Search results for: Risk Management.

Authors: Eulalia Torras, Andreu Bellot

Abstract:

To know whether students’ achievements are the result of online interaction and not just a consequence of individual differences themselves, it seems essential to link the teaching presence and social presence to the types of knowledge built. The research aim is to analyze the social presence in relation to two types of knowledge, declarative and procedural. Qualitative methodology has been used. The analysis of the contents was based on an observation protocol that included community of enquiry indicators and procedural and declarative knowledge indicators. The research has been conducted in three phases that focused on an observational protocol and indicators, results and conclusions. Results show that the teaching-learning processes have been characterized by the patterns of presence and types of knowledge. Results also show the importance of social presence support provided by the teacher and the students, not only in regard to the nature of the instructional support but also concerning how it is presented to the student and the importance that is attributed to it in the teaching-learning process, that is, what it is that assistance is offered on. In this study, we find that the presence based on procedural guidelines and declarative reflection, the management of shared meaning on the basis of the skills and the evidence of these skills entail patterns of learning. Nevertheless, the importance that the teacher attributes to each support aspect has a bearing on the extent to which the students reflect more on the given task.

Keywords: Education, online, teaching and learning processes, knowledge.

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Authors: M. Moslehpour, S. Khorsandi

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Due to shortage in IPv4 addresses, transition to IPv6 has gained significant momentum in recent years. Like Address Resolution Protocol (ARP) in IPv4, Neighbor Discovery Protocol (NDP) provides some functions like address resolution in IPv6. Besides functionality of NDP, it is vulnerable to some attacks. To mitigate these attacks, Internet Protocol Security (IPsec) was introduced, but it was not efficient due to its limitation. Therefore, SEND protocol is proposed to automatic protection of auto-configuration process. It is secure neighbor discovery and address resolution process. To defend against threats on NDP’s integrity and identity, Cryptographically Generated Address (CGA) and asymmetric cryptography are used by SEND. Besides advantages of SEND, its disadvantages like the computation process of CGA algorithm and sequentially of CGA generation algorithm are considerable. In this paper, we parallel this process between network resources in order to improve it. In addition, we compare the CGA generation time in self-computing and distributed-computing process. We focus on the impact of the malicious nodes on the CGA generation time in the network. According to the result, although malicious nodes participate in the generation process, CGA generation time is less than when it is computed in a one-way. By Trust Management System, detecting and insulating malicious nodes is easier.

Keywords: NDP, IPsec, SEND, CGA, Modifier, Malicious node, Self-Computing, Distributed-Computing.

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Authors: G. T. Balakayeva, K. K. Nurlybayeva, M. B. Zhanuzakov

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In the proposed work, we have developed software and designed a software architecture for the implementation of enterprise business processes. The proposed software has a multi-level architecture using a domain-specific tool. The developed architecture is a guarantor of the availability, reliability and security of the system and the implementation of business processes, which are the basis for effective enterprise management. Automating business processes, automating the algorithmic stages of an enterprise, developing optimal algorithms for managing activities, controlling and monitoring, reducing risks and improving results help organizations achieve strategic goals quickly and efficiently. The software described in this article can connect to the corporate information system via two methods: a desktop client and a web client. With an appeal to the application server, the desktop client program connects to the information system on the company's work PCs over a local network. Outside the organization, the user can interact with the information system via a web browser, which acts as a web client and connects to a web server. The developed software consists of several integrated modules that share resources and interact with each other through an API. The following technology stack was used during development: Node js, React js, MongoDB, Ngnix, Cloud Technologies, Python.

Keywords: Algorithms, document processing, automation, integrated modules, software architecture, software design, information system.

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Authors: Lara F. Horani, Shurong Tong

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Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.

Keywords: Analytic hierarchy process, green product, customer requirements for green design, importance weights for the customer requirements.

