Search results for: general data protection regulation

Authors: Petr Daniel Kovarik, Matt Kennedy, James Adams, Ajay Wilson, Andy Burns, Charles Kelly, Malcolm Jackson, Rahul Patil, Shahid Iqbal

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Introduction: Osteoradionecrosis (ORN) is a recognised toxicity of radiotherapy (RT) for head and neck cancer (HNC). Existing literature lacks any generally accepted definition and staging system for this toxicity. Objective: The objective is to analyse the outcome of the surgical and nonsurgical treatments of ORN. Material and Method: Data on 2303 patients treated for HNC with radical or adjuvant RT or RT-chemotherapy from January 2010 - December 2021 were retrospectively analysed. Median follow-up to the whole group of patients was 37 months (range 0–148 months). Results: ORN developed in 185 patients (8.1%). The location of ORN was as follows; mandible=170, maxilla=10, and extra oral cavity=5. Multiple ORNs developed in 7 patients. 5 patients with extra oral cavity ORN were excluded from treatment analysis as the management is different. In 180 patients with oral cavity ORN, median follow-up was 59 months (range 5–148 months). ORN healed in 106 patients, treatment failed in 74 patients (improving=10, stable=43, and deteriorating=21). Median healing time was 14 months (range 3-86 months). Notani staging is available in 158 patients with jaw ORN with no previous surgery to the mandible (Notani class I=56, Notani class II=27, and Notani class III=76). 28 ORN (mandible=27, maxilla=1; Notani class I=23, Notani II=3, Notani III=1) healed spontaneously with a median healing time 7 months (range 3–46 months). In 20 patients, ORN developed after dental extraction, in 1 patient in the neomandible after radical surgery as a part of the primary treatment. In 7 patients, ORN developed and spontaneously healed in irradiated bone with no previous surgical/dental intervention. Radical resection of the ORN (segmentectomy, hemi-mandibulectomy with fibula flap) was performed in 43 patients (all mandible; Notani II=1, Notani III=39, Notani class was not established in 3 patients as ORN developed in the neomandible). 27 patients healed (63%); 15 patients failed (improving=2, stable=5, deteriorating=8). The median time from resection to healing was 6 months (range 2–30 months). 109 patients (mandible=100, maxilla=9; Notani I=3, Notani II=23, Notani III=35, Notani class was not established in 9 patients as ORN developed in the maxilla/neomandible) were treated conservatively using a combination of debridement, antibiotics and Pentoclo. 50 patients healed (46%) with a median healing time 14 months (range 3–70 months), 59 patients are recorded with persistent ORN (improving=8, stable=38, deteriorating=13). Out of 109 patients treated conservatively, 13 patients were treated with Pentoclo only (all mandible; Notani I=6, Notani II=3, Notani III=3, 1 patient with neomandible). In total, 8 patients healed (61.5%), treatment failed in 5 patients (stable=4, deteriorating=1). Median healing time was 14 months (range 4–24 months). Extra orally (n=5), 3 cases of ORN were in the auditory canal and 2 in mastoid. ORN healed in one patient (auditory canal after 32 months. Treatment failed in 4 patients (improving=3, stable=1). Conclusion: The outcome of the treatment of ORN remains in general, poor. Every effort should therefore be made to minimise the risk of development of this devastating toxicity.

Keywords: head and neck cancer, radiotherapy, osteoradionecrosis, treatment outcome

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

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The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: M. S. Razana, Z. W. Shafiuddin

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Internal auditing is one of the most important activities for organizations that implement information security management systems (ISMS). The purpose of internal audits is to ensure the ISMS implementation is in accordance to the ISO/IEC 27001 standard and the organization’s own requirements for its ISMS. Competent internal auditors are the main element that contributes to the effectiveness of internal auditing activities. To realize this need, CyberSecurity Malaysia is now in the process of becoming a certification body that certifies ISMS internal auditors. The certification scheme will assess the competence of internal auditors in generic knowledge and skills in management systems, and also in ISMS-specific knowledge and skills. The certification assessment is based on the ISO/IEC 19011 Guidelines for auditing management systems, ISO/IEC 27007 Guidelines for information security management systems auditing and ISO/IEC 27001 Information security management systems requirements. The certification scheme complies with the ISO/IEC 17024 General requirements for bodies operating certification systems of persons. Candidates who pass the exam will be certified as an ISMS Internal Auditor, whose competency will be evaluated every three years.

