3129 ability to connect and share information is recognized as a critical factor in the development of logic and cognitive functioning, and in the socialization process , . Since then, many scholars have widely explored its impact in teaching and learning. For example, Barak and Gluck-Ofri  explored the impact of self- disclosure on different types of online forums and discovered that self-disclosure in emotional support forums recurs more frequently than in neutral discussion forums. In addition, Dietz-Uhler, Bishop-Clark and Howard  also showed that patterns of self-disclosure can take place in a synchronous chat room when the students are involved in discussing a specific topic. This is proven by Leung’s  study, which shows that chatting in a chat room context is linked to the depth of comment and intent for self-disclosure. In essence, the abovementioned studies have significantly confirmed that self-disclosure plays an important role in an online interaction environment.
Baptista, (1998) proposed the chaotic figure section . This section provides a better encryption algorithm than the traditional key algorithm and the start state. First, find the route of the curve from the map of the map to the encryption of the message. Then, discover the configuration. The initial state was considered the constant route (trajectory). To achieve a meaningful result, the chaotic equation must be repeated until the route reaches the destination site and the amount of repetition is maintained later, since the code of each message is the curved route that is based on the same process to produce the next digit.
The color feature is one of the most widely used visual features in image retrieval. Typically, the color of an image is represented through some color model. There exist various color models to describe color information. A color model is specified in terms of 3-D coordinate system and a subspace within that system where each color is represented by a single point. The more commonly used color models are RGB (red, green, blue) and HSV (hue, saturation, value). Thus the color content is characterized by 3-channels from some color model. One representation of the color content of the image is by using the color histogram. Statistically, it denotes the joint probability of the intensities of the three-color channels. The color is perceived by humans as a combination of three-color stimuli: Red, Green, and Blue, which forms a color space. RGB colors are called primary colors and are additive. By varying their combinations, other colors can be obtained. The representation of the HSV space is derived from the RGB space cube, with the main diagonal of the RGB model, as the vertical axis in HSV. 3.1.1 Color Histogram
In fifteen years, Huffman Coding has been replaced by arithmetic coding. Arithmetic coding attempt to replace a symbol input with a specific code. This algorithm replaces a stream of symbols input with a numeric floating-point single output. More bits are needed in the output numbers, and it causes the more complicated of received message. Dictionary-based compression algorithm uses a very different method for compressing the data. This algorithm replaces the variable-length string of symbols into a token. The token is an index in the order of words in the dictionary. When the token is smaller than the word, so the token will replace the phrase and compression occurs. There are many methods and compression algorithms, but in this paper will be discussed the method of compression using Huffman, Shannon-Fano and Adaptive Huffman.
For GBR protocol, beacon packets save the hop count from the sink to the destination node whenever they pass through nodes and return to the sink by selecting the path with lower hop count when selecting the routing path for data transfer. However, since data packet is transferred through the path with lower hop count, some nodes in all sensor nodes may cause local energy loss.
3503 optimization function is then developed for each class in the CR route. The route also serves as a measurement of initiatives represented by CR user in the specific route. The next phase (hop choosing phase) is in such a way that the candidate CR users are ranking themselves based on the spectrum’s choice as well as the local network together with the physical conditions. The ranks generally influence the CR users initiating information of subsequent routes. The initiative is typically tagged with delay functions engaged in RREQ request message forwarding. Accordingly, preferred users can be able to broadcast RREQ message earlier. Further, destination node typically chooses the final route capable of meeting all goals of preferred routing. It is also worth pointing out that maintenance of the route is also offered in CRP . It is having a proactive, as well as a reactive element. It is assumed that the architecture of the network is made up of stationary PU transmitters that are having locations which are known and maximum range of coverage similar to Television towers. CR users are mostly mobile and aware of locations but have limited information about PU receivers. Further, during proactive maintenance process, all CR users compare own location with known PU transmission locations. If CR nodes proceed towards PUs, in case of current route failure, a new path is detected proactively to retain connectivity.
