Search results for: supervisory control and data acquisition (scada)

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 544

Authors: Shahira El Shafie, Hanaa Eldash, Engy Ghabbour, Mohamed Eid

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Several immunologic defects can be found in patients with beta-thalassemia, among which the impairment of neutrophil phagocytic function is of utmost importance. Attention has been directed to the role of proinflammatory cytokines in neutrophil chemotaxis and phagocytosis. Interleukin-8 (IL-8) is an important chemotactic and activation peptide for neutrophils; changes in IL-8 level and potential correlation with neutrophil function can be relevant to immunomodulation pathophysiology in beta-thalassemia patients. This case-control study aimed to evaluate IL-8 level and to assess granulocyte recruitment, as markers of immunomodulation, in poly-transfused thalassemia patients attending Fayoum University Hospitals. The study was conducted on 50 patients with ß thalassemia and 32 age-matched controls. 21/50 patients were transfused more than ten times, and 29/50 were transfused in a lower frequency. Patients and controls were subjected to thorough history taking and clinical examination, measurement of IL-8 level using human IL-8 ELISA kit, and Rebuck skin window technique (RSWT) to assess granulocyte recruitment. Our data showed statistically significant higher levels of IL-8 in ß thalassemia patients compared to control with a much higher difference in patients transfused more than ten times. Neutrophil recruitment was significantly lower in ß thalassemia patients compared to control at 4 hours and 24 hours test time. Although IL-8, the main chemotactic pro-inflammatory cytokine showed a higher level in thalassemia patients, neutrophils recruitment was significantly lower, especially in those receiving more than ten transfusion times. Our findings suggest a possible role of other neutrophil chemotactic factors, defective neutrophil response, or increased IL-8 as compensation of abnormal function. We recommend the use of IL-8 and Rebuck skin window technique as useful markers of immunomodulation in thalassemia and further study for these biomarkers to assess their clinical implications and impact on the management of thalassemia patients.

Keywords: beta-thalassemia, Interleukin-8, Rebuck skin window technique, immunomodulation

Procedia PDF Downloads 183

Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Elisangela Sobreira, Denise Teixeira

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Visceral leishmaniasis is a public health problem in Brazil, it is the main reservoir dog. In the period 2012-2016 78 diagnoses were performed in dogs suspected. Blood samples were collected from the cephalic vein obtaining serum used for the indirect immunofluorescence test and enzyme-linked immunosorbent assay, while it collected a drop of blood for the rapid chromatographic immunoassay. Obtained in 32 dogs positive. The test is important for the control of this disease and is used routinely in the Zoonoses Control Center.

Keywords: Brazil, dogs, Leismaniasis, Zoonoses center

Procedia PDF Downloads 257

Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 805

Authors: Phillipa Evans, Christopher Trotter

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Aims: This study aims to examine the effectiveness of a practice skills framework implemented in three youth detention centres in Juvenile Justice in New South Wales (NSW), Australia. The study is supported by a grant from and Australian Research Council and NSW Juvenile Justice. Recent years have seen a number of incidents in youth detention centres in Australia and other places. These have led to inquiries and reviews with some suggesting that detention centres often do not even meet basic human rights and do little in terms of providing opportunities for rehabilitation of residents. While there is an increasing body of research suggesting that community based supervision can be effective in reducing recidivism if appropriate skills are used by supervisors, there has been less work considering worker skills in youth detention settings. The research that has been done, however, suggest that teaching interpersonal skills to youth officers may be effective in enhancing the rehabilitation culture of centres. Positive outcomes have been seen in a UK detention centre for example, from teaching staff to do five-minute problem-solving interventions. The aim of this project is to examine the effectiveness of training and coaching youth detention staff in three NSW detention centres in interpersonal practice skills. Effectiveness is defined in terms of reductions in the frequency of critical incidents and improvements in the well-being of staff and young people. The research is important as the results may lead to the development of more humane and rehabilitative experiences for young people. Method: The study involves training staff in core effective practice skills and supporting staff in the use of those skills through supervision and de-briefing. The core effective practice skills include role clarification, pro-social modelling, brief problem solving, and relationship skills. The training also addresses some of the background to criminal behaviour including trauma. Data regarding critical incidents and well-being before and after the program implementation are being collected. This involves interviews with staff and young people, the completion of well-being scales, and examination of departmental records regarding critical incidents. In addition to the before and after comparison a matched control group which is not offered the intervention is also being used. The study includes more than 400 young people and 100 youth officers across 6 centres including the control sites. Data collection includes interviews with workers and young people, critical incident data such as assaults, use of lock ups and confinement and school attendance. Data collection also includes analysing video-tapes of centre activities for changes in the use of staff skills. Results: The project is currently underway with ongoing training and supervision. Early results will be available for the conference.

