Search results for: multi features

Authors: Allaw Kamel, Bazzi Hasan

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Municipal solid waste (MSW) generation is among the most significant sources which threaten the global environmental health. Solid Waste Management has been an important environmental problem in developing countries because of the difficulties in finding sustainable solutions for solid wastes. Therefore, more efforts are needed to be implemented to overcome this problem. Lebanon has suffered a severe solid waste management problem in 2015, and a new landfill site was proposed to solve the existing problem. The study aims to identify and locate the most suitable area to construct a landfill taking into consideration the sustainable development to overcome the present situation and protect the future demands. Throughout the article, a landfill site selection methodology was discussed using Geographic Information System (GIS) and Multi Criteria Decision Analysis (MCDA). Several environmental, economic and social factors were taken as criterion for selection of a landfill. Soil, geology, and LUC (Land Use and Land Cover) indices with the Sustainable Development Index were main inputs to create the final map of Environmentally Sensitive Area (ESA) for landfill site. Different factors were determined to define each index. Input data of each factor was managed, visualized and analyzed using GIS. GIS was used as an important tool to identify suitable areas for landfill. Spatial Analysis (SA), Analysis and Management GIS tools were implemented to produce input maps capable of identifying suitable areas related to each index. Weight has been assigned to each factor in the same index, and the main weights were assigned to each index used. The combination of the different indices map generates the final output map of ESA. The output map was reclassified into three suitability classes of low, moderate, and high suitability. Results showed different locations suitable for the construction of a landfill. Results also reflected the importance of GIS and MCDA in helping decision makers finding a solution of solid wastes by a sanitary landfill.

Keywords: sustainable development, landfill, municipal solid waste (MSW), geographic information system (GIS), multi criteria decision analysis (MCDA), environmentally sensitive area (ESA)

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Authors: Dursun Yağız, Ahmet Afyon

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The study materials were collected from Isparta province in 2008. These materials were moved to the laboratory. The 'Most Chamber Techniques' were applied to the materials in the laboratory. Materials were examined with a stereo microscope. As a result of investigations carried out on the samples of sporophores which were developed in the laboratory, Paradiacheopsis erythropodia (Ing) Nann.-Bremek. and Paradiacheopsis longipes Hooff & Nann.-Bremek. species were identified. As a result of the literature research, it is determined that these taxa were new recordings in Turkey. The identified taxa have been added to Turkey's myxomycota. These two taxa’ microscopic features, photos, localities and substrate information were given.

Keywords: myxomycete, paradiacheopsis, Turkey, slime mould

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Authors: Bertalan Jillek, Péter Szabó, Judit Kopniczky, István Szabó, Balázs Patczai, Kinga Turzó

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Hip and knee prostheses are one of the most frequently used medical implants, that can significantly improve patients’ quality of life. Long term success and biointegration of these prostheses depend on several factors, like bulk and surface characteristics, construction and biocompatibility of the material. The applied surgical technique, the general health condition and life-quality of the patient are also determinant factors. Medical devices used in orthopedic surgeries have different surfaces depending on their function inside the human body. Surface roughness of these implants determines the interaction with the surrounding tissues. Numerous modifications have been applied in the recent decades to improve a specific property of an implant. Our goal was to compare the surface characteristics of typical implant materials used in orthopedic surgery and traumatology. Morphological and chemical structure of Vortex plate anodized titanium, cemented THR (total hip replacement) stem high nitrogen REX steel (SS), uncemented THR stem and cup titanium (Ti) alloy with titanium plasma spray coating (TPS), cemented cup and uncemented acetabular liner HXL and UHMWPE and TKR (total knee replacement) femoral component CoCrMo alloy (Sanatmetal Ltd, Hungary) discs were examined. Visualization and elemental analysis were made by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). Surface roughness was determined by atomic force microscopy (AFM) and profilometry. SEM and AFM revealed the morphological and roughness features of the examined materials. TPS Ti presented the highest Ra value (25 ± 2 μm, followed by CoCrMo alloy (535 ± 19 nm), Ti (227 ± 15 nm) and stainless steel (170 ± 11 nm). The roughness of the HXL and UHMWPE surfaces was in the same range, 147 ± 13 nm and 144 ± 15 nm, respectively. EDS confirmed typical elements on the investigated prosthesis materials: Vortex plate Ti (Ti, O, P); TPS Ti (Ti, O, Al); SS (Fe, Cr, Ni, C) CoCrMo (Co, Cr, Mo), HXL (C, Al, Ni) and UHMWPE (C, Al). The results indicate that the surface of prosthesis materials have significantly different features and the applied investigation methods are suitable for their characterization. Contact angle measurements and in vitro cell culture testing are further planned to test their surface energy characteristics and biocompatibility.

