site . blackraybansunglasses.com has a page, redirect.php, which conditionally redirects users to random spam pages. It uses a number of different Twitter accounts and shortened URLs to distribute its URL to other Twitter users. According to our dataset, it uses 6,585 different Twitter accounts and shortened URLs, and occupies about 2.83% of the sampled 232,333 tweets with URLs. When a user clicks on one of the shortened URLs, such as bit.ly/raCz5i distributed by zarzuelavbafpv0, heorshewillberedirectedtoaprivate redirection site, such as beginnersatlanta.tk, which seems to be managed by the operator of blackraybansunglasses.com. The user will then be repeatedly redirected to bestfreevideoonline.info and blackraybansunglasses.com. The redirection site blackraybansunglasses.com evaluates whether its visitors are normal browsers or crawlers using several methods, including cookie and user-agent checking. When it is sure that a current visitor is a normal browser, it redirects the visitor to forexstrategysite.com, which then ﬁnally redirects him or her to random spam pages. When blackraybansunglasses.com determines that a current visitor is not a normal browser, it simply redirects the visitor to google.com to avoid investigation. Therefore, crawlers may not be able to see forexstrategysite.com or the further spam pages. Another interesting point about blackraybansunglasses.com is that it uses the Twitter Web interface. Conventional Twitter spam detection schemes usually assumed that many spammers would use Twitter APIs to distribute their spam tweets. Advanced Twitter spammers, however, no longer rely on Twitter APIs, because they know that using APIs will distinguish their tweets from normal tweets. For instance, tweetattacks.com sells a Twitter spam program that uses the Web interface to deceive spam receivers and to circumvent API limits
Home security system can be described as introduction of technology within the home environment to provide convenience, security and energy efficiency to its occupants. Adding intelligence to home environment can provide increased quality of life for the people. There has been a significant increase in home automation in recent years due to higher affordability and advancement in Smart phones and tablets which allows vast connectivity. With the introduction of the Internet of Things, the research and implementation of home security are getting more popular. Much of the research attention has been given for security purpose. Various wireless technologies that can support some form of remote data transfer, sensing and control such as Bluetooth, Wi-Fi, RFID, and cellular networks have been utilized to embed various levels of intelligence in the home.
Television is one of the most popular entertaining systems now-a-days, but it also comes along with some drawbacks, continuous or frequent television viewing affects the natural sight of human beings. Watching television from a much closer distance affects eye-sight drastically; children do this frequently and they may have to wear spectacles with heavy numbers at an early age. This system will come into picture when a human being approaches the television and stays at a particular distance for a specific time, as this is dangerous for our eye-sight television will switch-off automatically. This system is based on the concept of face detection and further by using image processing. The television system control will be carried out by using microcontroller, and audio-video engineering.
A lot of research has been conducted to detect people within images and video frames, Our goal in this research is to develop a protection system against thefts, by analyzing video frames incoming from surveillance cameras, and running early alarm to discover, detecting thieves in realtime. Theft has many damages in the community. Failure in putting strategies for preventing theft has caused material, moral and psychological harm to the humans. All new technology comes to find rest and stability for the humans, by monitoring the properties especially when the owners are absent or far away. Now days the presence of cameras becomes very essential for monitoring places, it limits from theft , burglary, for this reason we have seen lot of theft occurs when a power outage. We want to prevent theft, narrowing the time for robbers and confusing them during robbery ,not only to alleviate its effects or pursuing criminals and disclosure them, this arrangements require more efforts and calling the police…etc. Our primary goal is for deterring criminals, we need achieving a preventive policy. In this research we could get a high rate of classification equivalent to 96% of detected humans in implementation time of approximately 0.5 seconds. Within this article, we will review the previous studies which had been done for discovering, detecting the humans and the steps which performed effectively are beside what enhancements we've made for. in summary ,we will review the obtained optimal values of the used parameters and analyze them .
Micorstrip patch antennas play a major role in day to day life. In this paper the designed microstrip patch antenna is compact sized with circular polarization for RFID applications. Different arbitrary shaped slots like square circle plus are used and parameters like return loss, gain and frequency are observed for each of the patches. All these are done using ANSOFT HFSS . The antenna is fabricated using duroid as dielectric substrate (relative permittivity =2.2, loss tangent=0.0004) and coaxial feed. These designed antennas are fabricated and used in realtime applications.
acceptance of such device in car, this is interesting according to , which found for every 3 drivers who were strongly in favor of onboard safety monitoring including alertness monitoring, four were completely opposed to it. This difference is maybe due to  investigate mainly bus and track drivers, who are more subject to privacy invading from companies. Although we found that pure private usage of such device is appealing to car drivers, it’s really hard to say how to prevent it from ”wrong” usage from authority like police or insurance companies. The answers to question 3 is expected, most people would like to trust the system only when they really feel tired.