Keywords: custody, practice skills, training, youth workers

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Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Chodidjah, Edi Dharmana, Hardhono, Sarjadi

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Breast cancer treatment options including surgery, radiation therapy, chemotherapy, and immunotherapy have not been effective. Besides, they have side effects. Keladi Tikus (Typhonium flagelliforme) has been shown to improve immune system, suppress tumor growth and induce apoptosis. One of the parameters for immune system, tumor growth and apoptosis is IFNγ (Interferon γ), VEGF (Vascular Endothelial Growth Factor) and Caspase 3 respectively. The aim of this study was to examine the effect of the administration of Keladi Tikus tuber extract at the dose of 200 mg/kgBW, 400 mg/KgBW, and 800 mg/kgBW on the level of IFNγ, VEGF and caspase 3 expression. In this experimental study using post test randomized control group design, 24 CH3 mice with tumor were randomly divided into 4 groups including control group and treated groups: Treated with 0.2 cc extract of Keladi Tikus at the dose of 200 mg/kgBW, 400 mg/kgBW, 800 mg/kgBW, respectively for 30 days. On day 31 the lymphatic tissue was taken and evaluated for its level of IFNγ, using ELISA. The tumor tissue was taken and subjected to immunohistochemistry staining for VEGF and caspase 3 expression evaluation. The data on IFNγ, VEGF and Caspase 3 expression were analyzed using One Way Anova with significant level of 0.05. One Way Anova resulted in p<0.05. LSD test showed that the level of IFNγ and Caspase 3 for control group was different from that of treated groups. There was no significant different between the treated group of 400 mg/KgBW and 800mg/KgBW. VEGF expressions for all the treated groups were significant. In conclusion, the oral administration of ethanolic extract of Keladi Tikus (Typhonium flagelliforme) at the dose of 200mg/kgBW, 400 mg/kgBW,800 mg/kgBW increases IFNγ, Caspase 3 and decreases VEGF expression in C3H mice with adenocarsinoma mamma.

Keywords: Typhonium flagelliforme, IFNγ, caspase 3, VEGF

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Authors: Atziri Moreno Vite, David Silva Gutiérrez

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Oil companies have become the key player in the world energy scenario thanks to their strong control of the level of hydrocarbon reserves and production. The present research aims to identify the main factors that explain the results of these companies through an in-depth review of the specialized literature and to analyze the results of these companies by means of econometric analysis with techniques such as Data Envelopment Analysis (DEA). The results show the relevance and impact of factors such as the level of employment or investment of the company.

