Search results for: fuzzy network project

Authors: Po-Chen Chen, Tsung-Han Yang, Zhi-Wei Zheng, Shih-Tsang Tang

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Falls are the most common accidents during mountain hiking, especially in high-altitude environments with unstable terrain or adverse weather. Balance ability is a crucial factor in hiking, effectively ensuring hiking safety and reducing the risk of injuries. If balance ability can be assessed simply and effectively, hikers can identify their weaknesses and conduct targeted training to improve their balance ability, thereby reducing injury risks. With the widespread use of smartphones and their built-in inertial sensors, this project aims to develop a simple Inertial Measurement Unit (IMU) balance measurement technique based on smartphones. This will provide hikers with an easy-to-use, low-cost tool for assessing balance ability, monitoring training effects in real-time, and continuously tracking balance ability through uploading cloud data uploads, facilitating personal athletic performance.

Keywords: balance, IMU, smartphone, wearable devices

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Authors: Chen Yao, Wang Ke

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Small towns are the most basic administrative institutions in our country, which are connected with cities and rural areas. Small towns play an important role in promoting local urban and rural economic development, providing the main public services and maintaining social stability in social governance. With the vigorous development of small towns and the transformation of industrial structure, the changes of social structure, spatial structure, and lifestyle are lagging behind, causing that the spatial form and landscape style do not belong to both cities and rural areas, and seriously affecting the quality of people’s life space and environment. The rural economy in Zhejiang Province has started, the society and the population are also developing in relative stability. In September 2016, Zhejiang Province set out the 'Technical Guidelines for Comprehensive Environmental Remediation of Small Towns in Zhejiang Province,' so as to comprehensively implement the small town comprehensive environmental remediation with the main content of strengthening the plan and design leading, regulating environmental sanitation, urban order and town appearance. In November 2016, Huzhou City started the comprehensive environmental improvement of small towns, strived to use three years to significantly improve the 115 small towns, as well as to create a number of high quality, distinctive and beautiful towns with features of 'clean and livable, rational layout, industrial development, poetry and painting style'. This paper takes Meixi Town, Zhangwu Town and Sanchuan Village in Huzhou City as the empirical cases, analyzes the small town public space by applying the relative theory of actor-network and space syntax. This paper also analyzes the spatial composition in actor and social structure elements, as well as explores the relationship of actor’s spatial practice and public open space by combining with actor-network theory. This paper introduces the relevant theories and methods of spatial syntax, carries out research analysis and design planning analysis of small town spaces from the perspective of quantitative analysis. And then, this paper proposes the effective updating strategy for the existing problems in public space. Through the planning and design in the building level, the dissonant factors produced by various spatial combination of factors and between landscape design and urban texture during small town development will be solved, inhabitant quality of life will be promoted, and town development vitality will be increased.

Keywords: small towns, urbanization, public space, updating

Procedia PDF Downloads 220

Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Noor Arda Adrina Daud, Mohd Hanafi Ali

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The compensating filter is placed between the patient and X-ray tube to compensate various density and thickness of human body. The main purpose of this project is to study the effect of compensating filter on image quality in lateral projection of thoracolumbar radiography. The study was performed by an X-ray unit where different thicknesses of aluminum were used as compensating filter. Specifically the relationship between thickness of aluminum, density and noise were evaluated. Results show different thickness of aluminum compensating filter improved the image quality of lateral projection thoracolumbar radiography. The compensating filter of 8.2 mm was considered as the optimal filter to compensate the thoracolumbar junction (T12-L1), 1 mm to compensate lumbar region and 5.9 mm to compensate thorax region. The aluminum wedge compensating filter was designed resulting in an acceptable image quality.

Keywords: compensating filter, aluminum, image quality, lateral, thoracolumbar

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Authors: Supattra Kanchanopast

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The purpose of this research is to develop and design a management information system for 7 eleven shop in Bangkok. The system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management. The implementation of the MIS for the mini-mart shop, can lessen the amount of paperwork and reduce repeating tasks so it may decrease the capital of the business and support an extension of branches in the future as well.