The purpose of this article is to describe semiautomatic video surveillance system that is able to detect suspicious situations using artificial vision, as well as to facilitate the operator’s work by generating visual and audible alerts. Most surveillance cameras installed today have static loca- tion and capture low quality images (we all have once seen on television news the images of an assault at shop where the action and the individual appears in small area of the image). Despite the high quality of the available tools for image processing, typical captured images are not very use- ful for crime investigation. The increasing need for securi- ty in public spaces makes real-timedetection of suspicious behavior essential, rather than simply recording them .
The complexity of the actual Lane line roads are often some degradation factors, such as shade, water, pave- ment cracks, etc., and in the discovery process, it is difficult to achieve high performance and reliability, so you need to optimize the algorithm. Lane detection is a vital operation in most of these applications as lanes provide, the scheme is depicted in Figure 1.
1. Kwok Yu Mak,  have proposed easily detachable and user friendly pothole detectionsystem which specializes in detecting potholes besides doing close range obstacle detection. The device which consists of two systems, one that is mounted on the front of a vehicle and the other is worn by the user manoeuvring the vehicle. The first system looks for an obstacle and second system warns the user about the obstacle by vibrating and blinking LEDs. Obstacles are detected using two non contact ultrasonic sensors and the device is run by two basic stamp modules. Sensing part is mounted on the lower front part of the vehicle and consists of two distance sensors. Once either of the sensors detects on object, a signal is sent wirelessly through a transmitter to second system which receives it using the wireless receiver of the pair. Second system in worn on the wrist of the user. It has a vibrator motor that starts vibrating once a signal of pothole detection received and two LEDs that light up when the sensor sense the obstacle. This part has two switches that the user can use one to shut down the whole system and the other to only turn off the vibrator if the user wishes to.
The eye is one of the sense organs that can give users better interaction closer to their need by observing the change of the eyes (open or closed). It is considered as a rich source for gathering information on our daily life. So, it is used in computer science area, especially in human computer interaction. This paper proposes a new system for detecting eye blinks accurately without any restriction on the background and the user does not have to wear any sensors or marks. No manual initialization is required in our proposed system. The proposed system works with the online and offline environment. It automatically classifies the eye as either open or closed at each video frame. The proposed system is tested with the users who wear glasses and the experiments proved its applicability. The proposed system is very easy to configure and use. It is totally non-intrusive and it only requires one low-cost web camera and computer.
Pump-and-dump schemes are fraudulent price manipulations through the spread of misinformation and have been around in economic settings since at least the 1700s. With new technologies around cryptocurrency trading, the problem has intensified to a shorter time scale and broader scope. The scientific literature on cryptocurrency pump- and-dump schemes is scarce, and government regulation has not yet caught up, leaving cryptocurrencies particu- larly vulnerable to this type of market manipulation. This paper examines existing information on pump-and-dump schemes from classical economic literature, synthesises this with cryptocurrencies, and proposes criteria that can be used to define a cryptocurrency pump-and-dump. These pump-and-dump patterns exhibit anomalous behaviour; thus, techniques from anomaly detection research are utilised to locate points of anomalous trading activity in order to flag potential pump-and-dump activity. The findings suggest that there are some signals in the trading data that might help detect pump-and-dump schemes, and we demonstrate these in our detectionsystem by examining sev- eral real-world cases. Moreover, we found that fraudulent activity clusters on specific cryptocurrency exchanges and coins. The approach, data, and findings of this paper might form a basis for further research into this emerging fraud problem and could ultimately inform crime prevention.
Automated orthogonal defect classification (AutoODC)  enhances Relevance annotation framework. It automatically classifies the software system defects using textual features of defect reports. The semi-supervised text classification approach enriches the Naive Bayes (NB) classifier using expectation-maximization. Bug-triage employs semi-supervised classification method for avoiding the deficiency of the labeled bug report . A string kernel  classifies the text documents based on the sub-sequence length of the feature. Kernel-based learning system text categorization exploits the Support vector machine. Clustering based classification (CBC) approach considers both labeled and unlabeled data of the dataset. Initially, CBC clusters the labeled data. It labels the unlabeled data depends on clusters. The trained set of expandable labeled data is the input for classifier for improving the accuracy of classification .
