Search results for: healthcare data security

Authors: Salizar Mohamed Ludin, Mohd Khairul Hasyimi Firdaus, Paul Arbon

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Purpose: This paper aims to develop Malaysian Government and community-level critical thinking, planning and action for improving community disaster resilience by reporting Phase 1, Part 1 of a larger community disaster resilience measurement study about adapting the Torrens Resilience Institute Australian Community Disaster Resilience Scorecard to the Malaysian context. Methodology: Pparticipatory action research encouraged key people involved in managing the six most affected areas in the 2014 flooding of Kelantan in Malaysia’s north-east to participate in discussions about adapting and self-testing the Australian Community Disaster Resilience Scorecard to measure and improve their communities’ disaster resilience. Findings: Communities need to strengthen their disaster resilience through better communication, cross-community cooperation, maximizing opportunities to compare their plans, actions and reactions with those reported in research publications, and aligning their community disaster management with reported best practice internationally while acknowledging the need to adapt such practice to local contexts. Research implications: There is a need for a Malaysia-wide, simple-to-use, standardized disaster resilience scorecard to improve the quality, quantity and capability of healthcare and emergency services’ preparedness, and to facilitate urgent reallocation of aid. Value: This study is the first of its kind in Malaysia. The resulting community disaster resilience guideline based on participants’ feedback about the Kelantan floods and scorecard self-testing has the potential for further adaptation to suit contexts across Malaysia, as well as demonstrating how the scorecard can be adapted for international use.

Keywords: community disaster resilience, CDR Scorecard, participatory action research, flooding, Malaysia

Procedia PDF Downloads 340

Authors: Yasser M. Saad, Amr A. El Hanafy, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, security and capital in many countries, particularly in Saudi Arabia. Inter simple sequence repeat technique was used to detect the genetic variations among some camel breeds (Majaheim, Safra, Wadah, and Hamara). Actual number of alleles, effective number of alleles, gene diversity, Shannon’s information index and polymorphic bands were calculated for each evaluated camel breed. Neighbor-joining tree that re-constructed for evaluated these camel breeds showed that, Hamara breed is distantly related from the other evaluated camels. In addition, the polymorphic sites, haplotypes and nucleotide diversity were identified for some camelidae cox1 gene sequences (obtained from NCBI). The distance value between C. bactrianus and C. dromedarius (0.072) was relatively low. Analysis of genetic diversity is an important way for conserving Camelus dromedarius genetic resources.

Keywords: camel, genetics, ISSR, neighbor-joining

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Authors: Sudaporn Arundee

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The purposes of this research were to study in three areas: (1) to study political understanding and participating of the constitutional monarchy, (2) to study the level of participation. This paper drew upon data collected from 395 Dusit residents by using questionnaire. In addition, a simple random sampling was utilized to collect data. The findings revealed that 94 percent of respondents had a very good understanding of constitution monarchy with a mean of 4.8. However, the respondents overall had a very low level of participation with the mean score of 1.69 and standard deviation of .719.

Keywords: political participation, constitutional monarchy, management and social sciences

Procedia PDF Downloads 256

Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: Robbie C. Murchison, Ibrahim Küçükdemiral, Andrew Cowell

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Thermal effects are the largest source of dimensional error in precision machining, and a major proportion is caused by ambient temperature variation. The use of coolant is a primary means of mitigating these effects, but there has been limited work on coolant temperature control. This research critically explored whether CNC-machine coolant refrigeration systems adapted to actively compensate for ambient temperature variation could increase machining accuracy. Accuracy data were collected from operators’ checklists for a CNC 5-axis mill and statistically reduced to bias and precision metrics for observations of one day over a sample period of 27 days. Temperature data were collected using three USB dataloggers in ambient air, the chiller inflow, and the chiller outflow. The accuracy and temperature data were analysed using Pearson correlation, then the thermodynamics of the system were described using system identification with MATLAB. It was found that 75% of thermal error is reflected in the hot coolant temperature but that this is negligibly dependent on ambient temperature. The effect of the coolant refrigeration process on hot coolant outflow temperature was also found to be negligible. Therefore, the evidence indicated that it would not be beneficial to adapt coolant chillers to compensate for ambient temperature variation. However, it is concluded that hot coolant outflow temperature is a robust and accessible source of thermal error data which could be used for prevention strategy evaluation or as the basis of other thermal error strategies.