Keywords: morphology, PE, roughness, titanium

Procedia PDF Downloads 126

Authors: Sutida Maneeanakekul, Dusit Wechakit, Somsak Piriyayota

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Coastal erosion is a major problem in Thailand, in both the Gulf of Thailand and the Andaman Sea coasts. According to the Department of Marine and Coastal Resources, land erosion occurred along the 200 km coastline with an average rate of 5 meters/year. Coastal erosion affects public and government properties, as well as the socio-economy of the country, including emigration in coastal communities, loss of habitats, and decline in fishery production. To combat the problem of coastal erosion, projects utilizing bamboo sticks for coastal defense against erosion were carried out in 5 areas beginning in November, 2010, including: Pak Klong Munharn- Samut Songkhram Province; Ban Khun Samutmaneerat, Pak Klong Pramong and Chao Matchu Shrine-Samut Sakhon Province,and Pak Klong Hongthong – Chachoengsao Province by Marine and Coastal Resources Department. In 2012, an evaluation of the effectiveness of solving the problem of coastal erosion by using bamboo stick was carried out, with a focus on three aspects. Firstly, the change in physical and biological features after using the bamboo stick technique was assessed. Secondly, participation of people in the community in the way of managing the problem of coastal erosion were these aspects evaluated as part of the study. The last aspect that was evaluated is the satisfaction of the community toward this technique. The results of evaluation showed that the amounts of sediment have dramatically changed behind the bamboo sticks lines. The increase of sediment was found to be about 23.50-56.20 centimeters (during 2012-2013). In terms of biological aspect, there has been an increase in mangrove forest areas, especially at Bang Ya Prak, Samut Sakhon Province. Average tree density was found to be about 4,167 trees per square meter. Additionally, an increase in production of fisheries was observed. Presently, the change in the evaluated physical features tends to increase in every aspect, including the satisfaction of people in community toward the process of solving the erosion problem. People in the community are involved in the preparatory, operation, monitoring and evaluation process to resolve the problem in the medium levels.

Keywords: bamboo sticks, coastal erosion, rehabilitate, Thailand sustainable development approach

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Authors: Zainab Dashti, Leila Vali