Keywords: ISMS internal audit, ISMS internal auditor, ISO/IEC 17024, competence, certification

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Authors: H. Yousefnia, S. Zolghadri

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The measurement of organ radiation exposure dose is one of the most important steps to be taken initially, for developing a new radiopharmaceutical. In this study, the dosimetric studies of a novel agent for SPECT-imaging of the bone metastasis, 111In-1,4,7,10-tetraazacyclododecane-1,4,7,10 tetraethylene phosphonic acid (111In-DOTMP) complex, have been carried out to estimate the dose in human organs based on the data derived from rats. The radiolabeled complex was prepared with high radiochemical purity in the optimal conditions. Biodistribution studies of the complex was investigated in the male Syrian rats at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was made based on data derived from the rats by the radiation absorbed dose assessment resource (RADAR) method. 111In-DOTMP complex was prepared with high radiochemical purity of >99% (ITLC). Total body effective absorbed dose for 111In-DOTMP was 0.061 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose with respect to the critical organs is satisfactory within the acceptable range for diagnostic nuclear medicine procedures. Generally, 111In-DOTMP has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastasis in the near future.

Keywords: In-111, DOTMP, Internal Dosimetry, RADAR

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Authors: Xuling Zhang, Yong Wang, Xingyun Liu, Shuangxue Xu

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Based on positive psychology, this study presented a mediated moderation model in which character strengths moderated the relationship between interpersonal relationship, job satisfaction and subjective well-being, with job satisfaction taking the mediation role among them. A total of 912 teachers participated in four surveys, which include the Oxford Happiness Questionnaire, Values in Action Inventory of Strengths, job satisfaction questionnaire, and the interpersonal relationship questionnaire. The results indicated that: (1) Taking interpersonal relationship as a typical work environmental variable, the result shows that it is significantly correlated to subjective well-being. (2) The character strengths of "kindness", “authenticity” moderated the effect of the teachers’ interpersonal relationship on subjective well-being. (3) The teachers’ job satisfaction mediated the above mentioned moderation effects. In general, this study shows that the teachers’ interpersonal relationship affects their subjective well-being, with their job satisfaction as mediation and character strengths of “kindness” and “authenticity” as moderation. The managerial implications were also discussed.

Keywords: character strength, subjective well-being, job satisfaction, interpersonal relationship

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Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

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The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate one-dimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: seismic data, Gokpinar Damp, urban planning, Denizli

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Authors: Tahar Tayachi, Ahlam Alrehaili

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Purpose: The purpose of this paper is to investigate the relationship between the corporate board characteristics and the dividend policy among firms on the Saudi Stock Exchange. Design/Methodology/Approach: This paper uses a sample of 103 nonfinancial firms over a time period of 4 years from 2015 to 2018. To investigate how corporate governance mechanisms such as board independence, the board size, frequency of meetings, and free cash flow impact dividends, the study uses Logit and Tobit models. Findings: This paper finds that board size, board independence, and frequency of board meetings have no influence on a firm’s decision to pay dividends, while board size has a significantly positive impact on the levels of cash dividends paid to investors. This study also finds that the level of free cash flows has a positively significant influence on both the decision to pay dividends and the magnitude of dividend payouts. Research Limitations/Implications: This paper attempts to study the effectiveness of dividend policy among some firms on the Saudi Stock Exchange. Practical Implications: The findings reveal that board characteristics, which represent one of the crucial mechanisms of corporate governance, were found to be complementary to corporate laws and regulations imposed on the Saudi market in 2015. The findings also imply that capital market authorities should revise their corporate regulations and ensure that protection laws are adequate and strong enough to protect the interests of all shareholders. Originality/Value: This paper is among the few studies focusing on dividend policy in Saudi Arabia. Finally, these findings suggest that the improvements in corporate laws in Saudi Arabia led to such an outcome, and it has become prevalent in dividend policy decisions and behaviors of Saudi firms.

