Search results for: communal practice network

Authors: Daniel Pyle, Nicole Pyle, Ben Lignugaris-Kraft, Lawrence Maheady

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Students with disabilities are not included in general education at the same rate as their peers without disabilities. There are multiple reasons cited for why inclusion rates vary, such as teachers' lack of knowledge of the successful delivery of inclusive practices to students with the most extensive support needs. However, decades of research document effective inclusive practices associated with benefits across domains for students with disabilities. One effective inclusive practice that teachers use to improve outcomes for students with disabilities is flexible grouping. Teachers can use flexible grouping to facilitate students working collaboratively by using peer-mediated interventions (PMIs). This article describes PMIs as a flexible grouping of High Leverage Practices (HLP). There are variations of PMIs to select from when using flexible grouping. PMIs are described by varied grouping arrangements and different instructional procedures to clarify the flexibility of grouping students and students’ roles within those groupings. In support of teachers’ use of flexible grouping in inclusive general education classrooms, we identify different PMI formats teachers can use depending on the preferred grouping arrangement, explain the distinctive characteristics of PMI models to distinguish expected procedures with peers, highlight outcomes associated with PMIs, and provide an overview of evaluating PMIs effectiveness.

Keywords: peer-mediated interventions, high leverage practices, flexible grouping, general education, special education

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Authors: Aishwarya Shekhar, Devesh Kumar Srivastava

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Cloud computing has emerged as a promising direction for cost efficient and reliable service delivery across data communication networks. The dynamic location of service facilities and the virtualization of hardware and software elements are stressing the communication networks and protocols, especially when data centres are interconnected through the internet. Although the computing aspects of cloud technologies have been largely investigated, lower attention has been devoted to the networking services without involving IT operating overhead. Cloud computing has enabled elastic and transparent access to infrastructure services without involving IT operating overhead. Virtualization has been a key enabler for cloud computing. While resource virtualization and service abstraction have been widely investigated, networking in cloud remains a difficult puzzle. Even though network has significant role in facilitating hybrid cloud scenarios, it hasn't received much attention in research community until recently. We propose Network as a Service (NaaS), which forms the basis of unifying public and private clouds. In this paper, we identify various challenges in adoption of hybrid cloud. We discuss the design and implementation of a cloud platform.

Keywords: cloud computing, networking, infrastructure, hybrid cloud, open stack, naas

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Authors: Saroj Kumar Rath

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India's Muslims represent 15 percent of the nation's population, the world's third largest group in any nation after Indonesia and Pakistan. Extremist groups like the Islamic State, Al Qaeda, the Taliban and the Haqqani network increasingly view India as a target. Several trends explain the rise: Terrorism threats in South Asia are linked and mobile - if one source is batted down, jihadists relocate to find another Islamic cause. As NATO withdraws from Afghanistan, some jihadists will eye India. Pakistan regards India as a top enemy and some officials even encourage terrorists to target areas like Kashmir or Mumbai. Meanwhile, a stream of Wahhabi preachers have visited India, offering hard-line messages; extremist groups like Al Qaeda and the Islamic State compete for influence, and militants even pay jihadists. Muslims as a minority population in India could offer fertile ground for the extremist recruiters. This paper argues that there is an urgent need for the Indian government to profile militants and examine social media sites to attack Wahhabi indoctrination while supporting education and entrepreneurship for all of India's citizens.

Keywords: Al Qaeda, terrorism, Islamic state, India, haqqani network, Pakistan, Taliban

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Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

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Authors: Fatema Salman, Ridha Hammam, Fatima Khairallah, Fatima Aradi, Nafeesa Abdulla, Mohammed Alsafar

