Search results for: conditional proportional reversed hazard rate model

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

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This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

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Authors: Asghar Arif

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Lung cancer has been recognized as one of the greatest common cancers, causing the annual mortality rate of about 1.2 million people in the world. Lung cancer is the most prevalent cancer in men and the third-most common cancer among women (after breast and digestive cancers).Recent evidences have shown the inflammatory process as one of the potential factors of cancer. Tuberculosis (TB), pneumonia, and chronic bronchitis are among the most important inflammation-inducing factors in the lungs, among which TB has a more profound role in the emergence of cancer.TB is one of the important mortality factors throughout the world, and 205,000 death cases are reported annually due to this disease. Chronic inflammation and fibrosis due to TB can induce genetic mutation and alternations. Parenchyma tissue of lung is involved in both diseases of TB and lung cancer, and continuous cough in lung cancer, morphological vascular variations, lymphocytosis processes, and generation of immune system mediators such as interleukins, are all among the factors leading to the hypothesis regarding the role of TB in lung cancer Some reports have shown that the induction of necrosis and apoptosis or TB reactivation, especially in patients with immune-deficiency, may result in increasing IL-17 and TNF_α, which will either decrease P53 activity or increase the expression of Bcl-2, decrease Bax-T, and cause the inhibition of caspase-3 expression due to decreasing the expression of mitochondria cytochrome oxidase. It has been also indicated that following the injection of BCG vaccine, the host immune system will be reinforced, and in particular, the rates of gamma interferon, nitric oxide, and interleukin-2 are increased. Therefore, CD4 + lymphocyte function will be improved, and the person will be immune against cancer.Numerous prospective studies have so far been conducted on the role of TB in lung cancer, and it seems that this disease is effective in that particular cancer.One of the main challenges of lung cancer is its correct and timely diagnosis. Unfortunately, clinical symptoms (such as continuous cough, hemoptysis, weight loss, fever, chest pain, dyspnea, and loss of appetite) and radiological images are similar in TB and lung cancer. Therefore, anti-TB drugs are routinely prescribed for the patients in the countries with high prevalence of TB, like Pakistan. Regarding the similarity in clinical symptoms and radiological findings of lung cancer, proper diagnosis is necessary for TB and respiratory infections due to nontuberculousmycobacteria (NTM). Some of the drug resistive TB cases are, in fact, lung cancer or NTM lung infections. Acid-fast staining and histological study of phlegm and bronchial washing, culturing and polymerase chain reaction TB are among the most important solutions for differential diagnosis of these diseases. Briefly, it is assumed that TB is one of the risk factors for cancer. Numerous studies have been conducted in this regard throughout the world, and it has been observed that there is a significant relationship between previous TB infection and lung cancer. However, to prove this hypothesis, further and more extensive studies are required. In addition, as the clinical symptoms and radiological findings of TB, lung cancer, and non-TB mycobacteria lung infections are similar, they can be misdiagnosed as TB.

Keywords: TB and lung cancer, TB people, TB servivers, TB and HIV aids

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Authors: Seyed Abdolreza Mosavi, Alireza Babakhan, Elham Sadat Hoseinifard

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Knowledge-based firms need to design mechanisms for continuous absorptive and creation of knowledge in order to ensure their survival in the competitive arena and to follow the path of development. Considering the project-oriented nature of product development activities in knowledge-based firms on the one hand and the importance of analyzing the factors affecting knowledge absorptive capacity in these firms on the other, the purpose of this study is to identify and classify the factors affecting project management practices on absorptive knowledge capacity. For this purpose, we have studied and reviewed the theoretical literature in the field of project management and absorptive knowledge capacity so as to clarify its dimensions and indexes. Then, using the ISM method, the relationship between them has been studied. To collect data, 21 questionnaires were distributed in project-oriented knowledge-based companies. The results of the ISM method analysis provide a model for the relationship between project management activities and knowledge absorptive capacity, which includes knowledge acquisition capacity, scope management, time management, cost management, quality management, human resource management, communications management, procurement management, risk management, stakeholders management and integration management. Having conducted the MICMAC analysis, we divided the variables into three groups of independent, relational and dependent variables and came up with no variables to be included in the group of autonomous variables.

