Search results for: quest based learning

Authors: Nicole Vlasman, Karamjeet Dhillon

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Over the past four years, the Healthy Relationships Program has been delivered in community organizations and schools across Canada. More than 240 groups have been facilitated in collaboration with 33 organizations. As a result, 2157 youth have been engaged in the programming. The purpose and scope of the Healthy Relationships Program are to offer sustainable, evidence-based skills through small group implementation to prevent violence and promote positive, healthy relationships in youth. The program development has included extensive networking at regional and national levels. The Healthy Relationships Program is currently being implemented, adapted, and researched within the Resilience and Inclusion through Strengthening and Enhancing Relationships (RISE-R) project. Alongside the project’s research objectives, the RISE-R team has worked to virtually share the ongoing findings of the project through a slow ontology approach. Slow ontology is a practice integrated into project systems and structures whereby slowing the pace and volume of outputs offers creative opportunities. Creative production reveals different layers of success and complements the project, the building blocks for sustainability. As a result of integrating a slow ontology approach, the RISE-R team has developed a Geographic Information System (GIS) that documents local landscapes through a Story Map feature, and more specifically, video installations. Video installations capture the cartography of space and place within the context of singular diverse community spaces (case studies). By documenting spaces via human connections, the project captures narratives, which further enhance the voices and faces of the community within the larger project scope. This GIS project aims to create a visual and interactive flow of information that complements the project's mixed-method research approach. Conclusively, creative project development in the form of a geographic information system can provide learning and engagement opportunities at many levels (i.e., within community organizations and educational spaces or with the general public). In each of these disconnected spaces, fragmented stories are connected through a visual display of project outputs. A slow ontology practice within the context of the RISE-R project documents activities on the fringes and within internal structures; primarily through documenting project successes as further contributions to the Centre for School Mental Health framework (philosophy, recruitment techniques, allocation of resources and time, and a shared commitment to evidence-based products).

Keywords: community programming, geographic information system, project development, project management, qualitative, slow ontology

Procedia PDF Downloads 146

Authors: Kingkan Pongsiri

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This paper aims to study the role and activities of the participants and the impact of activities created in the local area in order to sustainably develop the local areas. This study applied both qualitative and quantitative approaches presented in descriptive style; the data was collected via survey, observation and in-depth interviews with samples. The results illustrated five sorts of roles of participants of the Cicada Walking-street and four types of creative activities; recreation based, art based, cultural based, and live events. Integration of local characteristics, arts and cultures were presented creatively and interestingly. Participants are various. The roles of the participants found in the Cicada Market are group of the property and area management, entrepreneurs, leisure (entertaining persons), local people, and tourists. The good impacts on local communities are those in terms of economy, environmental friendly and local arts and cultures promoting. On the other hand, the traffic congestion, waste and the increasing of energy consumption are negative impacts from area development.

Keywords: creative tourism activity, destination development, sustainable development, walking street

Procedia PDF Downloads 238

Authors: Essam Al Daoud

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Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

Procedia PDF Downloads 159

Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

Procedia PDF Downloads 68

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.

Keywords: defense/attack strategies, information, networks, reliability, survivability

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Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Xiang Chen

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After the prohibition of tin-based fouling-prevention coatings in 2003, the researchers were directed toward eco-friendly coatings. Because of their nonstick, environmental, and economic benefits, foul-release nanocoatings have received a lot of attention. They use physical anti-adhesion terminology to deter any fouling attachment.Natural bioinspired surfaces have micro/nano-roughness and low surface free energy features, which may inspire the design of dynamic antifouling coatings. Graphene-based nanocomposite surfaces were designed to combat marine-fouling adhesion with ecological as well as eco-friendly effects rather than biocidal solutions. Polymer–graphenenanofiller hybrids are a novel class of composite materials in fouling-prevention applications. The controlled preparation of nanoscale orientation, arrangement, and direction along the composite building blocks would result in superior fouling prohibition. This work representsfoul-release nanocomposite top coats for marine coating applications with superhydrophobicity, surface inertness against fouling adherence, cost-effectiveness, and increased lifetime.