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Authors: L. P. K. Liyanage, N. R. P. Withana, A. L. Sandika

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The purpose of this study was to determine tourist and community perception-based sustainable tourism indicators as well as Human Pressure Index (HPI) and Tourist Activity Index (TAI). Study was carried out in Sinharaja forest which is considered as one of the major eco-tourism destination in Sri Lanka. Data were gathered using a pre-tested semi-structured questionnaire as well as records from Forest department. Convenient sampling technique was applied. For the majority of issues, the responses were obtained on multi-point Likert-type scales. Visual portrayal was used for display analyzed data. The study revealed that the host community of the Kudawa gets many benefits from tourism. Also, tourism has caused negative impacts upon the environment and community. The study further revealed the need of proper waste management and involvement of local cultural events for the tourism business in the Kudawa conservation center. The TAI, which accounted to be 1.27 and monthly evolution of HPI revealed that congestion can be occurred in the Sinharaja rainforest during peak season. The results provide useful information to any party involved with tourism planning anywhere, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: Kudawa conservation center, Sinharaja world heritage rainforest, sustainability indicators.

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Authors: Shaukat Wasi, Zubair A. Shaikh, Sajid Qasmi, Hussain Sachwani, Rehman Lalani, Aamir Chagani

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Automatic Extraction of Event information from social text stream (emails, social network sites, blogs etc) is a vital requirement for many applications like Event Planning and Management systems and security applications. The key information components needed from Event related text are Event title, location, participants, date and time. Emails have very unique distinctions over other social text streams from the perspective of layout and format and conversation style and are the most commonly used communication channel for broadcasting and planning events. Therefore we have chosen emails as our dataset. In our work, we have employed two statistical NLP methods, named as Finite State Machines (FSM) and Hidden Markov Model (HMM) for the extraction of event related contextual information. An application has been developed providing a comparison among the two methods over the event extraction task. It comprises of two modules, one for each method, and works for both bulk as well as direct user input. The results are evaluated using Precision, Recall and F-Score. Experiments show that both methods produce high performance and accuracy, however HMM was good enough over Title extraction and FSM proved to be better for Venue, Date, and time.

Keywords: Emails, Event Extraction, Event Detection, Finite state machines, Hidden Markov Model.

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Authors: Gupta Amit, Kumar Ramesh, Tewari P. C.

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies economic order quantity (EOQ), just in time (JIT), vendor managed inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: Inventory Policy, Ranking, DBA, Selection criteria.

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Authors: M. Eisakhani, A. Pauzi, O. Karim, A. Malakahmad, S.R. Mohamed Kutty, M. H. Isa

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Cameron Highlands is a mountainous area subjected to torrential tropical showers. It extracts 5.8 million liters of water per day for drinking supply from its rivers at several intake points. The water quality of rivers in Cameron Highlands, however, has deteriorated significantly due to land clearing for agriculture, excessive usage of pesticides and fertilizers as well as construction activities in rapidly developing urban areas. On the other hand, these pollution sources known as non-point pollution sources are diverse and hard to identify and therefore they are difficult to estimate. Hence, Geographical Information Systems (GIS) was used to provide an extensive approach to evaluate landuse and other mapping characteristics to explain the spatial distribution of non-point sources of contamination in Cameron Highlands. The method to assess pollution sources has been developed by using Cameron Highlands Master Plan (2006-2010) for integrating GIS, databases, as well as pollution loads in the area of study. The results show highest annual runoff is created by forest, 3.56 × 108 m3/yr followed by urban development, 1.46 × 108 m3/yr. Furthermore, urban development causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural activities and forest contribute the highest annual loads for phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr), respectively. Therefore, best management practices (BMPs) are suggested to be applied to reduce pollution level in the area.

Keywords: Cameron Highlands, Land use, Non-point Sources of Pollution

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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This study proposes a conceptual model and empirically tests the relationships between customers and librarians (i.e. tangibles, responsiveness, assurance, reliability and empathy) with a dependent variable (customer satisfaction) regarding library services. The SERVQUAL instrument was administered to 100 respondents which comprises of staff and students at a public higher learning institution in the Federal Territory of Labuan, Malaysia. They were public university library users. Results revealed that all service quality dimensions tested were significant and influenced customer satisfaction of visitors to a public university library. Assurance is the most important factor that influences customer satisfaction with the services rendered by the librarian. It is imperative for the library management to take note that the top five service attributes that gained greatest attention from library visitors- perspective includes employee willingness to help customers, availability of customer representatives online for response to queries, library staff actively and promptly provide services, signs in the building are clear and library staff are friendly and courteous. This study provides valuable results concerning the determinants of the service quality and customer satisfaction of public university library services from the users' perspective.