Keywords: oil companies, performance, determinants, productive

Procedia PDF Downloads 118

Authors: K. Y. Chen, Y. N. Jia, H. Chua, C. W. Kan

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In United States (US), the environmental policy went through two stages that are government control period and market mechanism period. In the government control period in the 1970s, environmental problems in U.S. are treated by mandatory direct control method, including promulgation of laws, formulation of emission standards and mandatory installation of pollution treatment equipment. After the 1980s, the environmental policy in U.S. went into the second stage, in which the government strengthened the incentives and coordination effects of market. Since then, environmental governance had been partially replaced by means of economic regulation of the market. Green Tax Policy and Marketable Pollution Permits are good examples of government's economic interventions. U.S. Federal Government regards environmental industry as high-tech industry which is promoted in this period. Therefore, in the paper, we aim to analyse the effect of environmental investment on the sustainable development in the US. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: United States, public environmental investment, analysis, sustainable development

Procedia PDF Downloads 245

Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

Procedia PDF Downloads 261

Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

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The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use Microsoft^TM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: aircraft aerodynamic model, total least squares estimation, piloting the aircraft, robust control, Microsoft Flight Simulator, MQ-1 predator

Procedia PDF Downloads 283

Authors: Tannia Vindel, Angel Matute, Erik Elvir, Kelvin Santos

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Currently in Honduras, is been incentivized the generation of energy using renewable fonts, such as: hydroelectricity, wind power, biomass and, more recently with the strongest growth, photovoltaic energy. In July 2015 were installed 455.2 MW of photovoltaic energy, increasing by 24% the installed capacity of the national interconnected system existing in 2014, according the National Energy Company (NEC), that made possible reduce the thermoelectric dependency of the system. Given the good results of those large-scale photovoltaic plants, arises the question: is it interesting for the distribution utility and for the consumers the integration of photovoltaic systems in micro-scale in the urban and rural areas? To answer that question has been researched the insertion of photovoltaic energy in the residential sector in Tegucigalpa and Comayagüela (Central District), Honduras to determine the technical and economic viability. Francisco Morazán department, according the National Statistics Institute (NSI), in 2001 had more than 180,000 houses with power service. Tegucigalpa, department and Honduras capital, and Comayagüela, both, have the highest population density in the region, with 1,300,000 habitants in 2014 (NSI). The residential sector in the south-central region of Honduras represents a high percentage being 49% of total consumption, according with NEC in 2014; where 90% of this sector consumes in a range of 0 to 300 kWh / month. All this, in addition to the high level of losses in the transmission and distribution systems, 31.3% in 2014, and the availability of an annual average solar radiation of 5.20 kWh/(m2∙day) according to the NASA, suggests the feasibility of the implementation of photovoltaic systems as a solution to give a level of independency to the households, and besides could be capable of injecting the non-used energy to the grid. The capability of exchange of energy with the grid could make the photovoltaic systems acquisition more affordable to the consumers, because of the compensation energy programs or other kinds of incentives that could be created. Technical viability of the photovoltaic systems insertion has been analyzed, considering the solar radiation monthly average to determine the monthly average of energy that would be generated with the technology accessible locally and the effects of the injection of the energy locally generated on the grid. In addition, the economic viability has been analyzed too, considering the photovoltaic systems high costs, costs of the utility, location and monthly energy consumption requirements of the families. It was found that the inclusion of photovoltaic systems in Tegucigalpa and Comayagüela could decrease in 6 MW the demand for the region if 100% of the households use photovoltaic systems, which acquisition may be more accessible with the help of government incentives and/or the application of energy exchange programs.

Keywords: grid connected, photovoltaic, residential, technical analysis

Procedia PDF Downloads 257

Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

Procedia PDF Downloads 181

Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 187

Authors: Jiraporn Adchariyaprasit

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The aesthetics of language in Thai poetry are emerged from the combination of sounds and meanings. The appreciation of such beauty can be achieved by means of education, acquisition of knowledge, and training. This research aims to study the learning process of aesthetics of language in Thai poetry for high school teachers in Bangkok and nearby provinces. There are 10 samples selected by purposive sampling for in-depth interviews. According to the research, there are four patterns in the learning process of aesthetics of language in Thai poetry which are 1) the study of characteristics and patterns of poetry, 2) the training of poetic reading, 3) the study of social and cultural contexts of poetry’s creation, and 4) the study of other sciences related to poetry such as linguistics, traditional dance, and so on.

