Abstract —The Learningpatterns found among the learners community is steadily progressing towards the digitalized world. The learningpatterns arise from acquiring and sharing knowledge. More impact is found on the usage of knowledge sharing tools such as facebook, linkedin, weblogs, etc that are dominating the traditional means oflearning. Since the knowledge patterns acquired through web unstructured data is insecure, it leads to poor decision making or decision making without a root cause. These acquired patterns are also shared to others which indirectly affect the trust patterns between users. In this paper, In order to streamline the knowledge acquisition patterns and their sharing means a new framework is defined as Social Networking based Knowledge Acquisition (SNKA) to formalize the observed data and the Dynamic Itemset Count (DIC) algorithm is tried for predicting the users about the usage of web content before and after the knowledge is acquired. Finally the rough idea in building a tool is also suggested.
From the perspective of the buyers, there are costs and benefits to funding supplier development. As noted by Millington et al. (2006), some buyers are only willing to fund for the long term. This certainly is logical, as buyers would need to ensure that the high cost of supplier development is recoverable through future profits made by capable suppliers. Yet there are also other issues that need to be assessed. There are limits to the ability of a buyer to provide supplier development. One issue relates to the lack of buyer knowledge. Buyers would be unlikely to provide funding for technical areas outside of their own field of expertise, thus necessitating the involvement of external parties, which might not be possible in certain circumstances due to issues of company privacy. Another issue could arise when a particular supplier is a subsidiary of a global company. The buyer would then be restricted to involving these particular suppliers in its development programs, as that supplier has already been involved in its own program at its company headquarters. Therefore, the ability of suppliers to provide "know-how" development opportunities for other suppliers might be different from their ability to provide "capacity" (Wagner & Hoegl, 2006). Thus, another possible reason for a lack of buyer-supported training could be due to the two different categories of suppliers. For the purpose of this research, dependent suppliers have been placed in the "capacity" category.
Other approach is the neural activity caption. The most used technique is EEG, where through electrodes located in the scalp catch the brain waves and with the data acquired, it is possible to analyse the brain activity during a task. In many studies, the most important component is MMN (mismatch negativity). This component is the indicator of a brain reaction to a pre-attention process. Other techniques used are: functional imaging, fMRI, functional imaging, MEG, and functional imaging, PET scan. [ 38 ] Finally, the mouse tracking and keyboard tracking are techniques used to measure and classify attention. These techniques have already been used to measure other variables, like, stress [ 40 ] and mental fatigue [ 9 , 41 , 42 ].
Learning is a system composed of several elements that interact to form a union. Elements of a learning system is student, faculty, facilities, materials, learning objectives, learning environment. Learning is a process of interaction between instructors and students. In the learning process students will gain about something they do not know, they will learn the knowledge in a more efficient, than the process will be a link on the new knowledge in a more stable cognitive structures, which can be obtained in the study . The purpose oflearning more emphasis to expand or add a student's knowledge, so that the student has the ability to express again the knowledge and understanding that have been studied, both within a short time or long time, which is obtained through a variety of ways in the learning process  .
In this section, we presented and criticized existing Mashup frameworks. Mashup development is still immature and at an early stage and thus needs more research. In particular, there is no significant formalizationof Mashup integration. For this reason, we conducted a study of three Mashup frameworks regarding to the end user satisfaction criteria defined in section 1.2. The conclusion drawn from this study led us to the need for new patterns and methodologies to improve Mashup development. The next section is dedicated to the proposal of a new Cloud-based Mashup architecture, that uses a new EIPs-based integration language, while allowing the end user service creation through a new intuitive and self- explanatory creation process. The last requirement – non functional requirement – is out of the scope of this paper.