Keywords: Service Quality, Customer Satisfaction, SERVQUAL Model, Multiple Regression Analysis

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: Jamileh Vasheghani Farahani

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The main purpose of this research is to show the current active faults and active tectonic of the area by three seismic networks in Tehran region: 1-Tehran Disaster Mitigation and Management Organization (TDMMO), 2-Broadband Iranian National Seismic Network Center (BIN), 3-Iranian Seismological Center (IRSC). In this study, we analyzed microearthquakes happened in Tehran city and its surroundings using the Tehran networks from 1996 to 2015. We found some active faults and trends in the region. There is a 200-year history of historical earthquakes in Tehran. Historical and instrumental seismicity show that the east of Tehran is more active than the west. The Mosha fault in the North of Tehran is one of the active faults of the central Alborz. Moreover, other major faults in the region are Kahrizak, Eyvanakey, Parchin and North Tehran faults. An important seismicity region is an intersection of the Mosha and North Tehran fault systems (Kalan village in Lavasan). This region shows a cluster of microearthquakes. According to the historical and microseismic events analyzed in this research, there is a seismic gap in SE of Tehran. The empirical relationship is used to assess the Mmax based on the rupture length. There is a probability of occurrence of a strong motion of 7.0 to 7.5 magnitudes in the region (based on the assessed capability of the major faults such as Parchin and Eyvanekey faults and historical earthquakes).

Keywords: Iran, major faults, microseismicity, Tehran.

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: False negative rate, intrusion detection system, machine learning methods, performance.

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Authors: Luis A. Morales Rosales, Saul E. Pomares Hernandez, Gustavo Rodriguez Gomez

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Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.

Keywords: Event ordering, fuzzy causal ordering, happenedbefore relation and cooperative systems.

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Authors: Sangamesh G. Sakri, Akash N. Patil, Sadashivappa M. Kotli

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Agro based industries in India are considered as the micro, small and medium enterprises (MSME). In India, MSMEs contribute approximately 8 percent of the country’s GDP, 42 percent of the manufacturing output and 40 percent of exports. The toor dal (scientific name Cajanus cajan, commonly known as yellow gram, pigeon pea) is the second largest pulse crop in India accounting for about 20% of total pulse production. The toor dal milling industry in India is one of the major agro-processing industries in the country. Most of the dal mills are concentrated in pulse producing areas, which are spread all over the country. In Karnataka state, Gulbarga is a district, where toor dal is the main crop and is grown extensively. There are more than 500 dal mills in and around the Gulbarga district to process dal. However, the majority of these dal milling units use traditional methods of processing which are energy and capital intensive. There exists a huge energy saving potential in these mills. An energy audit is conducted on a dal mill in Gulbarga to understand the energy consumption pattern to assess the energy saving potential, and an economic analysis is conducted to identify energy conservation opportunities.

Keywords: Conservation, demand side management, load curve, toor dal.

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Authors: Vijay Shankar

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Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In past, various estimation methods have been developed for different climatological data, and the accuracy of these methods varies with climatic conditions. Reference crop evapotranspiration (ET0) is a key variable in procedures established for estimating evapotranspiration rates of agricultural crops. Values of ET0 are used with crop coefficients for many aspects of irrigation and water resources planning and management. Numerous methods are used for estimating ET0. As per internationally accepted procedures outlined in the United Nations Food and Agriculture Organization-s Irrigation and Drainage Paper No. 56(FAO-56), use of Penman-Monteith equation is recommended for computing ET0 from ground based climatological observations. In the present study, seven methods have been selected for performance evaluation. User friendly software has been developed using programming language visual basic. The visual basic has ability to create graphical environment using less coding. For given data availability the developed software estimates reference evapotranspiration for any given area and period for which data is available. The accuracy of the software has been checked by the examples given in FAO-56.The developed software is a user friendly tool for estimating ET0 under different data availability and climatic conditions.

Keywords: Crop coefficient, Crop evapotranspiration, Field moisture, Irrigation Scheduling.