Keywords: agency theory, Tobit, corporate governance, dividend payout, Logit

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Authors: Nicholas P. Fenlon, Aisling Lavelle, David Mclean, Margaret O'riordan

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Background: The case for continuing professional development has been well made, and was formalized in Ireland in recent years through the enactment of the Medical Practitioner’s Act, which requires registered medical practitioners to complete a minimum of 50 hours CPD each year. The ICGP, who have been providing CPD opportunities to its members for many years, have responded to this need by developing a series of evidence-based, high-quality, multimedia modules across a range of clinical and non-clinical areas. (More traditional education opportunities are still being provided by the college also). Overview of Programme: The first module was released in September 2011, since when the eLearning program has grown steadily, and there are currently almost 20 modules available, with a further 5 in production. Each module contains three to six 10-minute video lessons, which use a combination of graphics, images, text, voice-over and clinical clips. These are supported by supplementary videos of expert pieces-to-camera, Q&As with content experts, clinical scenarios, external links and relevant documentation and other resources. Successful completion of MCQs will result in a Certificate of Completion, which can be printed or stored in Professional Competence portfolio. The Medical Practitioner’s Act requires doctors to gather CPD credits across 8 domains of practice, and various eLearning modules have been developed to address each. For instance, modules with a strong clinical content would include Management of Hypertension, Management of COPD, and Management of Asthma. Other modules focus on health promotion such as Promoting Smoking Cessation, Promoting Physical Activity, and Addressing Childhood Obesity. Modules where communication skills are keys include modules on Suicide Prevention and Management of Depression. Other modules, currently in development include non-clinical topics around risk management, including Confidentiality, Consent etc. Each module is developed by a core group, which includes where possible, a GP with a special interest in the area, and a content expert(s). The college works closely with a medical education consultant and a production company in developing and producing the modules. Modules can be accessed (with password) through the ICGP website and are available free to all ICGP members. Summary of Evaluation: There are over 1700 registered users to date (over 55% of College membership). The program was evaluated using an online survey in 2013 (N = 144/950 – 12%) and results were very positive overall but provided material for the further improvement of the program also. Future Plans: While knowledge can be imparted well through eLearning, skills and attitudes are more difficult to influence through an online environment. The college is now developing a series of linked workshops, which will lead to ICGP Professional Competence Awards. The first pilot workshop is scheduled for February 2015 and is Cardiology-themed. Participants will be required to complete the following 4 modules in advance of attending – Management of Hypertension, Management of Heart Failure, Promoting Smoking Cessation, and Promoting Physical Activity. The workshop will be case-based and interactive, addressing ECG Interpretation in General Practice. Conclusions: The ICGP have responded to members needs for high-quality evidence-based education delivered in a way that suits GPs.

Keywords: CPD opportunities, evidence-based, high quality, multimedia modules across a range of clinical and non-clinical areas, medical practitioner’s act

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Authors: Jingwei Du

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The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel

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In this study, a modification of Hennepe model for pervaporation separation of butanol from aqueous solutions using Polydimethylsiloxane (PDMS) mixed matrix membranes has been introduced and validated by experimental data. The model was compared to the original Hennepe model and few other models which are applicable for membrane gas separation processes such as Maxwell, Lewis Nielson and Pal. Theoretical modifications for non-ideal interface morphology have been offered to predict the permeability in case of interface void, interface rigidification and pore-blockage. The model was in a good agreement with experimental data.

Keywords: butanol, PDMS, modeling, pervaporation, mixed matrix membranes

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Authors: A. Javadi, H. Asad Beygi

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In line with the increasing demand for high-quality and safe food products, the present study is intended to examine the crude extract and juice of the fruit of Cucumis melo var. dudaim on tenderization of meat. Cubic pieces were selected from the biceps fermoris muscle of a five year-old female water buffalo; then, they were cut two or three hours after the buffalo was slaughtered. The selected samples were superficially exposed to the resolution obtained from the powder of the extract of Cucumis melo var. dudaim. Distilled water as a control sample and the powder of fruit extract of the mentioned plant with 0.5, 1 and 1.5 percent concentrations were experimented in the study. These samples were kept for three time spans of 2 hours, 7 and 14 days. Then, some tests were conducted on the samples both before and after cooking them. In general, with regard to the results obtained from the experiments and the investigations of the impact of time and different concentrations on the tenderization of buffalo meat, it can be argued that the time span of 2 hours and the concentration of 1.5 % can be considered as the best time and concentration for obtaining the most desirable tenderness. Also, tenderness increased in the samples kept for 7 and 14 days; however, due to the extraordinary decomposition, the samples were rather doughy and pasty.