Keywords: aesthetics, poetry, Thai poetry, poetry learning

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Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: Amy Elkington

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Women in abusive relationships who commit crimes under duress are unfairly treated by the English legal system. Despite the offence of Coercive Control being introduced in 2015 that recognises that a woman’s autonomy has been eroded, coercion is no longer a defence to women who feel compelled to act due to their partner’s behavior or abuse. This problem is intensified by the fact that women in abusive relationships are more likely to commit crimes to ensure their survival. Furthermore, the very fact that they are ‘associating’ with their abusive partners means that they are excluded from pleading a defence of duress. Women who kill their abusers may be able to reduce their conviction from murder to manslaughter, but this depends on successfully pleading either loss of control or diminished responsibility, both not without their issues, but this does not provide a defence where a lesser crime is committed. Self-defence is also widely unavailable to either murder or non-fatal offences, as the amount of force used is often deemed disproportionate because women are more likely to use weapons in their defence. Regardless, this would not provide a defence where the crime committed is one such as theft. An alternative that has been proposed would be to introduce a new defence that would work similarly to the exemption to prosecution afforded to those who are trafficked that commit crime under duress. Despite having support in the Lords in March 2021, this recommendation has been rejected by the Government on the basis that it would not achieve an appropriate balance of justice. The result is that abused women who commit crime are left without an appropriate defence. A doctrinal approach highlights the injustices in these types of cases and concludes that it is time for the current law of duress to change.

Keywords: coercive control, crime, defences, duress

Procedia PDF Downloads 192

Authors: Fauziah Mohd Sa’ad, Mohammad Aziz Shah, B. Mohammad Arip, Norazani Ahmad, Mohd Noor Idris, Hapsah M. Yusof

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This study was carried out to assess the application of person-centred therapy and Cognitive Psychology Ad-Din group counseling on self-concept, depression, and resilience of teenage pregnancy. This study involved 55 teenage pregnancy at three women’s refuge centers which are from KEWAJA, Rhaidatus Sakinah, and Taman Seri Puteri Cheras (JKM). Subjects were classed into two treatment groups and one control group. The Multidimensional Self-Concept Scale (MSCS), Beck Depression inventory (BDI) and Adolescent Resiliency Attitude Scale (ARAS) was administered to assess self-concept, depression, and resilience of teenage pregnancy. The control pre and post test design was used for this study. The research data were analyzed using descriptive analysis, ANOVA, MANCOVA and Tuckey Post Hoc with the significant level of .01 and .05. All treatment group received group counseling sessions for 7 consecutive week, once in each week. The Person-centred group and Cognitive Psychology Ad-Din group counseling showed a significant reduction (pre-test to post-test) on depression, enhancing self-concept and resilience of teenage pregnancy.

Keywords: group counseling, person-centred therapy, cognitive psychology Ad-Din, teenage pregnancy

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Authors: Jitendra Pratap, Jonathan Sivyer

