Search results for: frequency features

Authors: R. M. Bashir, Sabo Elizabeth

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Electronic learning is an increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. An investigation on the assessment of e-learning facilities and information need by open and distance learning students in Jalingo, Nigeria was conducted. Structured questionnaires were administered to 70 students of the university. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Information on assessment of e-learning facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women, a large proportion of the respondents are married and there are more matured students. A high proportion of the students obtained qualifications higher than the secondary school certificate. The proportion of computer literate students was higher compared with those students that owned a computer. Inadequate e-books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities. Inadequate computer facilities caused delay in examination schedule at the study center. Open and distance learning students required to a high extent information on university timetable and schedule of activities, books (hard and e-books) and reference materials and contact with course coordinators via internet for better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: Laila Seada, Ashraf Ibrahim, Amjad Al Shammari

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Background and Objectives: Breast carcinoma is the most common cancer of females in Hail region, accounting for 31% of all diagnosed cancer cases followed by thyroid carcinoma (25%) and colorectal carcinoma (13%). Methods: In the present retrospective study, all cases of breast lesions received at the histopathology department in King Khalid Hospital, Hail, during the period from May 2011 to April 2016 have been retrieved from department files. For all cases, a trucut biopsy, lumpectomy, or modified radical mastectomy was available for histopathologic diagnosis, while 105/140 (75%) had, as well, preoperative fine needle aspirates (FNA). Results: 49 cases out of 140 (35%) breast lesions were carcinomas: 44/49 (89.75%) was invasive ductal, 2/49(4.1%) invasive lobular carcinomas, 1/49(2.05%) intracystic low grade papillary carcinoma and 2/49 (4.1%) ductal carcinoma in situ (DCIS). Mean age for malignant cases was 45.06 (+/-10.58): 32.6% were below the age of 40 and 30.6 below 50 years, 18.3% below 60 and 16.3% below 70 years. For the benign group, mean age was 32.52 (+/10.5) years. Benign lesions were in order of frequency: 34 fibroadenomas, 14 fibrocystic disease, 12 chronic mastitis, five granulomatous mastitis, three intraductal papillomas, and three benign phyllodes tumor. Tubular adenoma, lipoma, skin nevus, pilomatrixoma, and breast reduction specimens constituted the remaining specimens. Conclusion: Breast lesions are common in our series and invasive carcinoma accounts for more than 1/3^rd of the lumps, with 63.2% incidence in pre-menopausal ladies, below the age of 50 years. FNA as a non-invasive procedure, proved to be an effective tool in diagnosing both benign and malignant/suspicious breast lumps and should continue to be used as a first assessment line of palpable breast masses.

Keywords: age incidence, breast carcinoma, fine needle aspiration, hail region

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Authors: Jaan Lellep, Shahid Mubasshar

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A numerical solution is developed for simply supported nanoarches based on the non-local theory of elasticity. The nanoarch under consideration has a step-wise variable cross-section and is weakened by crack-like defects. It is assumed that the cracks are stationary and the mechanical behaviour of the nanoarch can be modeled by Eringen’s non-local theory of elasticity. The physical and thermal properties are sensitive with respect to changes of dimensions in the nano level. The classical theory of elasticity is unable to describe such changes in material properties. This is because, during the development of the classical theory of elasticity, the speculation of molecular objects was avoided. Therefore, the non-local theory of elasticity is applied to study the vibration of nanostructures and it has been accepted by many researchers. In the non-local theory of elasticity, it is assumed that the stress state of the body at a given point depends on the stress state of each point of the structure. However, within the classical theory of elasticity, the stress state of the body depends only on the given point. The system of main equations consists of equilibrium equations, geometrical relations and constitutive equations with boundary and intermediate conditions. The system of equations is solved by using the method of separation of variables. Consequently, the governing differential equations are converted into a system of algebraic equations whose solution exists if the determinant of the coefficients of the matrix vanishes. The influence of cracks and steps on the natural vibration of the nanoarches is prescribed with the aid of additional local compliance at the weakened cross-section. An algorithm to determine the eigenfrequencies of the nanoarches is developed with the help of computer software. The effects of various physical and geometrical parameters are recorded and drawn graphically.

