Search results for: test data

Authors: A. V. Goncharova, T. A. Karpenyuk, Y. S. Tsurkan, R. U. Beisembaeva, A. M. Kalbaeva, T. D. Mukasheva, L. V. Ignatova

Abstract:

Microorganisms isolated from water and soil of Kazakhstan to identify potential high-effective producers of the arachidonic acid, exhibiting a wide range of physiological activity and having practical applications were screened. Based on the results of two independent tests (the test on the sensitivity of the growth processes of microorganisms to acetylsalicylic acid - an irreversible inhibitor of PGH-synthase involved in the metabolism of arachidonic acid and its derivatives, the test for inhibition of peroxidase activity of membrane-bounding fraction of PGH - synthase by acetylsalicylic acid) were selected microbial cultures which are potential highproducer of arachidonic acid. They are characterized by a stable strong growth in the laboratory conditions. Identification of microorganism cultures based on morphological, physiological, biochemical and molecular genetic characteristics was performed.

Keywords: Arachidonic acid, aspirin-sensitive culture, bacteria, producers, screening.

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Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah

Abstract:

Personalized learning becomes increasingly popular which not be restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability.The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT,it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores.Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.

Keywords: Analysis, Cognitive Load Theory, Item Response Theory, Learning, Motivation, Performance.

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Authors: Seo Young Kim, Tai Myong Choi

Abstract:

The main goal of microarray experiments is to quantify the expression of every object on a slide as precisely as possible, with a further goal of clustering the objects. Recently, many studies have discussed clustering issues involving similar patterns of gene expression. This paper presents an application of fuzzy-type methods for clustering DNA microarray data that can be applied to typical comparisons. Clustering and analyses were performed on microarray and simulated data. The results show that fuzzy-possibility c-means clustering substantially improves the findings obtained by others.

Keywords: Clustering, microarray data, Fuzzy-type clustering, Validation

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Authors: Ali Khajeh Samani, Mario M. Attard

Abstract:

Lateral expansion is a factor defining the level of confinement in reinforced concrete columns. Therefore, predicting the lateral strain relationship with axial strain becomes an important issue. Measuring lateral strains in experiments is difficult and only few report experimental lateral strains. Among the existing analytical formulations, two recent models are compared with available test results in this paper with shortcomings highlighted. A new analytical model is proposed here for lateral strain axial strain relationship and is based on the supposition that the concrete behaves linear elastic in the early stages of loading and then nonlinear hardening up to the peak stress and then volumetric expansion. The proposal for the lateral strain axial strain relationship after the peak stress is mainly based on the hypothesis that the plastic lateral strain varies linearly with the plastic axial strain and it is shown that this is related to the lateral confinement level.

Keywords: Confined Concrete, Lateral Strain, Triaxial test, Postpeak behavior

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Authors: Carolina Senabre, Sergio Valero, Emilio Velasco

Abstract:

The brake systems of vehicles are tested periodically by a “brake tester” at Ministry of Transport (MOT) stations. This tester measures the effectiveness of vehicle. This parameter is established by the International Committee of Vehicle Inspection (CITA). In this paper, we present an investigation of the influence of the tire size on the measurements of brake force on three MOT brake testers. We performed an analysis of the vehicle braking capacity test at MOT stations. The influence of varying wheel diameter and width on the measurement of braking at MOT stations has been analyzed. Thereby, the MOT brake tester as a verification system for a vehicle has been evaluated.

Keywords: Brake tester, wheel diameter, Ministry of transport facilities.

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Authors: Wararit Panichkitkosolkul

Abstract:

The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: Autoregressive, Ordinary least squares, Type I error, Power of the test, Monte Carlo simulation.

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

Abstract:

This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

Abstract:

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: Data grids, fault tolerance, chandy-lamport, clustering.

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Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mohamad Teshnelab, Ehsan Shahamatnia

Abstract:

The anti-lock braking systems installed on vehicles for safe and effective braking, are high-order nonlinear and timevariant. Using fuzzy logic controllers increase efficiency of such systems, but impose a high computational complexity as well. The main concept introduced by this paper is reducing computational complexity of fuzzy controllers by deploying problem-solution data structure. Unlike conventional methods that are based on calculations, this approach is based on data oriented modeling.

Keywords: ABS, Fuzzy controller, PSDS, Time-Memory tradeoff, Data oriented modeling.