Keywords: convenience store, the management information system, inventory management, 7 eleven shop

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Authors: A. Ardianto, M. A. Putera Agung, S. Pramusandi

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Power waterway is one of dam structures and as an intake vertical tunnel or well function for hydroelectric power plants in Jatigede area, Sumedang, West Java. Gate shaft is also one of parts the power waterway system. The paper concerns some consideration in determining a critical state parameter on the back stability analysis of gate shaft or excavation wall stability during excavation. Study analysis was carried out using without and with reinforcement system. Results study showed that reinforcement shaft could reduce the total displacement and safety factor could increases significantly. Based on the back calculation results, it was recommended to install some reinforcement materials and drainage system to reduce pore water pressure.

Keywords: power waterway, reinforcement, displacement, safety

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: J. Tamosaitiene

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The article focuses on the identification and classification of key risk management criteria that represent the most important sustainability aspects of the construction industry. The construction sector is one of the most important sectors in Lithuania. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects, the growth of enterprises and the sector. To establish the most important criteria for successful growth of the sector, a questionnaire for experts was developed. The analytic hierarchy process (AHP), the expert judgement method and other multicriteria decision making (MCDM) methods were used to develop the hybrid model. The results were used to develop an integrated knowledge system for the measurement of a risk level particular to construction projects. The article presents a practical case that details the developed system, sustainable aspects, and risk assessment.

Keywords: risk, system, model, construction

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Authors: Alexis D'Agostino, Amanda Pomeroy

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Background: Resource availability is essential to effective implementation of national nutrition policies. To this end, the SPRING Project has collected and analyzed budget data from government ministries in Uganda, international donors, and other nutrition implementers to provide data for the first time on what funding is actually allocated to implement nutrition activities named in the national nutrition plan. Methodology: USAID’s SPRING Project used the Uganda Nutrition Action Plan (UNAP) as the starting point for budget analysis. Thorough desk reviews of public budgets from government, donors, and NGOs were mapped to activities named in the UNAP and validated by key informants (KIs) across the stakeholder groups. By relying on nationally-recognized and locally-created documents, SPRING provided a familiar basis for discussions to increase credibility and local ownership of findings. Among other things, the KIs validated the amount, source, and type (specific or sensitive) of funding. When only high-level budget data were available, KIs provided rough estimates of the percentage of allocations that were actually nutrition-relevant, allowing creation of confidence intervals around some funding estimates. Results: After validating data and narrowing in on estimates of funding to nutrition-relevant programming, researchers applied a formula to estimate overall nutrition allocations. In line with guidance by the SUN Movement and its three-step process, nutrition-specific funding was counted at 100% of its allocation amount, while nutrition sensitive funding was counted at 25%. The vast majority of nutrition funding in Uganda is off-budget, with over 90 percent of all nutrition funding is provided outside of the government system. Overall allocations are split nearly evenly between nutrition-specific and –sensitive activities. In FY 2013/14, the two-year study’s baseline year, on- and off-budget funding for nutrition was estimated to be around 60 million USD. While the 60 million USD allocations compare favorably to the 66 million USD estimate of the cost of the UNAP, not all activities are sufficiently funded. Those activities with a focus on behavior change were the most underfunded. In addition, accompanying qualitative research suggested that donor funding for nutrition activities may shift government funding into other areas of work, making it difficult to estimate the sustainability of current nutrition investments.Conclusions: Beyond providing figures, these estimates can be used together with the qualitative results of the study to explain how and why these amounts were allocated for particular activities and not others, examine the negotiation process that occurred, and suggest options for improving the flow of finances to UNAP activities for the remainder of the policy tenure. By the end of the PBN study, several years of nutrition budget estimates will be available to compare changes in funding over time. Halfway through SPRING’s work, there is evidence that country stakeholders have begun to feel ownership over the ultimate findings and some ministries are requesting increased technical assistance in nutrition budgeting. Ultimately, these data can be used within organization to advocate for more and improved nutrition funding and to improve targeting of nutrition allocations.

Keywords: budget, nutrition, financing, scale-up

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Dariush Jafari, Seyed Ali Jafari

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The recommended limit for cadmium concentration in potable water is less than 0.005 mg/L. A continuous biosorption process using indigenous red seaweed, Gracilaria corticata, was performed to remove cadmium from the potable water. The process was conducted under fixed conditions and the breakthrough curves were achieved for three consecutive sorption-desorption cycles. A modeling based on Artificial Neural Network (ANN) was employed to fit the experimental breakthrough data. In addition, a simplified semi empirical model, Thomas, was employed for this purpose. It was found that ANN well described the experimental data (R2>0.99) while the Thomas prediction were a bit less successful with R2>0.97. The adjusted design parameters using the nonlinear form of Thomas model was in a good agreement with the experimentally obtained ones. The results approve the capability of ANN to predict the cadmium concentration in potable water.