Keywords: crack, nanoarches, natural frequency, step

Procedia PDF Downloads 123

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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Authors: Jiranun Sreecharit, Anongnat Boonrut, Kunvadee Munvaradee, Phechnoy Singchungchai

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Hatyai Hospital as center of hospital with a capacity of 670 beds. Medicine intensive care units (MICU240) provide care for critically ill patients who are at high risk need to be monitored closely. Intravenous catheter is vital to help assess the level of water in the body fluids and medications. Potential complications such as infection. We need to have guidelines for the care of patients who received intravenous catheter used to achieve good results. The operations research in this study was intended 1) To study the effects of practice for nurses in caring for patients with central venous catheter to infection rate and 2) To assess the satisfaction of nurses and patient care practices in central venous catheterization patients in the MICU 240. The sample of the patient's central venous catheter crisis that everyone who admitted in MICU 240 during the period from October 2013 to May 2014. Samples prior to practice and 148 samples with 249 case of practice. A systematic review of the research NSWHealth Statewide Guideline for Intensive Care. Data were analyzed by statistics, percentages and frequency NON-PARAMETRICS with Mann-Whitney U. The finding revealed that: 1. Results of the practice patient care central venous catheter infection rates were found to be reduced from 35.14 percent to 25.3 percent. 2. The results of the evaluation of nurses and patients in the patient care practices central venous catheter found to be satisfied and happy to work 85 percent.

Keywords: clinical practice guidelines, central venous catheter, infection satisfaction

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Authors: Rajesha Kumar Alambi, Mansour Ahmed, Garudachari Bhadrachari, Safiyah Al-Muqahwi, Mansour Al-Rughaib, Jibu P. Thomas

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Membrane-based pressure assisted osmosis (PAO) for seawater desalination has the potential to overcome the challenges of forward osmosis technology. PAO technology is gaining interest among the research community to ensure the sustainability of freshwater with a significant reduction in energy. The requirements of PAO membranes differ from the FO membrane; as it needs a slightly higher porous with sufficient mechanical strength to overcome the applied hydraulic pressure. The porous metal-organic framework (MOF) as a filler for the membrane synthesis has demonstrated a great potential to generate new channels for water transport, high selectivity, and reduced fouling propensity. Accordingly, this study is aimed at fabricating the UiO-66 MOF-based thin film nanocomposite membranes with specific characteristics for water desalination by PAO. A PAO test unit manufactured by Trevi System, USA, was used to determine the performance of the synthesized membranes. Further, the synthesized membranes were characterized in terms of morphological features, hydrophilicity, surface roughness, and mechanical properties. The 0.05 UiO-66 loaded membrane produced highest flux of 38L/m2h and with low reverse salt leakage of 2.1g/m²h for the DI water as feed solution and 2.0 M NaCl as draw solutions at the inlet feed pressure of 0.6 MPa. The new membranes showed a good tolerance toward the applied hydraulic pressure attributed to the fabric support used during the membrane synthesis.

Keywords: metal organic framework, composite membrane, desalination, salt rejection, flux

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Authors: Javad Saeidaskari, Nader Khalafian

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The undesirable impact of vibrations induced by road and railway traffic is an important concern in modern world. These vibrations are transmitted through soil and cause disturbances to the residence area and high-tech production facilities alongside the train/traffic lines. In this paper for the first time a new method of soil improvement with vibration absorber material, is used to increase the damping factor, in other word, to reduce the ability of wave transitions in sand. In this study standard Firoozkooh No. 161 sand is used as the host sand. The semi rigid polyurethane (PU) foam which used in this research is one of the common materials for vibration absorbing purposes. Series of cyclic triaxial tests were conducted on remolded samples with identical relative density of 70% of maximum dry density for different volume percentage of shredded PU foam. The frequency of tests was 0.1 Htz with shear strain of 0.37% and 0.75% and also the effective confining pressures during the tests were 100 kPa and 350 kPa. In order to find out the best soil-PU foam mixture, different volume percent of PU foam varying from 10% to 30% were examined. The results show that adding PU foam up to 20%, as its optimum content, causes notable enhancement in damping ratio for both shear strains of 0.37% (52.19% and 69% increase for effective confining pressures of 100 kPa and 350 kPa, respectively) and 0.75% (59.56% and 59.11% increase for effective confining pressures of 100 kPa and 350 kPa, respectively). The results related to shear modulus present significant reduction for both shear strains of 0.37% (82.22% and 56.03% decrease for effective confining pressures of 100 kPa and 350 kPa, respectively) and 0.75% (89.32% and 39.9% decrease for effective confining pressures of 100 kPa and 350 kPa, respectively). In conclusion, shredded PU foams effectively affect the dynamic properties of sand and act as vibration absorber in soil.