Keywords: meat, Cucumis melo var. dudaim, tenderization, water buffalo

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Authors: Aafaf El Jazouli, Ahmed Barakat, Rida Khellouk

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Mapping of soil degradation is derived from field observations, laboratory measurements, and remote sensing data, integrated quantitative methods to map the spatial characteristics of soil properties at different spatial and temporal scales to provide up-to-date information on the field. Since soil salinity, texture and organic matter play a vital role in assessing topsoil characteristics and soil quality, remote sensing can be considered an effective method for studying these properties. The main objective of this research is to asses soil degradation by combining remote sensing data and laboratory analysis. In order to achieve this goal, the required study of soil samples was taken at 50 locations in the upper basin of Oum Er Rbia in the Middle Atlas in Morocco. These samples were dried, sieved to 2 mm and analyzed in the laboratory. Landsat 8 OLI imagery was analyzed using physical or empirical methods to derive soil properties. In addition, remote sensing can serve as a supporting data source. Deterministic potential (Spline and Inverse Distance weighting) and probabilistic interpolation methods (ordinary kriging and universal kriging) were used to produce maps of each grain size class and soil properties using GIS software. As a result, a correlation was found between soil texture and soil organic matter content. This approach developed in ongoing research will improve the prospects for the use of remote sensing data for mapping soil degradation in arid and semi-arid environments.

Keywords: Soil degradation, GIS, interpolation methods (spline, IDW, kriging), Landsat 8 OLI, Oum Er Rbia high basin

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Authors: Ali Babajanzade, Hossein Bozorgian

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Cognitive load plays an important role in learning in general and L2 listening comprehension in particular. This study is an attempt to investigate the effect of metacognitive strategy intervention through dialogic interaction (MSIDI) on L2 listeners’ cognitive load. A mixed-method design with 50 participants of male and female Iranian lower-intermediate learners between 20 to 25 years of age was used. An experimental group (n=25) received weekly interventions based on metacognitive strategy intervention through dialogic interaction for ten sessions. The second group, which was control (n=25), had the same listening samples with the regular procedure without a metacognitive intervention program in each session. The study used three different instruments: a) a modified version of the cognitive load questionnaire, b) digit span tests, and c) focused group interviews to investigate listeners’ level of cognitive load throughout the process. Results testified not only improvements in listening comprehension in MSIDI but a radical shift of cognitive load rate within this group. In other words, listeners experienced a lower level of cognitive load in MSIDI in comparison with their peers in the control group.

Keywords: cognitive load theory, human mental functioning, metacognitive theory, listening comprehension, sociocultural theory

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Alok Madan, Arshad K. Hashmi

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The paper presents a plastic analysis procedure based on the energy balance concept for performance based seismic retrofit of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames with a ‘soft’ ground story using passive energy dissipation (PED) devices with the objective of achieving a target performance level of the retrofitted R/C frame for a given seismic hazard level at the building site. The proposed energy based plastic analysis procedure was employed for developing performance based design (PBD) formulations for PED devices for a simulated application in seismic retrofit of existing frame structures designed in compliance with the prevalent standard codes of practice. The PBD formulations developed for PED devices were implemented for simulated seismic retrofit of a representative code-compliant masonry infilled R/C frame with a ‘soft’ ground story using friction dampers as the PED device. Non-linear dynamic analyses of the retrofitted masonry infilled R/C frames is performed to investigate the efficacy and accuracy of the proposed energy based plastic analysis procedure in achieving the target performance level under design level earthquakes. Results of non-linear dynamic analyses demonstrate that the maximum inter-story drifts in the masonry infilled R/C frames with a ‘soft’ ground story that is retrofitted with the friction dampers designed using the proposed PBD formulations are controlled within the target drifts under near-field as well far-field earthquakes.