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Purpose: This study aims at measuring the extent of nurses’ knowledge and attitudes toward the use of physical restraints in different hospital wards at Salmaniya Medical Complex (SMC). Background: The habitual use of physical restraint is a widespread practice among nurses working in the clinical settings. Restraints inflict many deleterious consequences on patients physically and psychologically which in turn increases their morbidity and mortality risk and jeopardizes care quality. Nurses’ knowledge and attitudes toward physical restraints are crucial determinants of the persistence of this practice. Literature review: the evidence of lack of knowledge among nurses regarding the use of physical restraints is overwhelming in various clinical settings, especially in two main areas which are the negative consequences and the available alternatives to physical restraints. Studies explored nurses’ attitudes toward physical restraints yielded inconsistent findings. Equally comparable, some studies found that nurses hold positive attitudes toward the use of physical restraints while some others reported just the opposite. Methods: Self-administered knowledge and attitudes scales to 106 nurses working in the SMC. Findings: nurses hold the moderate level of knowledge about restraints (M=58%) with weak negative attitudes (M = -20%) toward using it. Significant moderately-strong negative correlation (r= -0.57, r2= 0.32, p= 0.000) was uncovered between nurses knowledge and their attitudes which provided an empirical explanation of this phenomenon (use of physical restraints). Recommendations: Induction of awareness program that especially focuses on the negative consequences and encourages the use of alternatives is an evident need. This effort necessarily should be adjoined with policy and procedure adjustments.

Keywords: attitudes, knowledge, nurses, restraints

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Authors: Yilei Yu

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Modernism, emerging in the Western world of the 20th century, attempted to create a universal international style, which pulled the architectural and social systems created by classicism back to an initial pure state. However, out of the introspection of the Modernism, Regionalism attempted to restore a humanistic environment and create flexible buildings during the 1950s. Meanwhile, as the first generation of architects came back, the wind of the Regionalism blew to Taiwan. However, with the increasing of political influence and the tightening of free creative space, from the second half of the 1950s to the 1980s, the "real" Regional Architecture, which should have taken roots in Taiwan, becomes the "fake" Regional Architecture filled with the oriental charm. Through the Comparative Method, which includes description, interpretation, juxtaposition, and comparison, this study analyses the difference of the style of the Modernist Chinese Architecture between the period before the 1980s and the after. The paper aims at exploring the development of Regionalism Architecture in Taiwan, which includes three parts. First, the burgeoning period of the "modernist Chinese architecture" in Taiwan was the beginning of the Chinese Nationalist Party's coming to Taiwan to consolidate political power. The architecture of the "Ming and Qing Dynasty Palace Revival Style" dominated the architectural circles in Taiwan. These superficial "regional buildings" have nearly no combination with the local customs of Taiwan, which is difficult to evoke the social identity. Second, in the late 1970s, the second generation of architects headed by Baode Han began focusing on the research and preservation of traditional Taiwanese architecture, and creating buildings combined the terroirs of Taiwan through the imitation of styles. However, some scholars have expressed regret that very few regionalist architectural works that appeared in the 1980s can respond specifically to regional conditions and forms of construction. Instead, most of them are vocabulary-led representations. Third, during the 1990s, by the end of the period of martial law, community building gradually emerged, which made the object of Taiwan's architectural concern gradually extended to the folk and ethnic groups. In the Yilan area, there are many architects who care about the local environment, such as the Field office Architects. Compared with the hollow regionality of the passionate national spirits that emerged during the martial law period, the local practice of the architect team in Yilan can better link the real local environmental life and reflect the true regionality. In conclusion, with the local practice case of the huge construction team in Yilan area, this paper focuses on the Spatial Practice by the Field office Architects to explore the spatial representation of the space and the practical enlightenment in the process of modernist Chinese architecture development in Taiwan.

Keywords: regionalism, modernism, Chinese architecture, political landscape, spatial representation

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Authors: Hideaki Endo, Mika Goto