Keywords: polyurethane foam, sand, damping ratio, shear modulus

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Authors: Mahmoud S Gewaily, Atif Hasan, Mohamed Kassab, Ali A. Mansour

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The current study was carried out on the nose of seventeenth healthy adult camels. Specimens were collected from slaughter houses then fixed, dissected and photographed. For ultra structural studies, fresh samples were fixed in different fixatives and prepared for examination by light, scanning and electron microscopes. Grossly, nose of the camel had narrow nostrils, slit like in outline. In the nasal cavity, the nasal vestibule was narrow and has scanty dorsal and lateral cartilaginous support. The Nasal conchae (dorsal, middle and ventral) enclosed the dorsal, middle conchal sinuses and no ventral conchal sinus; instead there was recess and bull a. The ethmoidal conchae (8 in number) were noticeably fewer than in the other domestic animals like ox and horse. The olfactory mucosa was restricted to a small area covering the caudal parts of the ethmoidal conchae. The lining epithelium of the nasal cavity changes gradually from stratified squamous epithelium in the nasal vestibule to pseudo stratified columnar ciliated in the respiratory region and finally, olfactory epithelium covering the caudal parts of the ethmoidal conchae. In the dromedary camel, a special feature was the presence of dense and relatively long hair covering the nostrils and the rostral part of the nasal vestibule. In conclusion, the anatomical features of the nose of the dromedary camel, especially in its rostral parts enable this animal to breathe properly in the sandy dry weather.

Keywords: camel nose, anatomy, dromedary camel, nasal vestibule

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Authors: Massimo Tadi, M. Hadi Mohammad Zadeh, Ozge Ogut

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Although how cities’ forms are structured is studied, more efforts are needed on systemic comprehensions and evaluations of the urban morphology through quantitative metrics that are able to describe the performance of a city in relation to its formal properties. More research is required in this direction in order to better describe the urban form characteristics and their impact on the environmental performance of cities and to increase their sustainability stewardship. With the aim of developing a better understanding of the built environment’s systemic structure, the intention of this paper is to present a holistic methodology for studying the behavior of the built environment and investigate the methods for measuring the effect of urban structure to the environmental performance. This goal will be pursued through an inquiry into the morphological components of the urban systems and the complex relationships between them. Particularly, this paper focuses on proximity, referring to the proximity of different land-uses, is a concept with which Integrated Modification Methodology (IMM) explains how land-use allocation might affect the choice of mobility in neighborhoods, and especially, encourage or discourage non-motived mobility. This paper uses proximity to demonstrate that the structure attributes can quantifiably relate to the performing behavior in the city. The target is to devise a mathematical pattern from the structural elements and correlate it directly with urban performance indicators concerned with environmental sustainability. The paper presents some results of this rigorous investigation of urban proximity and its correlation with performance indicators in four different areas in the city of Milan, each of them characterized by different morphological features.

Keywords: built environment, ecology, sustainable indicators, sustainability, urban morphology

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Din Eak Arathai

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The purpose of this research report is to investigate the language choice and use among the young generation of Malaysian Thais community. Besides that, it aims to investigate if there is a difference in language choice across the different domains. It will also examine if there has been a language shift from Thai to other languages by the young generation of Thai community in Malaysia. First the study focuses on the proficiency of Thai and other languages used by hundred (100) respondents belonging to young generation of Malaysian Thais aged range from 18-35. Next, language use and choice will be presented with a focus on the domains of family, friendship, entertainment and social. Finally, based on the findings and data collected, we will be able to see if language shift from Thai to other languages has occurred among the young Thai generation in Malaysia. The instrument used in this study was a 30-item questionnaire and the findings of the data analysis were presented in the form of frequency counts and percentages. The findings found that Thai language remains the most preferred language of choice among young Malaysian Thais but usage of other languages, such as Malay, English and Mandarin has increased and begun to influence the language choice of young Malaysian Thais and their proficiency of their mother tongue.In all the domains studied, Thai is almost exclusively the preferred language used when communicating with family. Malay is the most preferred language in communicating with friends while English is the most preferred language when communicating with colleagues. With regards to social and entertainment activities, young Malaysian Thais show great affinity for entertainment in the Thai language. In conclusion, the result of the study showed the beginning of young Malaysian Thais shifting to other languages, especially English and Malay through their daily choices when communicating with friends and family and especially through their language preferences in entertainment.