Keywords: energy methods, masonry infilled frame, near-field earthquakes, seismic protection, supplemental damping devices

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Authors: Amira Mabrouk

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This paper deals with the acceptability of urban toll in Tunisia. The price-based regulation, i.e. urban toll, is the outcome of a political process hampered by three-fold objectives: effectiveness, equity and social acceptability. This produces both economic interest groups and functions that are of incongruent preferences. The plausibility of this speculation goes hand in hand with the fact that these economic interest groups are also taxpayers who undeniably perceive urban toll as an additional charge. This wariness is coupled with an inquiry about the conditions of usage, the redistribution of the collected tax revenue and the idea of the leviathan state completes the picture. In a nutshell, if researches related to road congestion proliferate, no de facto legitimacy can be pleaded. Nonetheless, the theory on urban tolls engenders economists’ questioning of ways to reduce negative external effects linked to it. Only then does the urban toll appear to bear an answer to these issues. Undeniably, the urban toll suggests inherent conflicts due to the apparent no-payment principal of a public asset as well as to the social perception of the new measure as a mere additional charge. However, when the main concern is effectiveness is its broad sense and the social well-being, the main factors that determine the acceptability of such a tariff measure along with the type of incentives should be the object of a thorough, in-depth analysis. Before adopting this economic role, one has to recognize the factors that intervene in the acceptability of a congestion toll which brought about a copious number of articles and reports that lacked mostly solid theoretical content. It is noticeable that nowadays uncertainties float over the exact nature of the acceptability process. Accepting a congestion tariff could differ from one era to another, from one region to another and from one population to another, etc. Notably, this article, within a convenient time frame, attempts at bringing into focus a link between the social acceptability of the urban congestion toll and the value of time through a survey method barely employed in Tunisia, that of stated preference method. How can the urban toll, as a tax, be defined, justified and made acceptable? How can an equitable and effective tariff of congestion toll be reached? How can the costs of this urban toll be covered? In what way can we make the redistribution of the urban toll revenue visible and economically equitable? How can the redistribution of the revenue of urban toll compensate the disadvantaged while introducing such a tariff measure? This paper will offer answers to these research questions and it follows the line of contribution of JULES DUPUIT in 1844.

Keywords: congestion charge, social perception, acceptability, stated preferences

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Authors: Maximilian Winkens, Peter Nyhuis

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Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory

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Authors: Ferdi Afian, Inne Yuliawati

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Background: The change in causes of death from infectious diseases to non-communicable diseases also occurs in the aviation community in Indonesia. Non-communicable diseases are influenced by several internal risk factors, such as age, lifestyle changes and the presence of other diseases. These risk factors will increase the incidence of heart diseases resulting in the incapacity of Indonesian aviators which will disrupt flight safety. Method: The study was conducted by collecting secondary data. The retrieval of primary data was obtained from medical records at the Indonesian Aviation Health Center in 2016-2017. The subjects in this study were all cases of incapacity in Indonesian aviators medical conditions. Results: In this study, there were 15 cases of aviators in Indonesia who experienced incapacity of medical conditions related to heart and lung diseases in 2016-2017. Based on the secondary data contained in the flight medical records at the Aviation Health Center Aviation, it was found that several factors related to aviators incapacity causing its inability to carried out flight duties. Conclusion: Incapacity of Indonesian aviators medical conditions are most affected by the high value of Body Mass Index (86%) and less affected by high of Uric Acid in the blood (26%) and Hyperglycemia (26%).

Keywords: incapacity, aviators, flight, Indonesia

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Authors: Moustafa Ibrahim Moustafa

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The purpose of this study was to determine the immediate and long term effects of a multimodal program, with the addition of cervical sagittal curve restoration and forward head correction, on severity of dizziness, disability, frequency of dizziness, and severity of cervical pain. 72 patients with cervicogenic dizziness, definite hypolordotic cervical spine, and forward head posture were randomized to experimental or a control group. Both groups received the multimodal program, additionally, the study group received the Denneroll cervical traction. All outcome measures were measured at three intervals. The general linear model indicated a significant group × time effects in favor of experimental group on measures of anterior head translation (F=329.4 P < .0005), cervical lordosis (F=293.7 P < .0005), severity of dizziness (F=262.1 P < .0005), disability (F=248.9 P < .0005), frequency of dizziness (F=53.9 P < .0005), and severity of cervical pain (F=350.1 P < .0005). The addition of Dennroll cervical traction to a multimodal program can positively affect dizziness management outcomes.