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Background: The Middle East, in particular Kuwait, contains one of the highest rates of patients with Diabetes in the world. Generally, infections resistant to antibiotics among the diabetic population has been shown to be on the rise. This is the first study in Kuwait to compare the antibiotic resistance profiles and genotypic differences between the resistant isolates of Enterobacteriaceae obtained from diabetic and non-diabetic patients. Material/Methods: In total, 65 isolates were collected from diabetic patients consisting of 34 E. coli, 15 K. pneumoniae and 16 other Enterobacteriaceae species (including Salmonella spp. Serratia spp and Proteus spp.). In our control group, a total of 49 isolates consisting of 37 E. coli, 7 K. pneumoniae and 5 other species (including Salmonella spp. Serratia spp and Proteus spp.) were included. Isolates were identified at the species level and antibiotic resistance profiles, including Colistin, were determined using initially the Vitek system followed by double dilution MIC and E-test assays. Multi drug resistance (MDR) was defined as isolates resistant to a minimum of three antibiotics from three different classes. PCR was performed to detect ESBL genes (blaCTX-M, blaTEM & blaSHV), flouroquinolone resistance genes (qnrA, qnrB, qnrS & aac(6’)-lb-cr) and carbapenem resistance genes (blaOXA, blaVIM, blaGIM, blaKPC, blaIMP, & blaNDM) in both groups. Pulse field gel electrophoresis (PFGE) was performed to compare clonal relatedness of both E. coli and K.pneumonaie isolates. Results: Colistin resistance was determined in three isolates with MICs of 32-128 mg/L. A significant difference in resistance to ampicillin (Diabetes 93.8% vs control 72.5%, P value <0.002), augmentin (80% vs 52.5%, p value < 0.003), cefuroxime (69.2% vs 45%, p value < 0.0014), ceftazadime (73.8% vs 42.5%, p value <0.001) and ciprofloxacin (67.6% vs 40%, p value < 0.005) were determined. Also, a significant difference in MDR rates between the two groups (Diabetes 76.9%, control 57.5%, p value <0.036 were found. All antibiotic resistance genes showed a higher prevalence among the diabetic group, except for blaCTX-M, which was higher among the control group. PFGE showed a high rate of diversity between each group of isolates. Conclusions: Our results suggested an alarming rate of antibiotic resistance, in particular Colistin resistance (1.8%) among K. pneumoniea isolated from diabetic patients in Kuwait. MDR among Enterobacteriaceae infections also seems to be a worrying issue among the diabetics of Kuwait. More efforts are required to limit the issue of antibiotic resistance in Kuwait, especially among patients with diabetes mellitus.

Keywords: antibiotic resistance, diabetes, enterobacreriacae, multi antibiotic resistance

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Authors: Erhan Berk

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The purpose of this study is to examine the efficiency and productivity of the health care sector in Turkey based on four years of health care cross-sectional data. Efficiency measures are calculated by a nonparametric approach known as Data Envelopment Analysis (DEA). Productivity is measured by the Malmquist index. The research shows how DEA-based Malmquist productivity index can be operated to appraise the technology and productivity changes resulted in the Turkish hospitals which are located all across the country.

Keywords: data envelopment analysis, efficiency, health care, Malmquist Index

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Authors: F. Fekak, A. Gravouil, M. Brun, B. Depale

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During an earthquake, a bridge crane may be subjected to multiple impacts between crane wheels and rail. In order to model such phenomena, a time-history dynamic analysis with a multi-scale approach is performed. The high frequency aspect of the impacts between wheels and rails is taken into account by a Lagrange explicit event-capturing algorithm based on a velocity-impulse formulation to resolve contacts and impacts. An implicit temporal scheme is used for the rest of the structure. The numerical coupling between the implicit and the explicit schemes is achieved with a heterogeneous asynchronous time-integrator.

Keywords: bridge crane, earthquake, dynamic analysis, explicit, implicit, impact

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Hasan Çiçekli, Ahmet Gökçen, Uğur Çam

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In this paper, a comparative performance analysis of mostly used four nonlinearity cancellation techniques used to realize the passive resistor by MOS transistors is presented. The comparison is done by using an integrator circuit which is employing sequentially Op-amp, OTRA and ICCII as active element. All of the circuits are implemented by MOS-C realization and simulated by PSPICE program using 0.35 µm process TSMC MOSIS model parameters. With MOS-C realization, the circuits became electronically tunable and fully integrable which is very important in IC design. The output waveforms, frequency responses, THD analysis results and features of the nonlinearity cancellation techniques are also given.

