المصادر في القراءات القرآنية بين النصب والرفع

 In Arabic language the source from which all nouns and verbs are derived is called  (المصدر). Verbal noun (Al-Masdar:  (المصدر  is a very important derivative in Arabic. It is a noun derived from the verb to refer to the action or activity implied in the verb, e. G.  ((كتابة   “writing” as a process- derived from the verb (كتب) to  “write”. A verbal noun represents a change in the form of a verb which allows it to be used as a noun in a sentence. Verbal noun is a type of noun which can bear the article (ال) or tanwin   (تنوين ) and can be declined according to the sentence i.e. Nominative, accusative and genitive case. This article deals with the verbal nouns in the Holy Quran that appeared once in the nominative case and in other Qiraat it was read as accusative case. For e.g. (Al-Hamd) is read as nominative and accusative form. الرفع على قراءة حفص: ( الحمدُ لله رب العالمين ) و فى قراءة أخرى : ( الحمدَ لله رب العالمين ) Likewise other examples are: (سورةٌ أنزلناها )- (سورةً أنزلناها) (سلامٌ عليك)- (سلامًا عليك) Similarly : النصب على قراءة حفص: ( و بالوالدين إحسانًا) و فى قراءة أخرى : ( و بالوالدين إحسانٌ) Thus, the article highlights the semantic treasures embedded in the Qiraat of the Holy-Quran.

On Content Caching Mechanisms for Information-Centric Networking

Information-Centric Networking (ICN) is believed an alternative and future network to the host-centric model of the existing Internet infrastructure. ICN focuses on distribution and retrieval of contents instead of transfer of information between endpoints. It is based on the concept of publish-subscribe, naming and in-network caching. The concept of caching is universal in ICN and it is used within networks for reducing latency of information to users. Contents can be distributed in on-path caching or off-path caching. Off-path caching can be compared with tradition caching of content while on-path caching is more near and specific to ICN. The default caching strategy proposed for ICN is Leave Copy Everywhere (LCE) which leaves a copy of content on every node of a network that the INTEREST packet has traversed. But this caching strategy causes a huge redundancy, source consumption in network that minimizes the effectiveness of ICN. Popularity is a major factor we have to care about while caching content in network as it consumes more resources to cache content on every node that has requested by any user. Some contents in the network are requested more as compared to other so this factor can play an effective role in caching content in ICN. Other factor we need to take care about is caching content near end users so as to reduce the latency of information retrieval. In this research work, we have designed two caching strategies of LeafPop and LeafPopDown for ICN based on the factor of popularity. The objectives of designed caching strategies are reducing redundancy that default caching strategy of LCE is creating in ICN. In order to achieve desired objective, the content is placed in the network based on popularity factor in both caching strategies. In addition of considering popularity factor, content is placed near the end users so that latency to the end users could be minimized. The designed caching strategy of LeafPop is first evaluated against the default caching strategy of Leave Copy Everywhere (LCE) and popularity based caching strategy of Max-Gain In-network Caching (MAGIC) in terms of performance metrics of cache hits, diversity and eviction operations in same simulation environment. The LeafPop caching strategy is then compared with the new caching strategy of LeafPopDown for the same performance metrics. The proposed caching strategy of LeafPop is examined on SocialCCNSim simulator against the selected caching strategies. The results are evaluated on three topologies of Abilene, DTelekom and Tiger with α = 0.88, 1.1 and cache size of 1 GB and 10 GB. We have used Least Recently Used (LRU) replacement policy for the caching eviction operations. LeafPopDown caching strategy is then examined against LeafPop caching strategy on the same simulator. Here, the results are again evaluated on same three topologies of Abilene, DTelekom and Tiger with α = 0.88, 1.1 and cache size of 1 GB and 10 GB. The simulation results show that proposed caching strategy of LeafPop outperforms as compared to LCE and MAGIC in terms of cache hit, diversity and eviction operations. LeafPop caching strategy significantly increases cache hit on two topologies of Abilene and Tiger when we have cache sizes of 1 GB and 10 GB and α = 0.88, 1.1. The second proposed caching strategy of LeafPopDown outperforms against LeafPop in terms of cache hits, diversity and eviction operations on the chosen simulation parameters.