Hari Shankar Singh

Bio: Hari Shankar Singh is an academic researcher from Thapar University. The author has contributed to research in topics: Antenna (radio) & Monopole antenna. The author has an hindex of 12, co-authored 67 publications receiving 525 citations. Previous affiliations of Hari Shankar Singh include Banaras Hindu University & Indian Institute of Technology (BHU) Varanasi.

A Quad-Band Compact Diversity Antenna for GPS L1/Wi-Fi/LTE2500/WiMAX/HIPERLAN1 Applications

Abstract: In this letter, a low-profile quad-band antenna array for multiple-input-multiple-output (MIMO) application has been presented. The proposed two-antenna array operates at GPS L1/Bluetooth/Wi-Fi/LTE2500/WiMAX/HIPERLAN1 frequency bands. Each antenna element has an area of 25×10 mm2 over a small ground plane of the size 100×60 mm2. To maintain the small size of the antenna element, folded patch is used. A rectangular slot is etched on the main radiator to utilize the higher-order mode. A quarter-wavelength resonator is integrated at the edge of folded patch to get an additional resonance for quad-band operation. An antenna prototype is fabricated, and measured results are in good agreement with simulated results. Radiation characteristics and diversity performance of the proposed structure are presented.

Low Mutual Coupling Between MIMO Antennas by Using Two Folded Shorting Strips

Abstract: This paper presents a compact dual-band multiple input multiple output (MIMO) antenna with low mutual coupling, operating in the 2.4GHz band (2.4{2.485GHz) and 5.5GHz band (5.15{ 5.85GHz). The proposed antenna system consists of two antenna elements located at the top two corners of FR4 substrate (PCB). Each element dimension is reduced substantially by employing a folded structure and slots on the top patch plate, so that it takes up a small volume of 12 £ 9 £ 6mm 3 . To enhance port-to-port isolation and e-ciency of each antenna, an additional non-radiating folded shorting strip is connected between each antenna element and ground plane of PCB. The measured isolation values are lower than i28dB over the lower WLAN band (2.4{2.485GHz) and better than i26dB (i30dB in most of the band) across the higher WLAN band (5.15{5.85GHz). The improvement in antenna's e-ciency caused to raise up 1dB of efiective diversity gain of MIMO system. Furthermore, S-parameters, radiation patterns and diversity performance characteristics are provided.

Metamaterial-based UWB antenna

Abstract: A metamaterial-based novel compact microstrip antenna is presented for ultra-wideband (UWB) applications. The antenna consists of two layers of metamaterials made by etching a π-shaped slot and crossed-shaped slots, on the radiating patch and the ground plane, respectively. The series capacitance and shunt inductance developed due to the patterned radiating patch and ground plane lead to the left-handed behaviour of the metamaterial. The proposed antenna has a compact size of 30.8 × 27.6 × 0.8 mm3 and is fed by a 50 Ω microstrip line. The impedance bandwidth (−10 dB) is from 3 GHz to more than 14 GHz with maximum radiation in the horizontal plane and tends towards a directional pattern as the frequency increases.

Design of WLAN Band Notched UWB Monopole Antenna with Stepped Geometry Using Modified EBG Structure

Abstract: A WLAN band notched compact ultra-wideband (UWB) microstrip monopole antenna with stepped geometry is proposed. A L-slot loaded modifled mushroom type Electromagnetic Band Gap (EBG) is designed, analyzed and used to realize notched band characteristics for wireless local area network (WLAN) in the UWB frequency range. The proposed antenna having partial ground plane is fabricated on a low cost FR4 substrate having dimensions 40(Lsub) £ 30(Wsub) £ 1:6(h)mm 3 and is fed by a 50-› microstrip line. The results show that the proposed antenna achieves impedance bandwidth (VSWR 2) from 4.9GHz to 6GHz. Fidelity factor for proposed antenna is also analyzed to characterize time domain behavior. Simulation and measurement results of VSWR are found in good agreement.