Keywords: integrator circuits, MOS-C realization, nonlinearity cancellation, tuneable resistors

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Mohanad Rezeq, Tarik Aouam, Frederik Gailly

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In times of armed conflicts, various security checkpoints are placed by authorities to control the flow of merchandise into and within areas of conflict. The flow of humanitarian trucks that is added to the regular flow of commercial trucks, together with the complex security procedures, creates congestion and long waiting times at the security checkpoints. This causes distribution costs to increase and shortages of relief aid to the affected people to occur. Our research proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief aid, taking into account congestion at security checkpoints. The proposed tool is built around a multi-item humanitarian distribution planning model based on multi-phase design science methodology that has as its objective to minimize distribution and back ordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza War as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security checkpoints, and conduct computational experiments. The decision support tool generated a shipment plan that was compared to two benchmarks in terms of total distribution cost, average lead time and work in progress (WIP) at security checkpoints, and average inventory and backorders at distribution centers. The first benchmark is the shipment plan generated by the fixed capacity model, and the second is the actual shipment plan implemented by the planners during the armed conflict. According to our findings, modeling and optimizing supply chain flows reduce total distribution costs, average truck wait times at security checkpoints, and average backorders when compared to the executed plan and the fixed-capacity model. Finally, scenario analysis concludes that increasing capacity at security checkpoints can lower total operations costs by reducing the average lead time.

Keywords: humanitarian distribution planning, relief-aid distribution, congestion, clearing functions

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Authors: Zuhal Eltayeb Awad

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Alryad neighborhood is located in Khartoum town– the administrative center of the Capital of Sudan. The neighborhood is one of the high-income residential areas with villa type development of low-density. It was planned and developed in 1972 with large plots (600-875m²), wide crossing roads and balanced environment. Recently the area transformed into more compact urban form of high density, mixed-use integrated development with more intensive use of land; multi-storied apartments. The most important socio-economic process in the neighborhood has been the commercialization and deinitialization of the area in connect with the displacement of the residential function. This transformation affected the quality of the neighborhood and the inter-related features of the built environment. A case study approach was chosen to gather the necessary qualitative and quantitative data. A detailed survey on existing development pattern was carried out over the whole area of Alryad. Data on the built and social environment of the neighborhoods were collected through observations, interviews and secondary data sources. The paper reflected a theoretical and empirical interest in the particular characteristics of compact neighborhood with high density, and mixed land uses and their effect on social wellbeing of the residents all in the context of the sustainable development. The research problem is focused on the challenges of transformation that associated with compact neighborhood that created multiple urban problems, e.g., stress of essential services (water supply, electricity, and drainage), congestion of streets and demand for parking. The main objective of the study is to analyze the transformation of this area from residential use to commercial and administrative use. The study analyzed the current situation of the neighborhood compared to the five principles of sustainable neighborhood prepared by UN Habitat. The study found that the neighborhood is experienced changes that occur to inner-city residential areas and the process of change of the neighborhood was originated by external forces due to the declining economic situation of the whole country. It is evident that non-residential uses have taken place uncontrolled, unregulated and haphazardly that led to damage the residential environment and deficiency in infrastructure. The quality of urban life and in particular on levels of privacy was reduced, the neighborhood changed gradually to be a central business district that provides services to the whole Khartoum town. The change of house type may be attributed to a demand-led housing market and absence of policy. The results showed that Alryad is not fully sustainable and self-contained, street network characteristics and mixed land-uses development are compatible with the principles of sustainability. The area of streets represents 27.4% of the total area of the neighborhood. Residential density is 4,620 people/ km², that is lower than the recommendations, and the limited block land-use specialization is higher than 10% of the blocks. Most inhabitants have a high income so that there is no social mix in the neighborhood. The study recommended revision of the current zoning regulations in order to control and regulate undesirable development in the neighborhood and provide new solutions which allow promoting the neighborhood sustainable development.