Keywords: language choice, language use, language shift, language maintenance, young Malaysian Thais, code switching, code mixing

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Authors: Mostafa Mabrouk, Basma E. Abdel-Ghany, Mona Moaness, Bothaina M. Abdel-Hady, Hanan H. Beherei

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Tissue engineering became a promising field for bone repair and regenerative medicine in which cultured cells, scaffolds and osteogenic inductive signals are used to regenerate tissues. The annual cost of treating bone defects in Egypt has been estimated to be many billions, while enormous costs are spent on imported bone grafts for bone injuries, tumors, and other pathologies associated with defective fracture healing. The current study is aimed at developing a more strategic approach in order to speed-up recovery after bone damage. This will reduce the risk of fatal surgical complications and improve the quality of life of people affected with such fractures. 3D scaffolds loaded with cheap nano-particles that possess an osteogenic effect were prepared by nano-electrospinning. The Microstructure and morphology characterizations of the 3D scaffolds were monitored using scanning electron microscopy (SEM). The physicochemical characterization was investigated using X-ray diffractometry (XRD) and infrared spectroscopy (IR). The Physicomechanical properties of the 3D scaffold were determined by a universal testing machine. The in vitro bioactivity of the 3D scaffold was assessed in simulated body fluid (SBF). The bone-bonding ability of novel 3D scaffolds was also evaluated. The obtained nanofibrous scaffolds demonstrated promising microstructure, physicochemical and physicomechanical features appropriate for enhanced bone regeneration. Therefore, the utilized nanomaterials loaded with the drug are greatly recommended as cheap alternatives to growth factors.

Keywords: bone regeneration, cheap scaffolds, nanomaterials, active molecules

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Authors: Siveshnee Devar

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Background: The rate of absenteeism and prevalence of NCDs in South Africa is extremely high. This is consistent with other educational institutions and workplaces around the globe. In most cases the absence of health and the presence of one or more non communicable diseases coupled with the lack of physical exercise is a major factor in absenteeism. Absenteeism at the workplace comes at a huge cost to the employer and the country as a whole. Aim: Findings from this study was to develop a suitable nutritional wellness program for the workplace. Methodology: A needs analysis in the form of 24-hour recall, food frequency, health and socio demographic questionnaires was undertaken to determine the need for a wellness program for the institution. Anthropometric indices such as BMI, waist circumference and blood pressure were also undertaken to determine the state of health of the staff. Results: This study has found that obesity, central obesity, hypertension as well as deficiencies in nutrients and minerals were prevalent in this group. Fruit and vegetable consumption was also below the WHO recommendation. This study showed a link between diet, physical activity and diseases of lifestyle. There were positive correlations between age and systolic blood pressure, waist circumference and systolic blood pressure, waist circumference and diastolic blood pressure and waist-to-height ratio and BMI. Conclusion: The results indicated the need for immediate intervention in the form of a wellness program. Nutrition education is important for both the workplace and out. Education and knowledge are important factors for lifestyle changes. The proposed intervention is aimed at improving presenteeism and decreasing the incidence of non- communicable diseases. Presenteeism and good health are important factors for quality education at all educational institutions.

Keywords: absenteeism, non-communicable diseases, nutrition, wellness

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Authors: Anan Jarab, Riham Almrayat, Salam Alqudah, Maher Khdour, Tareq Mukattash, Sharell Pinto