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The global outbreak of the COVID-19 pandemic has seriously affected railway businesses. The number of railway passengers decreased due to the decline in the number of commuters and business travelers to avoid crowded trains and a sharp drop in inbound tourists visiting Japan. This has affected not only railway businesses but also related businesses, including hotels, leisure businesses, and retail businesses at station buildings. In 2021, the companies were divided into profitable and loss-making companies. This division suggests that railway companies, particularly loss-making companies, needed to decrease operational inefficiency. To measure the impact of COVID-19 and discuss the sustainable management strategies of railway companies, we examine the cost inefficiency of Japanese listed railway companies by applying stochastic frontier analysis (SFA) to their operational and financial data. First, we employ the stochastic frontier cost function approach to measure inefficiency. The cost frontier function is formulated as a Cobb–Douglas type, and we estimated parameters and variables for inefficiency. This study uses panel data comprising 26 Japanese-listed railway companies from 2005 to 2020. This period includes several events deteriorating the business environment, such as the financial crisis from 2007 to 2008 and the Great East Japan Earthquake of 2011, and we compare those impacts with those of the COVID-19 pandemic after 2020. Second, we identify the characteristics of the best-practice railway companies and examine the drivers of cost inefficiencies. Third, we analyze the factors influencing cost inefficiency by comparing the profiles of the top 10 railway companies and others before and during the pandemic. Finally, we examine the relationship between cost inefficiency and the implementation of efficiency measures for each railway company. We obtained the following four findings. First, most Japanese railway companies showed the lowest cost inefficiency (most efficient) in 2014 and the highest in 2020 (least efficient) during the COVID-19 pandemic. The second worst occurred in 2009 when it was affected by the financial crisis. However, we did not observe a significant impact of the 2011 Great East Japan Earthquake. This is because no railway company was influenced by the earthquake in this operating area, except for JR-EAST. Second, the best-practice railway companies are KEIO and TOKYU. The main reason for their good performance is that both operate in and near the Tokyo metropolitan area, which is densely populated. Third, we found that non-best-practice companies had a larger decrease in passenger kilometers than best-practice companies. This indicates that passengers made fewer long-distance trips because they refrained from inter-prefectural travel during the pandemic. Finally, we found that companies that implement more efficiency improvement measures had higher cost efficiency and they effectively used their customer databases through proactive DX investments in marketing and asset management.

Keywords: COVID-19 pandemic, stochastic frontier analysis, railway sector, cost efficiency

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Authors: Khalid Kaddoura, Tarek Zayed

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Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

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Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

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Authors: M. Moslehpour, S. Khorsandi

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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: CGA, ICMPv6, IPv6, malicious node, modifier, NDP, overall load, SEND, trust management

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

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Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: connected vehicles, GLOSA, intelligent transport systems, vehicle-to-infrastructure communication

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

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The loss of curd cohesiveness and syneresis are two common problems in the ultrafiltered cheese industry. In this study, by using membrane technology and protein modification, a modified cheese was developed and its properties were compared with a control sample. In order to decrease the lactose content and adjust the protein, acidity, dry matter and milk minerals, a combination of ultrafiltration, nanofiltration and reverse osmosis technologies was employed. For protein modification, a two-stage chemical and enzymatic reaction was employed before and after ultrafiltration. The physicochemical and microstructural properties of the modified ultrafiltered cheese were compared with the control one. Results showed that the modified protein enhanced the functional properties of the final cheese significantly (pvalue< 0.05), even if the protein content was 50% lower than the control one. The modified cheese showed 21 ± 0.70, 18 ± 1.10 & 25±1.65% higher hardness, cohesiveness and water-holding capacity values, respectively, than the control sample. This behavior could be explained by the developed microstructure of the gel network. Furthermore, chemical-enzymatic modification of milk protein induced a significant change in the network parameter of the final cheese. In this way, the indices of network linkage strength, network linkage density, and time scale of junctions were 10.34 ± 0.52, 68.50 ± 2.10 & 82.21 ± 3.85% higher than the control sample, whereas the distance between adjacent linkages was 16.77 ± 1.10% lower than the control sample. These results were supported by the results of the textural analysis. A non-linear viscoelastic study showed a triangle waveform stress of the modified protein contained cheese, while the control sample showed rectangular waveform stress, which suggested a better sliceability of the modified cheese. Moreover, to study the shelf life of the products, the acidity, as well as molds and yeast population, were determined in 120 days. It’s worth mentioning that the lactose content of modified cheese was adjusted at 2.5% before fermentation, while the lactose of the control one was at 4.5%. The control sample showed 8 weeks shelf life, while the shelf life of the modified cheese was 18 weeks in the refrigerator. During 18 weeks, the acidity of modified and control samples increased from 82 ± 1.50 to 94 ± 2.20 °D and 88 ± 1.64 to 194 ± 5.10 °D, respectively. The mold and yeast populations, with time, followed the semicircular shape model (R2 = 0.92, R2adj = 0.89, RMSE = 1.25). Furthermore, the mold and yeast counts and their growth rate in the modified cheese were lower than those for control one; Aforementioned result could be explained by the shortage of the source of energy for the microorganism in the modified cheese. The lactose content of the modified sample was less than 0.2 ± 0.05% at the end of fermentation, while this was 3.7 ± 0.68% in the control sample.