Keywords: ANN, biosorption, cadmium, packed-bed, potable water

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Authors: Sagar Hedaoo, Fazle Baki, Ahmed Azab

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In supply chain management, network design for scalable manufacturing facilities is an emerging field of research. Facility location allocation assigns facilities to customers to optimize the overall cost of the supply chain. To further optimize the costs, capacities of these facilities can be changed in accordance with customer demands. A mathematical model is formulated to fully express the problem at hand and to solve small-to-mid range instances. A dedicated constraint has been developed to restrict emissions in line with the Kyoto protocol. This problem is NP-Hard; hence, a simulated annealing metaheuristic has been developed to solve larger instances. A case study on the USA-Canada cross border crossing is used.

Keywords: emission, mixed integer linear programming, metaheuristic, simulated annealing

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Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Saïd, Hervé Bournot, Georges Le Palec

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This paper spots light on the effect of a point source pollution on streams, stemming out from intentional release caused by unconscious facts. The consequences of such contamination on ecosystems are very serious. Accordingly, effective tools are highly demanded in this respect, which enable us to come across an accurate progress of pollutant and anticipate different measures to be applied in order to limit the degradation of the environmental surrounding. In this context, we are eager to model a pollutant dispersion of a free surface flow which is ejected by an outfall sewer of an urban sewerage network in coastal water taking into account the influence of climatic parameters on the spread of pollutant. Numerical results showed that pollutant dispersion is merely due to the presence of vortices and turbulence. Hence, it was realized that the pollutant spread in seawater is strongly correlated with climatic conditions in this region.

Keywords: coastal waters, numerical simulation, pollutant dispersion, turbulent flows

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Authors: Dingyang Hu, Dan Liu

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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: F. Saptouw, L. Reddy

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Tertiary institutions are often faced with a challenge when incorporating social awareness into course content. The information campaigns in the media often alienate the viewers and the knowledge is not readily assimilated into the students’ consciousness. This paper will present a discussion of the results of collaborative teaching projects run by the Michaelis School of fine art and the HIV/AIDS, Inclusivity and Change Unit (HAICU) at the University of Cape Town. In these projects the artistic process is employed to generate ‘praxical knowledge’ in the student body about socially relevant issues like HIV-AIDS, Gender-Based Violence (GBV) and sexual identity, specifically LGBTQI. The combination of lectures, group discussions and the creative process has been a very successful way to disseminate information amongst the student population. Evidence of the project’s success will be provided by referencing interviews, focus groups as well as surveys done with the participants. This paper will conclude by arguing for the positive role of practice-led research in developing a socially conscious public.

Keywords: art, education, HIV-AIDS, practice-led research

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Authors: Tamilmani Thiruvengadam, Ramasthanan Arulampalam

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This project comprises laying approximately 1.8km of 400mm, 1200mm and 2400mm diameter sewer pipes using pipe jacking machines along Mugliston Park, Buangkok Drive, and Buangkok Link. The works include an estimated 14 circular shafts with depth ranging from 10.0 meters to 29.0 meters. Cast in-situ circular shaft will be used for the temporary shaft excavation. The geology is predominantly Backfill and old alluvium with weak material encountered in between. Where there is a very soft clay, F1 material or weak soil is expected, ground improvement will be carried out outside of the shaft followed by cast in-situ concrete ring wall within the improved soil zone. This paper presents the design methodology, analysis and results of temporary shafts for micro TBM launching and constructing permanent manholes. There is also a comparison of instrumentation readings with the analysis predicted values.

