Department of Electrical Engineering

Three-Dimensional (3-D) ICs are able to obtain significant performance benefits over two-dimensional (2-D) ICs based on the electrical and mechanical properties resulting from the new geometrical arrangement. The arrangement of 3-D ICs also offers opportunities for new circuit architecture based on the geometric capacity. The emerging 3-D VLSI integration and process technologies allow the new design opportunities in 3-D Network-on-Chip (NoC). The 3-D NoC can reduce significant amount of wire length for local and global interconnects. In this paper, we have proposed an efficient 3-D Asymmetric Torus routing algorithm for NoC. The 3-D torus has constant node degree, recursive structure, simple communication algorithms, and good scalability. A Quadrant-XYZ dimension order routing algorithm is proposed to build 3-D Asymmetric Torus NoC router. The algorithm partitions the geometrical space into quadrants and selects the nearest wrap-around edge to connect the destination node. Thus, the presented algorithm guarantees minimal paths to each destination based on routing regulations. The complexity of the algorithm is O (n). The proposed routing algorithm has been compared with the traditional XYZ algorithm and the comparison results show that the Quadrant-XYZ router has shorter path length. This paper presents a Register Transfer Logic (RTL) simulation model of Quadrant-XYZ dimension order routing algorithm for 3-D asymmetric torus NoC written in Verilog. The model represents the functional behavior of the routing chip down to the flit (byte) level. The 3-D asymmetric torus NoC has achieved a maximum operating frequency 750 MHz on Xilinx Vertex-6 programmable device.

As a first study, the use the Gabor filter bank is
made to generate features for face recognition. The features
so obtained on the application of SVM classifier yields
accuracy rate of 96.2%. With a view to improve the
performance, two more feature types, viz., wavelet features
and wavelet-fuzzy features resulting from the application of
2D wavelet transform on the Composite detail images and
the Approximate images at 3 levels of  decomposition, are
devised. The ROCs of three feature types show that waveletfuzzy features have a better performance. The performance
of Gabor features is slightly inferior to that of wavelet-fuzzy
features.  The algorithm was tested on ORL (Olivetti
Research Laboratory) database that has slight orientations
in face images.

Large companies have Data Centers numbering in thousands and are located at geographically wide spread places. The energy expenses are becoming an increasingly important proportion of the operating costs of the Data Centers. At the same time, the energy expense per unit can exhibit both temporal and geographic variations. The existing distributed systems should be able to exploit this variation for significant economic gains. In our scheme, clients may be routed to distant servers in search of cheap energy as in a multicast group of servers having data redundancy. We propose an application and a method of implementation of the Workflow Intuitive Formal Approach, an automatic decision making technique developed only recently, for dynamic detection and seamlessly transferring the functionalities from any existing Data Centre to an available least energy cost location.

The Objective of this research work is to prove significant role of each attribute to decide breast cancer type using Computer Aided Diagnosis. One of major challenges in medical domain is the extraction of intelligible knowledge from medical diagnostic data in minimum time and cost This research shows that out of these attributes stated, some attributes can be ignored to decide the type Breast Cancer as if the number of inputs are less then it reduces the time and cost in analyzing the breast cancer. In this paper, significant role of each attribute is proved
by experiment in MatLab.

Traffic management has been a major problem in all the developing as well as developed countries. Governments have been spending hefty amounts to manage various aspects of traffic
management using different methodologies. In this paper, a mathematical method is proposed to formulate congestion on a section of a main road having n number of possible alternate routes. This mathematical formulation would allow the decision makers to manage and give signals from far off control units. The
article further tries to propose a possible solution involving the derived mathematical formulae and the concepts of fuzzy logic.