However, SFNs are under different development stages even within this group: one of them is at the initial development stage, three are moving towards consolidation and the other two are facing critical crossroads according to the description of D’Aunno and Zuckerman (1987). These two SFNs generate benefits to members, but the entrepreneurs described a decline in motivation within the group and a reduced level of participation from members towards collective actions and presence in meetings. A member of SFN5 (Development – critical crossroads) mentioned that he notices that “some entrepreneurs just wait for benefits… Only part of them participate effectively in meetings and challenge problems faced by the network”. If such SFNs can once again motivate members and develop new collective actions, they may reach a consolidated level; otherwise, they may face decline. Estivalete, Pedrozo and Cruz (2008) stressed that in the development step the business networks have a shared learning process through exchange of information between the actors and this is due, in large part, to the engagement and degree of trust between network members.
Through the exhibition of three computerized educational projects in different microw orlds w e hope to have show n the possibilities of Logo in providing a learning environment. Program listings in LogoWriter have been provided. Although there are more modern versions of Logo available in the market, it is still felt that the purpose of the paper is w ell served by LogoWriter among other things because there are still many schools using Apple and Pre Window s PC computers, particularly in developing countries. The philosophy oflearning by teaching a dumb machine to solve a problem, that is by programming the solution, forces the programmer to master the topic, because the programs w ill not function correctly unless thay are very w ell thought out and are given a touch of generality. In contrast w ith other educational philosophies such as programmed instruction and drill and practice programs in Logo it is the student that programs the machine and not the opposite. Recent versions of Logo have even more facilities than the ones show n here. For example Object Logo  is an Object Oriented Language that can do fraction arithmetic, essentially unlimited floating point precision arithmetic, complex number arithmetic, handle an essentially unlimited number of turtles and other objects such as printing and draw ing w indow s, handling of buttons and sliders to control variables, etc. Microworlds  is an object oriented package that runs under Windows, manages menus, dialog w indow s and icons w ith the mouse. It has many instructions including some for color animation, and facilities to w ork multimedia, including voice recording, show ing video, editing of graphics w ith a very complete set of colors to design forms and background images. Logo Gráfico  developed in Pascal in Argentina is also object oriented, run under Window s has a Pascal like syntax w ith constructions such as w hile and until, very good color graphic animation facilities w ith extra large turtles and turtle forms called actors. It also has special instructions for teaching physics such as object that can be accelerated and follow the law s of mechanics in movements such as simple harmonic motion.
Moving across different types of representations is essential for the recognition that each representation presents a different perspective of rational numbers, and students’ understanding develops as the number of perspectives increases (Ponte & Quaresma, 2011; Tripathi, 2008). Gravemeijer (1999) reinforces that a model emerges when it is underpinned by representations. In this emergent modelling process, representations become models, as they allow a direct modelling of a contextualized situation and support the development of more formal mathematical knowledge (Gravemeijer, 1999). Consequently, learning rational numbers through models, at the elementary grades, may be a dynamic process required to co-develop representation and conceptual understanding. Contexts, within which representations can be perceived as models, are fundamental to understand and establish complex and meaningful relations (Brocardo, 2010). The number line, with an implied measure meaning, and the decimat (Roche, 2010) that emphasizes a part-whole meaning, are useful representations that highlight the multiplicative structure of rational numbers. Post, Cramer, Behr, Lesh, and Harel (1993) highlight the role of representations in understanding rational numbers, relating it to the flexibility with transformations between and within rational number representations. Thus, students’ flexibility in making transformations involving different representations can show their understanding of the rational numbers involved (Post, Wachsmuth, Lesh, & Behr, 1985).
The author uses Facebook page to record students attendance in the class and for students who are not in the class. Facebook page provides a feature of "asked a question." The author uses this feature to share a question where the students need to reply in the comment box to write their class code, name, and student number. For students that both attend in the class and Facebook will get point 1, otherwise 0.5. To navigate the information related to the online attendance, the author informs the meeting, date, material theme, and notes. This strategy is very useful to engage students who can’t join the class physically, so they are still able to join the class and receive the course materials. Students in the class are excited to participate in cyber class. Figure 3 shows the example of some students who inform their attendance via social media group.