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Authors: Blaise Fyama, Elie Museng, Grace Mukoma

Abstract:

In this article we present a java implementation of video telephony using the SIP protocol (Session Initiation Protocol). After a functional analysis of the SIP protocol, we relied on the work of Italian researchers of University of Parma-Italy to acquire adequate libraries for the development of our own communication tool. In order to optimize the code and improve the prototype, we used, in an incremental approach, test techniques based on a static analysis based on the evaluation of the complexity of the software with the application of metrics and the number cyclomatic of Mccabe. The objective is to promote the emergence of local start-ups producing IP video in a well understood local context. We have arrived at the creation of a video telephony tool whose code is optimized.

Keywords: Static analysis, coding, complexity, mccabe metrics, Sip, uml.

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, these projects propose AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project present the best-in-school techniques used to preserve data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptography techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures, and identifies potential correction/mitigation measures.

Keywords: Data privacy, artificial intelligence, healthcare AI, data sharing, healthcare organizations.

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Authors: Quratulain N. Rajput, Sajjad Haider

Abstract:

This paper applies Bayesian Networks to support information extraction from unstructured, ungrammatical, and incoherent data sources for semantic annotation. A tool has been developed that combines ontologies, machine learning, and information extraction and probabilistic reasoning techniques to support the extraction process. Data acquisition is performed with the aid of knowledge specified in the form of ontology. Due to the variable size of information available on different data sources, it is often the case that the extracted data contains missing values for certain variables of interest. It is desirable in such situations to predict the missing values. The methodology, presented in this paper, first learns a Bayesian network from the training data and then uses it to predict missing data and to resolve conflicts. Experiments have been conducted to analyze the performance of the presented methodology. The results look promising as the methodology achieves high degree of precision and recall for information extraction and reasonably good accuracy for predicting missing values.

Keywords: Information Extraction, Bayesian Network, ontology, Machine Learning

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Authors: Awni H. Alkhazaleh, Baljinder K. Kandola

Abstract:

In this study, a form-stable composite Paraffin/Nanoclay (PA-NC) has been prepared by absorbing PA into porous particles of NC to be used for low-temperature latent heat thermal energy storage. The leakage test shows that the maximum mass fraction of PA that can be incorporated in NC without leakage is 60 wt.%. Differential scanning calorimetry (DSC) has been used to measure the thermal properties of the PA and PA-NC both before and after incorporation in plasterboard (PL). The mechanical performance of the samples has been evaluated in flexural mode. The thermal energy storage performance has been studied using a small test chamber (100 mm × 100 mm × 100 mm) made from 10 mm thick PL and measuring the temperatures using thermocouples. The flammability of the PL+PL-NC has been discussed using a cone calorimeter. The results indicate that the form composite PA has good potential for use as thermal energy storage materials in building applications.

Keywords: Flammability, paraffin, plasterboard, thermal energy storage.

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Authors: S. Mohammadzadehmoghadam, Y. Dong

Abstract:

In this study, Bombyx mori silk fibroin/gelatin (SF/GT) nanocomposite with different GT ratio (SF/GT 100/0, 90/10 and 70/30) were prepared by electrospinning process and crosslinked with glutaraldehyde (GA) vapor. Properties of crosslinked SF/GT nanocomposites were investigated by scanning electron microscopy (SEM), mechanical test, water uptake capacity (WUC) and porosity. From SEM images, it was found that fiber diameter increased as GT content increased. The results of mechanical test indicated that the SF/GT 70/30 nanocomposites had both the highest Young’s modulus of 342 MPa and the highest tensile strength of about 14 MPa. However, porosity and WUC decreased from 62% and 405% for pristine SF to 47% and 232% for SF/GT 70/30, respectively. This behavior can be related to higher degree of crosslinking as GT ratio increased which altered the structure and physical properties of scaffolds. This study showed that incorporation of GT into SF nanofibers can enhance mechanical properties of resultant nanocomposite, but the GA treatment should be optimized to control and fine-tune other properties to warrant their biomedical application.

Keywords: Electrospinning, gelatin, mechanical properties, nanocomposites, silk fibroin.

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Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung, Jae-Cheol Ryou

Abstract:

Cell phone forensics to acquire and analyze data in the cellular phone is nowadays being used in a national investigation organization and a private company. In order to collect cellular phone flash memory data, we have two methods. Firstly, it is a logical method which acquires files and directories from the file system of the cell phone flash memory. Secondly, we can get all data from bit-by-bit copy of entire physical memory using a low level access method. In this paper, we describe a forensic tool to acquire cell phone flash memory data using a logical level approach. By our tool, we can get EFS file system and peek memory data with an arbitrary region from Korea CDMA cell phone.

