Search results for: common law legal system

Authors: Gayathri Vijayakumar, Preethi Baskaran

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The effluents that are let down by the industries mix with the water bodies and drastically affect the aquatic life, which leads to pollution and bio magnifications. Effluents mostly contain chemicals, heavy metals etc., and cause toxicity to the environment. The pharmaceutical industries too contribute. The by-products and other unwanted waste are discharged without any treatment; these causes DNA damage and affect behavior of aquatic life. The study was conducted on koi carp (Cyprinus carpio) the ornamental variety of common carp. A two week long study was conducted on them using common anti-depressant drug (Diazepam) in various concentrations. These drugs are known to cause behavioral damage and organ malfunctions (muscle twitch). The histopathological study conducted showed permanent muscle twitching and lesions in the fish samples studied. The sociability was also affected in the span of 14 days. Higher concentrations of this drug showed severe damage in the muscle structures. Thus, this drug can cause adverse effects on marine ecosystem and eventually cause bio magnification of drug by running through the food chain.

Keywords: pollution, toxicity, bio-magnifications, koi carp, muscle twitch, diazepam, histopathology

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Imaneh Abbasi, Ladan Fata, Majid Sadeghi, Sara Banihashemi, Abolfazl Mohammadee

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Background: Dimensional and transdiagnostic approaches as a result of high comorbidity among mental disorders have captured researchers and clinicians interests for exploring the latent factors of development and maintenance of some psychological disorders. The goal of present study is to compare some of these common factors between generalized anxiety disorder and unipolar mood disorder. Methods: 27 patients with generalized anxiety disorder, 29 patients with depression disorder were recruited using SCID-I and 69 non-clinical population were selected using GHQ cut off point. MANCOVA was used for analyzing data. Results: The results show that worry, rumination, intolerance of uncertainty, maladaptive metacognitive beliefs, and experiential avoidance were all significantly different between GAD and unipolar mood disorder groups. However, there were not any significant differences in difficulties in emotion regulation and neuroticism between GAD and unipolar mood disorder groups. Discussion: Results indicate that although there are some transdiagnostic and common factors in GAD and unipolar mood disorder, there may be some specific vulnerability factors for each disorder. Further study is needed for answering these questions.

Keywords: transdiagnostic, depression, generalized anxiety disorder, emotion regulation

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Mohd Tariq

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The three phase system drives produce the problem of more torque pulsations and harmonics. This issue prevents the smooth operation of the drives and it also induces the amount of heat generated thus resulting in an increase in power loss. Higher phase system offers smooth operation of the machines with greater power capacity. Five phase variable-speed induction motor drives are commonly used in various industrial and commercial applications like tractions, electrical vehicles, ship propulsions and conveyor belt drive system. In this work, a comparative analysis of the different modulation schemes applied on the five-level five-phase Packed U Cell (PUC) inverter fed induction motor drives is presented. The performance of the inverter is greatly affected with the modulation schemes applied. The system is modeled, designed, and implemented in MATLAB^®/Simulink environment. Experimental validation is done for the prototype of single phase, whereas five phase experimental validation is proposed in the future works.

Keywords: Packed U-Cell (PUC) inverter, five-phase system, pulse width modulation (PWM), induction motor (IM)

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Authors: T. Aboumahboub, R. Brecha, H. B. Shrestha, U. F. Hutfilter, A. Geiges, W. Hare, M. Schaeffer, L. Welder, M. Gidden

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The proposed stringent mitigation targets require an immediate start for a drastic transformation of the whole energy system. The current Australian energy system is mainly centralized and fossil fuel-based in most states with coal and gas-fired plants dominating the total produced electricity over the recent past. On the other hand, the country is characterized by a huge, untapped renewable potential, where wind and solar energy could play a key role in the decarbonization of the Australia’s future energy system. However, integrating high shares of such variable renewable energy sources (VRES) challenges the power system considerably due to their temporal fluctuations and geographical dispersion. This raises the concerns about flexibility gap in the system to ensure the security of supply with increasing shares of such intermittent sources. One main flexibility dimension to facilitate system integration of high shares of VRES is to increase the cross-sectoral integration through coupling of electricity to other energy sectors alongside the decarbonization of the power sector and reinforcement of the transmission grid. This paper applies a multi-sectoral energy system optimization model for Australia. We investigate the cost-optimal configuration of a renewable-based Australian energy system and its transformation pathway in line with the ambitious range of proposed climate change mitigation targets. We particularly analyse the implications of linking the electricity and transport sectors in a prospective, highly renewable Australian energy system.