Keywords: circular shaft, ground improvement, old alluvium, temporary shaft

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Authors: Markandeya Kunchi

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Usability testing (UT) is one of the vital steps in the User-centred design (UCD) process when designing a product. In an e-commerce ecosystem, UT becomes primary as new products, features, and services are launched very frequently. And, there are losses attached to the company if an unusable and inefficient product is put out to market and is rejected by customers. This paper tries to answer why UT is important in the product life-cycle of an E-commerce ecosystem. Secondary user research was conducted to find out work patterns, development methods, type of stakeholders, and technology constraints, etc. of a typical E-commerce company. Qualitative user interviews were conducted with product managers and designers to find out the structure, project planning, product management method and role of the design team in a mid-level company. The paper tries to address the usual apprehensions of the company to inculcate UT within the team. As well, it stresses upon factors like monetary resources, lack of usability expert, narrow timelines, and lack of understanding of higher management as some primary reasons. Outsourcing UT to vendors is also very prevalent with mid-level e-commerce companies, but it has its own severe repercussions like very little team involvement, huge cost, misinterpretation of the findings, elongated timelines, and lack of empathy towards the customer, etc. The shortfalls of the unavailability of a UT process in place within the team and conducting UT through vendors are bad user experiences for customers while interacting with the product, badly designed products which are neither useful and nor utilitarian. As a result, companies see dipping conversions rates in apps and websites, huge bounce rates and increased uninstall rates. Thus, there was a need for a more lean UT system in place which could solve all these issues for the company. This paper highlights on optimizing the UT process with a collaborative method. The degree of optimization and structure of collaborative method is the highlight of this paper. Collaborative method of UT is one in which the centralised design team of the company takes for conducting and analysing the UT. The UT is usually a formative kind where designers take findings into account and uses in the ideation process. The success of collaborative method of UT is due to its ability to sync with the product management method employed by the company or team. The collaborative methods focus on engaging various teams (design, marketing, product, administration, IT, etc.) each with its own defined roles and responsibility in conducting a smooth UT with users In-house. The paper finally highlights the positive results of collaborative UT method after conducting more than 100 In-lab interviews with users across the different lines of businesses. Some of which are the improvement of interaction between stakeholders and the design team, empathy towards users, improved design iteration, better sanity check of design solutions, optimization of time and money, effective and efficient design solution. The future scope of collaborative UT is to make this method leaner, by reducing the number of days to complete the entire project starting from planning between teams to publishing the UT report.

Keywords: collaborative method, e-commerce, product management method, usability testing

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Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: air pollution, AODV, re-scheduling, WSNs

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Authors: Santiago Macho, Miquel Montaner, Raivo Ruusalepp, Ferran Candela, Xavier Tarres, Rando Rostok

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During our lives, we generate a lot of personal information such as photos, music, text documents and videos that link us with our past. This data that used to be tangible is now digital information stored in our computers, which implies a software dependence to make them accessible in the future. Technology, however, constantly evolves and goes through regular shifts, quickly rendering various file formats obsolete. The need for accessing data in the future affects not only personal users but also organizations. In a digital environment, a reliable preservation plan and the ability to adapt to fast changing technology are essential for maintaining data collections in the long term. We present in this paper the European FP7 project called DURAFILE that provides the technology to preserve media files for personal users and organizations while maintaining their quality.

Keywords: artificial intelligence, digital preservation, social search, digital preservation plans

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Authors: Jiri Dufek

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The national model of the Czech Republic has been modified in a detailed way to get detailed travel demand in the municipality level (cities, villages over 300 inhabitants). As a technique for this detailed modelling, three-dimensional procedure for calibrating gravity models, was used. Besides of zone production and attraction, which is usual in gravity models, the next additional parameter for trip distribution was introduced. Usually it is called by “third dimension”. In the model, this parameter is a demand between regions. The distribution procedure involved calculation of appropriate skim matrices and its multiplication by three coefficients obtained by iterative balancing of production, attraction and third dimension. This type of trip distribution was processed in R-project and the results were used in the Czech Republic transport model, created in PTV Vision. This process generated more precise results in local level od the model (towns, villages)

Keywords: trip distribution, three dimension, transport model, municipalities

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Authors: Anisuzzaman Khan, A. J. K. Masud