Where cj(k) and dj(k) are approximations (low pass) and detail (high pass) coefficients respectively. The signal frequency in low pass filter will be divided by two in each level according to Nyquist theorem . This decomposition can be repeated to any level based on frequency band we desire and as the decomposition level increase, the bandwidth length will decrease and the detail will increase. In each level the frequency resolution will be doubled while time resolution is reduced by half. For this research, DWT act as pre- processing and the level decomposition use is 5 (1 detail coefficient and 5 approximation coefficient). The Daubechies 4 (db4) is selected as basis function because it yielded the lowest mean square error . The signal is decomposed into 5 levels so that it is easy to categorize into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz) and gamma wave (>30Hz). The sampling rate for the EEG data is 173.71 Hz and it will be divided by two according to Nyquist Theorem. Each band represented by coefficient can be observed in Table 3. By using MatLab, the raw EEG signal is decomposed into sub bands and the features are extracted.
Genome-wide association study (GWAS) focuses on non-coding regions and potentially to non- coding variants. Some of the genetic disorder has been identifies based on disease-associated mutations by sequencing the exome or coding region [2,3]. However, many of cases still remain undetermined because of the failure in analysis due to limitation of exome sequencing. This problem gives the strong reason that some of causative variants actually occur outside of coding region and inside regulatory. For example, mutation of the functional regulatory elements such as enhancers and insulators may results in cancer, diabetes, heart disease, obesity [4,5] and a rare disease called Hirschsprung's disease .
The method proposed by the writer for human hand gesture recognition consists of some processes. The processes carried out can be described as follows : the taking of human hand gesture by using camera; grouping of hand gesture videos with the type of hand gestures that was saved; every video of hand gestures will then be separated into several image frame; every image will then be processed using nearest neighbor algorithm; grayscalling frame frame differencing; four images will be selected from a set of images which had gone through the frame differencing process, and these images will be
Seller's reputation is based on the seller's historical behavior observation or evaluation of information derived from the seller's future behavior expectations. The reputation of the seller is calculated from historical transaction evaluation information obtained by the seller. In order to reduce the calculation time and storage load, this paper introduces a time window. First define a time window T , its length is setted according to the specific application of e-commerce platform 。 Time window T will be divided into a number of time periods from the initial trading time t 0 to the current time of t c , which are marked as
Named Entity Recognition (NER) is one of the important parts of Natural Language Processing (NLP). NER is supposed to find and classify expressions of special meaning in texts written in natural language. These expressions range from proper names of persons or organizations to dates and often hold the key information in texts. NER can be used for different important tasks. It can be used as a self-standing tool for full-text searching and filtering. Also it can be used as a preprocessing tool for other NLP tasks. These tasks can take advantage of marked Named Entities (NE) and handle them separately, which often results in better performance. Some of these tasks are Machine Translation, Question Answering, Text
Finally, the Unset operation is the same as Change(x, null). There is no way to delete a value x from the Bloom filter, because each 1 bit may have been the result of hash values that have that bit set for some other member x’. In the case of LBS providers, it should be relatively rare to need to delete a set element, and it may be sufficient to nullify the corresponding value in the backing store simply. Note, however, that for each additional null value in the backing store the cost of a look-up becomes very slightly slower. Thus, if many unset operations have been performed, the LBS provider may need to delete all null values, and then regenerate the Bloom filter based on the keys that are still in the backing store after the removal of the null values.
The proposed non-parametric detector of seismic signals provides true detection probability more than 90% at fixed false alarm probability 0.001 and signal-to-noise ratio 5 dB and more. These indicators are achieved by less hardware and software resources than it is proposed in [7-12]. Non-parametrical approach to object detection is free of overtraining taking place in neural networks especially if environment conditions are not stable. In addition, such non-parametrical detector is self- sufficient as there is no need to use any sensors besides seismic ones.