Keywords: knowledge absorptive capacity, project management practices, knowledge-based firms, interpretive structural modeling

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Authors: C. A. Roberts, S. L. Mascaro, J. R. Gerrish, J. L. Horner

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Management-intensive Grazing (MiG) is a practice that rotates livestock through paddocks in a way that best matches the nutrient requirements of the animal to the yield and quality of the pasture. In the USA, MiG has been taught to livestock producers throughout the state of Missouri in 2- and 3-day workshops called “Missouri Grazing Schools.” The economic impact of these schools was quantified using IMPLAN software. The model included hectares of adoption, animal performance, carrying capacity, and input costs. To date, MiG, as taught in the Missouri Grazing Schools, has been implemented on more than 70,000 hectares in Missouri. The economic impact of these schools is presently $125 million USD per year added to the state economy. This magnitude of impact is the result not only of widespread adoption but also because of increased livestock carrying capacity; in Missouri, a capacity increase of 25 to 30% has been well documented. Additional impacts have been MiG improving forage quality and reducing the cost of feed and fertilizer. The environmental impact of MiG in the state of Missouri is currently being estimated. Environmental impact takes into account the reduction in the application of commercial fertilizers; in MiG systems, nitrogen is supplied by N fixation from legumes, and much of the P and K is recycled naturally by well-distributed manure. The environmental impact also estimates carbon sequestration and methane production; MiG can increase carbon sequestration and reduce methane production in comparison to default grazing practices and feedlot operations in the USA.

Keywords: agricultural education, forage quality, management-intensive grazing, nutrient cycling, stock density, sustainable agriculture

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Authors: Firas Mohamad Al-Sabek

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The Purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.

Keywords: construction project, total quality management, management commitment, cost, theoretical framework

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

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In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

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Authors: Mohamed Abo El Nasr, Mohamed Shoeib, Abdelhamid Abdelkhalik, Amro Serag

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Background: Early assessment of severity of chest trauma, either blunt or penetrating is of critical importance in prediction of patient outcome. Different trauma scoring systems are widely available and are based on anatomical or physiological parameters to expect patient morbidity or mortality. Up till now, there is no ideal, universally accepted trauma score that could be applied in all trauma centers and is suitable for assessment of severity of chest trauma patients. Aim: Our aim was to compare various trauma scoring systems regarding their predictability of morbidity and mortality in chest trauma patients. Patients and Methods: This study was a prospective study including 400 patients with chest trauma who were managed at Tanta University Emergency Hospital, Egypt during a period of 2 years (March 2014 until March 2016). The patients were divided into 2 groups according to the mode of trauma: blunt or penetrating. The collected data included age, sex, hemodynamic status on admission, intrathoracic injuries, and associated extra-thoracic injuries. The patients outcome including mortality, need of thoracotomy, need for ICU admission, need for mechanical ventilation, length of hospital stay and the development of acute respiratory distress syndrome were also recorded. The relevant data were used to calculate the following trauma scores: 1. Anatomical scores including abbreviated injury scale (AIS), Injury severity score (ISS), New injury severity score (NISS) and Chest wall injury scale (CWIS). 2. Physiological scores including revised trauma score (RTS), Acute physiology and chronic health evaluation II (APACHE II) score. 3. Combined score including Trauma and injury severity score (TRISS ) and 4. Chest-Specific score Thoracic trauma severity score (TTSS). All these scores were analyzed statistically to detect their sensitivity, specificity and compared regarding their predictive power of mortality and morbidity in blunt and penetrating chest trauma patients. Results: The incidence of mortality was 3.75% (15/400). Eleven patients (11/230) died in blunt chest trauma group, while (4/170) patients died in penetrating trauma group. The mortality rate increased more than three folds to reach 13% (13/100) in patients with severe chest trauma (ISS of >16). The physiological scores APACHE II and RTS had the highest predictive value for mortality in both blunt and penetrating chest injuries. The physiological score APACHE II followed by the combined score TRISS were more predictive for intensive care admission in penetrating injuries while RTS was more predictive in blunt trauma. Also, RTS had a higher predictive value for expectation of need for mechanical ventilation followed by the combined score TRISS. APACHE II score was more predictive for the need of thoracotomy in penetrating injuries and the Chest-Specific score TTSS was higher in blunt injuries. The anatomical score ISS and TTSS score were more predictive for prolonged hospital stay in penetrating and blunt injuries respectively. Conclusion: Trauma scores including physiological parameters have a higher predictive power for mortality in both blunt and penetrating chest trauma. They are more suitable for assessment of injury severity and prediction of patients outcome.