Keywords: compact neighborhood, land uses, mixed use, residential area, transformation

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Authors: Ahmad Mohammad Sharqi, Mohamed Hechmi El Ouni, Saleh Alsulamy

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Due to the emerging technologies revolution worldwide, the need to exploit and employ innovative technologies for other functions and purposes in different aspects has become a remarkable matter. Saudi Arabia is considered one of the most powerful economic countries in the world, where the construction sector participates effectively in its economy. Thus, the construction sector in KSA should convoy the rapid digital revolution and transformation and implement smart devices on sites. A Smart Construction Site (SCS) includes smart devices, artificial intelligence, the internet of things, augmented reality, building information modeling, geographical information systems, and cloud information. This paper aims to study the level of implementation of SCS in KSA, analyze the obstacles and challenges of adopting SCS and find out critical success factors for its implementation. A survey of close-ended questions (scale and multi-choices) has been conducted on professionals in the construction sector of Saudi Arabia. A total number of twenty-nine questions has been prepared for respondents. Twenty-four scale questions were established, and those questions were categorized into several themes: quality, scheduling, cost, occupational safety and health, technologies and applications, and general perception. Consequently, the 5-point Likert scale tool (very low to very high) was adopted for this survey. In addition, five close-ended questions with multi-choice types have also been prepared; these questions have been derived from a previous study implemented in the United Kingdom (UK) and the Dominic Republic (DR), these questions have been rearranged and organized to fit the structured survey in order to place the Kingdom of Saudi Arabia in comparison with the United Kingdom (UK) as well as the Dominican Republic (DR). A total number of one hundred respondents have participated in this survey from all regions of the Kingdom of Saudi Arabia: southern, central, western, eastern, and northern regions. The drivers, obstacles, and success factors for implementing smart devices and technologies in KSA’s construction sector have been investigated and analyzed. Besides, it has been concluded that KSA is on the right path toward adopting smart construction sites with attractive results comparable to and even better than the UK in some factors.

Keywords: artificial intelligence, construction projects management, internet of things, smart construction sites, smart devices

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Authors: J. A. Gbadeyan, R. A. Kareem

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In this paper, we investigated the effects of unsteady internal heat generation of a two-step exothermic reactive hydromagnetic fluid flow under different chemical kinetics namely: Sensitized, Arrhenius and Bimolecular kinetics through an isothermal wall temperature channel. The resultant modeled nonlinear partial differential equations were simplified and solved using a combined Laplace-Differential Transform Method (LDTM). The solutions obtained were discussed and presented graphically to show the salient features of the fluid flow and heat transfer characteristics.

Keywords: unsteady, reactive, hydromagnetic, couette ow, exothermi creactio

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Authors: Jaime Leavitt, Katy Haralampides

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Numerical modelling has been used to investigate the long-term impact of a large dam on downstream wetland areas, specifically in terms of changing sediment dynamics in the system. The Mactaquac Generating Station (MQGS) is a 672MW run-of-the-river hydroelectric facility, commissioned in 1968 on the mainstem of the Wolastoq|Saint John River in New Brunswick, Canada. New Brunswick Power owns and operates the dam and has been working closely with the Canadian Rivers Institute at UNB Fredericton on a multi-year, multi-disciplinary project investigating the impact the dam has on its surrounding environment. With focus on the downstream river, this research discusses the initialization, set-up, calibration, and preliminary results of a 2-D hydrodynamic model using the Delft3d Flexible Mesh Suite (successor of the Delft3d 4 Suite). The flexible mesh allows the model grid to be structured in the main channel and unstructured in the floodplains and other downstream regions with complex geometry. The combination of grid types improves computational time and output. As the movement of water governs the movement of sediment, the calibrated and validated hydrodynamic model was applied to sediment transport simulations, particularly of the fine suspended sediments. Several provincially significant Protected Natural Areas and federally significant National Wildlife Areas are located 60km downstream of the MQGS. These broad, low-lying floodplains and wetlands are known as the Grand Lake Meadows Complex (GLM Complex). There is added pressure to investigate the impacts of river regulation on these protected regions that rely heavily on natural river processes like sediment transport and flooding. It is hypothesized that the fine suspended sediment would naturally travel to the floodplains for nutrient deposition and replenishment, particularly during the freshet and large storms. The purpose of this research is to investigate the impacts of river regulation on downstream environments and use the model as a tool for informed decision making to protect and maintain biologically productive wetlands and floodplains.