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Bangladesh is the largest delta in the world predominantly comprising large network of rives and wetlands. Wetlands in Bangladesh are represented by inland freshwater, estuarine brakishwater and tidal salt-water coastal wetlands. Bangladesh possesses enormous area of wetlands including rivers and streams, freshwater lakes and marshes, haors, baors, beels, water storage reservoirs, fish ponds, flooded cultivated fields and estuarine systems with extensive mangrove swamps. The past, present, and future of Bangladesh, and its people’s livelihoods are intimately connected to its relationship with water and wetlands. More than 90% of the country’s total area consists of alluvial plains, crisscrossed by a complex network of rivers and their tributaries. Floodplains, beels (low-lying depressions in the floodplain), haors (deep depression) and baors (oxbow lakes) represent the inland freshwater wetlands. Over a third of Bangladesh could be termed as wetlands, considering rivers, estuaries, mangroves, floodplains, beels, baors and haors. The country’s wetland ecosystems also offer critical habitats for globally significant biological diversity. Of these the deeply flooded basins of north-east Bangladesh, known as haors, are a habitat of wide range of wild flora and fauna unique to Bangladesh. The haor basin lies within the districts of Sylhet, Sunamgonj, Netrokona, Kishoregonj, Habigonj, Moulvibazar, and Brahmanbaria in the Northeast region of Bangladesh comprises the floodplains of the Meghna tributaries and is characterized by the presence of numerous large, deeply flooded depressions, known as haors. It covers about around 8,568 km2 area of Bangladesh. The topography of the region is steep at around foothills in the north and slopes becoming mild and milder gradually at downstream towards south. Haor is a great reservoir of aquatic biological resources and acts as the ecological safety net to the nature as well as to the dwellers of the haor. But in reality, these areas are considered as wastelands and to make these wastelands into a productive one, a one sided plan has been implementing since long. The programme is popularly known as Flood Control, Drainage and Irrigation (FCDI) which is mainly devoted to increase the monoculture rice production. However, haor ecosystem is a multiple-resource base which demands an integrated sustainable development approach. The ongoing management approach is biased to only rice production through FCDI. Thus this primitive mode of action is diminishing other resources having more economic potential ever thought.

Keywords: freshwater wetlands, biological diversity, biological resources, conservation and sustainable development

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Authors: W. S. Barber, S. L. King

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This paper reports on a pilot project to develop a collaborative partnership between a community college in rural northern Ontario, Canada, and an urban university in the greater Toronto area in Oshawa, Canada. Partner institutions will collaborate to address learning needs of university applicants whose goals are to attain an undergraduate university BA in Educational Studies and Digital Technology degree, but who may not live in a geographical location that would facilitate this pathways process. The UOIT BA degree is attained through a 2+2 program, where students with a 2 year college diploma or equivalent can attain a four year undergraduate degree. The goals reported on the project are as: 1. Our aim is to expand the BA program to include an additional stream which includes serious educational games, simulations and virtual environments, 2. Develop fully (using both synchronous and asynchronous technologies) online learning modules for use by university applicants who otherwise are not geographically located close to a physical university site, 3. Assess the digital competencies of all students, including members of local, distance and Indigenous communities using a validated tool developed and tested by UOIT across numerous populations. This tool, the General Technical Competency Use and Scale (GTCU) will provide the collaborating institutions with data that will allow for analyzing how well students are prepared to succeed in fully online learning communities. Philosophically, the UOIT BA program is based on a fully online learning communities model (FOLC) that can be accessed from anywhere in the world through digital learning environments via audio video conferencing tools such as Adobe Connect. It also follows models of adult learning and mobile learning, and makes a university degree accessible to the increasing demographic of adult learners who may use mobile devices to learn anywhere anytime. The program is based on key principles of Problem Based Learning, allowing students to build their own understandings through the co-design of the learning environment in collaboration with the instructors and their peers. In this way, this degree allows students to personalize and individualize the learning based on their own culture, background and professional/personal experiences. Using modified flipped classroom strategies, students are able to interrogate video modules on their own time in preparation for one hour discussions occurring in video conferencing sessions. As a consequence of the program flexibility, students may continue to work full or part time. All of the partner institutions will co-develop four new modules, administer the GTCU and share data, while creating a new stream of the UOIT BA degree. This will increase accessibility for students to bridge from community colleges to university through a fully digital environment. We aim to work collaboratively with Indigenous elders, community members and distance education instructors to increase opportunities for more students to attain a university education.

