M. Sadiq Ali Khan ¹, Khaliq Khanzada ¹, Huma Jamshed ¹

Affiliations
1 Department of Computer Science, University of Karachi, Karachi–75270, PK

Abstract

Cellular automata have proved many of its capabilities and have bestowed a lot in many fields. With the emergence of CA, fabric pattern production has increased in less amount of time. For weaving, cellular automata start with some pattern, then continues with a sequence of steps to produce a new pattern or to change the colour of the cell in a lattice, by using particular transition rules. The main purpose of using cellular automata algorithm as it provides the superlative edge maps and the outstanding quality with one pixel wide edge, with edges having no breaks. We assessed cellular automata capabilities and CA a lot contributions in pattern generation, transformation, and data processing. This research paper reflects the integration of cellular automata across different disciplines. In this paper, we assess the computationally enriched CA rules facilitating spot detection in the study of medical images for cancer diagnosis. The dynamic behaviour of CA increases the scope of transformation and makes it practical for morphing. CA provides prediction of protein structural class and processes dynamic simulation of protein. Flexibility of CA facilitates parallel processing using VLSI, colour graph modelling the linear rules, and its exercise in fabric weaving.

Keywords

Cellular Automata, Dynamic Behaviour, Medical Images, Morphing, Parallel Processing, VLSI.

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Abhay Saxena ¹, Chandrashekhar Patel ¹, M. Sadiq Ali Khan ²

Affiliations
1 Dev Sanskriti Vishvavidyalaya, Haridwar - 249411, Uttarakhand, IN
2 Department of Computer Science, University of Karachi, PK

Abstract

In our work we have designed CRC using the LVCMOS IO standards which are stands for Low Voltage Complementary Metal Oxide Semiconductor. In this work we have worked with four kinds of LVCMOS (LVCMOS 12, LVCMOS 15, LVCMOS 18, LVCMOS 25). For LVCMOS 12 when we scaled down the frequency form 50GHz to 10 GHz we found 64.41% reduction in total power. For LVCMOS 15 when we change down the frequency form 50GHz to 10GHz we found 67.58% reduction in total power. For LVCMOS 18 when we scaled down the frequency form 50GHz to 10 GHz we found 69.54% reduction in total power. In last when we reduced the frequency form 50GHz to 10GHz in LVCMOS 25 we found 64.41% reduction in total power. Our CRC design is implemented on Virtex-6 FPGA family.

Keywords

40 nm FPGA, CRC, Energy Efficient, Low Power, LVCMOS IO Standard.

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M. Sadiq Ali Khan ¹, Huma Jamshed ¹, Sumreena Bano ², Muhammad Navaid Anwar ²

Affiliations
1 University of Karachi
2 Sir Syed University of Engineering and Technology

Abstract

The Internet of Things (IoT) and Big Data have made the leap to turn into a mainstream issue and maintains board level priorities. Both IoT and big data are continuously creating headlines all over, drawing a huge amount of research interest and highlighting unique challenges. This growing recognition is due the intersection of both technologies with tremendous scope for business analytics and the prospective that still remains unexploited. Every day, industrial machine, health monitoring systems, sensors, and devices etc. connect to the Internet and exchange information. The future IoT will be extremely populated by huge quantity of heterogeneous networked embedded devices, which will be producing deluge of data. As businesses gets on new IoT project and tries to extract valuable information from enormous data volumes, a novel data management approach is called for. Conventional database management techniques and analytics methods fail to provide precise facilities to handle diverse data constantly flooding from numerous numbers of sources which are untold. This paper inspects the complex and fast moving data of IoT, and the existing position of data management techniques and challenges in storing and analyzing it.

Keywords

Big Data, Data Analytics, Internet of Things, Smart and Connected Things

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