Keywords: hydrodynamic modelling, national wildlife area, protected natural area, sediment transport.

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

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Authors: Ahmet Karakuş, Akif Can Kilic, Emre Alptekin

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A growing number of studies have been conducted to determine how well-being may be predicted using well-designed models. It is necessary to investigate the backgrounds of features in order to construct a viable Subjective Well-Being (SWB) model. We have picked the suitable variables from the literature on SWB that are acceptable for real-world data instructions. The goal of this work is to evaluate the model by feeding it with SWB characteristics and then categorizing the stress levels using machine learning methods to see how well it performs on a real dataset. Despite the fact that it is a multiclass classification issue, we have achieved significant metric scores, which may be taken into account for a specific task.

Keywords: machine learning, multiclassification problem, subjective well-being, perceived stress scale

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Authors: Ignatio Madanhire, Charles Mbohwa

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This study looks at the best model of aggregate planning activity in an industrial entity and uses the trial and error method on spreadsheets to solve aggregate production planning problems. Also linear programming model is introduced to optimize the aggregate production planning problem. Application of the models in a furniture production firm is evaluated to demonstrate that practical and beneficial solutions can be obtained from the models. Finally some benchmarking of other furniture manufacturing industries was undertaken to assess relevance and level of use in other furniture firms

Keywords: aggregate production planning, trial and error, linear programming, furniture industry

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Authors: Hideyuki Shintani, Ichiro Koshijima

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In Cyber Physical System (CPS), if there are a large number of persons in the process, a role of person in CPS might be different comparing with the one-man system. It is also necessary to consider how Human-in-The-Loop Cyber Physical Systems (HiTLCPS) ensure safety of each person in the loop process. In this paper, the authors discuss a system safety framework with an illustrative example with STAMP model to clarify what point for safety should be considered and what role of person in the should have.

Keywords: cyber-physical-system, human-in-the-loop, safety, STAMP model

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: Roseliza Mat Alipiah, David Raffaelli, J. C. R. Smart

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This research is a new approach as it integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiments (CEs) were used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows: The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly, the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

Keywords: Bayesian belief network (BBN), choice experiments (CE), multi-criteria decision analysis (MCDA), aquaculture

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Authors: Keunhong Chae, Seokho Yoon

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We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.

Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: A. Vaidya-Soocheta, K. M. Wong-Hon-Lang

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Craft and fashion have always been interlinked. The combination of both often gives stunning results. The present study introduces ‘Paper Cutting Craft Techniques’ like the Japanese –Kirigami, Mexican –PapelPicado, German –Scherenschnitte, Polish –Wycinankito in textiles to develop innovative and novel design structures as embellishments and ornamentation. The project studies various ways of using these paper cutting techniques to obtain interesting features and delicate design patterns on fabrics. While paper has its advantages and related uses, it is fragile rigid and thus not appropriate for clothing. Fabric is sturdy, flexible, dimensionally stable and washable. In the present study, the cut out techniques develop creative design motifs and patterns to give an inventive and unique appeal to the fabrics. The beauty and fascination of lace in garments have always given them a nostalgic charm. Laces with their intricate and delicate complexity in combination with other materials add a feminine touch to a garment and give it a romantic, mysterious appeal. Various textured and decorative effects through fabric manipulation are experimented along with the use of paper cutting craft skills as an innovative substitute for developing lace or “Broderie Anglaise” effects on textiles. A number of assorted fabric types with varied textures were selected for the study. Techniques to avoid fraying and unraveling of the design cut fabrics were introduced. Fabrics were further manipulated by use of interesting prints with embossed effects on cut outs. Fabric layering in combination with assorted techniques such as cutting of folded fabric, printing, appliqué, embroidery, crochet, braiding, weaving added a novel exclusivity to the fabrics. The fabrics developed by these innovative methods were then tailored into garments. The study thus tested the feasibility and practicability of using these fabrics by designing a collection of evening wear garments based on the theme ‘Nostalgia’. The prototypes developed were complemented by designing fashion accessories with the crafted fabrics. Prototypes of accessories add interesting features to the study. The adaptation and application of this novel technique of paper cutting craft on textiles can be an innovative start for a new trend in textile and fashion industry. The study anticipates that this technique will open new avenues in the world of fashion to incorporate its use commercially.