Keywords: aboriginal, college, competencies, digital, universities

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Authors: Seyed Abolhassan Naeini, Maedeh Akhavan Tavakkoli

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Determining soil engineering properties is essential for geotechnical problems. In addition to high cost, invasive soil survey methods can be time-consuming, so geophysical methods can be an excellent choice to determine soil characteristics. In this study, geoelectric investigation using the Wenner arrangement method has been used to determine the amount of soil corrosion in soil layers in a project site as a case study. This study aims to assess the degree of corrosion of soil layers to a depth of 5 meters and find the variation of soil electrical resistance versus depth. For this purpose, the desired points in the study area were marked and specified, and all withdrawals were made within the specified points. The collected data have been processed by standard and accepted methods, and the results have been presented in the form of calculation tables and curves of electrical resistivity with depth.

Keywords: Wenner array, geoelectric, soil corrosion, electrical soil resistance

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

Abstract:

In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: Kai Zhu, Shanhua He, Yujiao Chang

Abstract:

This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.

Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok

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Authors: Langhit Kurar, Loren Charles

Abstract:

Introduction: In light of recent BOAST 12 (August 2016) published guidance on management of ankle fractures, the project aimed to highlight key discrepancies throughout the care trajectory from admission to point of discharge at a district general hospital. Wide breadth of data covering three key domains: accident and emergency, radiology, and orthopaedic surgery were subsequently stratified and recommendations on note documentation, and outpatient follow up were made. Methods: A retrospective twelve month audit was conducted reviewing results of ankle fracture management in 37 patients. Inclusion criterion involved all patients seen at Darent Valley Hospital (DVH) emergency department with radiographic evidence of an ankle fracture. Exclusion criterion involved all patients managed solely by nursing staff or having sustained purely ligamentous injury. Medical notes, including discharge summaries and the PACS online radiographic tool were used for data extraction. Results: Cross-examination of the A & E domain revealed limited awareness of the BOAST 12 recent publication including requirements to document skin integrity and neurovascular assessment. This had direct implications as this would have changed the surgical plan for acutely compromised patients. The majority of results obtained from the radiographic domain were satisfactory with appropriate X-rays taken in over 95% of cases. However, due to time pressures within A & E, patients were often left without a post manipulation XRAY in a backslab. Poorly reduced fractures were subsequently left for a long period resulting in swollen ankles and a time-dependent lag to surgical intervention. This had knocked on implications for prolonged inpatient stay resulting in hospital-acquired co-morbidity including pressure sores. Discussion: The audit has highlighted several areas of improvement throughout the disease trajectory from review in the emergency department to follow up as an outpatient. This has prompted the creation of an algorithm to ensure patients with significant fractures presenting to the emergency department are seen promptly and treatment expedited as per recent guidance. This includes timing for X-rays taken in A & E. Re-audit has shown significant improvement in both documentation at time of presentation and appropriate follow-up strategies. Within the orthopedic domain, we are in the process of creating an ankle fracture pathway to ensure imaging and weight bearing status are made clear to the consulting clinicians in an outpatient setting. Significance/Clinical Relevance: As a result of the ankle fracture algorithm we have adapted the BOAST 12 guidance to shape an intrinsic pathway to not only improve patient management within the emergency department but also create a standardised format for follow up.

Keywords: ankle, fracture, BOAST, radiology

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Authors: Nighat Ayub, Masood Ahmad

Abstract:

In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

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Authors: Yi-Jiun Chou, Ying-Hsuan Li, Yi-Jung Liu, Hsin-Yu Chiang, Hsuan-Ching Wang

Abstract:

Background: Patients received therapeutic hypothermia (TH) after resuscitation from cardiac arrest are more dependent on continue and intensive nursing care. It involves many difficult steps, especially achieving target body temperature. To our best knowledge, there is no consensus or recommended standards on nursing practice of TH. Aim: The aim of this study is to increase the completion rate of nursing care at therapeutic hypothermia. Methods: We took five measures: (1) Amendment of nursing standards of therapeutic hypothermia; (2) Amendment of TH checklist items to nursing records; (3) Establishment of monitor procedure; (4) Design each period of TH care reminder cards; (5) Providing in-service training sections of TH for ICU nursing staff. Outcomes: The completion rate of nursing care at therapeutic hypothermia increased from 78.1% to 89.3%. Conclusion: The project team not only increased the completion rate but also improved patient safety and quality of care.

Keywords: therapeutic hypothermia, nursing, critical care, quality of care

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