Keywords: decarbonization, energy system modelling, renewable energy, sector coupling

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Amalia Sholihati, Bambang Riyanto Trilaksono

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As an island nation, is a necessity for the Republic of Indonesia to have a capable military defense on land, sea or air that the development of military weapons such as rockets for air defense becomes very important. RKX rocket-200 is one of the guided missiles which are developed by consortium Indonesia and coordinated by LAPAN that serve to intercept the target. RKX-200 is designed to have the speed of Mach 0.5-0.9. RKX rocket-200 belongs to the category two-stage rocket that control is carried out on the second stage when the rocket has separated from the booster. The requirement for better performance to intercept missiles with higher maneuverability continues to push optimal guidance law development, which is derived from non-linear equations. This research focused on the design and implementation of a guidance system based OGL on the rocket RKX-200 while considering the limitation of rockets such as aerodynamic rocket and actuator. Guided missile control system has three main parts, namely, guidance system, navigation system and autopilot systems. As for other parts such as navigation systems and other supporting simulated on MATLAB based on the results of previous studies. In addition to using the MATLAB simulation also conducted testing with hardware-based ARM TWR-K60D100M conjunction with a navigation system and nonlinear models in MATLAB using Hardware-in-the-Loop Simulation (HILS).

Keywords: RKX-200, guidance system, optimal guidance law, Hils

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Authors: S. Sudhharani

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Energy distribution networks are the main link between the energy industry and consumers and are subject to the most scrutiny and testing of any category. As a result, it is important to monitor energy levels during the distribution phase. Power distribution networks, on the other hand, remain subject to common problems, including voltage breakdown, power outages, harmonics, and capacitor switching, all of which disrupt sinusoidal waveforms and reduce the quality and power of the network. Using power appliances in the form of custom power appliances is one way to deal with energy quality issues. Dynamic Voltage Restorer (DVR), integrated with network and distribution networks, is one of these devices. At the same time, by injecting voltage into the system, it can adjust the voltage amplitude and phase in the network. In the form of injections and three-phase syncing, it is used to compensate for the difficulty of energy quality. This article examines the recent use of DVR for power compensation and provides data on the control of each DVR in distribution networks.

Keywords: dynamic voltage restorer (DVR), power quality, distribution networks, control systems(PWM)

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Authors: Andres Frederic

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We present the MindFlow system supporting the detection and the diagnosis of stresses. The heart of the system is a knowledge synthesis engine allowing occupational health stakeholders (psychologists, occupational therapists and human resource managers) to formulate queries related to stress and responding to users requests by recommending a pattern of stress if one exists. The stress pattern diagnosis is based on expert knowledge stored in the MindFlow stress ontology including stress feature vector. The query processing may involve direct access to the MindFlow system by occupational health stakeholders, online communication between the MindFlow system and the MindFlow domain experts, or direct dialog between a occupational health stakeholder and a MindFlow domain expert. The MindFlow knowledge model is generic in the sense that it supports the needs of psychologists, occupational therapists and human resource managers. The system presented in this paper is currently under development as part of a Dutch-Japanese project and aims to assist organisation in the quick diagnosis of stress patterns.

Keywords: occupational stress, stress management, physiological measurement, accident prevention

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Authors: Zuhier Altawallbeh

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This paper investigates the approximate analytical solutions of general form of Volterra integro-differential equations system by using the residual power series method (for short RPSM). The proposed method produces the solutions in terms of convergent series requires no linearization or small perturbation and reproduces the exact solution when the solution is polynomial. Some examples are given to demonstrate the simplicity and efficiency of the proposed method. Comparisons with the Laplace decomposition algorithm verify that the new method is very effective and convenient for solving system of pantograph equations.