Keywords: non-linear viscoelastic, protein modification, semicircular shape model, ultrafiltered cheese

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Authors: Fakhrosadat Sajjadian, Ramin Ghasemi Shayan

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The tumor microenvironment plays an fundamental part in tumor start, movement, metastasis, and treatment resistance. It varies from ordinary tissue in terms of its extracellular network, vascular and lymphatic arrange, as well as physiological conditions. The clinical application of atomic cancer imaging is regularly prevented by the tall commercialization costs of focused on imaging operators as well as the constrained clinical applications and little showcase measure of a few operators. . Since numerous cancer types share comparable characteristics of the tumor microenvironment, the capacity to target these biomarkers has the potential to supply clinically translatable atomic imaging advances for numerous types encompassing cancer and broad clinical applications. Noteworthy advance has been made in focusing on the tumor microenvironment for atomic cancer imaging. In this survey, we summarize the standards and methodologies of later progresses in atomic imaging of the tumor microenvironment, utilizing distinctive imaging modalities for early discovery and conclusion of cancer. To conclude, The tumor microenvironment (TME) encompassing tumor cells could be a profoundly energetic and heterogeneous composition of safe cells, fibroblasts, forerunner cells, endothelial cells, flagging atoms and extracellular network (ECM) components.

Keywords: molecular, imaging, TME, medicine

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Authors: Christelle Rabbat, Carole Vouebou, Sary Awad, Alan Jean-Marie

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Hydrogen has been proven to be a viable alternative to standard fuels as it is easy to produce and only generates water vapour and zero carbon emissions. However, despite the hydrogen benefits, the widespread adoption of hydrogen fuel cell vehicles and internal combustion engine vehicles is impeded by several challenges. The lack of refueling infrastructures remains one of the main hindering factors due to the high costs associated with their design, construction, and operation. Besides, the lack of hydrogen vehicles on the road diminishes the economic viability of investing in refueling infrastructure. Simultaneously, the absence of accessible refueling stations discourages consumers from adopting hydrogen vehicles, perpetuating a cycle of limited market uptake. To address these challenges, the implementation of adequate policies incentivizing the use of hydrogen vehicles and the reduction of the investment and operation costs of hydrogen refueling stations (HRS) are essential to put both investors and customers at ease. Even though the transition to hydrogen cars has been rather slow, public transportation companies have shown a keen interest in this highly promising fuel. Besides, their hydrogen demand is easier to predict and regulate than personal vehicles. Due to the reduced complexity of designing a suitable hydrogen supply chain for public vehicles, this sub-sector could be a great starting point to facilitate the adoption of hydrogen vehicles. Consequently, this study will focus on designing a chain of on-site green HRS for the public transportation network in Nantes Metropole leveraging the latest relevant technological advances aiming to reduce the costs while ensuring reliability, safety, and ease of access. To reduce the cost of HRS and encourage their widespread adoption, a network of 7 H35-T40 HRS has been designed, replacing the conventional J-T valves with turbo-expanders. Each station in the network has a daily capacity of 1,920 kg. Thus, the HRS network can produce up to 12.5 tH2 per day. The detailed cost analysis has revealed a CAPEX per station of 16.6 M euros leading to a network CAPEX of 116.2 M euros. The proposed station siting prioritized Nantes metropole’s 5 bus depots and included 2 city-centre locations. Thanks to the turbo-expander technology, the cooling capacity of the proposed HRS is 19% lower than that of a conventional station equipped with J-T valves, resulting in significant CAPEX savings estimated at 708,560 € per station, thus nearly 5 million euros for the whole HRS network. Besides, the turbo-expander power generation ranges from 7.7 to 112 kW. Thus, the power produced can be used within the station or sold as electricity to the main grid, which would, in turn, maximize the station’s profit. Despite the substantial initial investment required, the environmental benefits, cost savings, and energy efficiencies realized through the transition to hydrogen fuel cell buses and the deployment of HRS equipped with turbo-expanders offer considerable advantages for both TAN and Nantes Metropole. These initiatives underscore their enduring commitment to fostering green mobility and combatting climate change in the long term.