Keywords: collection, fabric cutouts, nostalgia, prototypes

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Authors: Amr Saeb, Khalid Al-Rubeaan, Mohamed Abouelhoda, Manojkumar Selvaraju, Hamsa Tayeb

Abstract:

Background: P. mirabilis is a common uropathogenic bacterium that can cause major complications in patients with long-standing indwelling catheters or patients with urinary tract anomalies. In addition, P. mirabilis is a common cause of chronic osteomyelitis in diabetic foot ulcer (DFU) patients. Methodology: P. mirabilis SCDR1 was isolated from a diabetic ulcer patient. We examined P. mirabilis SCDR1 levels of resistance against nano-silver colloids, the commercial nano-silver and silver containing bandages and commonly used antibiotics. We utilized next generation sequencing techniques (NGS), bioinformatics, phylogenetic analysis and pathogenomics in the identification and characterization of the infectious pathogen. Results: P. mirabilis SCDR1 is a multi-drug resistant isolate that also showed high levels of resistance against nano-silver colloids, nano-silver chitosan composite and the commercially available nano-silver and silver bandages. The P. mirabilis-SCDR1 genome size is 3,815,621 bp with G+C content of 38.44%. P. mirabilis-SCDR1 genome contains a total of 3,533 genes, 3,414 coding DNA sequence genes, 11, 10, 18 rRNAs (5S, 16S, and 23S), and 76 tRNAs. Our isolate contains all the required pathogenicity and virulence factors to establish a successful infection. P. mirabilis SCDR1 isolate is a potential virulent pathogen that despite its original isolation site, wound, it can establish kidney infection and its associated complications. P. mirabilis SCDR1 contains several mechanisms for antibiotics and metals resistance including, biofilm formation, swarming mobility, efflux systems, and enzymatic detoxification. Conclusion: P. mirabilis SCDR1 is the spontaneous nano-silver resistant bacterial strain. P. mirabilis SCDR1 strain contains all reported pathogenic and virulence factors characteristic for the species. In addition, it possesses several mechanisms that may lead to the observed nano-silver resistance.

Keywords: Proteus mirabilis, multi-drug resistance, silver nanoparticles, resistance, next generation sequencing techniques, genome analysis, bioinformatics, phylogeny, pathogenomics, diabetic foot ulcer, xenobiotics, multidrug resistance efflux, biofilm formation, swarming mobility, resistome, glutathione S-transferase, copper/silver efflux system, altruism

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Sandeep Singh Waraich

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Wireless sensor network (WSN ) consists of a large number of sensor nodes. The disparity in their energy consumption usually lead to the loss of equilibrium in wireless sensor network which may further results in an energy hole problem in wireless network. In this paper, we have considered the inclusion of orphan nodes which usually remain unutilized as intermediate nodes in multi-hop routing. The Orphan Node Inclusion (ONI) Protocol lets the cluster member to bring the orphan nodes into their clusters, thereby saving important resources and increasing network lifetime in critical applications of WSN.