Keywords: integro-differential equation, pantograph equations, system of initial value problems, residual power series method

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Authors: Irina E. Sukovataya, Oleg S. Sutormin, Valentina A. Kratasyuk

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Effect of viscosity of media on kinetic parameters of the coupled enzyme system NADH:FMN-oxidoreductase–luciferase was investigated with addition of organic solvents (glycerol and sucrose), because bioluminescent enzyme systems based on bacterial luciferases offer a unique and general tool for analysis of the many analytes and enzymes in the environment, research, and clinical laboratories and other fields. The possibility of stabilization and increase of activity of the coupled enzyme system NADH:FMN-oxidoreductase–luciferase activity in vicious aqueous-organic mixtures have been shown.

Keywords: coupled enzyme system of bioluminescence bacteria NAD(P)H:FMN-oxidoreductase–luciferase, glycerol, stabilization of enzymes, sucrose

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Authors: Bindu I. Somarajan, Viney Gupta, Gagandeep Kaur Walia, Jasbir Kaur, Sunil Kumar, Shikha Gupta, Abadh K. Chaurasia, Dinesh Gupa, Abhinav Kaushik, Aditi Mehta, Vipin Gupta, Arundhati Sharma

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Background: Juvenile onset primary open angle glaucoma (JOAG), affects individuals under the age of 40 years. Studies on a few families of JOAG, that led to the discovery of the Myocilin gene, reported the disease to have an autosomal dominant pattern of inheritance. However, sporadic forms of JOAG been seen to be more common in some populations. Most pathological homozygous mutations in the CYP1B1 gene associated with JOAG have been seen among sporadic cases. Given the higher prevalence of sporadic JOAG cases in our population, we aimed to look for common mutations E229K and R368H, the two most common variants in the CYP1B1 gene associated with glaucoma. Objective: To determine the frequency and evaluate genotype phenotype correlation of CYP1B1 E229K and R368H mutations in a cohort of 120 sporadic Juvenile open angle glaucoma patients.Methods: Unrelated JOAG patients whose first degree relatives had been examined and found to be unaffected were included in the study. The patients and their parents were screened for E229K and R368H mutations. The phenotypic characteristics were compared between probands with and with out these mutations by SPSS v16. Results: Out of 120 JOAG patients included in the study, the E229K mutation was seen in 9 probands (7.5%) and R368H in 7 (5.8%). The average age of onset of the disease (p=0.3) and the highest untreated IOP (p=0.4) among those carrying mutations was not significantly different from those who did not have these mutations. The proportion of probands with angle dysgenesis among those with E229K and R368H mutations was 70% (11 out of 16) in comparison to 65% (67 out of 104) of those who did not harbour these mutations (p=0.56). Similarly the probands with moderate to high myopia among those with E229K and R368H mutations was 20% (3 out of 16) in comparison to 18% (18 out of 104) of those who did not harbour these mutations(p=0.59). Conclusion: The frequency of E229K and R368H mutations of the CYP1B1 gene is low even among sporadic JOAG patients. Moreover there is no clinical correlation between the presence of these mutations and disease severity

Keywords: CYP1B1, gene, IOP, JOAG, mutation

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Authors: Saman Javadi, Mohammad Hassan Mahmoudi, Fatemeh Jafari, Aminreza Neshat

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Urmia Lake’s water level has been dropped during the past decade. Although the most common reason in studies was declared climate change, but observation of adjacent lake (like Van in Turkey) is not the same as the common reason. Most of studies were focused on climate and land use change, but groundwater resource as one of the most important element is negligible. Due to population and agriculture activities growth, exploration of groundwater resource has been increased. In as much as continued decline of water levels can lead to saltwater intrusion, reduce stream discharge near outcrop regions and threaten groundwater quality, aquifers of this region were affected by saltwater intrusion of Urmia Lake. In this research comparison of saltwater intrusion into eastern and western coastal aquifer was studied. In conclusion eastern aquifers are in a critical situation; vice versa the western ones are in a better situation. Thus applying management of groundwater operation would be necessary for eastern aquifers.