Individual users' reports are visualized on the map as "polylines" that go along roads or highways. The term polyline refers to "polygonal lines." This is what Google calls lines that follow a road or a specific area. These are also color-coded in the same way as the intersection status indicators. The intersections' status is derived from the status of the polylines passing through them, in fact. So to say, if a polyline with the status set to "congested" passes through an intersection, that intersection's status will also be set to "congested," and it will change its color to red to reflect this change. Users may also click on intersection markers to read comments contributed by users when submitting reports that go through the intersections. Users may also utilize the search module to find an intersection quickly. Figure 6(a) shows the Main Activity and figure 6(b) shows the Search Module that is accessible from the toolbar.
3522 The implementation of MCES is a new breakthrough to the existing elevator systems in the year 2002. Its main purpose is to reduce the construction cost of building extra elevator shafts . It is implemented by allowing more than one elevator car in an elevator shaft instead of using extra elevator shafts with only one elevator car. This special feature of MCES enables the hall calls from different floors can be answered at the same time with different elevator cars within the same elevator shaft. Hence, the waiting time of passenger has been greatly reduced. However, it is a very complex elevator system as it needs to consider many problems such as car collision, live-lock and reversal problems . Besides, it is still not able to transport a large number of passengers efficiently if the passengers are calling from the same floor, especially during the up-peak traffic. For that reason, the feature of double-deck elevator system is integrated into multi-car elevator system to develop a new hybridized elevator system. This research is to find out the efficiency of the hybridized elevator system as compared to MCES. It is time saving and lower cost to compare the performance of hybridized elevator system and MCES through simulation.
There are four stages that are involved in software reuse: representation, retrieval, adaptation and incorporation . At the representation the initial draft of the software to be developed is presented as query to the reuse system. The software artifacts that are similar to the query with minimal adaptation cost are selected in the retrieval stage. During the adaptation, the retrieved artifacts are modified for future reuse. Finally, at the integration stage the new artifacts are stored back to repository. Among all the reuse stages retrieval plays a critical role . It consists of two main activities: navigation and matching. The navigation determines the order in which artifacts are visited in the repository, while the matching defines the order in which artifacts are selected based on their similarity with the query draft. This paper focus on the matching based on the similarity between the software designs modelled with UML diagrams.
The proposed scheme is tested on 3 different images (gray and true color); Table (1) shows the general characteristics for the tested images displayed in Fig.1; Table (2) shows the default quantization values: Q0 the quantization parameter for DC coefficients, Q1the quantization parameter for AC coefficients, and Alpha the scaling factor for AC coefficients also; applied to the tested images; the scheme compared with the results of applying the standard JPEG method on the same set of images shown in Fig.(2). The proposed algorithm was tested on a laptop computer with a Processor: Intel ® Core ™ i7 CPU Q740 @1.73 GHz, RAM 8.00 GB, x64-based processor). C# programming language was used to implement the proposed scheme.
In this survey, a new model has been proposed to classify sentiment of many documents in English using the Self-Organizing Map algorithm, a testing data set and a training data set with the multi- dimensional vectors based on the sentiment lexicons of the bESD with Hadoop Map (M) /Reduce (R) in the Cloudera parallel network environment. Based on our proposed new model, we have achieved 88.72% accuracy of the testing data set in Table 2. Until now, not many studies have shown that the clustering methods can be used to classify data. Our research shows that clustering methods are used to classify data and, in particular, can be used to classify the sentiments (positive, negative, or neutral) in text.
This paper discusses the software requirements validation in the earliest stage of software development. Requirements validation is one of the most important phases in software development project to avoid requirements errors from propagate to the later stage. This phase is also crucial in order to achieve the best quality of requirements that reflects the user’s expectation and needs. From our analysis, many studies were validating the functional requirements using the semi-formal approach/method. For this, UML models were the most frequent used for requirements validation. In terms of the techniques, prototyping was the most favourite followed by simulation, model-based and testing-based requirements validation. Our analysis also found that the most important quality criteria of requirements were consistency, correctness and completeness.