Keywords: CNC manufacturing, machine-tool, precision machining, thermal error

Procedia PDF Downloads 92

Authors: Ana Fouto

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Background: Continuing Personal Development (CPD) enables professionals to keep up to date with the professional requirements, broadening their knowledge and expertise. However, much of the research explores the registered professionals’ experiences and the factors that influence their choice of engaging, despite the unregistered staff providing the majority of the direct patient care. Aim: To explore the Nursing/Midwifery Assistants’ (NAs) perception of the concept of CPD, as well as explore the factors that influence the NAs to engage (or not) with CPD experiences. Methodology: This pilot study used a qualitative approach through a case study, where a semi-structured interview was applied to three NAs to explore the factors that influence the decision-making of process of CPD engagement. Thematic analysis was used to analyse their answers and interpret patterns and associations. Findings: All the participants agreed that CPD is important and relevant to their practice and personal lives. Five main categories were identified: NAs’ scope of practice, the impact of CPD; decision-making process; challenges; changes required. Although similar findings to the registered nurses were identified, the lack of CPD regulation for NAs and the rapid evolution of their role make the CPD engagement more problematic. Conclusion: Engagement with CPD is influenced by a wide range of professional (organisational and national) and personal factors. NAs perceive lack of management support at different stages of the CPD activities as a main influence. Organisations should be more flexible in the recruitment, offer of CPD choices, content, delivery, and contractual arrangements of NAs, which may increase engagement.

Keywords: nursing assistants, engagement, factors, pilot, continuing professional development (CPD)

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Authors: Loizos A. Hadjivasiliou, May Chehab

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Confronted with the human tragedy unfolding in the Mediterranean during the 2011-2016 period, the European Union introduced for the first time the “hotspot approach”, the establishment of facilities for initial reception, identification registration, and fingerprinting of asylum seekers and migrants arriving in the EU by sea, at the frontline Member States. However, the lack of a comprehensive collective policy on migration management and border security left the Mediterranean Member States, mainly Italy, Greece, and Cyprus, struggling to overcome these challenges. The current study sheds light on the implementation of the hotspot approach as the frontispiece of the European response to the migration challenges, which, limited to the operational and financial support of the hosting member states, leads to heterogeneous burden-sharing. Within this framework, it highlights the fact that the implementation of the hotspots as a panacea carries the risk of transforming the Mediterranean member states into giant hotspots with unpredictable consequences for the future of the Schengen area.

Keywords: asylum, burden sharing, hotspots, migration management policy, Schengen area

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Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

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Authors: Kefaya Qaddoum

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Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.

Keywords: tomato yield prediction, naive Bayes, redundancy, WSG

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Authors: Blanka Havlickova

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In the last ten years, there are growing numbers of troops with machine guns serving on streets of European cities. We can see them around government buildings, major transport hubs, synagogues, galleries and main tourist landmarks. As the main purpose of armed soldier’s presence in European cities authorities declare the prevention of terrorist attacks and psychological support for tourists and domestic population. The main objective of the following study is to find out whether the deployment of armed soldiers in European cities has a calming and reassuring effect on Czech citizens (if the presence at armed soldiers make the Czech population feel more secure) or rather becomes a stress factor (the presence of soldiers standing guard in full military fatigues recalls serious criminality and terrorist attacks which are reflected in the fears and insecurity of Czech population). The initial hypothesis of this study is connected with the priming theory, the idea that when we are exposed to an image (armed soldier), it makes us unconsciously focus on a topic connected with this image (terrorism). This paper is based on a quantitative public survey, which was carried out in the form of electronic questioning among the citizens of the Czech Republic. Respondents answered 14 questions about two European cities – London and Paris. Besides general questions investigating the respondents' awareness of these cities, some of the questions focused on the fear that the respondents had when picturing themselves leaving next Monday for the given city (London or Paris). The questions asking about respondent´s travel fears and concerns were accompanied by different photos. When answering the question about fear some respondents have been presented with a photo of Westminster Palace and the Eiffel with ordinary citizens while other respondents have been presented with a picture of the Westminster Palace, the and Eiffel's tower not only with ordinary citizens, but also with one soldier holding a machine gun. The main goal of this paper is to analyse and compare data about concerns for these two groups of respondents (presented with different pictures) and find out if and how an armed soldier with a machine gun in front of the Westminster Palace or the Eiffel Tower affects the public's concerns about visiting the site. In other words, the aim of this paper is to confirm or rebut the hypothesis that the look at a soldier with a machine gun in front of the Eiffel Tower or the Westminster Palace automatically triggers the association with a terrorist attack leading to an increase in fear and insecurity among Czech population.