Keywords: chest trauma, trauma scores, blunt injuries, penetrating injuries

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Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison

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In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H₂O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO₂ emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.

Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

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Fermentation is well known as an essential process in cocoa beans. Besides to develop the precursor of cocoa flavour, it also induce the colour changes in the beans.The fermentation process is reported to be influenced by duration of pod storage and fermentation. Therefore, this study was conducted to evaluate colour of Malaysian cocoa beans and how the pods storage and fermentation duration using shallow box technique will effect on it characteristics. There are two factors being studied ie duration of cocoa pod storage (0, 2, 4, and 6 days) and duration of cocoa fermentation (0, 1, 2, 3, 4 and 5 days). The experiment is arranged in 4 x 6 factorial design with 24 treatments and arrangement is in a Completely Randomised Design (CRD). The produced beans is inspected for colour changes under artificial light during cut test and divided into four groups of colour namely fully brown, purple brown, fully purple and slaty. Cut tests indicated that cocoa beans which are directly dried without undergone fermentation has the highest slaty percentage. However, application of pods storage before fermentation process is found to decrease the slaty percentage. In contrast, the percentages of fully brown beans start to dominate after two days of fermentation, especially from four and six days of pods storage batch. Whereas, almost all batch have percentage of fully purple less than 20%. Interestingly, the percentage of purple brown beans are scattered in the entire beans batch regardless any specific trend. Meanwhile, statistical analysis using General Linear Model showed that the pods storage has a significant effect on the colour characteristic of the Malaysian dried beans compared to fermentation duration.

Keywords: cocoa beans, colour, fermentation, shallow box

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Authors: Apurva Singh, S. P. Jaiswar, Apala Priyadarshini, Akancha Pandey