Keywords: wireless sensor network, orphan node, clustering, ONI protocol

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Authors: Azhin Hamad Ameen

Abstract:

This research paper explores the concept of secularism in Iraq, analyzing its historical development, contemporary manifestations, and potential future trajectories. Using a combination of qualitative and quantitative methods, including archival research, interviews with experts and practitioners, and surveys of public opinion, the study examines the complex and often contested relationship between religion, politics, and state power in Iraq. The research finds that secularism has played a significant role in shaping Iraq's political and social landscape over the past century, reflecting both the influence of Western modernity and the challenges of managing religious diversity in a multiethnic, multi-sectarian society. However, the study also reveals that secularism in Iraq is highly contested and fragmented, with competing visions and interpretations among different groups and factions. The research identifies several key factors that have contributed to this fragmentation, including the legacy of colonialism, sectarian conflicts, external interventions, and the rise of Islamist movements. Despite these challenges, the study suggests that secularism continues to hold important potential for promoting democratic governance, protecting human rights, and fostering social cohesion in Iraq. The research concludes by outlining several key policy recommendations for strengthening secularism in Iraq, including promoting interfaith dialogue and tolerance, enhancing public education and civic engagement, and supporting grassroots initiatives for social and political reform. Overall, this research contributes to our understanding of the complex dynamics of secularism in Iraq and highlights the urgent need for innovative and inclusive approaches to promoting democratic governance and social justice in the country.

Keywords: secularism, Iraq, religion, politics, state power, historical development, contemporary manifestations, multiethnic society, multi-sectarian society, western modernity, religious diversity, fragmentation, colonialism, sectarian conflicts, external interventions, Islamist movements, democratic governance, human rights, social cohesion, interfaith dialogue, tolerance, public education, civic engagement, grassroots initiatives, social and political reform

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Authors: Sandra Cecilia Bautista-Rodríguez, Vladimir Melgarejo

Abstract:

Climate change, loss of ecosystems, increasing poverty, increasing marginalization of rural communities and declining food security are global issues that require urgent attention. In this regard, a great deal of research has focused on how agroecosystems respond to these challenges as they provide ecosystem services (ES) that lead to higher levels of resilience, adaptation, productivity and self-sufficiency. Hence, the valuing of ecosystem services plays an important role in the decision-making process for the design and management of agroecosystems. This paper aims to define the link between ecosystem service valuation methods and ES value dimensions in agroecosystems from ecological economics and agroecology. The method used to identify valuation methodologies was a literature review in the fields of Agroecology and Ecological Economics, based on a strategy of information search and classification. The conceptual framework of the work is based on the multidimensionality of value, considering the social, ecological, political, technological and economic dimensions. Likewise, the valuation process requires consideration of the ecosystem function associated with ES, such as regulation, habitat, production and information functions. In this way, valuation methods for ES in agroecosystems can integrate more than one value dimension and at least one ecosystem function. The results allow correlating the ecosystem functions with the ecosystem services valued, and the specific tools or models used, the dimensions and valuation methods. The main methodologies identified are multi-criteria valuation (1), deliberative - consultative valuation (2), valuation based on system dynamics modeling (3), valuation through energy or biophysical balances (4), valuation through fuzzy logic modeling (5), valuation based on agent-based modeling (6). Amongst the main conclusions, it is highlighted that the system dynamics modeling approach has a high potential for development in valuation processes, due to its ability to integrate other methods, especially multi-criteria valuation and energy and biophysical balances, to describe through causal cycles the interrelationships between ecosystem services, the dimensions of value in agroecosystems, thus showing the relationships between the value of ecosystem services and the welfare of communities. As for methodological challenges, it is relevant to achieve the integration of tools and models provided by different methods, to incorporate the characteristics of a complex system such as the agroecosystem, which allows reducing the limitations in the processes of valuation of ES.

Keywords: ecological economics, agroecosystems, ecosystem services, valuation of ecosystem services

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