financial accounting information systems. Internal system has indicators internal control system, human resource competencies, standard operating procedures, and support of top management, indicators get the lowest loading factor is the support of top management and that have the ultimate loading factor is the competence of human resources with a high level of significance means that if competency of human resources in information system handles private Polytechnic in East Java have competence in their field of expertise, training is done if there is a change of software, and employees have experience in the field of financial accounting information system performance is not good. All indicators on the internal system gain factor loading above which have been required so that the internal system indicator has a very strong influence is not significant to the performance of financial accounting information systems in private Polytechnic in East Java. This is because the compensation and motivation of employees in the private Polytechnic in East Java is still low, so even though the internal control, human resource competencies, standard operating procedures, and support of top management have been done properly then the impact on the performance of financial accounting information systems on private Polytechnic in Java East is not good. The empirical findings do not support some of the research results , the analysis of the factors that affect the performance of accounting information systems, with the findings of user involvement, support of top management, formulation, training & education, commitment control information systems affect the performance of accounting information systems. In addition, this study does not support  , the findings of the Internal organization have a positive relationship with AIS is reinforced by the adoption processes , .
To facilitate the development of adaptable service oriented systems for a specific domain, we have proposed the CADSSO development approach. To produce an adaptable system, the variability must carefully be analyzed and designed in the first stages of a modeling approach. Indeed, our approach has planned a model specific to the variability specification. To take advantage of contextual information, the context of use was also modeled via a context model. In addition and for better concerns separation, adaptation rules have been modeled separately with decision tables. The domain business modeling aims to complete the generation of the dynamic code, so allowing being close to full code generation.
This paper proposes a new approach to extend the limitation of the previous algorithm by enabling their capability to generate a concurrent plan. The proposed algorithm based on Hierarchical Task Network (HTN) enhances SHOP2 planning system to detect and generate a concurrent plan based on the output of SHOP2 (sequence plan). To trigger the availability of concurrent planning, allocation of resources based on web services inputs is used. The inputs (resources) are compared with SHOP2 operator, and concurrent plan will initialize if the instance of inputs equal to SHOP2 operator. To evaluate our approach, we perform two experiments using pathway information retrieval and logistic dataset from SHOP2 benchmark problem. The result of pathway information retrieval shows that this approach is able to find and generate a concurrent plan, but it takes longer computational time. Meanwhile, by using logistic dataset, the proposed algorithm is efficient to handle concurrent tasks based on cost reduction by some pruned operators. Therefore, in our future work, we intend to examine the approach in other complex Bioinformatics and system biology workflow which widely used web services as their analysis tools.
255 third level of DWT decomposition in (LL3) sub band, while Fig. 1(c) shows the second four watermarks was embedded in the fourth level of DWT decomposition in (LL4, HL4, LH4, HH4) sub bands. They are distributed in different locations inside the image space, and this will improve the robustness and the security of the system.
The main usage, we take into consideration here is the guidance of a p2p based virtual node extended supercomputer for equivalent calculations in the parallel synchronous process  . The bulk synchronous parallel process provides the outline view of the practical arrangement and the connection capabilities of the network hardware (e. g., a cluster of workstations,a parallel computer or a set of nodes connected by the wireless network). A bulk synchronous parallel system comprises of a set of bulk procedures and a series of super-steps with
Table 2 also shows that learner behaviours in the learning content design features (prerequisites, flowchart, references, objectives and details, help features (FAQ), support features (collaborate with teacher and expert), and evaluation feature (open question and pre-quiz) have significant effect on identifying the learning preferences for rational Learning Style. The findings also show that significant learner patterns include temporal behaviour with prerequisites, flowcharts, and FAQ features and navigation behaviour with references, objectives, open questions, communication channels with teachers and experts learning objects. Thus, it could be inferred that the rational learners tend to spend more time at reading and reviewing prerequisite topics and skills before studying a new topic. More time is also taken at logical thinking when viewing flowcharts. These learners tend to read the official help feature through reading the most common questions and its official answers. Furthermore, rational learners tend to navigate and browse official references such as books and articles to look for an intended topic/terminology/concept and prefer to open more communications channel with teachers and experts when facing challenges. In essence, it is found that rational learners adopt different WBES design features classified according to the main system components (Figure 6) as listed below:
Dissolved gas analysis is a common method for diagnosing faults in electrical transformers and determining the type of faults early on, depending on the specific standards used. Applying dissolved gas analysis methods can be used in diagnosis and in the evaluation process. There are many methods used in the diagnosis of faults in power transformers, including traditional and intelligent .The use of an intelligent expert system relies on dissolved gas analysis using artificial neural networks, and it gives excellent results in diagnosing faults and assessing the quality of insulating oil during service and the application of appropriate treatment.