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Objective: The aim of this study is to find the association of PON1 gene polymorphism with pesticides In RPL subjects. Background: Recurrent pregnancy loss (RPL) is defined as three or more sequential abortions before the 20th week of gestation. Pesticides and its derivatives (organochlorine and organophosphate) are proposed to accommodate a ruler chemical for RPL in the sub-humid region of India. The paraoxonase-1 enzyme (PON1) plays an important role in the toxicity of some organophosphate pesticides, with low PON1 activity being associated with higher pesticide sensitivity Methodology: This is a case-control study done in Department of Obstetrics & Gynaecology & Department of Biochemistry, K.G.M.U, Lucknow, India. The subjects were enrolled after fulfilling the inclusion & exclusion criteria. Inclusion criteria: Cases- Subject having two or more spontaneous abortions & Control- Healthy female having one or more alive child was selected. Exclusion criteria: Cases & Control- Subject having the following disease will be excluded from the study Diabetes mellitus, Hypertension, Tuberculosis, Immunocompromised patients, any endocrine disorder and genital, colon or breast cancer any other malignancies. Blood samples were collected in EDTA tubes from cases & healthy control women & genomic DNA was extracted by phenol-chloroform method. The estimation of pesticides residue from blood was done by HPLC. Biochemical estimation was also performed. Genotyping of PON1 gene polymorphism was performed by RFLP. Statistical analysis of the data was performed using the SPSS16.3 software. Results: A sum of total 14 pesticides (12 organochlorine and 2 organophosphate) selected on the basis of their persistent nature and consumption rate. The significant level of pesticide (ppb) estimated by the Mann whiney test and it was found to be significant at higher level of β-HCH (p:0.04), γ-HCH (p:0.001), δ-HCH (p: 0.002), chloropyrifos (p:0.001), pp-DDD (p:0.001) and fenvalrate (p: 0.001) in case group compare to its control. The level of antioxidant enzymes were found to be significantly decreased among the cases. Wild homozygous TT was more frequent and prevalent among control groups. However, heterozygous group (Tt) was more in cases than control groups (CI-0.3-1.3) (p=0.06). Conclusion: Higher levels of pesticides with endocrine disrupting potential in cases indicate the possible role of these compounds as one of the causes of recurrent pregnancy loss. Possibly, increased pesticide level appears to indicate increased levels of oxidative damage that has been associated with the possible cause of Recurrent Miscarriage, it may reflect indirect evidence of toxicity rather than the direct cause. Since both factors are reported to increase risk, individuals with higher levels of these 'Toxic compounds' especially in 'high-risk genotypes' might be more susceptible to recurrent pregnancy loss.

Keywords: paraoxonase, pesticides, PON1, RPL

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: Justin Durham, Chanda Rooney, Robert Mather, Mickie Vanhoy

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The psychological construct of empathy is to understand a person’s cognitive perspective and experience the other person’s emotional state. Deciphering emotional states is conducive for interpreting vicarious pain. Observing others' physical pain activates neural networks related to the actual experience of pain itself. The study addresses empathy as a nonlinear dynamic process of simulation for individuals to understand the mental states of others and experience vicarious pain, exhibiting self-organized criticality. Such criticality follows from a combination of neural networks with an excitatory feedback loop generating bistability to resonate permutated empathy. Cortical networks exhibit diverse patterns of activity, including oscillations, synchrony and waves, however, the temporal dynamics of neurophysiological activities underlying empathic processes remain poorly understood. Mu rhythms are EEG oscillations with dominant frequencies of 8-13 Hz becoming synchronized when the body is relaxed with eyes open and when the sensorimotor system is in idle, thus, mu rhythm synchrony is expected to be highest in baseline conditions. When the sensorimotor system is activated either by performing or simulating action, mu rhythms become suppressed or desynchronize, thus, should be suppressed while observing video clips of painful injuries if previous research on mirror system activation holds. Twelve undergraduates contributed EEG data and survey responses to empathy and psychopathy scales in addition to watching consecutive video clips of sports injuries. Participants watched a blank, black image on a computer monitor before and after observing a video of consecutive sports injuries incidents. Each video condition lasted five-minutes long. A BIOPAC MP150 recorded EEG signals from sensorimotor and thalamocortical regions related to a complex neural network called the ‘pain matrix’. Physical and social pain are activated in this network to resonate vicarious pain responses to processing empathy. Five EEG single electrode locations were applied to regions measuring sensorimotor electrical activity in microvolts (μV) to monitor mu rhythms. EEG signals were sampled at a rate of 200 Hz. Mu rhythm desynchronization was measured via 8-13 Hz at electrode sites (F3 & F4). Data for each participant’s mu rhythms were analyzed via Fast Fourier Transformation (FFT) and multifractal time series analysis.