Redziejowski developed Mouse , a parser generator based on PEG. Using a PEG, Mouse generates Java code for a recursive descent parser. It offers limited resources for memoization, hence the name Mouse instead of Packrat. Mouse does not allow the explicit use of attributes. Semantic actions are represented by tags that can only be inserted at the end of each alternative of a rule. The code for the semantic actions is written as a method in a separate Java class. Methods are bound to semantic actions using the same name as the tags. Inside these semantic actions, it is possible to associate values with the symbols of a rule. This scheme allows a peculiar implementation of synthesized attributes, but not inherited attributes. In LGI (Language Generator by Instil) , instead of generating a descent recursive parser, a PEG is represented as an abstract syntax tree (AST) that is interpreted. Interpretation allows more flexibility, but it is less eﬃcient than generated code. LGI implements full memoization, but again the memory management is very ineﬃcient. The input must be com- pletely read before processing and stored in memory. Memoization is implemented using a two-dimensional array, with a line for each nonterminal, and a column for each input symbol. There is no way to deﬁne values for attributes, nor semantic actions. The result of processing an input is a syntax tree created to represent this input.
4. Middle ear reflectance assessment in three steps: (A) Obtaining the reflectance curve in the frequency range 200---6000 Hz at an intensity of 60 dB SPL. Each stimu- lus lasted 0.1---10 s per point. Collection was carried out with the chirp acoustic stimulus. (B) Retest to confirm the obtained reflectance curve. (C) The procedure was repeated, with the simultaneous presence of contralat- eral noise through insertion phones at 30 dBNS in relation to the white noise threshold. In the end, three measures were obtained in each ear. Based on the three measures, the difference between the response levels collected with and without contralateral noise was calculated.
With respect to the problem of translation classification, two separate classifiers for handling multi-word and word-to-word translations are trained, using previously ex- tracted and manually classified translation pairs as correct or incorrect. Several insights are useful for distinguishing the adequate multi-word candidates from those that are inadequate such as, lack or presence of parallelism, spurious terms at translation ends such as determiners, co-ordinated conjunctions, properties such as orthographic similar- ity between translations, the occurrence and co-occurrence frequency of the translation pairs. Morphological coverage reflecting stem and suffix agreements are explored as key features in classifying word-to-word translations. Given that the evaluation of extracted translation equivalents depends heavily on the human evaluator, incorporation of an automated filter for appropriate and inappropriate translation pairs prior to human eval- uation contributes to tremendously reduce this work, thereby saving the time involved and progressively improving alignment and extraction quality. It can also be applied to filtering of translation tables used for training machine translation engines, and to detect bad translation choices made by translation engines, thus enabling significative productivity enhancements in the post-edition process of machine made translations.
As result of the Turkey’s economic growth and heavy migration processes from rural areas, Istanbul has experienced a high urbanization rate, with severe impacts on the environment in terms of natural resources pressure, land-cover changes and uncontrolled sprawl. As a consequence, the city became extremely vulnerable to natural and man-made hazards, inducing ground deformation phenomena that threaten buildings and infrastructures and often cause significant socio-economic losses. Therefore, the detection and monitoring of such deformation patterns is of primary importance for hazard and risk assessment as well as for the design and implementation of effective mitigation strategies. Aim of this work is to analyze the spatial distribution and temporal evolution of deformations affecting the Istanbul metropolitan area, by exploiting advanced Differential SAR Interferometry (DInSAR) techniques. In particular, we apply the Small BAseline Subset (SBAS) approach to a dataset of 43 TerraSAR-X images acquired, between November 2010 and June 2012, along descending orbits with an 11-day revisit time and a 3 m x 3 m spatial resolution. The SBAS processing allowed us to remotely detect and monitor subsidence patterns over all the urban area as well as to provide detailed information at the scale of the single building. Such SBAS measurements, effectively integrated with ground-based monitoring data and thematic maps, allows to explore the relationship between the detected deformation phenomena and urbanization, contributing to improve the urban planning and management.
