback to the eco-city greening buildings.

Keywords: Daily light integral, plant design, urban open space.

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Authors: Mohammad H. Almomani, Rosmanjawati Abdul Rahman

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In this paper, we consider the effect of the initial sample size on the performance of a sequential approach that used in selecting a good enough simulated system, when the number of alternatives is very large. We implement a sequential approach on M=M=1 queuing system under some parameter settings, with a different choice of the initial sample sizes to explore the impacts on the performance of this approach. The results show that the choice of the initial sample size does affect the performance of our selection approach.

Keywords: Ranking and Selection, Ordinal Optimization, Optimal Computing Budget Allocation, Subset Selection, Indifference-Zone, Initial Sample Size.

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Authors: Mikulas Patocka

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This paper presents an architecture of current filesystem implementations as well as our new filesystem SpadFS and operating system Spad with rewritten VFS layer targeted at high performance I/O applications. The paper presents microbenchmarks and real-world benchmarks of different filesystems on the same kernel as well as benchmarks of the same filesystem on different kernels – enabling the reader to make conclusion how much is the performance of various tasks affected by operating system and how much by physical layout of data on disk. The paper describes our novel features–most notably continuous allocation of directories and cross-file readahead – and shows their impact on performance.

Keywords: Filesystem, operating system, VFS, performance, readahead

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Authors: Yao-Tien Wang, Hsiang-Fu Yu, Dung Chen Chiou

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In wireless and mobile communications, this progress provides opportunities for introducing new standards and improving existing services. Supporting multimedia traffic with wireless networks quality of service (QoS). In this paper, a grey-fuzzy controller for radio resource management (GF-RRM) is presented to maximize the number of the served calls and QoS provision in wireless networks. In a wireless network, the call arrival rate, the call duration and the communication overhead between the base stations and the control center are vague and uncertain. In this paper, we develop a method to predict the cell load and to solve the RRM problem based on the GF-RRM, and support the present facility has been built on the application-level of the wireless networks. The GF-RRM exhibits the better adaptability, fault-tolerant capability and performance than other algorithms. Through simulations, we evaluate the blocking rate, update overhead, and channel acquisition delay time of the proposed method. The results demonstrate our algorithm has the lower blocking rate, less updated overhead, and shorter channel acquisition delay.

Keywords: radio resource management, grey prediction, fuzzylogic control, wireless networks, quality of service.

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Authors: T. Teo, S. W. Lye, Y. F. Li, Z. Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that using a developed channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available brain computer interface (BCI) 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring, ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: Neurophysiology, monitoring, EEG, outliers, electroencephalography.

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

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Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: Computer vision, Siamese network, pose estimation, pose tracking.

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

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Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease.

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Authors: Dong-Woo Lim, Chang-Jae Chun, Hyung-Myung Kim

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We consider a two-way relay network where two sources exchange information. A relay helps the two sources exchange information using the decode-and-XOR-forward protocol. We investigate the power minimization problem with minimum rate constraints. The system needs two time slots and in each time slot the required rate pair should be achievable. The power consumption is minimized in each time slot and we obtained the closed form solution. The simulation results confirm that the proposed power allocation scheme consumes lower total power than the conventional schemes.

Keywords: Decode-and-XOR-forward, power minimization, two-way relay

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Authors: Neeraj Nehra, R. B. Patel, V. K. Bhat

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Use of the Internet and the World-Wide-Web (WWW) has become widespread in recent years and mobile agent technology has proliferated at an equally rapid rate. In this scenario load balancing becomes important for P2P systems. Beside P2P systems can be highly heterogeneous, i.e., they may consists of peers that range from old desktops to powerful servers connected to internet through high-bandwidth lines. There are various loads balancing policies came into picture. Primitive one is Message Passing Interface (MPI). Its wide availability and portability make it an attractive choice; however the communication requirements are sometimes inefficient when implementing the primitives provided by MPI. In this scenario we use the concept of mobile agent because Mobile agent (MA) based approach have the merits of high flexibility, efficiency, low network traffic, less communication latency as well as highly asynchronous. In this study we present decentralized load balancing scheme using mobile agent technology in which when a node is overloaded, task migrates to less utilized nodes so as to share the workload. However, the decision of which nodes receive migrating task is made in real-time by defining certain load balancing policies. These policies are executed on PMADE (A Platform for Mobile Agent Distribution and Execution) in decentralized manner using JuxtaNet and various load balancing metrics are discussed.

Keywords: Mobile Agents, Agent host, Agent Submitter, PMADE.

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Authors: Ramaswamy Palaniappan, Nai-Jen Huan

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Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method.

Keywords: Autoregressive, Brain-Computer Interface, Electroencephalogram, Neural Network.