Keywords: desynchronization, dynamical systems theory, electroencephalography (EEG), empathy, multifractal time series analysis, mu waveform, neurophysiology, pain simulation, social cognition

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: Delia Gabriela Moisa, Demos Parapanos, Tim Heap

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The tourism sector is mainly comprised of small and medium-sized tourism enterprises (SMEs), representing approximately 80% of global businesses in this field. These entities require focused attention and support to address challenges, ensuring their competitiveness and relevance in a dynamic industry characterized by continuously changing customer preferences. To address these challenges, it becomes imperative to consider not only socio-demographic factors but also delve into the intricate interplay of psychological elements influencing consumer behavior. This study investigates the impact of personality traits and travel motivations on visitor activities in Cumbria, United Kingdom, an iconic region marked by UNESCO World Heritage Sites, including The Lake District National Park and Hadrian's Wall. With a £4.1 billion tourism industry primarily driven by SMEs, Cumbria serves as an ideal setting for examining the relationship between tourist psychology and activities. Employing the Big Five personality model and the Travel Career Pattern motivation theory, this study aims to explain the relationship between psychological factors and tourist activities. The study further explores SME perspectives on personality-based market segmentation, providing strategic insights into addressing evolving tourist preferences.This pioneering mixed-methods study integrates quantitative data from 330 visitor surveys, subsequently complemented by qualitative insights from tourism SME representatives. The findings unveil that socio-demographic factors do not exhibit statistically significant variations in the activities pursued by visitors in Cumbria. However, significant correlations emerge between personality traits and motivations with preferred visitor activities. Open-minded tourists gravitate towards events and cultural activities, while Conscientious individuals favor cultural pursuits. Extraverted tourists lean towards adventurous, recreational, and wellness activities, while Agreeable personalities opt for lake cruises. Interestingly, a contrasting trend emerges as Extraversion increases, leading to a decrease in interest in cultural activities. Similarly, heightened Agreeableness corresponds to a decrease in interest in adventurous activities. Furthermore, travel motivations, including nostalgia and building relationships, drive event participation, while self-improvement and novelty-seeking lead to adventurous activities. Additionally, qualitative insights from tourism SME representatives underscore the value of targeted messaging aligned with visitor personalities for enhancing loyalty and experiences. This study contributes significantly to scholarship through its novel framework, integrating tourist psychology with activities and industry perspectives. The proposed conceptual model holds substantial practical implications for SMEs to formulate personalized offerings, optimize marketing, and strategically allocate resources tailored to tourist personalities. While the focus is on Cumbria, the methodology's universal applicability offers valuable insights for destinations globally seeking a competitive advantage. Future research addressing scale reliability and geographic specificity limitations can further advance knowledge on this critical relationship between visitor psychology, individual preferences, and industry imperatives. Moreover, by extending the investigation to other districts, future studies could draw comparisons and contrasts in the results, providing a more nuanced understanding of the factors influencing visitor psychology and preferences.

Keywords: personality trait, SME, tourist behaviour, tourist motivation, visitor activity

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Authors: Fella Lahmar

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This chapter investigates the educational reforms in Algeria, highlighting the challenges and complexities that arise in the context of globalization, equity, and decolonization. While Algeria’s education system historically had a socialist-economic model grounded in Islamic values, contemporary reforms reflect global influences and aspirations for cultural authenticity. The study employed a qualitative approach, utilizing semi-structured interviews with a diverse sample of 15 participants intimately involved in the Algerian education system. Analysis of the data reveals a discrepancy between the educational system’s pedagogical practices and students’ diverse learning needs, implying ramifications for educational equity and social justice. Furthermore, a critical tension was evident between global influences, local cultural authenticity, and the endeavor to decolonize education. In conclusion, the chapter advocates for reforms that prioritize the students’ holistic development and well-being while fostering intrinsic motivation and engagement. This entails re-evaluating curriculum frameworks, assessment strategies, and pedagogies in light of Algeria’s cultural and religious heritage. The chapter also calls for future research to explore methods for innovatively integrating cultural heritage into education in ways to cultivate learners who are both locally grounded and globally aware.