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Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba

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Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.

Keywords: Wireless sensor network, node, application, monitoring, insecurity, environment.

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Authors: Payel Ghosh, Rama Chandra Pradhan, Sabyasachi Mishra

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Jamun (Syzygium cuminii L.) is one of the important indigenous minor fruit with high medicinal value. The jamun cultivation is unorganized and there is huge loss of this fruit every year. The perishable nature of the fruit makes its postharvest management further difficult. Due to the strong cell wall structure of pectin-protein bonds and hard seeds, extraction of juice becomes difficult. Enzymatic treatment has been commercially used for improvement of juice quality with high yield. The objective of the study was to optimize the best treatment method for juice extraction. Enzymes (Pectinase and Tannase) from different stains had been used and for each enzyme, best result obtained by using response surface methodology. Optimization had been done on the basis of physicochemical property, nutritional property, sensory quality and cost estimation. According to quality aspect, cost analysis and sensory evaluation, the optimizing enzymatic treatment was obtained by Pectinase from Aspergillus aculeatus strain. The optimum condition for the treatment was 44 ^oC with 80 minute with a concentration of 0.05% (w/w). At these conditions, 75% of yield with turbidity of 32.21NTU, clarity of 74.39%T, polyphenol content of 115.31 mg GAE/g, protein content of 102.43 mg/g have been obtained with a significant difference in overall acceptability.

Keywords: Jamun, enzymatic treatment, physicochemical property, sensory analysis, optimization.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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Authors: Diana Fajardo, Sebastián Ortiz, Oscar Herrera, Angélica Santis

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Currently, in Colombia is arising a problem related to collecting used lubricant oils which are generated by the increment of the vehicle fleet. This situation does not allow a proper disposal of this type of waste, which in turn results in a negative impact on the environment. Therefore, through the comparative analysis of various heuristics, the best solution to the VRP (Vehicle Routing Problem) was selected by comparing costs and times for the collection of used lubricant oils in the city of Pereira, Colombia; since there is no presence of management companies engaged in the direct administration of the collection of this pollutant. To achieve this aim, six proposals of through methods of solution of two phases were discussed. First, the assignment of the group of generator points of the residue was made (previously identified). Proposals one and four of through methods are based on the closeness of points. The proposals two and five are using the scanning method and the proposals three and six are considering the restriction of the capacity of collection vehicle. Subsequently, the routes were developed - in the first three proposals by the Clarke and Wright's savings algorithm and in the following proposals by the Traveling Salesman optimization mathematical model. After applying techniques, a comparative analysis of the results was performed and it was determined which of the proposals presented the most optimal values in terms of the distance, cost and travel time.

Keywords: Heuristics, optimization model, savings algorithm used vehicular oil, VRP.

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter.

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Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

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This article illustrates a model selection management approach for virtual prototypes in interactive simulations. In those numerical simulations, the virtual prototype and its environment are modelled as a multiagent system, where every entity (prototype,human, etc.) is modelled as an agent. In particular, virtual prototyp ingagents that provide mathematical models of mechanical behaviour inform of computational methods are considered. This work argues that selection of an appropriate model in a changing environment,supported by models? characteristics, can be managed by the deter-mination a priori of specific exploitation and performance measures of virtual prototype models. As different models exist to represent a single phenomenon, it is not always possible to select the best one under all possible circumstances of the environment. Instead the most appropriate shall be selecting according to the use case. The proposed approach consists in identifying relevant metrics or indicators for each group of models (e.g. entity models, global model), formulate their qualification, analyse the performance, and apply the qualification criteria. Then, a model can be selected based on the performance prediction obtained from its qualification. The authors hope that this approach will not only help to inform engineers and researchers about another approach for selecting virtual prototype models, but also assist virtual prototype engineers in the systematic or automatic model selection.

Keywords: Virtual prototype models, domain, qualification criterion, model qualification, model assessment, environmental modelling.