Keywords: terrorism, security measures, priming, risk perception

Procedia PDF Downloads 257

Authors: Palanisamy Sivanandy, Tan Tyng Wei, Tan Wee Loon, Lim Chong Yee

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Background: Patient safety has become a major concern over recent years with elevated medication errors; particularly prescribing and dispensing errors. Meticulous prescription screening and diligent drug dispensing is therefore important to prevent drug-related adverse events from inflicting harm to patients. Hence, pharmacists play a significant role in this scenario. The evaluation of patient safety in a pharmacy setup is crucial to contemplate current practices, attitude and perception of pharmacists towards patient safety. Method: The questionnaire for Pharmacy Survey on Patient Safety Culture developed by the Agency for Healthcare and Research Quality (AHRQ) was used to assess patient safety. Main objectives of the study was to evaluate the attitude and perception of pharmacists towards patient safety in retail pharmacies setup in Malaysia. Results: 417 questionnaire were distributed via convenience sampling in three different states of Malaysia, where 390 participants were responded and the response rate was 93.52%. The overall positive response rate (PRR) was ranged from 31.20% to 87.43% and the average PRR was found to be 67%. The overall patient safety grade for our pharmacies was appreciable and it ranges from good to very good. The study found a significant difference in the perception of senior and junior pharmacists towards patient safety. The internal consistency of the questionnaire contents /dimensions was satisfactory (Cronbach’s alpha - 0.92). Conclusion: Our results reflect that there was positive attitude and perception of retail pharmacists towards patient safety. Despite this, various efforts can be implemented in the future to amplify patient safety in retail pharmacies setup.

Keywords: patient safety, attitude, perception, positive response rate, medication errors

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Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi

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A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.

Keywords: posture correction, posture training, riding posture, riding simulator

Procedia PDF Downloads 480

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Sadaf Kalhori

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Introduction: Doxorubicin (DOX)-induced cardiotoxicity is widely known as the most severe complication of anthracycline-based chemotherapy in patients with cancer. It is unknown whether Deferiprone (DFP), could reduce the severity of DOX-induced cardiotoxicity by inhibiting free radical reactions. Thus, this study was performed to assess the protective effect of Deferiprone on DOX-induced cardiotoxicity in a rat model. Methods: The rats were divided into five groups. Group one was a control group. Group 2 was DOX (2 mg/kg/day, every other day for 12 days), and Group three to five which receiving DOX as in group 2 and DFP 75,100 and 150 mg/kg/day, for 19 days, respectively. DFP was starting 5 days prior to the first DOX injection and two days after the last DOX injection throughout the study. Electrocardiographic and hemodynamic studies, along with histopathological examination, were conducted. In addition, serum sample was taken and total cholesterol, Malone dialdehyde, triglyceride, albumin, AST, ALT, total protein, lactate dehydrogenase, total anti-oxidant and creatine kinase were assessed. Result: Our results showed the normal structure of endocardial, myocardial and pericardial in the control group. Pathologic data such as edema, hyperemia, bleeding, endocarditis, myocarditis and pericarditis, hyaline degeneration, cardiomyocyte necrosis, myofilament degeneration and nuclear chromatin changes were assessed in all groups. In the DOX group, all pathologic data was seen with mean grade of 2±1.25. In the DFP group with a dose of 75 and 100 mg, the mean grade was 1.41± 0.31 and 1±.23, respectively. In DFP group with a dose of 150, the pathologic data showed a milder change in comparison with other groups with e mean grade of 0.45 ±0.19. Most pathologic data in DFP groups showed significant changes in comparison with the DOX group (p < 0.001). Discussion: The results also showed that DFP treatment significantly improved DOX-induced heart damage, structural changes in the myocardium, and ventricular function. Our data confirm that DFP is protective against cardiovascular-related disorders induced by DOX. Clinical studies are needed to be involved to examine these findings in humans.