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Background: The prevalence of diabetes in Jordan is among the highest in the world, making it a particularly alarming health problem there. It has been indicated that poor adherence to the prescribed therapy lead to poor glycemic control and enhance the development of diabetes complications and unnecessary hospitalization. Purpose: To explore factors associated with medication non-adherence in patients with type 2 diabetes in Jordan. Materials and Methods: Variables including socio-demographics, disease and therapy factors, diabetes knowledge, and health-related quality of life in addition to adherence assessment were collected for 171 patients with type 2 diabetes using custom-designed and validated questionnaires. Logistic regression was performed to develop a model with variables that best predicted medication non-adherence in patients with type 2 diabetes in Jordan. Results: The majority of the patients (72.5%) were non-adherent. Patients were found four times less likely to adhere to their medications with each unit increase in the number of prescribed medications (OR = 0.244, CI = 0.08-0.63) and nine times less likely to adhere to their medications with each unit increase in the frequency of administration of diabetic medication (OR = 0.111, CI = 0.04-2.01). Patients in the present study were also approximately three times less likely (OR = 0.362, CI = 0.24-0.87) to adhere to their medications if they reported having concerns about side effects and twice more likely to adhere to medications (OR = 0.493, CI = 0.08-1.16) if they had one or more micro-vascular complication. Conclusion: The current study revealed low adherence rate to the prescribed therapy among Jordanians with type 2 diabetes. Simplifying dosage regimen, selecting treatments with lower side effects along with an emphasis on diabetes complications should be taken into account when developing care plans for patients with type 2 diabetes.

Keywords: type 2 diabetes, adherence, glycemic control, clinical pharmacist, Jordan

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Authors: Shetie Gatew

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Current soil maps of Ethiopia do not represent accurately the soils of Nech Sar National Park. In the framework of studies on the ecology of the park, we prepared a soil map based on field observations and a digital terrain model derived from SRTM data with a 30-m resolution. The landscape comprises volcanic cones, lava and basalt outflows, undulating plains, horsts, alluvial plains and river deltas. SOTER-like terrain mapping units were identified. First, the DTM was classified into 128 terrain classes defined by slope gradient (4 classes), relief intensity (4 classes), potential drainage density (2 classes), and hypsometry (4 classes). A soil-landscape relation between the terrain mapping units and WRB soil units was established based on 34 soil profile pits. Based on this relation, the terrain mapping units were either merged or split to represent a comprehensive soil and terrain map. The soil map indicates that Leptosols (30 %), Cambisols (26%), Andosols (21%), Fluvisols (12 %), and Vertisols (9%) are the most widespread Reference Soil Groups of the park. In contrast, the harmonized soil map of Africa derived from the FAO soil map of the world indicates that Luvisols (70%), Vertisols (14%) and Fluvisols (16%) would be the most common Reference Soil Groups. However, these latter mapping units are not consistent with the topography, nor did we find such extensive areas occupied by Luvisols during the field survey. This case study shows that with the now freely available SRTM data, it is possible to improve current soil information layers with relatively limited resources, even in a complex terrain like Nech Sar National Park.

Keywords: andosols, cambisols, digital elevation model, leptosols, soil-landscaps relation

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Yildiray Korkmaz, Mehmet Aksoy

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In today's operations, countries want to reach their aims in the shortest way due to economical, political and humanitarian aspects. The most effective way of achieving this goal is to be able to penetrate strategic targets. Strategic targets are generally located deep inside of the countries and are defended by modern and efficient surface to air missiles (SAM) platforms which are operated as integrated with Intelligence, Surveillance and Reconnaissance (ISR) systems. On the other hand, these high valued targets are buried deep underground and hardened with strong materials against attacks. Therefore, to penetrate these targets requires very detailed intelligence. This intelligence process should include a wide range that is from weaponry to threat assessment. Accordingly, the framework of the attack package will be determined. This mission package has to execute missions in a high threat environment. The way to minimize the risk which depends on loss of life is to use packages which are formed by UAVs. However, some limitations arising from the characteristics of UAVs restricts the performance of the mission package consisted of UAVs. So, the mission package should be formed with UAVs under the leadership of a fifth generation manned aircraft. Thus, we can minimize the limitations, easily penetrate in the deep inside of the enemy territory with minimum risk, make a decision according to ever-changing conditions and finally destroy the strategic targets. In this article, the strengthens and weakness aspects of UAVs are examined by SWOT analysis. And also, it revealed features of a mission package and presented as an example what kind of a mission package we should form in order to get marginal benefit and penetrate into strategic targets with the development of autonomous mission execution capability in the near future.