Keywords: green hydrogen, refueling stations, turbo-expander, heavy-duty vehicles

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Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

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Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: S. Anastasiou, C. Nathanailides

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There is considerable evidence to suggest that employees participation in the decision-making process of an organisation, has a positive effect on job satisfaction and work performance of the employees. The purpose of the present work was to examine the HRM practices, demographics and the level of job satisfaction of employees in Greek Aquaculture fish farms. A survey of employees (n=86) in 6 Greek Aquaculture Firms was carried out. The results indicate that HRM practices such as recruitment of the personnel and communication between the departments did not vary between different firms. The most frequent method of recruitment was through the professional network or the personal network of the managers. The preferred method of HRM communication was through the line managers and through group meeting. The level of job satisfaction increased with work experience participation and participation in the decision making process. A high percentage of the employees (81,3%±8.39) felt that they frequently participated in the decision making process. The Aquaculture employees exhibited high level of job satisfaction (88,1±6.95). The level of job satisfaction was related with participation in the decision making process (-0.633, P<0.05) but was not related with as age or gender. In terms of the working conditions, employees were mostly satisfied with their work itself, their colleagues and mostly dissatisfied with working hours, salary issues and low prospects of pay rises.

Keywords: aquaculture, human resources, job satisfaction

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Authors: Vinay Gupta, Seema Malhotra

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Background: Patients who usually consume tobacco are unaware of its ill effects completely therefore it becomes necessary to educate and counselling them after obtaining their knowledge about tobacco. Aim: To measure prevalence of tobacco use among dental outpatients and to evaluation of tobacco user attending dental outpatients (OPD) prepared to quit. Methods: A cross-sectional survey, which was carried out on patients attending Outside Patient Department (OPD) of dental college of King Georges Medical University, Lucknow, India. All the patients who consumed tobacco attending the Dental College were asked to participate in the study. The questionnaire was written in English/ Hindi (local language). Participation in this study was voluntary and the questionnaire was anonymous and self-administered. The proposal of this survey had been approved by the ethical committee of institution. Informed consent was obtained from all the participants. Results: Prevalence of tobacco user attending the Dental OPD was 46.4%. Male tobacco user represented 85.9%. Smokeless tobacco (57%) user were more than smoking (1.4%) and 18.9% were using both smokeless and smoking tobacco. 40.7% start using tobacco since less than 5 years. 55.3% uses tobacco after get up in the morning. 87.1% tobacco user knows that it cause cancer. 54.8% respond that warning sign on packet/pouch effect on mind but due to addiction, it would not work out. 54.8% attempted for quitting but not successful. 90.0% willing to quit in future if facility provide. Conclusion: Higher prevalence of tobacco usage among study population and will to quit in future shows need of cessation clinic in every dental institution in India.

Keywords: tobacco, knowledge, practice, counselling

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Authors: Karla E. Sanchez-Cazares, Kim H. Parker, Jennifer H. Tweedy

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The purpose of this work is to develop a simple compartmental model of cerebral fluid balance including blood and cerebrospinal-fluid (CSF). At the first level the cerebral arteries and veins are modelled as bifurcating trees with constant scaling factors between generations which are connected through a homogeneous microcirculation. The arteries and veins are assumed to be non-rigid and the cross-sectional area, resistance and mean pressure in each generation are determined as a function of blood volume flow rate. From the mean pressure and further assumptions about the variation of wall permeability, the transmural fluid flux can be calculated. The results suggest the next level of modelling where the cerebral vasculature is divided into three compartments; the large arteries, the small arteries, the capillaries and the veins with effective compliances and permeabilities derived from the detailed vascular model. These vascular compartments are then linked to other compartments describing the different CSF spaces, the cerebral ventricles and the subarachnoid space. This compartmental model is used to calculate the distribution of fluid in the cranium. Known volumes and flows for normal conditions are used to determine reasonable parameters for the model, which can then be used to help understand pathological behaviour and suggest clinical interventions.