E_learning technologies are generally categorized as asynchronous or synchronous. Asynchronous activities use technologies such as blogs, wikis, and discussion boards. The idea here is that participants may engage in the exchange of ideas or information without the dependency of other participant's involvement at the same time. Electronic mail (Email) is also asynchronous in that mail can be sent or received without having both the participants’ involvement at the same time. Asynchronous learning also gives students the ability to work at their own pace. This is particularly beneficial for students who have health problems. They have the opportunity to complete their work in a low stress environment.
The fresh strain 18 was more virulent in vivo, as shown by the number of positive cultures and by the severity of the lesions observed at the histopathologic examination, despite the lower in vitro production of proteinase and phospholipase when compared to strain 743, stocked for several years on mineral oil and presenting a higher enzymatic activity. Based on results of the present study, it is possible to infer that although C. albicans possesses various putative virulence factors, for instance the production of hydrolytic enzymes as an attribute to adhere to epithelial cells and consequently to invade the host, other factors may be involved for the success of this organism as a pathogen. Host immunity is an important factor to modulate the status of C. albicans in the organism. As shown in the present study,
More and more scholars are turning to the Internet to find scientific information and academic institutions are devoting more and more resources to improving their presence on the web. The web is probably already the main showcase for universities, but in the near future the virtual institution might be as important and representative as a real one. In a world where every day we become more interconnected, the global visibility of academia is clearly linked to their commitment to the worldwide web 
Collaborative work is also suggested in many policy documents, namely related to statistical contents (Abrantes et al., 1999). Piaget and Vygotsky (Tryphon & Vonèche, 1996) underlined the role of communication in knowledge appropriation and in pupils’ performances. Vygotsky (1981) stresses the need to (re)construct meanings since knowledge is socially constructed and pre-existing to individuals, which means that it needs to be deconstructed and then reconstructed in order to become meaningful to a given person. Social interactions, namely peer ones, play a major role in this process, although what is meant by collaborative work changes across different research reports and papers (van der Linden, Erkens, Schmidt, & Renshaw, 2000). When we consider that we implemented collaborative work we have three different levels in mind: among peers, during class activities in which pupils are stimulated to interact in dyads or in small groups in order to co-construct solving strategies and answers; among teachers and researchers (some of them take both positions), when they are conceiving tasks, reflecting upon their practices or analyzing data; and, at a lower level of achievement, among research groups (César, 2003; César et al., 2001). Dyad or small group peer interactions while pupils are solving problems (César, 1998), or investigative tasks (Branco, Matos, Ventura, & Santos, 2004), as well as when they are participating in the whole class discussion (César, Mendes, & Carmo, 2001), contribute to knowledge appropriation, and also to the development of competencies, such as making conjectures, arguing, respecting one another’s viewpoint, sense of responsibility and autonomy, and a critical sense, among others.
Alzheimer´s Disease (AD), first defined by Alois Alzheimer, a German psychiatrist and neuropathologist in 1907 (Zilka and Novak, 2006), is the most common form of dementia in the elderly (Berr et al. 2005, Cummings 2004). AD is a progressive neurodegenerative disorder characterized by deterioration of cognitive and functional capacities and several neuropsychiatric and behavioral symptoms (Jalbert et al. 2008). The risk of dementia grows exponentially with age (Ziegler-Graham et al. 2008). While dementia shortens the lives of those affected, its greatest impact is upon the quality of life, both of those living with dementia, and their family and caregivers (Prince et al. 2015). Close to 50 million people worldwide are currently living with dementia, and this number is projected to double every 20 years, reaching 74.7 million in 2030 and 131.5 million in 2050 (Prince et al. 2015). By 2050, there is expected to be one new case of AD every 33 seconds, or nearly a million new cases per year, and AD prevalence is projected to be 11 million to 16 million in United States (Alzheimer’s Association 2012). Dementia also has a huge economic impact. The worldwide cost associated with this increasing dementia prevalence is expected to rise from the current $818 billion to $2 trillion by 2030 (Prince et al. 2015). Given the unprecedented personal, societal, and healthcare costs, it is not surprising that global efforts to develop and implement dementia risk reduction strategies are occurring (Greenwood and Parrott 2017).