Keywords: cardiomyopathy, deferiprone, doxorubicin, rat

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Authors: Mariam Tsitsagi, Ana Berdzenishvili

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Rainfall intensity change is one of the main indicators of climate change. It has a great influence on agriculture as one of the main factors causing soil erosion. Splash and sheet erosion are one of the most prevalence and harmful for agriculture. It is invisible for an eye at first stage, but the process will gradually move to stream cutting erosion. Our study provides the assessment of rainfall erosivity potential with the use of modern research methods in Kakheti region. The region is the major provider of wheat and wine in the country. Kakheti is located in the eastern part of Georgia and characterized quite a variety of natural conditions. The climate is dry subtropical. For assessment of the exact rate of rainfall erosion potential several year data of rainfall with short intervals are needed. Unfortunately, from 250 active metro stations running during the Soviet period only 55 of them are active now and 5 stations in Kakheti region respectively. Since 1936 we had data on rainfall intensity in this region, and rainfall erosive potential is assessed, in some old papers, but since 1990 we have no data about this factor, which in turn is a necessary parameter for determining the rainfall erosivity potential. On the other hand, researchers and local communities suppose that rainfall intensity has been changing and the number of haily days has also been increasing. However, finding a method that will allow us to determine rainfall erosivity potential as accurate as possible in Kakheti region is very important. The study period was divided into three sections: 1936-1963; 1963-1990 and 1990-2015. Rainfall erosivity potential was determined by the scientific literature and old meteorological stations’ data for the first two periods. And it is known that in eastern Georgia, at the boundary between steppe and forest zones, rainfall erosivity in 1963-1990 was 20-75% higher than that in 1936-1963. As for the third period (1990-2015), for which we do not have data of rainfall intensity. There are a variety of studies, where alternative ways of calculating the rainfall erosivity potential based on lack of data are discussed e.g.based on daily rainfall data, average annual rainfall data and the elevation of the area, etc. It should be noted that these methods give us a totally different results in case of different climatic conditions and sometimes huge errors in some cases. Three of the most common methods were selected for our research. Each of them was tested for the first two sections of the study period. According to the outcomes more suitable method for regional climatic conditions was selected, and after that, we determined rainfall erosivity potential for the third section of our study period with use of the most successful method. Outcome data like attribute tables and graphs was specially linked to the database of Kakheti, and appropriate thematic maps were created. The results allowed us to analyze the rainfall erosivity potential changes from 1936 to the present and make the future prospect. We have successfully implemented a method which can also be use for some another region of Georgia.

Keywords: erosivity potential, Georgia, GIS, Kakheti, rainfall

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Authors: Qiong Li

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This study investigated in which condition computer-mediated communication (CMC) could promote pragmatic development. The focal feature included four Chinese sentence final particles (SFPs), a, ya, ba, and ne. They occur frequently in Chinese, and function as mitigators to soften the tone of speech. However, L2 acquisition of SFPs is difficult, suggesting the necessity of additional exposure to or explicit instruction on Chinese SFPs. This study follows this line and aims to explore two research questions: (1) Is CMC combined with data-driven instruction more effective than CMC alone in promoting L2 Chinese learners’ SFP use? (2) How does L2 Chinese learners’ SFP use change over time, as compared to the production of native Chinese speakers? The study involved 19 intermediate-level learners of Chinese enrolled at a private American university. They were randomly assigned to two groups: (1) the control group (N = 10), which was exposed to SFPs through CMC alone, (2) the treatment group (N = 9), which was exposed to SFPs via CMC and data-driven instruction. Learners interacted with native speakers on given topics through text-based CMC over Skype. Both groups went through six 30-minute CMC sessions on a weekly basis, with a one-week interval after the first two CMC sessions and a two-week interval after the second two CMC sessions (nine weeks in total). The treatment group additionally received a data-driven instruction after the first two sessions. Data analysis focused on three indices: token frequency, type frequency, and acceptability of SFP use. Token frequency was operationalized as the raw occurrence of SFPs per clause. Type frequency was the range of SFPs. Acceptability was rated by two native speakers using a rating rubric. The results showed that the treatment group made noticeable progress over time on the three indices. The production of SFPs approximated the native-like level. In contrast, the control group only slightly improved on token frequency. Only certain SFPs (a and ya) reached the native-like use. Potential explanations for the group differences were discussed in two aspects: the property of Chinese SFPs and the role of CMC and data-driven instruction. Though CMC provided the learners with opportunities to notice and observe SFP use, as a feature with low saliency, SFPs were not easily noticed in input. Data-driven instruction in the treatment group directed the learners’ attention to these particles, which facilitated the development.