Keywords: UAV, autonomy, mission package, strategic attack, mission planning

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Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: Hannah Nagel, Hayley Lang, Albert Sole Guitart, Natasha Lean, Rachel Allavena, Cleide Sprohnie-Barrera, Alex Young

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Aggressive neoplasia of the hoof is a rare occurrence in horses and has been only sporadically described in the literature. In the few cases reported intra-hoof wall, aggressive neoplasia has been documented radiographically and has been described with variable imaging characteristics. These include a well-defined osteolytic area, a smoothly outlined semi-circular defect, an extensive draining tract beneath the hoof wall, as well as an additional large area of osteolysis or an extensive central lytic region. A 20-year-old Quarterhorse gelding and a 10-year-old Thoroughbred gelding were both presented for chronic reoccurring lameness in the left forelimb and left hindlimb, respectively. Both of the cases displayed radiographic lesions that have been previously described but also displayed osteoproliferative expansile regions of additional bone formation. Changes associated with hoof neoplasia are often non-specific due to the nature and capacity of bone to react to pathological insult, which is either to proliferate or be absorbed. Both cases depict and describe imaging findings seen on radiography, contrast radiography, computed tomography, and magnetic resonance imaging before reaching a histological diagnosis of malignant melanoma and squamous cell carcinoma. Although aggressive hoof wall neoplasia is rare, there are some imaging features which may raise our index of suspicion for an aggressive hoof wall lesion. This case report documents two horses with similar imaging findings who underwent multiple assessments, surgical interventions, and imaging modalities with a final diagnosis of malignant neoplasia.

Keywords: horse, hoof, imaging, radiography, neoplasia

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Authors: Mahani Razali, Nordin Mamat

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The purpose of the study is to explore how computer technology is integrated into pre-school activities and its relationship with children’s social interaction behaviour in pre-school classroom. The major question of interest in the present study is to investigate the social interaction behaviour of children when using computers in the Malaysian pre-school classroom. This research is based on three main objectives which are to identify children`s social interaction during computer play activities, teacher’s role and parent’s participation to develop children`s social interaction. This qualitative study was carried out among 25 pre-school children, three teachers and three parents as the research sample. On the other hand, parent’s support was obtained from their discussions, supervisions and communication at home. The data collection procedures involved structured observation which was to identify social interaction behaviour among pre-school children through computer play activities; as for semi-structured interviews, it was done to study the perception of the teachers and parents on the acquired social interaction behaviour among the children. Besides, documentation analysis method was used as to triangulate acquired information with observations and interviews. In this study, the qualitative data analysis was tabulated in descriptive manner with frequency and percentage format. This study primarily focused on social interaction behaviour elements among the pre-school children. Findings revealed that the children showed positive outcomes on the social interaction behaviour during their computer play. This research summarizes that teacher’s role and parent’s support can improve children`s social interaction behaviour through computer play activities. As a whole, this research highlighted the significance of computer play activities as to stimulate social interaction behavior among the pre-school children.

Keywords: early childhood, emotional development, parent support, play

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Authors: Benhaddadi M., Déry D.

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Electric motors are the single biggest consumer of electricity, and the consumption will have more than to double by 2050. Meanwhile, the existing technologies offer the potential to reduce the motor energy demand by up to 30 %, whereas the know-how to realise energy savings is not extensively applied. That is why the authors first conducted a detailed analysis of the regulation of the electric motor market in North America To illustrate the colossal energy savings potential permitted by the VFD, the authors have equipped experimental setup, based on centrifugal pump, simultaneously equipped with regulating throttle valves and variable frequency drive VFD. The obtained experimental results for 1.5 HP motor pump are extended to another motor powers, as centrifugal pumps that are different in power may have similar operational characteristics if they are located in a similar kind of process, permitting the simulations for 5 HP and 100 HP motors. According to the obtained results, VFDs tend to be most cost-effective when fitted to larger motor pumps, in addition to higher duty cycle of the motor and relative time operating at lower than full load. The energy saving permitted by the VFD use is huge, and the payback period for drive investment is short. Nonetheless, it’s important to highlight that there is no general rule of thumb that can be used to obtain the impact of the relative time operating at lower than full load. Indeed, in terms of energy-saving differences, 50 % flow regulation is tremendously better than 75 % regulation, but a slightly enhanced relative to 25 %. Two main distinct reasons can explain this somewhat not anticipated results: the characteristics of the process and the drop in efficiency when motor is operating at low speed.