Keywords: foul-release nanocoatings, graphene-based nanocomposite, polymer, nanofillers

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Authors: Muhammad Shafiq, Huynh Trung Luong

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In this paper, we proposed a commitment based revenue sharing contract for a supply chain comprising one manufacturer and one retailer facing highly uncertain demand of a short life span fashionable product. In our model, the retailer reserves a commitment level with the manufacturer prior to the selling season. In response, the manufacturer allocates and produces a specific quantity which is the maximum available quantity for the retailer. The retailer is motivated to commit more by offering higher revenue sharing percentage for reserved capacity than non-reserved capacity. Due to asymmetric information, it is found that the manufacturer can optimize quantity allocation decision while the commitment level decision of the retailer may not be optimal.

Keywords: supply chain coordination, revenue sharing contract, commitment based revenue sharing, quantity allocation

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Deddi Nordiawan

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Effective public policy creation required a strong budget system, both in terms of design and implementation. Performance-based Budget is an evolutionary approach with two substantial characteristics; first, the strong integration between budgeting and planning, and second, its existence as guidance so that all activities and expenditures refer to measurable performance targets. There are four processes in the government that should be followed in order to make the budget become performance-based. These four processes consist of the preparation of a vision according to the bold aspiration, the formulation of outcome, the determination of output based on the analysis of organizational resources, and the formulation of Value Creation Map that contains a series of programs and activities. This is consistent with the concept of logic model which revealed that the budget performance should be placed within a relational framework of resources, activities, outputs, outcomes and impacts. Through the issuance of Law 17/2003 regarding State Finance, local governments in Indonesia have to implement performance-based budget. Central Government then issued Government Regulation 58/2005 which contains the detail guidelines how to prepare local governments budget. After a decade, implementation of performance budgeting in local government is still not fully meet expectations, though the guidance is completed, socialization routinely performed, and trainings have also been carried out at all levels. Accordingly, this study views the practice of performance-based budget at local governments as a problematic situation. This condition must be approached with a system approach that allows the solutions from many point of views. Based on the fact that the infrastructure of budgeting has already settled, the study then considering the situation as complexity. Therefore, the intervention needs to be done in the area of human activity system. Using Soft Systems Methodology, this research will reconstruct the process of performance-based budget at local governments is area of human activity system. Through conceptual models, this study will invite all actors (central government, local government, and the parliament) for dialogue and formulate interventions in human activity systems that systematically desirable and culturally feasible. The result will direct central government in revise the guidance to local government budgeting process as well as a reference to build the capacity building strategy.

Keywords: soft systems methodology, performance-based budgeting, Indonesia, public policy

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Authors: Chun-Chung Chen, Bo-Han Lee, Yu-Chi Sung

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Monitoring the status of tensioning force of stay cables is a significant issue for the assessment of structural safety of extradosed bridges. Moreover, it is known that there is a high correlation between the existing tension force and the vibration frequencies of cables. This paper presents the characteristic of frequencies of stay cables of a field extradosed bridge by using vibration-based monitoring methods. The vibration frequencies of each stay cables were measured in stages from the beginning to the completion of bridge construction. The result shows that the vibration frequency variation trend of different lengths of cables at each measured stage is different. The observed feature can help the application of the bridge long-term monitoring system and contribute to the assessment of bridge safety.

Keywords: vibration-based method, extradosed bridges, bridge health monitoring, bridge stay cables

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Authors: Indrasen Raghupatruni, Michael Glora, Ralf Diekmann, Thomas Demmer

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As the trend in automotive technology is fast moving towards hybridization and electrification to curb emissions as well as to improve the fuel efficiency, air-conditioning systems in passenger cars have not caught up with this trend and still remain as the major energy consumers amongst others. Adsorption based air-conditioning systems, e.g. with silica-gel water pair, which are already in use for residential and commercial applications, are now being considered as a technology leap once proven feasible for the passenger cars. In this paper we discuss a methodology, challenges and feasibility of implementing an adsorption based air-conditioning system in a passenger car utilizing the exhaust waste heat. We also propose an optimized control strategy with interfaces to the engine control unit of the vehicle for operating this system with reasonable efficiency supported by our simulation and validation results in a prototype vehicle, additionally comparing to existing implementations, simulation based as well as experimental. Finally we discuss the influence of start-stop and hybrid systems on the operation strategy of the adsorption air-conditioning system.