Keywords: cerebrovascular, compartmental model, CSF model, vascular network

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Authors: John Morales, Armando Guzman

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Protection relay algorithms play a crucial role in Electric Power System stability, where, it is clear that lightning strokes produce the mayor percentage of faults and outages of Transmission Lines (TLs) and Distribution Feeders (DFs). In this context, it is imperative to develop novel protection relay algorithms. However, in order to get this aim, Electric Power Systems (EPS) network have to be simulated as real as possible, especially the lightning phenomena, and EPS elements that affect their behavior like direct and indirect lightning, insulator string, overhead line, soil ionization and other. However, researchers have proposed new protection relay algorithms considering common faults, which are not produced by lightning strokes, omitting these imperative phenomena for the transmission line protection relays behavior. Based on the above said, this paper presents the possibilities of using the Alternative Transient Program ATP-Draw for the modeling and simulation of some models to make lightning stroke studies, especially for protection relays, which are developed through Transient Analysis of Control Systems (TACS) and MODELS language corresponding to the ATP-Draw.

Keywords: back-flashover, faults, flashover, lightning stroke, modeling of lightning, outages, protection relays

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

Abstract:

An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

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Authors: Farouk Shehu Abdulwahab

Abstract:

The concept of farmer-farmer knowledge sharing was introduced to bridge the extension worker-farmer ratio gap in developing countries. However, the idea was poorly accepted, especially in typical agrarian communities. Therefore, the study explores the concept of a farmer-to-farmer knowledge-sharing network to enhance extension service delivery. The study collected data from 80 farmers randomly selected through a series of multiple stages. The Data was analysed using a 5-point Likert scale and descriptive statistics. The Likert scale results revealed that 62.5% of the farmers are satisfied with farmer-to-farmer knowledge-sharing networks. Moreover, descriptive statistics show that lack of capacity building and low level of education are the most significant problems affecting farmer-farmer sharing networks. The major implication of these findings is that the concept of farmer-farmer knowledge-sharing networks can work better for farmers in developing countries as it was perceived by them as a reliable alternative for information sharing. Therefore, the study recommends introducing incentives into the concept of farmer-farmer knowledge-sharing networks and enhancing the capabilities of farmers who are opinion leaders in the farmer-farmer concept of knowledge-sharing to make it more sustainable.

Keywords: agricultural productivity, extension, farmer-to-farmer, livelihood, technology transfer

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Authors: Maria M. S. Pires, Andre F. X. Gloria, Pedro J. A. Sebastiao

Abstract:

The technological advances in the area of Internet of Things have been creating more and more solutions in the area of agriculture. These solutions are quite important for life, as they lead to the saving of the most precious resource, water, being this need to save water a concern worldwide. The paper proposes the creation of an Internet of Things system based on a network of sensors and interconnected actuators that automatically monitors the quality of the rainwater that is stored inside a tank in order to be used for irrigation. The main objective is to promote sustainability by reusing rainwater for irrigation systems instead of water that is usually available for other functions, such as other productions or even domestic tasks. A mobile application was developed for Android so that the user can control and monitor his system in real time. In the application, it is possible to visualize the data that translate the quality of the water inserted in the tank, as well as perform some actions on the implemented actuators, such as start/stop the irrigation system and pour the water in case of poor water quality. The implemented system translates a simple solution with a high level of efficiency and tests and results obtained within the possible environment.

Keywords: internet of things, irrigation system, wireless sensor and actuator network, ESP32, sustainability, water reuse, water efficiency

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Authors: Mir Afzal Tajik

Abstract:

The 'Strengthening Teacher Education in Pakistan' (STEP) is an innovative programme jointly funded by the Government of Canada and the Aga Khan Foundation Canada and implemented by the Aga Khan University - Institute for Educational Development (AKU-IED) in partnership with the local governments, education departments and communities in the provinces of Balochistan, Sindh and Gilgit-Baltistan in Pakistan. One of the key components of the programme is professional development of teachers, head teachers and teacher educators through a variety of teacher education programmes including a two-year Masters of Education (MEd) Programme offered by AKU-IED. A number of teachers, head teachers and teacher educators from these provinces have been developed through the MEd Programme. This paper discusses a qualitative research study conducted to explore the nature, relevance, rigor and richness of the experiences of the MEd graduates, and how these experiences have fostered their own professional development and their ability to bring about positive changes in their schools. The findings of the study provide useful insights into the graduates’ self-actualization, transformation of their professional beliefs and practices, the difference they have made in their schools, and the challenges they face. The study also provides evidences of how the implementation of this multi-stakeholders and multi-partners STEP programme has led to the development of ‘communities of practice’ in schools. The study then makes a number of recommendations for policy and practice related to teacher education programmes as well as for partnerships in education.