Keywords: computer-mediated communication, data-driven instruction, pragmatic development, second language Chinese, sentence final particles

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

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Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

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Authors: Volkan Kaya, Ersin Elbasi

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Watermarking and stenography are getting importance recently because of copyright protection and authentication. In watermarking we embed stamp, logo, noise or image to multimedia elements such as image, video, audio, animation and text. There are several works have been done in watermarking for different purposes. In this research work, we used watermarking techniques to embed patient information into the medical magnetic resonance (MR) images. There are two methods have been used; frequency domain (Digital Wavelet Transform-DWT, Digital Cosine Transform-DCT, and Digital Fourier Transform-DFT) and spatial domain (Least Significant Bits-LSB) domain. Experimental results show that embedding in frequency domains resist against one type of attacks, and embedding in spatial domain is resist against another group of attacks. Peak Signal Noise Ratio (PSNR) and Similarity Ratio (SR) values are two measurement values for testing. These two values give very promising result for information hiding in medical MR images.

Keywords: watermarking, medical image, frequency domain, least significant bits, security

Procedia PDF Downloads 289

Authors: Reka Zsuzsanna Mathe

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The globalization and the Europeanization have significantly contributed to a change in the role of the nation-states. The global economic crisis, the climate changes, and the recent refugee crisis, are just a few among many challenges that cannot be effectively addressed by the traditional role of the nation-states. One of the main roles of the states is to solve collective action problems, however due to their changing roles; apparently this is getting more and more difficult. Depending on political culture, collective action problems are solved either through cooperation or conflict. The political culture of Central and Eastern European (CEE) countries is marked by low civic participation and by a weak civil society. In this type of culture collective action problems are likely to be induced through conflict, rather than the democratic process of dialogue and any type of social change is probably to be introduced by social movements. Several studies have been conducted on the social movements of the CEE countries, yet, it is still not clear if the most significant social movements of the region tend to choose rather the cooperative or the conflictual way as action strategy. This study differentiates between a national and a European action field, having different social orders. The actors of the two fields are the broadly understood civil society members, conceptualized as social movements. This research tries to answer the following questions: a) What are the norms that best characterize the CEE countries’ social order? b) What type of actors would prefer a change and in which areas? c) Is there a significant difference between the main actors active in the national versus the European field? The main hypotheses are that there are conflicting norms defining the national and the European action field, and there is a significant difference between the action strategies adopted by social movements acting in the two different fields. In mapping the social order, the study uses data provided by the European Social Survey. Big data of the Global Data on Events, Location and Tone (GDELT) database offers information regarding the main social movements and their preferred type of action. The unit of the analysis is the so called ‘Visegrad 4’ countries: Poland, Czech Republic, Slovakia and Hungary and the research uses data starting from 2005 (after the European accession of these four countries) until May, 2017. According to the data, the main hypotheses were confirmed.

Keywords: big data, Central and Eastern Europe, civil society, GDELT, social movements

Procedia PDF Downloads 164

Authors: Udeh Nneka Evelyn

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The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

Procedia PDF Downloads 584

Authors: Latha V. Prabhu, B.V. Murlimanju, P.J. Jiji, Mangala M. Pai

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Background: The capitate is the largest among the carpal bones. There exists no literature about the vascular foramina of the capitate bone. The objective of the present study was to investigate the morphology and number of the nutrient foramina in the cadaveric dried capitate bones of the Indian population. Methods: The present study included 59 capitate bones (25 right sided and 34 left sided) which were obtained from the gross anatomy laboratory of our institution. The bones were macroscopically observed for the nutrient foramina and the data was collected with respect to their number. The tabulation of the data and analysis were done. Results: All of our specimens (100%) exhibited the nutrient foramina over the non-articular and articular surfaces. The foramina were observed at the medial, lateral, palmar and dorsal surfaces of the capitate bones. The foramina were ranged from 6 to 23 in each capitate bone. In the medial surface, the foramina ranged from 1 to 6, lateral surface from 0 to 7, the foramina ranged between 0 and 5 in the palmar surface. However most of the foramina were located at the dorsal surface which ranged from 3 to 11. Conclusion: We believe that the present study has provided additional data about the nutrient foramina of the capitate bones. The data is enlightening to the orthopedic surgeon and would help in the hand surgeries. The knowledge about the foramina is also important to the radiologists to prevent the misinterpretation of the findings in the x ray and computed tomogram scan films. The foramina may mimick like erosions and ossicles. The morphological knowledge of the vasculature, their foramina of entry and number is required to understand the concepts in the avascular necrosis of the capitate.