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Introduction: Dual energy/Spectral CT scanning permits simultaneous acquisition of two x-ray spectra datasets and can complement radiological diagnosis by allowing tissue characterisation (e.g., uric acid vs. non-uric acid renal stones), enhancing structures (e.g. boost iodine signal to improve contrast resolution), and quantifying substances (e.g. iodine density). However, the latter showed inconsistent results between the 2 main modes of dual energy scanning (i.e. dual source vs. dual layer). Therefore, the present study aimed to determine which technology is more accurate in quantifying iodine density. Methods: Twenty vials with known concentrations of iodine solutions were made using Optiray 350 contrast media diluted in sterile water. The concentration of iodine utilised ranged from 0.1 mg/ml to 1.0mg/ml in 0.1mg/ml increments, 1.5 mg/ml to 4.5 mg/ml in 0.5mg/ml increments followed by further concentrations at 5.0 mg/ml, 7mg/ml, 10 mg/ml and 15mg/ml. The vials were scanned using Dual Energy scan mode on a Siemens Somatom Force at 80kV/Sn150kV and 100kV/Sn150kV kilovoltage pairing. The same vials were scanned using Spectral scan mode on a Philips iQon at 120kVp and 140kVp. The images were reconstructed at 5mm thickness and 5mm increment using Br40 kernel on the Siemens Force and B Filter on Philips iQon. Post-processing of the Dual Energy data was performed on vendor-specific Siemens Syngo VIA (VB40) and Philips Intellispace Portal (Ver. 12) for the Spectral data. For each vial and scan mode, the iodine concentration was measured by placing an ROI in the coronal plane. Intraclass correlation analysis was performed on both datasets. Results: The iodine concentrations were reproduced with a high degree of accuracy for Dual Layer CT scanner. Although the Dual Source images showed a greater degree of deviation in measured iodine density for all vials, the dataset acquired at 80kV/Sn150kV had a higher accuracy. Conclusion: Spectral CT scanning by the dual layer technique has higher accuracy for quantitative measurements of iodine density compared to the dual source technique.

Keywords: CT, iodine density, spectral, dual-energy

Procedia PDF Downloads 117

Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

Procedia PDF Downloads 345

Authors: V. K. Tewari, M. Hussain, H. K. D. Gupta

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B-Methylprednisolone-level-1-benefit (20%) usually given in paraplegia (but within 8hrs). Patients wait-long-duration for physiological-recovery. Intrathecal-Sodium-Nitroprusside(ITSNP) has been used-in vasospasm-due-to-subarachnoid-hemorrhage. ITSNP-has been studied-here for wide-window-period-range for-treatment, fast-recovery/affordability. 2- for acute-cases-and 1-mechanism-for chronic-cases, which-are-interrelated, are being-proposed-for-physiological-recovery. retrograde-neurotransmission, vasospasm and long-term-potentiation-(ltp) mechanisms are proposed here for recovery. It’s a case-control-prospective-study. 82paraplegia-patients(10patients taken as control-no superfusion or dextrose5% superfusion and 72patients as ITSNP-group). The mean time for superfusion was 14.11 days. ITSNP administered at a dosage of 0.2 mg/kg bo wt. Pre/post ITSNP monitored by SSEP/MEP. After-2-Hours in ITSNP-group Mean-Change-From-Baseline-Asia Motor/Sensory-Score 13.84%/13.10%, after-24-hours MOTOR-1.27-points decrease(3.77%) and SENSORY 10.5points-increase(6.22%)as compared to Control-group no-change noted upto 24-hours, At-7days ITSNP motor/sensory;11.56%/6.22% as compared to Control-group 7.60/4.48%, At-2-months in ITSNP 27.69%/6.22% as compared to Control-group 16.02/4.5%. SSEP/MEP-documented-improvements-noted. ITSNP, a-swift-acting-drug in treatment-of-paraplegia, is effective within-two-hours(mean-change-MOTOR-13.84% and SENSORY-13.10%) on-mean14.11th postparaplegia-day with a small-detrimental-response after-24-hours which-recovers-fast.

Keywords: paraplegias, intrathecal sodium nitroprusside, retrograde transmission, the 10, 000 fold effect, perforators, vasodilatations, long term potenciations

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Authors: Yili Liu, Honghao Ren, Mariko Kondo

Abstract:

In the field of second language (L2) speech learning, it is well-known that that learner’s first language (L1) phonetic and phonological characteristics will be transferred into their L2 production and perception, which lead to foreign accent. For L1 Mandarin learners of Japanese, the confusion of /u/ and /o/ in /CjV/ sequences has been observed in their utterance frequently. L1 transfer is considered to be the cause of this issue, however, other factors which influence the identification of /Cju/ and /Cjo/ sequences still under investigation. This study investigates the perception of Japanese /Cju/ and /Cjo/ units by L1 Mandarin learners of Japanese. It further examined whether learners’ proficiency, syllable position, phonetic features of preceding consonants and background noise affect learners’ performance in perception. Fifty-two Mandarin-speaking learners of Japanese and nine native Japanese speakers were recruited to participate in an identification task. Learners were divided into beginner, intermediate and advanced level according to their Japanese proficiency. The average correct rate was used to evaluate learners’ perceptual performance. Furthermore, the comparison of the correct rate between learners’ groups and the control group was conducted as well to examine learners’ nativelikeness. Results showed that background noise tends to pose an adverse effect on distinguishing /u/ and /o/ in /CjV/ sequences. Secondly, Japanese proficiency has no influence on learners’ perceptual performance in the quiet and in background noise. Then all learners did not reach a native-like level without the distraction of noise. Beginner level learners performed less native-like, although higher level learners appeared to have achieved nativelikeness in the multi-talker babble noise. Finally, syllable position tends to affect distinguishing /Cju/ and /Cjo/ only under the noisy condition. Phonetic features of preceding consonants did not impact learners’ perception in any listening conditions. Findings in this study can give an insight into a further understanding of Japanese vowel acquisition by L1 Mandarin learners of Japanese. In addition, this study indicates that L1 transfer is not the only explanation for the confusion of /u/ and /o/ in /CjV/ sequences, factors such as listening condition and syllable position are also needed to take into consideration in future research. It also suggests the importance of perceiving speech in a noisy environment, which is close to the actual conversation required more attention to pedagogy.

Keywords: background noise, Chinese learners of Japanese, /Cju/ and /Cjo/ sequences, second language perception

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Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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Authors: Maha Deif, Alaa Eldin Hassan, Eman Shaat, Nesrine Elazhary, Eman Magdy

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Background: Erythropoietin (EPO) is a hematopoietic factor with multiple protective effects. The aim of the present study was to investigate the potential effect of EPO administration on renal functions and hypoxia inducible factor 1-alpha (HIF-1a) in diabetic rat kidneys. Methodology: The current study was carried out on 40 male albino rats divided into four groups (n= 10 in each). Group I served as normal control, group II was the diabetic control, group III rats received EPO on the same day of diagnosis of diabetes mellitus (DM), while group IV received the first dose of EPO 2 weeks after the diagnosis of DM. Results: The results showed that EPO supplementation leads to a significant decrease in serum urea, urinary protein and creatinine clearance as well as a significant increase in renal HIF-1a in group III and IV rats compared to the diabetic control group (group II). However, fasting blood glucose was significantly decreased in group III as compared to the diabetic control group in the third week, but no significant difference was reported in the fourth week among groups II, III and IV. Conclusion: EPO administration leads to the improvement of renal functions and increased levels of HIF-1a in diabetic rats.

Keywords: erythropoietin, diabetic nephropathy, hypoxia-inducible factor1-alpha, renal functions

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Authors: Maha Al-Soudani, Gilles Klysz, Jean-Paul Balayssac

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The aim of this paper is to use Ground Penetrating Radar (GPR) as a non-destructive testing (NDT) method to increase its accuracy in recognizing the geometric reinforced concrete structures and in particular, the position of steel bars. This definition will help the managers to assess the state of their structures on the one hand vis-a-vis security constraints and secondly to quantify the need for maintenance and repair. Several configurations of acquisition and processing of the simulated signal were tested to propose and develop an appropriate imaging algorithm in the propagation medium to locate accurately the rebar. A subsequent experimental validation was used by testing the imaging algorithm on real reinforced concrete structures. The results indicate that, this algorithm is capable of estimating the reinforcing steel bar position to within (0-1) mm.

Keywords: GPR, NDT, Reinforced concrete structures, Rebar location.