Keywords: Forensics, logical method, acquisition, cell phone, flash memory.

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

Abstract:

Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: Roberto Sabatini, Terry Moore, Chris Hill

Abstract:

This paper presents a novel Global Navigation Satellite System (GNSS) Avionics Based Integrity Augmentation (ABIA) system architecture suitable for civil and military air platforms, including Unmanned Aircraft Systems (UAS). Taking the move from previous research on high-accuracy Differential GNSS (DGNSS) systems design, integration and experimental flight test activities conducted at the Italian Air Force Flight Test Centre (CSV-RSV), our research focused on the development of a novel approach to the problem of GNSS ABIA for mission- and safety-critical air vehicle applications and for multi-sensor avionics architectures based on GNSS. Detailed mathematical models were developed to describe the main causes of GNSS signal outages and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system is able to generate integrity cautions (predictive flags) and warnings (reactive flags), as well as providing steering information to the pilot and electronic commands to the aircraft/UAS flight control systems. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In other words, this novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).

Keywords: Global Navigation Satellite Systems (GNSS), Integrity Augmentation, Unmanned Aircraft Systems, Aircraft Based Augmentation, Avionics Based Integrity Augmentation, Safety-Critical Applications.

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Authors: Mohamed Hanine, Abdesadik Bendarag, Omar Boutkhoum

Abstract:

Currently, the field of data migration is very topical. As the number of applications developed rapidly, the ever-increasing volume of data collected has driven the architectural migration from Relational Database Management System (RDBMS) to NoSQL (Not Only SQL) database. This very recent technology is important enough in the field of database management. The main aim of this paper is to present a methodology for data migration from RDBMS to NoSQL database. To illustrate this methodology, we implement a software prototype using MySQL as a RDBMS and MongoDB as a NoSQL database. Although this is a hard engineering work, our results show that the proposed methodology can successfully accomplish the goal of this study.

Keywords: Data Migration, MySQL, RDBMS, NoSQL, MongoDB.

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Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

Abstract:

An analytical 4-DOF nonlinear model of a de Laval rotor-stator system based on Energy Principles has been used theoretically and experimentally to investigate fault symptoms in a rotating system. The faults, namely rotor-stator-rub, crack and unbalance are modeled as excitations on the rotor shaft. Mayes steering function is used to simulate the breathing behaviour of the crack. The fault analysis technique is based on waveform signal, orbits and Fast Fourier Transform (FFT) derived from simulated and real measured signals. Simulated and experimental results manifest considerable mutual resemblance of elliptic-shaped orbits and FFT for a same range of test data.

Keywords: A breathing crack, fault, FFT, nonlinear, orbit, rotorstator rub, vibration analysis.

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Authors: Erik Vassøy Olsen, Hirpa G. Lemu

Abstract:

Inspired by the Formula-1 competition, IMechE (Institute of Mechanical Engineers) and Formula SAE (Society of Mechanical Engineers) organize annual competitions for University and College students worldwide to compete with a single-seat racecar they have designed and built. Design of the chassis or the frame is a key component of the competition because the weight and stiffness properties are directly related with the performance of the car and the safety of the driver. In addition, a reduced weight of the chassis has direct influence on the design of other components in the car. Among others, it improves the power to weight ratio and the aerodynamic performance. As the power output of the engine or the battery installed in the car is limited to 80 kW, increasing the power to weight ratio demands reduction of the weight of the chassis, which represents the major part of the weight of the car. In order to reduce the weight of the car, ION Racing team from University of Stavanger, Norway, opted for a monocoque design. To ensure fulfilment of the competition requirements of the chassis, the monocoque design should provide sufficient torsional stiffness and absorb the impact energy in case of possible collision. The study reported in this article is based on the requirements for Formula Student competition. As part of this study, diverse mechanical tests were conducted to determine the mechanical properties and performances of the monocoque design. Upon a comprehensive theoretical study of the mechanical properties of sandwich composite materials and the requirements of monocoque design in the competition rules, diverse tests were conducted including 3-point bending test, perimeter shear test and test for absorbed energy. The test panels were homemade and prepared with equivalent size of the side impact zone of the monocoque, i.e. 275 mm x 500 mm, so that the obtained results from the tests can be representative. Different layups of the test panels with identical core material and the same number of layers of carbon fibre were tested and compared. Influence of the core material thickness was also studied. Furthermore, analytical calculations and numerical analysis were conducted to check compliance to the stated rules for Structural Equivalency with steel grade SAE/AISI 1010. The test results were also compared with calculated results with respect to bending and torsional stiffness, energy absorption, buckling, etc. The obtained results demonstrate that the material composition and strength of the composite material selected for the monocoque design has equivalent structural properties as a welded frame and thus comply with the competition requirements. The developed analytical calculation algorithms and relations will be useful for future monocoque designs with different lay-ups and compositions.