Keywords: randomized controlled trial, traction, dizziness, cervical

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Authors: Muneera Abdul Haleem Bukhari, Maryam I. Alshirawi, Elsayed S. Elkhamisi

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This study aimed at understanding the relationship between psychological security and self-esteem among Adolescent with Mild Intellectual Disability, exploring the levels of psychological security and self-esteem, as well as determining the differences between genders in psychological security and self-esteem. The sample of the study contained (60) Adolescent with Mild Intellectual Disability, (34) males and (26) females who are enrolled in the Vocational and Social Rehabilitation Center and Hope Institute in the Kingdom of Bahrain. Their ages are between (15-23) years old. The Psychological Security Scale and self-Esteem Scale (prepared by James Battle) were used by the researcher. Results showed that levels of psychological security and self-esteem among Adolescents with Mild Intellectual Disability was above average; results also showed the order of the psychological security dimensions in the following manner (future outlook – mood - family security – social security) and the order of the dimensions of self-esteem in the following manner (social self-esteem – personal self-esteem – general self-esteem) among Adolescent with Mild Intellectual Disability; as for the differences between genders, the study showed that there was an increased level of psychological security among males. However, there was no difference in self-esteem between both sexes.

Keywords: psychological security, self-esteem, adolescent, intellectual disability, the Kingdom of Bahrain

Procedia PDF Downloads 393

Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

Procedia PDF Downloads 468

Authors: Azadeh Yasari, Michael Ganzle, Stephen Strelkov, Nuanyi Liang, Jonathan Curtis, Nat N. V. Kav

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Pathogenic fungi cause significant yield losses and quality reductions to major crops including wheat, canola, and barley. Toxic metabolites produced by phytopathogenic fungi also pose significant risks to animal and human health. Extensive application of synthetic fungicides is not a sustainable solution since it poses risks to human, animal and environmental health. Unsaturated fatty acids may provide an environmentally friendly alternative because of their direct antifungal activity against phytopathogens as well as through the stimulation of plant defense pathways. The present study assessed the in vitro and in vivo efficacy of two hydroxy fatty acids, coriolic acid and ricinoleic acid, against the phytopathogens Fusarium graminearum, Pyrenophora tritici-repentis, Pyrenophora teres f. teres, Sclerotinia sclerotiorum, and Leptosphaeria maculans. Antifungal activity of coriolic acid and ricinoleic acid was evaluated using broth micro-dilution method to determine the minimum inhibitory concentration (MIC). Results indicated that both ricinoleic acid and coriolic acid showed antifungal activity against phytopathogens, with the strongest inhibitory activity against L. maculans, but the MIC varied greatly between species. An antifungal effect was observed for coriolic acid in vivo against pathogenic fungi of wheat and barley. This effect was not correlated to the in vitro activity because ricinoleic acid with equivalent in vitro antifungal activity showed no protective effect in vivo. Moreover, neither coriolic acid nor ricinoleic acid controlled fungal pathogens of canola. In conclusion, coriolic acid inhibits some phytopathogens in vivo and may have the potential to be an effective crop protection agent.

Keywords: coriolic acid, minimum inhibitory concentration, pathogenic fungi, ricinoleic acid

Procedia PDF Downloads 178

Authors: Alper Serdar Anli

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Analysis of temporal variation of reference evapotranspiration (ET0) is important in arid and semi-arid regions where water resources are limited. In this study, temporal variation of reference evapotranspiration (ET0) and meteorological drought analysis through SPEI (Standardized Precipitation Evapotranspiration Index) method have been carried out in provinces of Central Anatolia Region, Turkey. Reference evapotranspiration of concerning provinces in the region has been estimated using Penman-Monteith method and one calendar year has been split up four periods as r1, r2, r3 and r4. Temporal variation of reference evapotranspiration according to four periods has been analyzed through parametric Dickey-Fuller test and non-parametric Mann-Whitney U test. As a result, significant increasing trends for reference evapotranspiration have been detected and according to SPEI method used for estimating meteorological drought in provinces, mild drought has been experienced in general, and however there have been also a significant amount of events where moderate and severely droughts occurred.