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Authors: Melissa Mattos, Camila Lima, Ibraim Castro, Augusto Carioca, Saulo Magalhães, Paula Freitas, Keciany Oliveira

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Obesity is a chronic, multifactorial, relapsing disease that has increased dramatically over the years. Its control is considered a public health issue, and more and more treatments and interventions are being studied to reduce its prevalence. When interventions in lifestyle and the use of drugs do not generate lasting results, bariatric procedures emerge as a resource for obesity control. The main guidelines for the treatment of obesity emphasize the need for pre-procedure and post-procedure nutritional monitoring to avoid nutritional deficiencies that may occur. The individual who undergoes bariatric surgery needs to understand the changes that will be necessary for life in view of the intense anatomical and metabolic changes that result from surgical techniques. To assess the nutritional profile of patients who undergo bariatric surgery, we analyzed data from the medical records of all people who underwent sleeve-type bariatric surgery from January to June 2022 at a clinic in the City of Fortaleza. 38 patients were analyzed, 32 women and 6 men in the pre-surgical period, 6 and 12 months after surgery. The data showed an average weight loss of 24.45% at 6 months and 30.85% at 12 months, with a reduction of 21.32% and 30.41%, respectively, in the fat percentage, also indicating that 13.15% used drugs for weight loss during this period, leading to reflection on the isolated long-term efficacy of bariatric surgery, requiring multidisciplinary follow-up for a change in lifestyle. Only 12 individuals, corresponding to 31.57%, reached eutrophic BMI 12 months after surgery, 20 individuals remained overweight, corresponding to 52.63% of the sample, and 6 individuals (15.78%) remained in the BMI obese class I. As for body composition, there was a 52.39% reduction in fat mass and a 12.82% reduction in muscle mass, and 21% of individuals underwent cholecystectomy. Sleeve-type bariatric surgery promoted significant weight loss after 1 year of the procedure, with a reduction in body fat percentage and fat mass. Most patients were still overweight and had a significant reduction in muscle mass.

Keywords: bariatric surgery, sleeve gastrectomy, obesity, sleeve

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Nour Mohamad Fayad

Abstract:

Complex and extensively researched, the impact of corruption on economic growth seems to be intricate. Many experts believe that corruption reduces economic development. However, counterarguments have suggested that corruption either promotes growth and development or has no significant impact on economic performance. Clearly, there is no consensus in the economics literature regarding the possible relationship between corruption and economic development. Corruption's complex and clandestine nature, which makes it difficult to define and measure, is one of the obstacles that must be overcome when investigating its effect on an economy. In an attempt to contribute to the ongoing debate, this study examines the impact of corruption on economic growth in the Middle East and North Africa (MENA) region between 2000 and 2021 using a Customized Corruption Index-CCI and panel data on MENA countries. These countries were selected because they are understudied in the economic literature, and despite the World Bank's recent emphasis on corruption in the developing world, the MENA countries have received little attention. The researcher used Cobb-Douglas functional form to test corruption in MENA using a customized index known as Customized Corruption Index-CCI to track corruption over almost 20 years, then used the dynamic panel data. The findings indicate that there is a positive correlation between corruption and economic growth, but this is not consistent across all MENA nations. First, the relatively recent lack of data from MENA nations. This issue is related to the inaccessibility of data for many MENA countries, particularly regarding the returns on resources, private malfeasance, and other variables in Gulf countries. In addition, the researcher encountered several restrictions, such as electricity and internet outages, due to the fact that he is from Lebanon, a country whose citizens have endured difficult living conditions since the Lebanese crisis began in 2019. Demonstrating a customized index known as Customized Corruption Index-CCI that suits the characteristics of MENA countries to peculiarly measure corruption in this region, the outcome of the Customized Corruption Index-CCI is then compared to the Corruption Perception Index-CPI and Control of Corruption from World Governance Indicator-CC from WGI.

Keywords: corruption, economic growth, corruption measurements, empirical review, impact of corruption

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Authors: Carlos Riascos, Peter Thomson

Abstract:

Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

Procedia PDF Downloads 295