سال:1398 | دوره: | شماره: |تعداد مقالات:6

By increasing, the complexity of chips and integrating more components into a chip has made network – on-chip known as an important infrastructure for network communications on the system, and is a good alternative to traditional ways and using the bus. By increasing the density of chips, the possibility of fault in the chip network increases and providing correction and fault tolerance methods is one of the principles of today's chip design. Faults may have undesirable effects on the correct system operation and system performance. In this paper the communication infrastructure fault has been considered as same as link and router fault and the fault tolerance low cost routing algorithm has been suggested base on local fault information By using quad neighbor fault information to avoid back tracking in routing in order to select possible minimal path to destination. In this article, we have suggested cost aware fault tolerance (CAFT) routing algorithm. Our contribution in this algorithm is minimum local fault information, minimum routing decision overhead by implementing routing logic base and determining shortest possible path. For deadlock freedom using an additional virtual channel along Y dimension and prohibiting certain routing turns. In order to evaluate the performance of our routing, we compared it with other fault tolerant routing in terms of average packet latency, throughput and power.

Vehicle detection and classification of vehicles play an important role in decision making for the purpose of traffic control and management. this paper presents novel approach of automating detecting and counting vehicles for traffic monitoring through the usage of background subtraction and morphological operators. We present adaptive background subtraction that is compatible with weather and lighting changes. Among the various challenges involved in the background modeling process, the challenge of overcoming lighting scene changes and dynamic background modeling are the most important issues. The basic architecture of our approach is done in 3 steps: 1-background subtraction 2-segmentation module 3-detection of objects and counting vehicles. We present an adaptive background at each frame after using binary motion mask to create instantaneous image of background. To remove noises we use morphological operators and then start to segment images, detect vehicles and count them. Algorithm is effi cient and able to run in real-time. Some experimental results and conclusions are presented.

Renewable Energy Sources (RES) are well-defined as energy sources, that are in abundance within the natural surroundings and are much inexhaustible. In addition, hydroelectricity (HE) is a vital part of world renewable energy supply and Hydropower remains a bulk source of electricity generation because of its environmental friendliness in nature. Modeling is the analysis of the non-linear models which represent the fundamental parts of the Hydropower plant (governor, turbine, servomotor). This paper studies accurate and elaborate hydraulic turbine and governor models and its implementation in MATLAB/Simulink combined with the Sims cape Power Systems (SPS). An effort has been created to develop a plant model and examine the suitableness of controllers during a governor model for fault incidence within the system by means Simulink based simulation. The Ziegler– Nichols tuning methodology was applied for specifying the gain coefficients of a governor (PID-PI) under 50% of load demand from the plant. Also, MATLAB/Simulink gave the chance to record and compare the figures of the plant with PID & PI controllers through simulation tests within the commonest cases (three-phase fault, load demand variation) with a view of finding out the potency and therefore, the stability of the system.

There are many algorithms for optimizing the search engine results, ranking takes place according to one or more parameters such as; Backward Links, Forward Links, Content, click through rate and etc. The quality and performance of these algorithms depend on the listed parameters. The ranking is one of the most important components of the search engine that represents the degree of the vitality of a web page. It also examines the relevance of search results with the user's query. In this paper, we try to optimize the search engine results ranking by using the hybrid of the structure-based algorithms (Distance Rank algorithm) and user feedback-based algorithms (Time Rank algorithm). The proposed method acts on multiple parameters and with more parameters it tries to get better results while keeping the complexity and running time of the algorithms. Average distance and average attention time have been evaluated on web pages and by using the obtained data, proposed method performance has been evaluated. We compare proposed method with several famous algorithms such as Time Rank, Page Rank, R Rank, WPR and sNorm(p) in this field by applying Precision@N (P@N), Average Precision (AP), Mean Reciprocal Rank (MRR), Mean Average Precision (MAP), Discounted Cumulative Gain (DCG) and Normalized Discounted Cumulative Gain (NDCG) criteria. The results indicate better performance in comparison with existing algorithms.

Various numbering schemes are used to track different versions and revisions of files, software packages, and documents. One major challenge in this regard is the lack of an allpurpose, adaptive, comprehensive and efficient standard. To resolve the challenge, this article presents Quadruple Adaptive Version Numbering Scheme. In the proposed scheme, the version identifier consists of four integers. These four numbers from Left to Right are called: "Release Sequence Number", "Generation Number", "Features List Number", and "Corrections List Number" respectively. In the article, special values are given for the quadruple numbers and their meanings are described. QAVNS is an "Adaptive" scheme; this means that it has the capability to track the different versions and revisions of files, software packages, project output documents, design documents, rules, manuals, style sheets, drawings, graphics, administrative and legal documents, and the other types of "Informational Objects" in different environments, without alterations in its structure. The proposed scheme has the capability to monitor changes in the types of informational objects, such as virtual machine memory, in the live migration process. The experimental and analytical results indicate the desirability and effectiveness of the proposed scheme in satisfying the desired expectations. The proposed scheme can become a common standard and successfully applied in all academic, engineering, administrative, legislative, legal, manufacturing, industrial, operational, software development, documentary and other environments. The standardization of this scheme and its widespread usage can be a great help in improving everyone's understanding of the numbering of versions & revisions.

Automatic image annotation is a process in which computer systems automatically assign the textual tags related with visual content to a query image. In most cases, inappropriate tags generated by the users as well as the images without any tags among the challenges available in this field have a negative effect on the query's result. In this paper, a new method is presented for automatic image annotation with the aim at improving the obtained tags, as well as reducing the effect of unrelated tags. In the proposed method, first, the initial tags are determined by extracting the low-level features of the image and using neighbor voting method. Afterwards, each initial tag is assigned by a degree based on the neighbor image features of the query image. Finally, they will be ranked based on summing the degrees of each tag and the best tags will be selected by removing the unrelated tags. The experiments conducted on the proposed method using the NUSWIDE dataset and the commonly used evaluation metrics demonstrate the effectiveness of the proposed system compared to the previous works.