Keywords: coastal aquifer, groundwater over-exploration, saltwater intrusion, Urmia Lake

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Authors: R. Kiran, B. R. Lakshmikantha, R. V. Parimala

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Secure operation of power systems requires monitoring of the system operating conditions. Phasor measurement units (PMU) are the device, which uses synchronized signals from the GPS satellites, and provide the phasors information of voltage and currents at a given substation. The optimal locations for the PMUs must be determined, in order to avoid redundant use of PMUs. The objective of this paper is to make system observable by using minimum number of PMUs & the implementation of stability software at 22OkV grid for on-line estimation of the power system transfer capability based on voltage and thermal limitations and for security monitoring. This software utilizes State Estimator (SE) and synchrophasor PMU data sets for determining the power system operational margin under normal and contingency conditions. This software improves security of transmission system by continuously monitoring operational margin expressed in MW or in bus voltage angles, and alarms the operator if the margin violates a pre-defined threshold.

Keywords: state estimator (SE), flexible ac transmission systems (FACTS), optimal location, phasor measurement units (PMU)

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Authors: Krishnan Manickavasagam, Manikandan Shanmugam

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Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

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Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

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Authors: Hongshan Guo

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Ground-source heat pumps provide stable and reliable heating and cooling when designed properly. The confounding effect of the borehole depth for a GSHP system, however, is rarely taken into account for any optimization: the determination of the borehole depth usually comes prior to the selection of corresponding system components and thereafter any optimization of the GSHP system. The depth of the borehole is important to any GSHP system because the shallower the borehole, the larger the fluctuation of temperature of the near-borehole soil temperature. This could lead to fluctuations of the coefficient of performance (COP) for the GSHP system in the long term when the heating/cooling demand is large. Yet the deeper the boreholes are drilled, the more the drilling cost and the operational expenses for the circulation. A controller that reads different building load profiles, optimizing for the smallest costs and temperature fluctuation at the borehole wall, eventually providing borehole depth as the output is developed. Due to the nature of the nonlinear dynamic nature of the GSHP system, it was found that between conventional optimal controller problem and model predictive control problem, the latter was found to be more feasible due to a possible history of both the trajectory during the iteration as well as the final output could be computed and compared against. Aside from a few scenarios of different weighting factors, the resulting system costs were verified with literature and reports and were found to be relatively accurate, while the temperature fluctuation at the borehole wall was also found to be within acceptable range. It was therefore determined that the MPC is adequate to optimize for the investment as well as the system performance for various outputs.

Keywords: geothermal borehole, MPC, dynamic modeling, simulation

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Authors: Eftychia Damaskou

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This article intends to place the question of the adequate approach for teaching multilingualism within the public education. Linguistic education, as it is defined by the Common European Framework of Reference for the Languages, is no longer the proficiency in one or two languages. It’s about the development of a linguistic repertoire, where all linguistic skills find their place. In fact, the linguistic theories that frame the development of plurilingual competence point out the affective and intercultural aspect of such a process, insisting on an awareness of linguistic diversification, rather than an acquisition of communicative competence in many languages. In this spirit, our article attempts to go beyond a mere plurilingual awareness, present a research based on an experience in class, within 115 pupils, aiming at the development of plurilingual competence in five unknown foreign languages. This experience was held through a teaching unit personally conceived and applied, and consisted of a series of 6 activities based on a cross-linguistic content approach. The data analysis proves to be very interesting, as it reveals the development of plurilingual competences, as well as positive attitudes towards less common languages by the majority of our sample.

