Wireless Sensor Networks (WSNs) consisted of various low-cost devices that had limited
battery power for surveillance of certain vicinity. The objective of WSNs had accomplished the given
tasks within time in an efficient manner. The main concern was to prolong the network lifetime to
save energy. The heterogeneous nodes deployed in the given vicinity divided into two
INSTANT-OFF and NEVER-OFF states and then each one further subdivided into three (Good,
Better and Best) by Fuzzy Inference System (FIS). The cluster boundary was defined by parameter
Distance from Base Station (DisBS) and its linguistic terms such as very close, close, medium, far
and very far to meet the unequal clustering approach. The INSTANT-OFF (Good, Better and Best)
which had three states active, idle, sleep and always worked as Cluster Members (CMs) to sense the
physical environment. The NEVER-OFF (Good, Better and Best) had active and idle states. The first
two most optimum NEVER-OFF selected as Cluster Head (CH) and Data Collector (DC) and the
remaining belonged to CMs. If only one NEVER-OFF (Good, Better or Best) was available in a
cluster then both jobs as CH as well as DC performed by it. If none NEVER-OFF (Good, Better and
Best) were available in the cluster then re-clustering setup took place by BS.
In this research, Near-Optimal Energy Aware Approach through INSTAN-OFF and NEVER-OFF
Clustering by Fuzzy Logic (NOEA-INCFL), the energy was consumed during sensing, processing
and transmission phase by its appropriate nodes. The CMs worked as a reactive manner and saved
energy by idle and sleep states while the CH and DC worked in a proactive mode and saved energy in
idle state. The sensing job was done by CMs that consumed a minor amount of energy and
transmitted packets of 200 bits length to DC. The second more energy consumption job was
processing, performed by DC. The DC received packets of 200 bits length from CMs and aggregated
them into 6400 bits length packets then delivered it to CH. The most energy consumption job was
communication with BS that performed by CH hop by hop through other CH. The unequal clustering
approach maintained the consumption of energy levels throughout WSNs. The reactive and proactive
mechanisms saved the energy as 85.1033% in 2000 rounds; increased lifetime up to 774 rounds,
re-clustering setup took place after 1912 rounds as well as enhanced the throughput as 100% and
latency time 0.001123 in the first round. This approach was implemented and evaluated through MATLABand its simulation in OMNET++.
نواب جعفر علی خاں اثرؔ لکھنوی افسوس ہے کہ ۶ جون کو نواب جعفر علی خاں اثر لکھنوی نے انتقال کیا، وہ اس دور کے استاد فن شاعر اور اردو زبان و ادب کے نامور محقق تھے، اس کے جملہ متعلقات پر ان کی نظر بڑی گہری اور محققانہ تھی، اور اس میں ان کا قول سند کی حیثیت رکھتا تھا، ان کی ذات لکھنؤ کی تہذیب و شائستگی اور قدیم شرافت و وضعداری کا نمونہ تھی، ان کی زندگی کا بڑا حصہ سرکاری ملازمت میں گذرا، کلکٹری کے عہدے سے ریٹائر ہوئے لیکن تصنیف و تالیف و تلاش و تحقیق کا مشغلہ ہمیشہ جاری رہا اور انھوں نے اردو زبان و ادب کے مختلف پہلوؤں پر محققانہ مضامین اور مستقل کتابیں لکھیں، ان کا سب سے بڑا کارنامہ فرہنگ اثر ہے جس کی پہلی جلد شائع ہوچکی ہے، ان کی وفات سے اردو زبان کا ایک بڑا محقق اٹھ گیا، اور قدیم تہذیب کی ایک اہم یادگار مٹ گئی، اﷲ تعالیٰ ان کی مغفرت فرمائے۔ (شاہ معین الدین ندوی، جون ۱۹۶۷ء)
Islamic education curriculum has central value for education process, as education vision direction. Islamic education mission is how to create religious people by leaning perfectly. Curriculum becomes one of success applications and quality in education institution most. Curriculum will develop based on global world and people life style existency. Therefore, education should view people life style increased as learning source that is becomed a value for curriculum step making. Beside that, islamic education curriculum development also becomes teacher’s choice to implement learning manner in class. In where, it’s implementation should be arranged and systematically to make maximal learning either in development vision, indicator, lesson teory, lesson model proccess, learning evaluation or teacher’s development skill. The process of islamic education curriculum development must be done good and awesome also seeing several factors as supports and obstacles of it. In other to get an education result based on such the plan made before(education planning).
The whole class of evolutionary computing algorithms is inspired by the process of evolution in nature. Compared to the traditional optimization algorithms, a few striking features of these algorithms include their ability to address non-differentiable cost functions, robustness to the dynamically changing environment, and implementation on parallel machines. However, it was not until one and half decade ago, when these algorithms attracted researchers and got acknowledgement in terms of their application to the real world problems. The main reason behind this increased interest of the researchers owes to the ever increasing computing power. As a result evolutionary computing algorithms have been widely investigated and successfully applied for a number of problems belonging to diverse areas. In this dissertation the standard binary particle swarm optimization (PSO) and its soft version, namely soft PSO (SPSO) have been applied to four different problems of digital communication. Due to the exponentially growing computational complexity with the number of users in optimum maximum likelihood detector (OMLD), suboptimum techniques have received significant attention. We have proposed the SPSO for the multiuser detection (MUD) in synchronous as well as asynchronous multicarrier code division multiple access (MC- CDMA) systems. The performance of SPSO based MUD has been investigated to be near optimum, while its computational complexity is far less than OMLD. Particle swarm optimization (PSO) aided with radial basis functions (RBF) has been suggested to carry out multiuser detection (MUD) for synchronous direct sequence code division multiple access (DS-CDMA) systems. The MUD problem has been taken as a pattern classification problem and radial basis functions have been used due to their excellent performance for pattern classification. The two variants of PSO have also been used in a joint manner for the task of the channel and data estimation based on the maximum likelihood principle. The PSO algorithm works at two different levels. At the upper level the continuous PSO estimates the channel, while at the lower level, the soft PSO detects the data. The simulation results have proved to be better than that of joint Genetic algorithm and Viterbi algorithm (GAVA) approach.