Keywords: adsorption air-conditioning, feasibility study, optimized control strategy, prototype vehicle

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Authors: A. A. Altalbe, N. W Bergmann

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There has been significant recent interest in on-line learning, as well as considerable work on developing technologies for virtual laboratories for engineering students. After reviewing the state-of-the-art of virtual laboratories, this paper steps back from the technology issues to look in more detail at the pedagogical issues surrounding virtual laboratories, and examines the role of gathering student feedback in the development of such laboratories. The main contribution of the paper is a set of student surveys before and after a prototype deployment of a simulation laboratory tool, and the resulting analysis which leads to some tentative guidelines for the design of virtual engineering laboratories.

Keywords: engineering education, elearning, electrical engineering, virtual laboratories

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Authors: Li Li, Ahmed A. Abd El-Latif, Aya El-Fatyany, Mohamed Amin

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This paper proposes a new secret image sharing method based on integer discrete cosine transform (IntDCT). It first transforms the original image into the frequency domain (DCT coefficients) using IntDCT, which are operated on each block with size 8*8. Then, it generates shares among each DCT coefficients in the same place of each block, that is, all the DC components are used to generate DC shares, the ith AC component in each block are utilized to generate ith AC shares, and so on. The DC and AC shares components with the same number are combined together to generate DCT shadows. Experimental results and analyses show that the proposed method can recover the original image lossless than those methods based on traditional DCT and is more sensitive to tiny change in both the coefficients and the content of the image.

Keywords: secret image sharing, integer DCT, lossless recovery, sensitivity

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan

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Authors: Djamel Saba, Fatima Zohra Laallam, Brahim Berbaoui

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This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.

Keywords: communications protocols, control process, energy management, hybrid energy system, modelization, multi-agents system, simulation

Procedia PDF Downloads 316

Authors: Woosik Jang, Seung Heon Han, Seung Won Baek

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Natural gas (NG) is an energy resource in a few countries, and most NG producers do business in politically unstable countries. In addition, as 90% of the LNG market is controlled by a small number of international oil companies (IOCs) and national oil companies (NOCs), entry of latecomers into the market is extremely limited. To meet these challenges, project viability needs to be assessed based on limited information from a project screening perspective. However, the early stages of the project have the following difficulties: (1) What are the factors to consider? (2) How many professionals do you need to decide? (3) How to make the best decision with limited information? To address this problem, this study proposes a model for evaluating LNG project viability based on the Dempster-Shafer theory (DST). A total of 11 indicators for analyzing the gas field, reflecting the characteristics of the LNG industry, and 23 indicators for analyzing the market environment, were identified. The proposed model also evaluates the LNG project based on the survey and provides uncertainty of the results based on DST as well as quantified results. Thus, the proposed model is expected to be able to support the decision-making process of the gas field project using quantitative results as a systematic framework, and it was developed as a stand-alone system to improve its usefulness in practice. Consequently, the amount of information and the mathematical approach are expected to improve the quality and opportunity of decision making for LNG projects for enterprises.

Keywords: project screen, energy enterprise, decision support system, Dempster-Shafer theory

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Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

Procedia PDF Downloads 121

Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

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Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: clustering, fake news detection, feature selection, machine learning, social media, support vector machine

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Authors: Mustafa Aydın, Ali Murat Sunbul

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Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

Procedia PDF Downloads 645

Authors: Zhao Haoyue

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Due to the combined effects of climate change, urban expansion, and population growth, various environmental issues, such as urban heat islands and pollution, arise. Therefore, reliable information on urban environmental climate is needed to address and mitigate the negative effects. The emergence of urban climate maps provides a practical basis for urban climate regulation and improvement. This article takes Shapingba District, Chongqing City, as an example to study the construction method of urban thermal environment climate maps based on GIS spatial analysis technology. The thermal load, ventilation potential analysis map, and thermal environment comprehensive analysis map were obtained. Based on the classification criteria obtained from the climate map, corresponding protection and planning mitigation measures have been proposed.