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Authors: Sankalp Devanand, Prateek Agasimani, V. S. Shamith, Rohith Neeraje

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Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English to Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity etc.

Keywords: Machine translation, English to Sanskrit, natural language processing, word meaning retrieval, FastText embeddings.

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Authors: P. Prasanna Murali Krishna, M. V. Subramanyam, K. Satya Prasad

Abstract:

File sharing in networks is generally achieved using Peer-to-Peer (P2P) applications. Structured P2P approaches are widely used in adhoc networks due to its distributed and scalability features. Efficient mechanisms are required to handle the huge amount of data distributed to all peers. The intrinsic characteristics of P2P system makes for easier content distribution when compared to client-server architecture. All the nodes in a P2P network act as both client and server, thus, distributing data takes lesser time when compared to the client-server method. CHORD protocol is a resource routing based where nodes and data items are structured into a 1- dimensional ring. The structured lookup algorithm of Chord is advantageous for distributed P2P networking applications. However, structured approach improves lookup performance in a high bandwidth wired network it could contribute to unnecessary overhead in overlay networks leading to degradation of network performance. In this paper, the performance of existing CHORD protocol on Wireless Mesh Network (WMN) when nodes are static and dynamic is investigated.

Keywords: Wireless mesh network (WMN), structured P2P networks, peer to peer resource sharing, CHORD protocol, DHT.

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Authors: Elijah Acquah-Andoh

Abstract:

The UK has had its fair share of the shale gas revolutionary waves blowing across the global oil and gas industry at present. Although, its exploitation is widely agreed to have been delayed, shale gas was looked upon favorably by the UK Parliament when they recognized it as genuine energy source and granted licenses to industry to search and extract the resource. This, although a significant progress by industry, there yet remains another test the UK fracking resource must pass in order to render shale gas extraction feasible – it must be economically extractible and sustainably so. Developing unconventional resources is much more expensive and risky, and for shale gas wells, producing in commercial volumes is conditional upon drilling horizontal wells and hydraulic fracturing, techniques which increase CAPEX. Meanwhile, investment in shale gas development projects is sensitive to gas price and technical and geological risks. Using a Two-Factor Model, the economics of the Bowland shale wells were analyzed and the operational conditions under which fracking is profitable in the UK was characterized. We find that there is a great degree of flexibility about Opex spending; hence Opex does not pose much threat to the fracking industry in the UK. However, we discover Bowland shale gas wells fail to add value at gas price of $8/ Mmbtu. A minimum gas price of $12/Mmbtu at Opex of no more than $2/ Mcf and no more than $14.95M Capex are required to create value within the present petroleum tax regime, in the UK fracking industry.

Keywords: Capex, economical, investment, profitability, shale gas development, sustainable.

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Authors: Abdallah Al Sabbagh

Abstract:

Next Generation Wireless Network (NGWN) is expected to be a heterogeneous network which integrates all different Radio Access Technologies (RATs) through a common platform. A major challenge is how to allocate users to the most suitable RAT for them. An optimized solution can lead to maximize the efficient use of radio resources, achieve better performance for service providers and provide Quality of Service (QoS) with low costs to users. Currently, Radio Resource Management (RRM) is implemented efficiently for the RAT that it was developed. However, it is not suitable for a heterogeneous network. Common RRM (CRRM) was proposed to manage radio resource utilization in the heterogeneous network. This paper presents a user level Markov model for a three co-located RAT networks. The load-balancing based and service based CRRM algorithms have been studied using the presented Markov model. A comparison for the performance of load-balancing based and service based CRRM algorithms is studied in terms of traffic distribution, new call blocking probability, vertical handover (VHO) call dropping probability and throughput.

Keywords: Heterogeneous Wireless Network, Markov chain model, load-balancing based and service based algorithm, CRRM algorithms, Beyond 3G network.

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Authors: Sanghyeok Oh, Yunli Lee, Kwangjin Hong, Kirak Kim, Keechul Jung

Abstract:

This paper proposes view-point insensitive human pose recognition system using neural network. Recognition system consists of silhouette image capturing module, data driven database, and neural network. The advantages of our system are first, it is possible to capture multiple view-point silhouette images of 3D human model automatically. This automatic capture module is helpful to reduce time consuming task of database construction. Second, we develop huge feature database to offer view-point insensitivity at pose recognition. Third, we use neural network to recognize human pose from multiple-view because every pose from each model have similar feature patterns, even though each model has different appearance and view-point. To construct database, we need to create 3D human model using 3D manipulate tools. Contour shape is used to convert silhouette image to feature vector of 12 degree. This extraction task is processed semi-automatically, which benefits in that capturing images and converting to silhouette images from the real capturing environment is needless. We demonstrate the effectiveness of our approach with experiments on virtual environment.

Keywords: Computer vision, neural network, pose recognition, view-point insensitive.

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