Keywords: multilingual awareness, multilingual teaching material, plurilingual competence

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Authors: Monica M. Marcos

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In the framework of Archaeological Research, Heritage Conservation and Restoration, the object of study is metrology applied in composition of religious architecture in ancient Egypt, and usefulness in Archaology. The objective is the determination of the geometric and metrological relations in architectural models and the module used in the initial project of the buildings. The study and data collection of religious buildings, tombs and temples of the ancient Egypt, is completed with plans. The measurements systematization and buildings modulation makes possible to establish common compositional parameters, with a module determined by the measurement unit used. The measurement system corresponding to the main period of egyptian history, was the Egyptian royal cubit. The analysis of units measurements, used in architectural design, provides exact numbers on buildable spaces dimensions. It allows establishing proportional relationships between them, and finding a geometric composition module, on which the original project was based. This responds to a philosophical and functional concept of projected spaces. In the heritage rehabilitation and restoration field, knowledge of metrology helps in excavation, reconstruction and restoration of construction elements. The correct use of metrology contributes to the identification of possible work areas, helping to locate where the damaged or missing areas are. Also in restoration projects, metrology is useful for reordering and locating decontextualized parts of buildings. The conversion of measurements taken in the current International System to the ancient egyptian measurements, allows understand its conceptual purpose and its functionality, which makes easier to carry out archaeological intervention. In the work carried out in archaeological excavations, metrology is an essential tool for locating sites and establishing work zones.

Keywords: egyptology, metrology, archaeology, measurements, Egyptian cubit

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Authors: Sridhar Rapuru, D. Mallikarjunreddy, Rajanarendra Sai

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In this reign of the internet, the access of any multimedia file to the users at any time with a superior quality is needed. To achieve this goal, it is very important to have a good network without any interruptions between the satellites along with various earth stations. For that purpose, a high speed inter-satellite optical wireless communication system (IsOWC) is designed with space and polarization diversity techniques. IsOWC offers a high bandwidth, small size, less power requirement and affordable when compared with the present microwave satellite systems. To improve the efficiency and to reduce the propagation delay, inter-satellite link is established between the satellites. High accurate tracking systems are required to establish the reliable connection between the satellites as they have their own orbits. The only disadvantage of this IsOWC system is laser beam width is narrower than the RF because of this highly accurate tracking system to meet this requirement. The satellite uses the 'ephemerides data' for rough pointing and tracking system for fine pointing to the other satellite. In this proposed IsOWC system, laser light is used as a wireless connectedness between the source and destination and free space acts as the channel to carry the message. The proposed system will be designed, simulated and analyzed for 6000km with an improvement of data rate over previously existing systems. The performance parameters of the system are Q-factor, eye opening, bit error rate, etc., The proposed system for Inter-satellite Optical Wireless Communication System Design Using Diversity Techniques finds huge scope of applications in future generation communication purposes.

Keywords: inter-satellite optical wireless system, space and polarization diversity techniques, line of sight, bit error rate, Q-factor

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Authors: Tahany W. Sadak, Fouly, A. Anwer, M. Rizk

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The current investigation presents a study on the hydraulic performance of an electro-hydraulic servo solenoid valve controlled linear piston used in hydraulic systems. Advanced methods have been used to measure and record laboratory experiments, to ensure accurate analysis and evaluation. Experiments have been conducted under different values of temperature (28, 40 and 50 °C), supply pressure (10, 20, 30, 40 and 50 bar), system stiffness (32 N/mm), and load (0.0 & 5560 N). It is concluded that increasing temperature of hydraulic oil increases the quantity of flow rate, so it achieves an increase of the quantity of flow by 5.75 % up to 48.8 % depending on operating conditions. The values of pressure decay at low temperature are less than the values at high temperature. The frequency increases with the increase of the temperature. When we connect the springs to the system, it decreases system frequency. These results are very useful in the process of packing and manufacturing of fluid products, where the properties are not affected by 50 °C, so energy and time are saved.