Keywords: avascular necrosis, capitate, morphology, nutrient foramen

Procedia PDF Downloads 346

Authors: Phenias Nsabimana, Jérôme W. Some, Hilda Vasanthakaalam, Stefaan De Henauw, Souheila Abbeddou

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Tools for the dietary assessment in adults are limited in low- and middle-income settings. The objective of this study was to develop and validate a semi-quantitative food frequency questionnaire (FFQ) against the multiple pass-24 h recall tool for use in urban and rural Rwanda. A total of 212 adults (154 females and 58 males), 18-49 aged, including 105 urban and 107 rural residents, from the four regions of Rwanda, were recruited in the present study. A multiple-pass 24- H recall technique was used to collect dietary data in both urban and rural areas in four different rounds, on different days (one weekday and one weekend day), separated by a period of three months, from November 2020 to October 2021. The details of all the foods and beverages consumed over the 24h period of the day prior to the interview day were collected during face-to-face interviews. A list of foods, beverages, and commonly consumed recipes was developed by the study researchers and ten research assistants from the different regions of Rwanda. Non-standard recipes were collected when the information was available. A single semi-quantitative FFQ was also developed in the same group discussion prior to the beginning of the data collection. The FFQ was collected at the beginning and the end of the data collection period. Data were collected digitally. The amount of energy and macro-nutrients contributed by each food, recipe, and beverage will be computed based on nutrient composition reported in food composition tables and weight consumed. Median energy and nutrient contents of different food intakes from FFQ and 24-hour recalls and median differences (24-hour recall –FFQ) will be calculated. Kappa, Spearman, Wilcoxon, and Bland-Altman plot statistics will be conducted to evaluate the correlation between estimated nutrient and energy intake found by the two methods. Differences will be tested for their significance and all analyses will be done with STATA 11. Data collection was completed in November 2021. Data cleaning is ongoing and the data analysis is expected to be completed by July 2022. A developed and validated semi-quantitative FFQ will be available for use in dietary assessment. The developed FFQ will help researchers to collect reliable data that will support policy makers to plan for proper dietary change intervention in Rwanda.

Keywords: food frequency questionnaire, reproducibility, 24-H recall questionnaire, validation

Procedia PDF Downloads 145

Authors: Ruangdech Sirikit

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The purposes of this research were to study the variables affecting the quality assessment of mathematics subject in Thailand by using value-added analysis on TIMSS 2011. The data used in this research is the secondary data from the 2011 Trends in International Mathematics and Science Study (TIMSS), collected from 6,124 students in 172 schools from Thailand, studying only mathematics subjects. The data were based on 14 assessment tests of knowledge in mathematics. There were 3 steps of data analysis: 1) To analyze descriptive statistics 2) To estimate competency of students from the assessment of their mathematics proficiency by using MULTILOG program; 3) analyze value added in the model of quality assessment using Value-Added Model with Hierarchical Linear Modeling (HLM) and 2 levels of analysis. The research results were as follows: 1. Student level variables that had significant effects on the competency of students at .01 levels were Parental care, Resources at home, Enjoyment of learning mathematics and Extrinsic motivation in learning mathematics. Variable that had significant effects on the competency of students at .05 levels were Education of parents and self-confident in learning mathematics. 2. School level variable that had significant effects on competency of students at .01 levels was Extra large school. Variable that had significant effects on competency of students at .05 levels was medium school.

Keywords: quality assessment, value-added model, TIMSS, mathematics, Thailand

Procedia PDF Downloads 286

Authors: Devin Simmons

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At the USDOT’s Bureau of Transportation Statistics, a biannual census of ferry operators in the U.S. is conducted, with results such as route mileage used to determine federal funding levels for operators. AIS data allows for the possibility of using GIS software and geographical methods to confirm operator-reported mileage for individual ferry routes. As part of the USDOT’s work on the ferry census, an algorithm was developed that uses AIS data for ferry vessels in conjunction with known ferry terminal locations to model the average route travelled for use as both a cartographic product and confirmation of operator-reported mileage. AIS data from each vessel is first analyzed to determine individual journeys based on the vessel’s velocity, and changes in velocity over time. These trips are then converted to geographic linestring objects. Using the terminal locations, the algorithm then determines whether the trip represented a known ferry route. Given a large enough dataset, routes will be represented by multiple trip linestrings, which are then filtered by DBSCAN spatial clustering to remove outliers. Finally, these remaining trips are ready to be averaged into one route. The algorithm interpolates the point on each trip linestring that represents the start point. From these start points, a centroid is calculated, and the first point of the average route is determined. Each trip is interpolated again to find the point that represents one percent of the journey’s completion, and the centroid of those points is used as the next point in the average route, and so on until 100 points have been calculated. Routes created using this algorithm have shown demonstrable improvement over previous methods, which included the implementation of a LOESS model. Additionally, the algorithm greatly reduces the amount of manual digitizing needed to visualize ferry activity.