Keywords: central Anatolia region, drought index, Penman-Monteith, reference evapotranspiration, temporal variation

Procedia PDF Downloads 312

Authors: Tanvi P. Patel, Warish D. Patel

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Association rule mining forms the core of data mining and it is termed as one of the well-known methodologies of data mining. Objectives of mining is to find interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories. Hence, association rule mining is imperative to mine patterns and then generate rules from these obtained patterns. For efficient targeted query processing, finding frequent patterns and itemset mining, there is an efficient way to generate an itemset tree structure named Memory Efficient Itemset Tree. Memory efficient IT is efficient for storing itemsets, but takes more time as compare to traditional IT. The proposed strategy generates maximal frequent itemsets from memory efficient itemset tree by using levelwise pruning. For that firstly pre-pruning of items based on minimum support count is carried out followed by itemset tree reconstruction. By having maximal frequent itemsets, less number of patterns are generated as well as tree size is also reduced as compared to MEIT. Therefore, an enhanced approach of memory efficient IT proposed here, helps to optimize main memory overhead as well as reduce processing time.

Keywords: association rule mining, itemset mining, itemset tree, meit, maximal frequent pattern

Procedia PDF Downloads 372

Authors: F. Lops, G. Disciglio, A. Carlucci, G. Gatta, L. Frabboni, A. Tarantino, E. Tarantino

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Phelipanche ramosa L. Pomel is a root holoparasitic weed plant of many cultivations, particularly of tomato (Lycopersicum esculentum L.) crop. In Italy, Phelipanche problem is increasing, both in density and in acreage. The biological control of this parasitic weed involves the use of living organisms as numerous fungi and bacteria that can infect the parasitic weed, while it may improve the crop growth. This paper deals with the biocontrol with microorganism, including Arbuscular mycorrhizal (AM) fungi and fungal pathogens as Fusarium oxisporum spp. Colonization of crop roots by AM fungi can provide protection of crops against parasitic weeds because of a reduction in their seed germination and attachment, while F. oxisporum, isolated from diseased broomrape tubercles, proved to be highly virulent on P. ramosa. The experimental trial was carried out in open field at Foggia province (Apulia Region, Southern Italy), during the spring-summer season 2016, in order to evaluate the effect of four biological treatments: AM fungi and Fusarium oxisporum applied in the soil alone or combined together, and Rizosum Max^® product, compared with the untreated control, to reduce the P. ramosa infestation in processing tomato crop. The principal results to be drawn from this study under field condition, in contrast of those reported previously under laboratory and greenhouse conditions, show that both AM fungi and F. oxisporum do not provide the reduction of the number of emerged shoots of P. ramosa. This can arise probably from the low efficacy seedling of the agent pathogens for the control of this parasite in the field. On the contrary, the Rizosum Max^® product, containing AM fungi and some rizophere bacteria combined with several minerals and organic substances, appears to be most effective for the reduction of P. ramosa infestation.

Keywords: Arbuscular mycorrhized fungi, biocontrol methods, Phelipanche ramosa, tomato crop

Procedia PDF Downloads 462

Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

Procedia PDF Downloads 497

Authors: Nouha Ben Salah, Mohamed Ali Omri

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This paper treats the association between disclosure level and the cost of equity capital in Tunisian’slisted firms. This relation is tested by using two models. The first is used for testing this relation directly by regressing firm specific estimates of cost of equity capital on market beta, firm size and a measure of disclosure level. The second model is used for testing this relation by introducing information asymmetry as mediator variable. This model is suggested by Baron and Kenny (1986) to demonstrate the role of mediator variable in general. Based on a sample of 21 non-financial Tunisian’s listed firms over a period from 2000 to 2004, the results prove that greater disclosure is associated with a lower cost of equity capital. However, the results of indirect relationship indicate a significant positive association between the level of voluntary disclosure and information asymmetry and a significant negative association between information asymmetry and cost of equity capital in contradiction with our previsions. Perhaps this result is due to the biases of measure of information asymmetry.

Keywords: cost of equity capital, voluntary disclosure, information asymmetry, and Tunisian’s listed non-financial firms

Procedia PDF Downloads 517