An Auto-Identification (Auto-ID) technology has achieved significant growth in various verticals as industries, purchasing and distribution technologies, manufacturing companies,
defence and material flow system. Auto-ID is the term used to describe the process of automatic data collection and identification that occurs in real-time. Automatic identification procedures exist to provide  information about people, animals, goods and products in transit. Radio frequency identification (RFID) is a general term that is used to describe a system that
transmits the identity (in the form of a unique identification number) of an object wirelessly, using radio waves without any line-of-sight between tagged objects and readers (Auto-ID
Technical report, 2002; Khan M Ayoub et al.,  2009). RFID is based on Radio Frequency, which operates in different frequency bands viz. low frequency (LF), high frequency (HF) and ultrahigh frequency (UHF). The frequency band is determined by the requirement of application like read range, sensitivity etc.  The RFID Devices are capable of operating in frequency ranging from 125 KHz to beyond 2.5 GHz, however, due to regulatory restrictions (typically country specific) on use of radio–frequency spectrum, only few frequencies are commonly used. The two most common are 13.56 MHz in the HF band and frequency
around 900 MHz in UHF band. The frequency affects the characteristics of the resulting sensing environment, for instance HF signal propagate more easily through plastic, paper
and moisture as compared to UHF, where as UHF signals having longer range. RFID tags may derive the energy to operate either from an on-tag battery or by scavenging power from the electromagnetic radiation emitted by readers. The most obvious technology that is comparable to RFID for many application areas is Barcode. Both these technologies involve the addition of a ‘tag’ or ‘label’ to an item that contains information about that item which allows it to be identified by a computer system. 
A system designed to identify objects based on RFID tags has two advantages over conventional Barcode systems:

The growing demand of applications in consumer electronics has increased the number of computing resources in single chip. The applications need many computing resources such as CPU, DSP, and specific IPs to build a system in System-on-Chip (SoC). Therefore, interconnection between each other becomes another challenging issue. In this paper, we have presented
the emerging paradigm of networks that is applied to SoC design. This paper presents history, evolution and state-of-art of Network-on-Chip (NoC). The paper also presents discussion on routing and architecture of NoC.

Soft computing is an enriching domain that helps to encode
uncertainty and imprecision that exists in real world. Integration
of soft computing techniques in the systems lends added
advantage to the existing systems to allow solutions to otherwise
unsolvable problems. Fuzzy architecture has been extensively
researched and applied in medical domain. This paper suggests
incorporating a new logic: Neutrosophic logic in medical
domain and also discusses the possibility of extending the
capabilities of the  fuzzy systems by  employing  neutrosophic
systems.

Three-Dimensional (3-D) ICs are able to obtain significant performance benefits over two-dimensional (2-D) ICs based on the electrical
and mechanical properties resulting from the new geometrical arrangement. The arrangement of 3-D ICs also offers opportunities for new
circuit architecture based on the geometric capacity. The emerging 3-D VLSI integration and process technologies allow the new design
opportunities in 3-D Network-on-Chip (NoC). The 3-D NoC can reduce significant amount of wire length for local and global
interconnects. In this paper, we have proposed an efficient 3-D Asymmetric Torus routing algorithm for NoC. The 3-D torus has constant
node degree, recursive structure, simple communication algorithms, and good scalability. A Quadrant-XYZ dimension order routing
algorithm is proposed to build 3-D Asymmetric Torus NoC router. The algorithm partitions the geometrical space into quadrants and
selects the nearest wrap-around edge to connect the destination node. Thus, the presented algorithm guarantees minimal paths to each
destination based on routing regulations. The complexity of the algorithm is O (n). The proposed routing algorithm has been compared with
the traditional XYZ algorithm and the comparison results show that the Quadrant-XYZ router has shorter path length. This paper presents a
Register Transfer Logic (RTL) simulation model of Quadrant-XYZ dimension order routing algorithm for 3-D asymmetric torus NoC
written in Verilog. The model represents the functional behavior of the routing chip down to the flit (byte) level. The 3-D asymmetric torus
NoC has achieved a maximum operating frequency 750 MHz on Xilinx Vertex-6 programmable device.

This is widely accepted that Network-on-Chip represents a promising solution for forthcoming complexembedded systems. The current SoC Solutions are built from heterogeneous hardware and Softwarecomponents integrated around a complex communication infrastructure. The crossbar is a vital component of in any NoC router. In this work, we have designed a crossbar interconnect for serial bit data transferand 128-parallel bit data transfer. We have shown comparision between power and delay for the serial bitand parallel bit data transfer through crossbar switch. The design is implemented in 0.180 micron SMC technology.The bit rate achived in serial transfer is slow as compared with parallel data transfer. Thesimulation resuls show that the critical path delay is less for parallel bit data transfer but power dissipationis high.