Keywords: Composite material, formula student, ion racing, monocoque design, structural equivalence.

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Authors: Anurag Sharma, Christian W. Omlin

Abstract:

Self-organizing map (SOM) is a well known data reduction technique used in data mining. It can reveal structure in data sets through data visualization that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOM, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of an adaptive heuristic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOM. The application of our method to several standard data sets demonstrates its feasibility. PSO algorithm utilizes a so-called U-matrix of SOM to determine cluster boundaries; the results of this novel automatic method compare very favorably to boundary detection through traditional algorithms namely k-means and hierarchical based approach which are normally used to interpret the output of SOM.

Keywords: cluster boundaries, clustering, code vectors, data mining, particle swarm optimization, self-organizing maps, U-matrix.

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Authors: H. Eshraghi., L. Salehi.

Abstract:

The purpose of this study was to survey the effect of organizational communication system on the conflict in physical education offices of Isfahan province. The research methodology of this research was a descriptive study. All employees working in physical education offices of Isfahan province were included in the sample for this study (N= 236). Researcher made questionnaire and demographic questionnaire were used as investigation instruments. Based on the result of chi square test, there is significant difference between organizational communication system and interpersonal conflict. The most of participants evaluate communication in an informal way and pointed out that the communication channels were not open. Based on the result of binomial test, interpersonal conflict exists in physical education offices of Isfahan.

Keywords: Communication, Employees, Interpersonal conflict.

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Authors: Wen-Chi Hou, Cheng Luo, Zhewei Jiang, Feng Yan

Abstract:

In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells- values. The cosine transform is known to have a good energy compaction property and thus can approximate data distribution functions easily with small number of coefficients. The derived estimator is accurate and easy to update. We perform experiments to compare its performance with a well-known technique - the (Haar) wavelet. The experimental results show that the cosine transform performs much better than the wavelet in estimation accuracy, speed, space efficiency, and update easiness.

Keywords: DCT, Data Cube

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Authors: Vahid Zeighami, Mohsen Ghasemi, Reza Akbari

Abstract:

In this work, a Multi-Level Artificial Bee Colony (called MLABC) for optimizing numerical test functions is presented. In MLABC, two species are used. The first species employs n colonies where each of them optimizes the complete solution vector. The cooperation between these colonies is carried out by exchanging information through a leader colony, which contains a set of elite bees. The second species uses a cooperative approach in which the complete solution vector is divided to k sub-vectors, and each of these sub-vectors is optimized by a colony. The cooperation between these colonies is carried out by compiling sub-vectors into the complete solution vector. Finally, the cooperation between two species is obtained by exchanging information. The proposed algorithm is tested on a set of well-known test functions. The results show that MLABC algorithm provides efficiency and robustness to solve numerical functions.

Keywords: Artificial bee colony, cooperative artificial bee colony, multilevel cooperation.

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Authors: L. R. Ferreira, R. Biscaro, C. C. Danziger, C. M. Galhardi, L. C. Biscaro, R. C. Biscaro, I. S. Vasconcelos, L. C. R. Ferreira, R. Reis, L. H. Oliveira

Abstract:

Introduction: There is a worldwide trend for the employer to be aware of investing in health promotion that goes beyond occupational hygiene approaches with the implementation of a comprehensive program with integration between occupational health and safety, and social/psychosocial responsibility in the workplace. Work accommodation is a necessity in most companies as it allows the worker to return to its function respecting its physical limitations. This study had the objective to verify if the integration of health and safety in the companies, with the inclusion of the concept of TWH promoted by an occupational health service has impacted in the management of absenteeism of workers in work accommodation. Method: A retrospective and paired cohort study was used, in which the impact of the implementation of the Program for the Health/Safety Integration and Total Worker Health Concept (PHSITWHC) was evaluated using the indices of absenteeism, health attestations, days and hours of sick leave of workers that underwent job accommodation/rehabilitation. This was a cohort study and the data were collected from January to September of 2017, prior to the initiation of the integration program, and compared with the data obtained from January to September of 2018, after the implementation of the program. For the statistical analysis, the student's t-test was used, with statistically significant differences being made at p < 0.05. Results: The results showed a 35% reduction in the number of absenteeism rate in 2018 compared to the same period in 2017. There was also a significant reduction in the total numbers of days of attestations/absences (mean of 2,8) as well as days of attestations, absence and sick leaves (mean of 5,2) in 2018 data after the implementation of PHSITWHC compared to 2017 data, means of 4,3 and 25,1, respectively, prior to the program. Conclusion: It can be concluded that the inclusion of the PHSITWHC was associated with a reduction in the rate of absenteeism of workers that underwent job accommodation. It was observed that, once health and safety were approached and integrated with the inclusion of the TWH concept, it was possible to reduce absenteeism, and improve worker’s quality of life and wellness, and work accommodation management.

Keywords: Absenteeism, health/safety integration, work accommodation management, total worker health.

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Authors: Alfred Chen, Shr Yu Lu, Cong Seng Hong, Yur-June Wang

Abstract:

This research attempts to study the feasibility of augmenting an augmented reality (AR) image card on a Quick Response (QR) code. The authors have developed a new visual tag, which contains a QR code and an augmented AR image card. The new visual tag has features of reading both of the revealed data of the QR code and the instant data from the AR image card. Furthermore, a handheld communicating device is used to read and decode the new visual tag, and then the concealed data of the new visual tag can be revealed and read through its visual display. In general, the QR code is designed to store the corresponding data or, as a key, to access the corresponding data from the server through internet. Those reveled data from the QR code are represented in text. Normally, the AR image card is designed to store the corresponding data in 3-Dimensional or animation/video forms. By using QR code's property of high fault tolerant rate, the new visual tag can access those two different types of data by using a handheld communicating device. The new visual tag has an advantage of carrying much more data than independent QR code or AR image card. The major findings of this research are: 1) the most efficient area for the designed augmented AR card augmenting on the QR code is 9% coverage area out of the total new visual tag-s area, and 2) the best location for the augmented AR image card augmenting on the QR code is located in the bottom-right corner of the new visual tag.

Keywords: Augmented reality, QR code, Visual tag, Handheldcommunicating device

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Authors: Yih-Chuan Lin, Jung-Hong Li

Abstract:

In this paper, we propose a reversible watermarking scheme based on histogram shifting (HS) to embed watermark bits into the H.264/AVC standard videos by modifying the last nonzero level in the context adaptive variable length coding (CAVLC) domain. The proposed method collects all of the last nonzero coefficients (or called last level coefficient) of 4×4 sub-macro blocks in a macro block and utilizes predictions for the current last level from the neighbor block-s last levels to embed watermark bits. The feature of the proposed method is low computational and has the ability of reversible recovery. The experimental results have demonstrated that our proposed scheme has acceptable degradation on video quality and output bit-rate for most test videos.

Keywords: Reversible data hiding, H.264/AVC standard, CAVLC, Histogram shifting

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Authors: Ahmed Amin Mousa, Mona Yacoub

Abstract:

This study depends on tracking children style through what they have drawn after being introduced to 16 visual content through National Geographic Abu Dhabi Channel programs and the study of the changing features in their drawings before applying the visual act with them. The researchers used Goodenough-Harris Test to analyse children drawings and to extract the features which changed in their drawing before and after the visual content. The results showed a positive change especially in the shapes of animals and their properties. Children become more aware of animals’ shapes. The study sample was 220 kindergarten children divided into 130 girls and 90 boys at the Orman Experimental Language School in Dokki, Giza, Egypt. The study results showed an improvement in children drawing with 85% than they were before watching videos.

Keywords: National Geographic, children drawing, kindergarten, Goodenough-Harris Test.

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Authors: Samee Ullah Khan, C. Ardil

Abstract:

In this paper, a mathematical model for data object replication in ad hoc networks is formulated. The derived model is general, flexible and adaptable to cater for various applications in ad hoc networks. We propose a game theoretical technique in which players (mobile hosts) continuously compete in a non-cooperative environment to improve data accessibility by replicating data objects. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity, and communication costs. The proposed technique is extensively evaluated against four well-known ad hoc network replica allocation methods. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution quality

Keywords: Data replication, auctions, static allocation.

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Authors: Pavel Y. Tabakov, Kevin Duffy

Abstract:

The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Keywords: Classification, clustering, data minig, genetic algorithms.

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