Keywords: STEP, change agents, Pakistan, Canada, teacher education, MEd

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Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

Abstract:

Objective: Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. Methods: 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as independent component analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. Results: The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. Conclusion: This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: ICA, RSN, refractory epilepsy, rsfMRI

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Authors: Fisayo G. Ojo, Shamala K. Subramaniam, Zuriati Ahmad Zukarnain

Abstract:

As technology is advancing and wireless applications are becoming dependable sources, while the physical layer of the applications are been embedded into tiny layer, so the more the problem on energy efficiency and consumption. This paper reviews works done in recent years in wireless applications and distributed computing, we discovered that applications are becoming dependable, and resource allocation sharing with other applications in distributed computing. Applications embedded in distributed system are suffering from power stability and efficiency. In the reviews, we also prove that discrete event simulation has been left behind untouched and not been adapted into distributed system as a simulation technique in scheduling of each event that took place in the development of distributed computing applications. We shed more lights on some researcher proposed techniques and results in our reviews to prove the unsatisfactory results, and to show that more work still have to be done on issues of energy efficiency in wireless applications, and congestion in distributed computing.

Keywords: discrete event simulation (DES), distributed computing, energy efficiency (EE), internet of things (IOT), quality of service (QOS), user equipment (UE), wireless mesh network (WMN), wireless sensor network (wsn), worldwide interoperability for microwave access x (WiMAX)

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Authors: Rara Wulan Anggareni, Narita Putri, Riski Septianing Astuti

Abstract:

Breastfeeding is a key to prevent mortality and morbidity in children. It is also the second highest risk responsible for Disability Adjusted Life Years (DALYs) among children below five years old. UNICEF estimates that during 1995 – 2003, there are only about 38% infants in developing countries who get to be exclusively breastfed during the first six months of their lives. According to Demography and Health Survey in Indonesia 2007, breastfeed practice rate still considered as low which is about 41%. One of the factors causing the low breastfeed practice rate in Indonesia is the anxiety and postpartum depression, and also the weanling dilemma in which mother feels that her breastmilk cannot suffice infant needs. Those factors finally resulting into low or even stopped production of breastmilk. Breastmilk production can be enhanced by consuming food containing phytosterol and lactogoga effect. Food with the highest phytosterol level is Sauropus androgynus (L.) Merr leaf (merr leaf). In this study, we made alternative food which named Chocomerr for breastfeeding mothers. Chocomerr consists of merr leaves which have lactogoga effect and chocolate for relaxation. Based on organoleptic tests conducted towards 2 age groups, which are 18 – 21 and 25 – 40 years old, this product gets good acceptance in taste, texture, and colour categories. Chocomerr can be used as an alternative way for increasing breastmilk production to aim for the decreasing number of DALYs among children aged under 5 years old.

Keywords: breastfeeding, increasing, chocolate, merr leaves

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Authors: Jesvin Puay-Hwa Yeo, Laavanya Kathiravelu, Sa’Eda Binte Buang

Abstract:

In the early days, myths and taboos were used by our ancestors to give explanations to the existence of nature and man, as well as to propitiate fortunes and to avoid unluckiness and harm. Myths and taboos are deeply rooted in our cultures and environment, and they form certain characteristics of any society, even in modern societies. With decades of the three main ethnic communities in Singapore – Malay, Indian and Chinese – living together, there has been intermingling and intermixing of traditions and practices. This may mean that what we think is a ‘Malay’ practice is actually one that is a hybrid of the Chinese and Malay. A good example would be the practice of covering all mirrors in a house of mourning. Therefore, the proposed seeks to explore and understand the underlying social influences of Singapore’s oral tradition. As part of a bigger cultural research project: Designing Cultures, the proposed paper focused on using secondary data to contribute to the overall cultural understanding of the integral connections between oral traditions, people and landscapes. The proposed paper will discuss in details the initials findings of the research project, including the two manners that contributed to the intermixing of myths and taboos. The first is the presence of social institutions such as religions, and the second is the presence of cross-cultural minorities such as the Straits Chinese. As well as other observations included the use and influence of Chinese oral traditions such as folklore among the early Chinese immigrants through social institutions.

Keywords: cultural belief, multiracial society, myths, oral tradition

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