Keywords: impact of globalization on education, parental involvement in education, marketization of education, policy enactment and reform, curriculum overload, holistic approach, shadow education

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Authors: Mengping Cheng, John Everatt, Alison Arrow, Amanda Denston

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Based on the available evidence, Chinese heritage language learners have a basic level of Chinese language proficiency with lower capability in literacy compared to speaking. Low levels of literacy are likely related to the lack of reading activities in current textbook-based pedagogy used in Chinese community schools. The present study aims to use Reading to Learn pedagogy which is a top-down language learning model and test the effectiveness of Reading to Learn on Chinese heritage learners’ written vocabulary acquisition. A quasi-experiment with the pre-test/post-test non-equivalent group design was conducted. The experimental group received Reading to Learn instructions and the control group had traditional textbook-based instructions. Participants were given Chinese characters tasks (a recognize-and-read task and a listen-and-point task), vocabulary tasks (a receptive vocabulary task and a productive vocabulary task) and a sentence cloze test in pre-tests and post-tests. Data collection is in progress and results will be available shortly. If the results show more improvement of Chinese written vocabulary in the experimental group than in the control group, it will be recommended that Reading to Learn pedagogy is valuable to be used to maintain and develop Chinese heritage language literacy.

Keywords: Chinese heritage language, experimental research, Reading to Learn pedagogy, vocabulary acquisition

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Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: content analysis, factors, integrated waste management system, time series

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Authors: Maryam Solgi, Behzad Shahmohammadi, Morteza Raissi Dehkordi

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One of the main steps for seismic retrofitting of buildings is to determine the vulnerability of structures. While current procedures for evaluating existing buildings are complicated, and there is no limitation between short, middle-high, and tall buildings. This research utilizes a simplified method for assessing structures, which is adequate for existing reinforced concrete buildings. To approach this aim, Simple Lateral Mechanisms Analysis (SLaMA) procedure proposed by NZSEE (New Zealand Society for Earthquake Engineering) has been carried out. In this study, three RC moment-resisting frame buildings are determined. First, these buildings have been evaluated by inelastic static procedure (Pushover) based on acceptance criteria. Then, Park-Ang Damage Index is determined for the whole members of each building by Inelastic Time History Analysis. Next, the Simple Lateral Mechanisms Analysis procedure, a hand method, is carried out to define the capacity of structures. Ultimately, existing procedures are compared with Peak Ground Acceleration caused to fail (PGAfail). The results of this comparison emphasize that the Pushover procedure and SLaMA method define a greater value of PGAfail than the Park-Ang Damage model.

Keywords: peak ground acceleration caused to fail, reinforced concrete moment-frame buildings, seismic vulnerability analysis, simple lateral mechanisms analysis

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Authors: Thao Nguyen, Maximiliano Hyon, Sany Rajagukguk, Anna Melkonyan

