انجمن کامپیوتر ایران

استنتاج گرامر 1 يكي از موضوعات تحقيقات ي مهم در زمينه پردازش زبان هاي طبيعي 2 است. مي توان است نتاج گرامر را بر اساس ميزان استفاده از اطلاعات (تهيه شده توسط انسان) در مرحله ي آموزش، به سه ن وع بامر بي 3، بي مربي 4 و نيمه مربي 5 تقسيم بند ي نمود . در اين مقاله، يك روش استخراج گرامر بامربي سريع ارائه مي شود كه از الگوريتم ويتربي 6 استفاده م ي كند . الگوريتم ارائه شده از يك مدل احتمالاتي جديد تحت عنوان "بايگرم قواعد" 7 استفاده مي كند. آزمايشات نشان م ي دهد كه اگرچه نتايج بدست آمده از روش پيشنهادي در مقايسه با بهترين روش موجود 8، ضعيف تر است ولي از اين روش مي توان د ر كاربردهاي ب ي درنگ نظير پردازش صوت كه نياز به تجزيه سريع دارند ، بهره برد . همچنين در بسياري از كا ربردها نظير ترجمه ماشيني و استخراج رابطه كه از درخت تجزيه جزيي 9 استفاده مي كنند ، استفاده از اين روش ميتواند سودمند باشد.

اين مقاله شرحي است بر طرح و معماري يك عامل تجاري براي رقابت TAC SCM. عامل فوق برحسب مديريت توزيع شده در زير بخش ها بنا شده است. هر بخش به طور مستقل به اموري كه به آن سپرده شده است، رسيدگي مي كند. براي اين منظور همگي از موتور استنتاج فازي استفاده مي كند. اين موتور فازي اجازه بيان قانون هاي فازي را به صورت نمادين فراهم مي كند. منابع و اطلاعات براي تمامي بخش ها مشترك بوده و هريك در صورت نياز به نتايج تصميم هاي بخش هاي ديگر دسترسي دارند. استفاده از منطق فازي، امكان نزديك تر شدن روند تصميم سازي عامل را به تصميم گيري انساني ايجاد نموده و امكان اصلاح و تغيير استراتژي عامل را تسهيل مي كند.

در اين مقاله يک روش شيي گرا براي باس WISHBONE ارايه گرديده است . بر اساس روش ارايه شده مدلسازي ساختار هاي مختلف باس WٌISHBONE به صور ت شئ گرا پياده سازي گرديده است . در اين روش کاربر مي تواند ويژگي هاي باس مورد نظر خود را تعيين و طراحي را انجام دهد. توانايي هاي ويژه اين روش در برطرف کردن ناهماهنگي هاي موجود بين رابط هاي WISHBONE از قبيل ناهماهنگي هايي که در اثر تفاوت سايز سيگنال ها ي آرايه اي، تفاوت سازمان داده ،يکسان نبودن granularity و يا يکسان نبودن شيوه آدرس دهي ايجاد ميشوند مي باشد . مقايسه اين روش و دو روش به کار رفته در PERLilog و Altium Designer نشان ميدهد که اين روش مدلسازي علاوه بر سادگي و سهولت کاربرد قابليت هاي بيشتر و حوزه پوشش وسيع تري را فراهم ميکند . براي پياده سازي اين روش ابزار WB_PERLilog به وسيله نويسندگان اين مقاله تهيه شد . اين ابزار از توسعه يک ابزار طراحي متن باز و بازسازي ساختار کلاس WISHBONE در آن، به نام PERLilog به دست آمده است . ابزار طراحي شده به کاربر امکان مي دهد که کد لازم براي ايجاد اتصالات WISHBONE براي برقراري ارتباط بين IP Core هاي از پيش نوشته شده به زبان Verilog که داراي رابط WISHBONE هستند را به صورت خودکار و به صورت شئ گرا توليد کند.

Wireless networks are poised to support a myriad of existing as well as emerging multimedia streaming applications. With increase in use of wireless local area networks (WLANs), ranging from simple data transfer to bandwidth-intense, delay-sensitive, and loss-tolerant multimedia applications, issues regarding quality of service (QoS) have become a major research endeavor. Several challenges posed by robust video streaming over 802.11 WLANs include coping with packet losses caused by network buffer overflow, link erasures, or deadline misses. A major observation is that the retry limit settings of the MAC layer can be optimized in a way such that the overall packet loss caused by link erasure, buffer overflow, or deadline miss is minimized. In this paper, we propose a novel solution for minimizing packet loss in multimedia applications over WLANs. Simulation results justify the improved quality of the received video based on our proposed approach.

This paper proposes an algorithm for the detection of resistive delay faults in deep submicron technology using dynamic strength scaling, which is applicable for 45 nm and below. The approach uses an advanced coding system to build logical functions that are sensitive to strength and able to detect even the slightest voltage changes in the circuit. Such changes are caused by interconnection resistive behavior and result in timing-related defects.

In this paper, we propose a new method for mobile robot path planning in dynamic environment when the trajectories of obstacles are unknown. Our algorithm first utilizes a global approach called clearance based probabilistic roadmap method to find a suitable path and then locally apply evolutionary algorithm to keep the structure of the path when obstacles collide with the path. As a result, the path will act like an elastic band. To reach real time applicability, a light fitness function is proposed compare to other genetic algorithms to reduce the computation time needed for calculating and repairing path. Simulation results show that our method not only can keep the original structure of path, but also repair operation is done quickly even in the scenes with many obstacles.

In this paper we propose a new approach for text region extraction in camera-captured document images. Texture-Edge Descriptor, TED, is utilized for text region extraction. TED is an 8-bit binary number which its bits are structural. This structural bits and special text region characteristics in document images make TED an appropriate descriptor for text region extraction. Applying well-known water flow method to the text regions extracted by TED, results in fast and good quality document image binarization. Experimental results demonstrate the effectiveness of our method for text region extraction and document image binarization.

In this paper, a novel inference engine named fuzzyevidential hybrid engine has been proposed using Dempster-Shafer theory of evidence and fuzzy sets theory. This hybrid engine operates in two phases. In the first phase, it models the input information’s vagueness through fuzzy sets. In following, extracting the fuzzy rule set for the problem, it applies the fuzzy inference rules on the acquired fuzzy sets to produce the first phase results. At second phase, the acquired results of previous stage are assumed as basic beliefs for the problem propositions and in this way, the belief and plausibility functions (or the belief interval) are set. Gathering information from different sources, they provide us with diverse basic beliefs which should be fused to produce an integrative result. For this purpose, evidential combination rules are used to perform the information fusion. Having applied the proposed engine on the coronary heart disease (CHD) risk assessment, it has yielded 86 percent accuracy rate in the CHD risk prediction.

This paper, proposes the use of a reinforcement learning approach for a target tracking sensor network application. Harsh and unpredictable situations of sensor nodes in such an application requires a selftuning mechanism for the nodes to adapt their behavior over time. The method is examined under high dynamic network conditions and compared with a similar method called SORA over different performance measures. The results show a significant improvement over the compared method in the environments with high level of dynamism.

Due to the changing and dynamic environment of web services, Quality of Service (QoS) becomes a key factor to differentiate service providers. Since current web service standards and technologies suffer from the lack of QoS Management, having architectures capable of supporting QoS verification, selection, negotiation and monitoring is inevitable. Software agents have been recognized as a promising technology for managing web services. Using FIPA compliant Multi Agents we were able to propose a Multi Agents based web service QoS Management Architecture. We also introduced a QoS based web service clustering method which helps us to select the best service that suits user quality preferences.