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Authors: Nkechi Neboh, Josiah Adeyemo, Abimbola Enitan, Oludayo Olugbara

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Evolutionary Algorithms (EAs) have been used widely through evolution theory to discover acceptable solutions that corresponds to challenges such as natural resources management. EAs are also used to solve varied problems in the real world. EAs have been rapidly identified for its ease in handling multiple objective problems. Reservoir operations is a vital and researchable area which has been studied in the last few decades due to the limited nature of water resources that is found mostly in the semi-arid regions of the world. The state of some developing economy that depends on electricity for overall development through hydropower production, a renewable form of energy, is appalling due to water scarcity. This paper presents a review of the applications of evolutionary algorithms to reservoir operation for hydropower production. This review includes the discussion on areas such as genetic algorithm, differential evolution, and reservoir operation. It also identified the research gaps discovered in these areas. The results of this study will be an eye opener for researchers and decision makers to think deeply of the adverse effect of water scarcity and drought towards economic development of a nation. Hence, it becomes imperative to identify evolutionary algorithms that can address this issue which can hamper effective hydropower generation.

Keywords: Evolutionary algorithms, genetic algorithm, hydropower, multi-objective, reservoir operations.

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Authors: Sanae Attioui, Said Najah

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The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: Ahmed Mostafa, Mohamed Mahmoud, Nesreen H. Hafez, Mohamed Fahim

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This retrospective study includes 60 patients with pre-invasive breast cancer. Aim of the study: Evaluation of premalignant lesions of the breast (DCIS), different treatment methods and outcome. Patients and methods: 60 patients with DCIS were studied from the period between 2005 to 2012, for 38 patients the primary surgical method was wide local resection (WLE) (63.3%) and the other cases (22 patients, 36.7%) had mastectomy, fourteen cases from those who underwent local excision received radiotherapy, while no adjuvant radiotherapy was given for those who underwent mastectomy. In case of hormonal receptor positive DCIS lesions hormonal treatment (Tamoxifen) was given after local control. Results: No difference in overall survival between mastectomy & breast conserving therapy (wide local excision and adjuvant radiotherapy), however local recurrence rate is higher in case of breast conserving therapy, also no role of Axillary evacuation in case of DCIS. The use of hormonal therapy decreases the incidence of local recurrence by about 98%. Conclusion: The main management of DCIS is local treatment (wide local excision and radiotherapy) with hormonal treatment in case of hormone receptor positive lesions.

Keywords: Ductal carcinoma in situ, surgical treatment, radiotherapy, breast conserving therapy, hormonal treatment.

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Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R. M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

Abstract:

Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool has been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will offer reliable and systematic information on natural and anthropogenic ground motion phenomena across Europe.

Keywords: Ground displacements, InSAR, natural hazards, satellite imagery.

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Authors: K. Durairaj, I. N. Umar

Abstract:

The asynchronous discussion forum is one of the most widely used activities in learning management system environment. Online forum allows participants to interact, construct knowledge, and can be used to complement face to face sessions in blended learning courses. However, to what extent do the students perceive the benefits or advantages of forum remain to be seen. Through content and social network analyses, instructors will be able to gauge the students’ engagement and knowledge construction level. Thus, this study aims to analyze the students’ level of knowledge construction and their participation level that occur through online discussion. It also attempts to investigate the relationship between the level of knowledge construction and their social interaction patterns. The sample involves 23 students undertaking a master course in one public university in Malaysia. The asynchronous discussion forum was conducted for three weeks as part of the course requirement. The finding indicates that the level of knowledge construction is quite low. Also, the density value of 0.11 indicating the overall communication among the participants in the forum is low. This study reveals that strong and significant correlations between SNA measures (in-degree centrality, out-degree centrality) and level of knowledge construction. Thus, allocating these active students in different group aids the interactive discussion takes place. Finally, based upon the findings, some recommendations to increase students’ level of knowledge construction and also for further research are proposed.

Keywords: Asynchronous Discussion Forums, Content Analysis, Knowledge Construction, Social Network Analysis.

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Authors: M. Dezvarei, S. Morovati

Abstract:

In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: Clonal algorithm, proton exchange membrane fuel cell, particle swarm optimization, real valued mutation.