Keywords: motor, drive, energy efficiency, centrifugal pump

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

Procedia PDF Downloads 323

Authors: Wong Kean Hin, Kumarason A. L. V. Rasiah

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A building provides shelter and protection for an individual to live, work, sleep, procreate or engage in leisurely activities comfortably. Currently, a very popular term related to building was often stated by many parties, which is sustainability. A sustainable building is environmental friendly, healthy to the occupants, as well as efficient in electricity and water. This particular research is important to any parties that are involved in the construction industry. This research will provide the awareness and acceptability of Malaysian public towards sustainable residential building. It will also provide the developers about which sustainable features that the people usually want so that the developers can build a sustainable housing that suits the needs of people. Then, propose solutions to solve the difficulties of implementing sustainability in Malaysian housing industry. Qualitative and quantitative research methods were used throughout the process of data collection. The quantitative research method was distribution of questionnaires to 100 Malaysian public and 50 individuals that worked in developer companies. Then, the qualitative method was an interview session with experienced personnel in Malaysian construction industry. From the data collected, there is increasingly Malaysian public and developers are aware about the existence of sustainability. Moreover, the public is willing to invest on sustainable residential building with minimum additional cost. However, there is a mismatch in between sustainable elements provided by developers and the public needs. Some recommendations to improve the progression of sustainability had been proposed in this study, which include laws enforcement, cooperation between the both government sector with private sector, and private sector with private sector, and learn from modern countries. These information will be helpful and useful for the future of sustainability development in Malaysia.

Keywords: acceptability, awareness, Malaysian housing industry, sustainable elements, green building index

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Authors: Lufei Mao, Hongwei Chen, Zijiao Chai

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Informal housing is a widespread phenomenon in developing countries. In many newly-emerging cities in China, rapid urbanization leads to an influx of population as well as a shortage of housing. Under this background, container housing, a new form of informal housing, gradually appears on a small scale on urban temporary land in recent years. Container housing, just as its name implies, transforms containers into small houses that allow migrant workers group to live in it. Scholars in other countries have established sound theoretical frameworks for informal housing study, but the research fruits seem rather limited on this small scale housing form. Unlike the cases in developed countries, these houses, which are outside urban planning, bring about various environmental, economic, social and governance issues. Aiming to figure out this new-born housing form, a survey mainly on two container housing settlements in Hangzhou, China was carried out to gather the information of them. Based on this thorough survey, the paper concludes the features and problems of infrastructure, environment and social communication of container housing settlements. The result shows that these containers were lacking of basic facilities and were restricted in a small mess temporary land. Moreover, because of the deficiency in management, the rental rights of these containers might not be guaranteed. Then the paper analyzes the factors affecting the formation and evolution of container housing settlements. It turns out that institutional and policy factors, market factors and social factors were the main three factors that affect the formation. At last, the paper proposes some suggestions for the governance of container housing and the utility pattern of urban temporary land.

Keywords: container housing, informal housing, urban temporary land, urban governance

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Mona Hejazi, Ali Motie Nasrabadi

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Epilepsy is a persistent neurological disorder that affects more than 50 million people worldwide. Hence, there is a necessity to introduce an efficient prediction model for making a correct diagnosis of the epileptic seizure and accurate prediction of its type. In this study we consider how the Effective Connectivity (EC) patterns obtained from intracranial Electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict imminent seizures, as this will enable the patients (and caregivers) to take appropriate precautions. We use this definition because we believe that effective connectivity near seizures begin to change, so we can predict seizures according to this feature. Results are reported on the standard Freiburg EEG dataset which contains data from 21 patients suffering from medically intractable focal epilepsy. Six channels of EEG from each patients are considered and effective connectivity using Directed Transfer Function (DTF) and Granger Causality (GC) methods is estimated. We concentrate on effective connectivity standard deviation over time and feature changes in five brain frequency sub-bands (Alpha, Beta, Theta, Delta, and Gamma) are compared. The performance obtained for the proposed scheme in predicting seizures is: average prediction time is 50 minutes before seizure onset, the maximum sensitivity is approximate ~80% and the false positive rate is 0.33 FP/h. DTF method is more acceptable to predict epileptic seizures and generally we can observe that the greater results are in gamma and beta sub-bands. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Keywords: effective connectivity, Granger causality, directed transfer function, epilepsy seizure prediction, EEG

Procedia PDF Downloads 451