Keywords: ferry vessels, transportation, modeling, AIS data

Procedia PDF Downloads 180

Authors: Kitti Leangkrua

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This paper presents a risk-based maintenance strategy of a power transformer in order to optimize operating and maintenance costs. The methodology involves the study and preparation of a database for the collection the technical data and test data of a power transformer. An evaluation of the overall condition of each transformer is performed by a program developed as a result of the measured results; in addition, the calculation of the main equipment separation to the overall condition of the transformer (% HI) and the criteria for evaluating the importance (% ImI) of each location where the transformer is installed. The condition assessment is performed by analysis test data such as electrical test, insulating oil test and visual inspection. The condition of the power transformer will be classified from very poor to very good condition. The importance is evaluated from load criticality, importance of load and failure consequence. The risk matrix is developed for evaluating the risk of each power transformer. The high risk power transformer will be focused firstly. The computerized program is developed for practical use, and the maintenance strategy of a power transformer can be effectively managed.

Keywords: asset management, risk-based maintenance, power transformer, health index

Procedia PDF Downloads 311

Authors: Jennifer Foss, DNP, RN-BC, NEA-BC

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Stress and burnout in the bedside registered nurse have deleterious consequences for registered nurses, patients, and the hospitals that employ them. The objective of this study was to determine whether a sixty-minute mindfulness workshop was effective in reducing perceived levels of stress and decreasing mindfulness in registered nurses working in the acute care setting. Registered nurses at a community hospital in the Northeast part of the country were recruited through e-mail and flyers in breakrooms. Participants completed the Perceived Stress Scale (PSS) and Mindfulness Attention Awareness Scale (MAAS) two weeks prior to taking part in the intervention and two weeks post intervention. Of the twenty-three registered nurses who completed the baseline questionnaires, 91% were female with an average age between 30-39 years. Sixty-five percent of subjects completed the questionnaires two weeks post intervention. Two weeks post intervention, registered nurses reported a decrease in perception of stress (pre and post PSS was .133) and was not significant (t=1.293, df=14, p=.217). Likewise, an increase in mindful attention .325 was reported two-weeks post intervention and indicated a favorable tendency to enter a mindful state. This finding was also not significant (t=-1.990, df=14, p=.066). In this study, nurses reported decreases in perceived stress and increases in mindfulness after attending a sixty-minute mindfulness workshop. Further research is needed to determine the long-term impact of mindfulness-based training on nurses' stress and mindfulness skills. The results of this study add to the body of literature that supports the benefits of mindfulness-based interventions in the healthcare setting.

Keywords: Stress, burnout, nursing, acute care nursing

Procedia PDF Downloads 76

Authors: Nora Neuteboom

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This study investigates household financial behaviors during unemployment spells in the Netherlands using high-frequency transaction data through a event study specification integrating propensity score matching. In our specification, we contrasted treated individuals, who underwent job loss, with non-treated individuals possessing comparable financial characteristics. The initial onset of unemployment triggers a substantial surge in income, primarily attributed to transition payments, but swiftly drops post-unemployment, with unemployment benefits covering slightly over half of former salary earnings. Despite a re-employment rate of around half within six months, the treatment group experiences a persistent average monthly earnings reduction of approximately 600 EUR by month. Spending patterns fluctuate significantly, surging before unemployment due to transition payments and declining below non-treated individuals post-unemployment, indicating challenges to fully smooth consumption after job loss. Furthermore, our study disentangles the effects of transition payments and liquidity holdings on spending, revealing that transition payments exert a more pronounced and prolonged impact on consumption smoothing than liquidity holdings. Transition payments significantly stimulate spending, particularly in pin and iDEAL categories, contrasting a much smaller relative spending impact of liquidity holdings.

Keywords: household consumption, transaction data, big data, propensity score matching

Procedia PDF Downloads 29