Keywords: electro-hydraulic servo valve, fluid power control system, system stiffness, static and dynamic performance

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Authors: Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Widjojo Suprapto

Abstract:

Manufacturing companies in East Java develop their own ERP system or alter the ERP system which is developed by other companies to suit their needs. To make their own system, the companies mostly assign several employees from various departments to create a project team, and the employees are from the departments that are going to utilize the ERP system as the integrated data. The project team decides the making of the ERP system from the preparation stage until the going live implementation process. In designing the business process, the top management is working together with the project team until the project is accomplished. The completion of the ERP projects depends on the project to be undertaken itself, the strategy chosen to complete the project, the work method selection, the measurement system to monitor the project, the evaluation system of the project, and, in the end, the declaration of 'going live' of the ERP project. There is an increase in the business performance for the companies that have implemented the information technology or ERP as they manage to integrate all management functions within their companies. To investigate, some questionnaires are distributed to 100 manufacturing companies, and 90 questionnaires are returned; however, there are only 46 companies that develop their own ERP system, so the response rate is 46%. The result of data analysis using PLS shows that the management competency brings impacts to the project team and the process design. The process design is adjusted to the real process in order to implement the ERP, but it does not bring direct impacts to the business performance. The implementation of ERP brings positive impacts to the company business performance.

Keywords: management competency, project team, process design, ERP implementation, business performance

Procedia PDF Downloads 217

Authors: C. U. Om Kumar, S. Kishore, A. Geetha

Abstract:

An Operating system (OS) is software that manages computer hardware and software resources by providing services to computer programs. One of the important user expectations of the operating system is to provide the practice of defending information from unauthorized access, disclosure, modification, inspection, recording or destruction. Operating system is always vulnerable to the attacks of malwares such as computer virus, worm, Trojan horse, backdoors, ransomware, spyware, adware, scareware and more. And so the anti-virus software were created for ensuring security against the prominent computer viruses by applying a dictionary based approach. The anti-virus programs are not always guaranteed to provide security against the new viruses proliferating every day. To clarify this issue and to secure the computer system, our proposed expert system concentrates on authorizing the processes as wanted and unwanted by the administrator for execution. The Expert system maintains a database which consists of hash code of the processes which are to be allowed. These hash codes are generated using MD5 message-digest algorithm which is a widely used cryptographic hash function. The administrator approves the wanted processes that are to be executed in the client in a Local Area Network by implementing Client-Server architecture and only the processes that match with the processes in the database table will be executed by which many malicious processes are restricted from infecting the operating system. The add-on advantage of this proposed Expert system is that it limits CPU usage and minimizes resource utilization. Thus data and information security is ensured by our system along with increased performance of the operating system.

Keywords: virus, worm, Trojan horse, back doors, Ransomware, Spyware, Adware, Scareware, sticky software, process table, MD5, CPU usage and resource utilization

Procedia PDF Downloads 427

Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

Abstract:

The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

Procedia PDF Downloads 227

Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

Abstract:

Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

Procedia PDF Downloads 691

Authors: Cihan Cilbircioğlu

Abstract:

Allium sativum L.(garlic) and Allium. cepa L. (onion) are the most common species of the Allium spp. and are produced at the very high rate all over the world. The yield loss caused by pests is the most important problem in the production of these crops. In the absence of control measures, yield loss would be around 35% on average. The yield loss sometimes depending on the pest species and population density can reach about 100%. Mites and nematodes are the most important pests of them. These pests that cause damage to A. sativum and A. cepa shows a wide range of taxonomic categories. The number of common pest mite and nematode species that cause damage to either A. sativum and A. cepa are over 20 species. In this study, detailed information on morphology, life cycle, management, and symptoms of the economically most important harmful important mite (acari) and nematode species of onion and garlic has been provided through careful survey of corresponding researches in Turkey and given information about new practices and approaches on their controls.

Keywords: onion, garlic, pest, acari, nematoda control methods, Turkey

Procedia PDF Downloads 485

Authors: Mohammed Jamal Al-Mansor, Kok Beng Gan

Abstract:

This paper develops an optimized embedding of payload in medical image by using genetic optimization. The goal is to preserve region of interest from being distorted because of the watermark. By using this developed system there is no need of manual defining of region of interest through experts as the system will apply the genetic optimization to select the parts of image that can carry the watermark with guaranteeing less distortion. The experimental results assure that genetic based optimization is useful for performing steganography with less mean square error percentage.

Keywords: AES, DWT, genetic algorithm, watermarking

Procedia PDF Downloads 409

Authors: Anita Kushwaha

Abstract:

We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

Procedia PDF Downloads 272