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Introduction: Type 2 Diabetes is a well-established risk factor for severe SARS-CoV-2 infection. Uncontrolled hyperglycemia in patients with established or newly diagnosed diabetes is associated with poor outcomes, including increased mortality and hospital length of stay. Objectives: Our study aims to compare three different glycemic management strategies and their association with clinical outcomes in patients hospitalized for moderate to severe SARS-CoV-2 infection. Identifying optimal glycemic management strategies will improve the quality of patient care and improve their outcomes. Method: This is a retrospective observational study on patients hospitalized at Adventist Health White Memorial with severe SARS-CoV-2 infection from 11/1/2020 to 02/28/2021. The following inclusion criteria were used: positive SARS-CoV-2 PCR test, age >18 yrs old, diabetes or random glucose >200 mg/dL on admission, oxygen requirement >4L/min, and treatment with glucocorticoids. Our exclusion criteria included: ICU admission within 24 hours, discharge within five days, death within five days, and pregnancy. The patients were divided into three glycemic management groups: Group 1, managed solely by the Primary Team, Group 2, by Pharmacy; and Group 3, by Endocrinologist. Primary outcomes were average glucose on Day 5, change in glucose between Days 3 and 5, and average insulin dose on Day 5 among groups. Secondary outcomes would be upgraded to ICU, inpatient mortality, and hospital length of stay. For statistics, we used IBM® SPSS, version 28, 2022. Results: Most studied patients were Hispanic, older than 60, and obese (BMI >30). It was the first CV-19 surge with the Delta variant in an unvaccinated population. Mortality was markedly high (> 40%) with longer LOS (> 13 days) and a high ICU transfer rate (18%). Most patients had markedly elevated inflammatory markers (CRP, Ferritin, and D-Dimer). These, in combination with glucocorticoids, resulted in severe hyperglycemia that was difficult to control. Average glucose on Day 5 was not significantly different between groups primary vs. pharmacy vs. endocrine (220.5 ± 63.4 vs. 240.9 ± 71.1 vs. 208.6 ± 61.7 ; P = 0.105). Change in glucose from days 3 to 5 was not significantly different between groups but trended towards favoring the endocrinologist group (-26.6±73.6 vs. 3.8±69.5 vs. -32.2±84.1; P= 0.052). TDD insulin was not significantly different between groups but trended towards higher TDD for the endocrinologist group (34.6 ± 26.1 vs. 35.2 ± 26.4 vs. 50.5 ± 50.9; P=0.054). The endocrinologist group used significantly more preprandial insulin compared to other groups (91.7% vs. 39.1% vs. 65.9% ; P < 0.001). The pharmacy used more basal insulin than other groups (95.1% vs. 79.5% vs. 79.2; P = 0.047). There were no differences among groups in the clinical outcomes: LOS, ICU upgrade, or mortality. Multivariate regression analysis controlled for age, sex, BMI, HbA1c level, renal function, liver function, CRP, d-dimer, and ferritin showed no difference in outcomes among groups. Conclusion: Given high-risk factors in our population, despite efforts from the glycemic management teams, it’s unsurprising no differences in clinical outcomes in mortality and length of stay.

Keywords: glycemic management, strategies, hospitalized, SARS-CoV-2, outcomes

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Authors: Bessaha Hassiba, Bouraada Mohamed

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Layered double hydroxide with Zn/(Al+Fe) molar ratio of 3:1 was synthesized by co-precipitation method and their calcined product was obtained by heating treatment of ZAF-HT at 500°C. The calcined and uncalcined materials were used to remove weak acid dyes: indigo carmine (IC) and green bezanyl-F2B (F2B) in aqueous solution. The synthesized materials were characterized by XRD, SEM, FTIR and TG/DTA analysis confirming the formation of pure layered structure of ZAF-HT, the destruction of the original structure after calcination and the intercalation of the dyes molecules. Moreover, the interlayer distance increases from 7.645 Å in ZAF-HT to 19.102 Å after the dyes sorption. The dose of the adsorbents was chosen 0.5 g/l while the initial concentrations were 250 and 750 mg/l for indigo carmine and green bezanyl-F2B respectively. The sorption experiments were carried out at ambient temperature and without adjusting the initial solution pH (pHi = 6.10 for IC and pHi = 5.01 for F2B). In addition, the maximum adsorption capacities obtained by ZAF-HT and CZAF for both dyes followed the order: CZAF-F2B (1501.4 mg.g-1) > CZAF-IC (617.3 mg.g-1) > ZAF-HT-IC (41.4 mg.g-1) > ZAF-HT-F2B (28.9 mg.g-1). The removal of indigo carmine and green bezanyl-F2B by ZAF-HT was due to the anion exchange and/or the adsorption on the surface. By using the calcined material (CZAF), the removal of the dyes was based on a particular property, called ‘memory effect’. CZAF recover the pristine structure in the presence anionic molecules such as acid dyes where they occupy the interlayer space. The sorption process was spontaneous in nature and followed pseudo-second-order. The isotherms showed that the removal of IC and F2B by ZAF-HT and CZAF were consistent with Langmiur model.