The mobility of the cellular users indicates non-uniform load (traffic)
in different regions of the wireless network. This calls for a channel
allocation technique which is able to adapt with the changing load
pattern in different regions. The paper addresses the issue of efficient
time bound channel allocation in cellular network with non-uniform
traffic load distribution. The proposed technique identifies “heavy
load cells and partitions the cells of the network into groups where
the “heavy load cells will act as a group head. The number
of such groups is not known a priori. A pure dynamic channel
allocation technique, whether central or distributed, may require
more computation and allocation time. A hybrid channel allocation
technique being a combination of fixed and dynamic allocation can
prove to be better time efficient channel allocation technique for realtime
wireless communication networks. In this paper, we propose a
hybrid traffic aware channel allocation technique which adapts itself
on the basis of altering load patterns for every region. The technique
is based on backpropagation algorithm for identifying the traffic
trends of different regions or cells and utilizes the information for
clustering cells and spectrum allocation in an intra-cluster manner.

Channel allocation in wireless communication
network plays a crucial role in the performance of the
network. Fixed scheme for channel allocation does not
account for any non-uniform traffic in the network.
Dynamic scheme, on the other hand, ensures that whenever
a cell requires a channel, it is allocated pertaining to the
frequency reuse constraints. The fact that distributed
dynamic channel allocation technique has recently gained
popularity is due to its high reliability and scalability. In
this paper we propose a token based mutual exclusion
technique to solve the problem of distributed dynamic
channel allocation. We will show through simulation, how
message exchange between cells is reduced in token based
relaxed mutual exclusion as opposed to other relaxed
mutual exclusion techniques.

Accuracy is one of the most important aspects while designing forecasting model. Particularly, accuracy in fuzzy prediction system considerably depends on subjectively decided parameters such as membership function and relative weight of past observations. In this regard, we have proposed a novel concept to optimize ordered weighted aggregation (OWA) based fuzzy time series predictor (FTSP) using genetic algorithm (GA). Firstly, accurateness of FTSP is enhanced by applying effective method of aggregation on past observations using OWA weights. These weights are determined on the basis of importance of fuzzy set in the system by employing regularly increasing monotonic (RIM) quantifiers. Subsequently, GA is used to optimize membership functions of FTSP by generating its wide range of parameters in the region of time series. Lastly, this model is capable of controlling its performance by varying GA parameters. To assess proposed method, we used dataset of enrollments and outpatient visits, as used by almost all previous research in this domain. Evaluation results indicate coalescing OWA and GA for FTSP significantly reduced mean square error (MSE) and average forecasting error rate (AFER).

In order to maintain the quality power supply and reliable operation of power delivery service to the utilities with minimum interruption, it is extremely important that the transmission line faults need to be detected and located in a reliable and accurate manner. To meet these requirement an approach based on discrete wavelet transform using neural network (NN) is proposed to estimate the fault location of the three phase transmission line and the results have been compared with the conventional method (measuring the sequence components of voltage and current). The proposed approach is based on the measurements of the three phase fault current signals at one terminal of the transmission line (at relaying point), created for different fault operating conditions using MATLAB software. To accomplish the task, features of these measured signals are extracted in terms of summation of ninth level detail coefficients using multi-resolution analysis (MRA) based on discrete wavelet transform, selecting daubechies4 (db4) as mother wavelet at 100 kHz sampling frequency. These features are then used as an input to train and test the feed forward neural network (FFNN) to provide fault location from the relaying point on the transmission line. The NN estimates the location of the fault with a significant reduction in percentage error compared to the conventional method of fault location for wide variations of operating condition. Hence, the use of multi-resolution analysis (MRA) based on discrete wavelet transform in combination with NN is quite promising for fault location estimation of the transmission line.

The detection of singular points (core and delta) accurately and reliably is very important for classification and matching of fingerprints. This paper presents a new approach for core point detection based on scale invariant feature transform (SIFT). Firstly, SIFT points are extracted ,then reliability and ridge frequency criteria are applied to reduce the candidate points required to make a decision on the core point. Finally a suitable mask is applied to detect an accurate core point. Experiments on FVC2002 and FVC2004 databases show that our approach locates a unique reference point with high accuracy. Results of our approach are compared with those of the existing methods in terms of accuracy of core point detection.