Keywords: urban climate, GIS, heat island analysis, urban thermal environment

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Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

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Authors: Daniel J. Glauber

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Knowledge transfer between personnel could benefit an organization’s improved competitive advantage in the marketplace from a strategic approach to knowledge management. The lack of information sharing between personnel could create knowledge transfer gaps while restricting the decision-making processes. Knowledge transfer between personnel can potentially improve information sharing based on an implemented knowledge management strategy. An organization’s capacity to gain more knowledge is aligned with the organization’s prior or existing captured knowledge. This case study attempted to understand the overall influence of a KMS within the corporate environment and knowledge exchange between personnel. The significance of this study was to help understand how organizations can improve the Return on Investment (ROI) of a knowledge management strategy within a knowledge-centric organization. A qualitative descriptive case study was the research design selected for this study. The lack of information sharing between personnel may create knowledge transfer gaps while restricting the decision-making processes. Developing a knowledge management strategy acceptable at all levels of the organization requires cooperation in support of a common organizational goal. Working with management and executive members to develop a protocol where knowledge transfer becomes a standard practice in multiple tiers of the organization. The knowledge transfer process could be measurable when focusing on specific elements of the organizational process, including personnel transition to help reduce time required understanding the job. The organization studied in this research acknowledged the need for improved knowledge management activities within the organization to help organize, retain, and distribute information throughout the workforce. Data produced from the study indicate three main themes including information management, organizational culture, and knowledge sharing within the workforce by the participants. These themes indicate a possible connection between an organizations KMS, the organizations culture, knowledge sharing, and knowledge transfer.

Keywords: knowledge transfer, management, knowledge management strategies, organizational learning, codification

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Mark Deschaine, David Whale

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Utilization of online instruction continues to increase at universities, placing more emphasis on the exploration of issues related to adult graduate student engagement. This reflective case study reviews non-traditional student engagement in online courses. The goals of the study are to enhance student focus, attention and interaction. Findings suggest that interactivity seemed to be a key in keeping students involved and achieving, with specific activities routinely favored by students. It is recommended that time spent engaging students is worthwhile and results in greater course satisfaction and academic effort.

Keywords: online learning, student achievement, student engagement, technology

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Authors: Tigabu Dagne Akal

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Electronic health records (EHRs) can help to store, maintain, and make the appropriate handling of patient histories for proper treatment and decision. Merging the EHRs with big data analytics (BDA) capabilities enable healthcare stakeholders to provide effective and efficient treatments for chronic diseases. Though there are huge opportunities and efforts that exist in the deployment of EMRs and the development of BDA, there are challenges in addressing resources and organizational capabilities that are required to achieve the competitive advantage and sustainability of EHRs and BDA. The resource-based view (RBV), information system (IS), and non- IS theories should be extended to examine organizational capabilities and resources which are required for successful data analytics in the healthcare industries. The main purpose of this study is to develop a conceptual framework for the development of healthcare BDA capabilities based on past works so that researchers can extend. The research question was formulated for the search strategy as a research methodology. The study selection was made at the end. Based on the study selection, the conceptual framework for the development of BDA capabilities in the healthcare settings was formulated.

Keywords: EHR, EMR, Big data, Big data analytics, resource-based view

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Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

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Authors: Shuyu Zhang

Abstract:

The waterfront historical district, as a type of historical districts on the verge of waters such as the sea, lake, and river, have a relatively special urban form. In the past preservation and renewal of traditional historic districts, there have been many discussions on the land range, and the waterfront and marginal spaces are easily overlooked. However, the waterfront space of the historic districts, as a cultural landscape heritage combining historical buildings and landscape elements, has strong ecological and sustainable values. At the same time, Suzhou and Venice, as sister water cities in history, have more waterfront spaces that can be compared in urban form and other levels. Therefore, this paper focuses on the waterfront historic districts in Venice and Suzhou, establishes quantitative evaluation indicators for environmental perception, makes analogies, and promotes the renewal and activation of the entire historical district by improving the spatial quality and vitality of the waterfront area. First, this paper uses multi-source data for analysis, such as Baidu Maps and Google Maps API to crawl the street view of the waterfront historic districts, uses machine learning algorithms to analyze the proportion of cultural landscape elements such as green viewing rate in the street view pictures, and uses space syntax software to make quantitative selectivity analysis, so as to establish environmental perception evaluation indicators for the waterfront historic districts. Finally, by comparing and summarizing the waterfront historic districts in Venice and Suzhou, it reveals their similarities and differences, characteristics and conclusions, and hopes to provide a reference for the heritage preservation and renewal of other waterfront historic districts.

Keywords: waterfront historical district, cultural landscape, perception, multi-source Data

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Authors: Jothilakshmy Nagammal

Abstract:

This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

Procedia PDF Downloads 420