Keywords: acid dyes, adsorption, calcination, layered double hydroxides

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

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Authors: Soumia Merat, Lynda Djerbal, Ramdane Bahar, Mohammed Amin Benbouras

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Along with shear wave, many soil parameters are associated with the standard penetration test (SPT) as a dynamic in situ experiment. Both SPT-N data and geophysical data do not often exist in the same area. Statistical analysis of correlation between these parameters is an alternate method to estimate Vₛ conveniently and without additional investigations or data acquisition. Shear wave velocity is a basic engineering tool required to define dynamic properties of soils. In many instances, engineers opt for empirical correlations between shear wave velocity (Vₛ) and reliable static field test data like standard penetration test (SPT) N value, CPT (Cone Penetration Test) values, etc., to estimate shear wave velocity or dynamic soil parameters. The relation between Vs and SPT- N values of Algiers area is predicted using the collected data, and it is also compared with the previously suggested formulas of Vₛ determination by measuring Root Mean Square Error (RMSE) of each model. Algiers area is situated in high seismic zone (Zone III [RPA 2003: réglement parasismique algerien]), therefore the study is important for this region. The principal aim of this paper is to compare the field measurements of Down-hole test and the empirical models to show which one of these proposed formulas are applicable to predict and deduce shear wave velocity values.

Keywords: empirical models, RMSE, shear wave velocity, standard penetration test

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Authors: M. Maleki Sadabad, A. Pointing, N. Marashi

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With respect to the role and increasing importance of technology for countries development, in recent decades technology development has paid attention in a systematic form. Nowadays the markets face with highly complicated and competitive conditions in foreign markets, therefore, evaluation and selection of technology effectiveness and also formulating technology strategy have changed into a vital subject for some organizations. The study introduces the standards of empowerment evaluation and technology attractiveness especially strategic technologies which explain the way of technology evaluation, selection and finally formulating suitable technology strategy in the field of drilling in South Azadegan oil field. The study firstly identifies the key challenges of oil fields in order to evaluate the technologies in field of drilling in South Azadegan oil field through an interview with the experts of industry and then they have been prioritised. In the following, the existing and new technologies were identified to solve the challenges of South Azadegan oil field. In order to explore the ability, availability, and attractiveness of every technology, a questionnaire based on Julie indices has been designed and distributed among the industry elites. After determining the score of ability, availability and attractiveness, every technology which has been obtained by the average of expert’s ideas, the technology package has been introduced by Morin’s model. The matrix includes four areas which will follow the especial strategy. Finally, by analysing the above matrix, the technology options have been suggested in order to select and invest.

Keywords: technology, technology identification, drilling technologies, technology capability

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Authors: Reza Akbari, Jalal MontazeriFashtali, PeymanMomeni Taromsari

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Pipeline systems, play an important role as a vital element in reducing or increasing the risk of earthquake damage and vulnerability. Pipelines are suitable, cheap, fast, and safe routes for transporting oil, gas, water, sewage, etc. The sepipelines must pass from a wide geographical area; hence they will structurally face different environmental and underground factors of earthquake forces’ effect. Therefore, structural engineering analysis and design for this type of lines requires the understanding of relevant parameters behavior and lack of familiarity with them can cause irreparable damages and risks to design and execution, especially in the face of earthquakes. Today, buried pipelines play an important role in human life cycle, thus, studying the vulnerability of pipeline systems is of particular importance. This study examines the behavior of buried pipelines affected by strike-slip fault. Studied fault is perpendicular to the tube axis and causes stress and deformation in the tube by sliding horizontally. In this study, the pipe-soil interaction is accurately simulated, so that one can examine the large displacements and strains, nonlinear material behavior and contact and friction conditions of soil and pipe. The results can be used for designing buried pipes and determining the amount of fault displacement that causes the failure of the buried pipes.

Keywords: pipe lines , earthquake , fault , soil-fault interaction

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