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Authors: Mohammad Reza Haj Seyed Hadi, Fereshteh Ghanepasand, Mohammad Taghi Darzi

Abstract:

The main objective of this study was to determine the effects of Nitrogen fixing bacteria and manure application on the seed yield and yield components in black cumin (Nigella sativa L.). The experiment was carried out at the RAN Research Station in Firouzkouh in 2012. A 4×4 factorial experiment, arranged in a randomized complete blocks designed with three replications. Nitrogen fixing bacteria at 4 levels (control, Azotobacter, Azospirillum and Azotobacter + Azospirillum) and manure application at 4 levels (0, 2.5, 5 and 7.5 ton ha-1) were used at this investigation. The present results have shown that the highest height, 1000 seeds weight, seed number per follicle, follicle yield, seed yield and harvest index were obtained after using Azotobacter and Azospirillum, simultaneously. Manure application only effects on follicle yield and by 5ton manure ha-1 the highest follicle yield obtained. Results of this investigation showed that the maximum seed yield obtained when Aotobacter+Azospirillum inoculated with black cumin seeds and 5 ton manure ha-1 applied. According to the results of this investigation the integrated management of Azotobacter and Azospirillum with manure application is the best treatment for achieving the maximum quantitative charactersitics of Black cumin.

Keywords: Azotobacter, azospirillum, black cumin, yield, yield components.

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Authors: Sirimanee Banjong

Abstract:

This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop preservice teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling a course entitled Seminar in Early Childhood Education provided during second semester of academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at x= 3.4, S.D.=0.6 2and the after-treatment average score at x 4.29 , S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at x=3.31, S.D.=0.60 and the after-treatment average score at x=4.42, S.D.=0.66 Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: Learning camp, leadership skills, teamwork skills.

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Authors: Cynthia Sau Chun Yip, Richard Fielding

Abstract:

High meat and especially red meat intakes are significantly and positively associated with a multiple burden of diseases and also high greenhouse gas (GHG) emissions. This study investigated population meat intake patterns in Hong Kong. It quantified the burden of disease and GHG emission outcomes by modeling to adjust Hong Kong population meat intakes to recommended healthy levels. It compared age- and sex-specific population meat, fruit and vegetable intakes obtained from a population survey among adults aged 20 years and over in Hong Kong in 2005-2007, against intake recommendations suggested in the Modelling System to Inform the Revision of the Australian Guide to Healthy Eating (AGHE-2011-MS) technical document. This study found that meat and meat alternatives, especially red meat intakes among Hong Kong males aged 20+ years and over are significantly higher than recommended. Red meat intakes among females aged 50-69 years and other meat and alternatives intakes among aged 20-59 years are also higher than recommended. Taking the 2005-07 age- and sex-specific population meat intake as baselines, three counterfactual scenarios of adjusting Hong Kong adult population meat intakes to AGHE-2011-MS and Pre-2011 AGHE recommendations by the year 2030 were established. Consequent energy intake gaps were substituted with additional legume, fruit and vegetable intakes. To quantify the consequent GHG emission outcomes associated with Hong Kong meat intakes, Cradle-to-ready-to-eat lifecycle assessment emission outcome modelling was used. Comparative risk assessment of burden of disease model was used to quantify the health outcomes. This study found adjusting meat intakes to recommended levels could reduce Hong Kong GHG emission by 17%-44% when compared against baseline meat intake emissions, and prevent 2,519 to 7,012 premature deaths in males and 53 to 1,342 in females, as well as multiple burden of diseases when compared to the baseline meat intake scenario. Comparing lump sum meat intake reduction and outcome measures across the entire population, and using emission factors, and relative risks from individual studies in previous co-benefit studies, this study used age- and sex-specific input and output measures, emission factors and relative risks obtained from high quality meta-analysis and meta-review respectively, and has taken government dietary recommendations into account. Hence evaluations in this study are of better quality and more reflective of real life practices. Further to previous co-benefit studies, this study pinpointed age- and sex-specific population and meat-type-specific intervention points and leverages. When compared with similar studies in Australia, this study also showed that intervention points and leverages among populations in different geographic and cultural background could be different, and that globalization also globalizes meat consumption emission effects. More regional and cultural specific evaluations are recommended to promote more sustainable meat consumption and enhance global food security.

Keywords: Burden of diseases, greenhouse gas emissions, Hong Kong diet, sustainable meat consumption.

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