A MapReduce-based scalable discovery and indexing of structured big data

Abstract: Various methods and techniques have been proposed in past for improving performance of queries on structured and unstructured data. The paper proposes a parallel B-Tree index in the MapReduce framework for improving efficiency of random reads over the existing approaches. The benefit of using the MapReduce framework is that it encapsulates the complexity of implementing parallelism and fault tolerance from users and presents these in a user friendly way. The proposed index reduces the number of data accesses for range queries and thus improves efficiency. The B-Tree index on MapReduce is implemented in a chained-MapReduce process that reduces intermediate data access time between successive map and reduce functions, and improves efficiency. Finally, five performance metrics have been used to validate the performance of proposed index for range search query in MapReduce, such as, varying cluster size and, size of range search query coverage on execution time, the number of map tasks and size of Input/Output (I/O) data. The effect of varying Hadoop Distributed File System (HDFS) block size and, analysis of the size of heap memory and intermediate data generated during map and reduce functions also shows the superiority of the proposed index. It is observed through experimental results that the parallel B-Tree index along with a chained-MapReduce environment performs better than default non-indexed dataset of the Hadoop and B-Tree like Global Index (Zhao etal., 2012) in MapReduce. Solution for the lack of indexing in the MapReduce frameworksHadoop is proposed.Parallel implementation of existing B-Tree index is carried out in MapReduce.Parallel implementation of range search query is carried out in MapReduce.Cluster size, query coverage, number of map tasks and size of I/O data are analyzed.HDFS block size and, heap memory and intermediate data generated are analyzed.Proposed parallel B-Tree index provides high scalability and efficient data search.

The Priority R-Tree: A Practically Efficient and Worst-Case-Optimal R-Tree

Abstract: The query efficiency of a data structure that stores a set of objects, can normally be assessed by analysing the number of objects, pointers etc. looked at when answering a query. However, if the data structure is too big to fit in main memory, data may need to be fetched from disk. In that case, the query efficiency is easily dominated by moving the disk head to the correct locations, rather than by reading the data itself. To reduce the number of disk accesses, once can group the data into blocks, and strive to bound the number of different blocks accessed rather than the number of individual data objects read. An R-tree is a general-purpose data structur that stores a hierarchical grouping of geometric objects into blocks. Many heuristics have been designed to determine which objects should be grouped together, but none of these heuristics could give a guarantee on the resulting worst-case query time. We present the Priority R-tree, or PR-tree, which is the first R-tree variant that always answers a window query by accessing $O((N/B)^{1-1/d} + T/B)$ blocks, where $N$ is the number of $d$-dimensional objects stored, $B$ is the number of objects per block, and $T$ is the number of objects whose bounding boxes intersect the query window. This is provably asymptotically optimal. Experiments show that the PR-tree performs similar to the best known heuristics on real-life and relatively nicely distributed data, but outperforms them significantly on more extreme data.

Bending and On-Arm Effects on a Wearable Antenna for 2.45 GHz Body Area Network

Abstract: Three types of flexible textile antennas for 2.45 GHz body area network (BAN) are compared in this letter. Two types of conducting materials are used to form radiation patch and ground plane; they are called copper foil tape (CFT, 0.05 mm thickness) and Shieldex (SH, 0.13 mm thickness, 0.009 Ohm surface resistivity). The substrate is a thin felt with relative permittivity of 1.2 and the thickness of 2 mm. In order to satisfy these requirements of small frequency shifting when the antenna is bent and placed on human body, two shorting probes are used to connect the radiation patch and ground plane. Compared to the antenna without shorting probes, the size of proposed antenna is reduced from 96 ×47 to 70 ×25 mm 2 , and the measured minimum value of S11 in free space is also decreased from -14.59 to -33.30 dB. Furthermore, an antenna with smaller size of 46 ×25 mm 2 is designed by modifying the proposed structure, and it can act as a wearable antenna as well.

The state of the art and taxonomy of big data analytics: view from new big data framework

Abstract: Big data has become a significant research area due to the birth of enormous data generated from various sources like social media, internet of things and multimedia applications. Big data has played critical role in many decision makings and forecasting domains such as recommendation systems, business analysis, healthcare, web display advertising, clinicians, transportation, fraud detection and tourism marketing. The rapid development of various big data tools such as Hadoop, Storm, Spark, Flink, Kafka and Pig in research and industrial communities has allowed the huge number of data to be distributed, communicated and processed. Big data applications use big data analytics techniques to efficiently analyze large amounts of data. However, choosing the suitable big data tools based on batch and stream data processing and analytics techniques for development a big data system are difficult due to the challenges in processing and applying big data. Practitioners and researchers who are developing big data systems have inadequate information about the current technology and requirement concerning the big data platform. Hence, the strengths and weaknesses of big data technologies and effective solutions for Big Data challenges are needed to be discussed. Hence, due to that, this paper presents a review of the literature that analyzes the use of big data tools and big data analytics techniques in areas like health and medical care, social networking and internet, government and public sector, natural resource management, economic and business sector. The goals of this paper are to (1) understand the trend of big data-related research and current frames of big data technologies; (2) identify trends in the use or research of big data tools based on batch and stream processing and big data analytics techniques; (3) assist and provide new researchers and practitioners to place new research activity in this domain appropriately. The findings of this study will provide insights and knowledge on the existing big data platforms and their application domains, the advantages and disadvantages of big data tools, big data analytics techniques and their use, and new research opportunities in future development of big data systems.

Learning Multi-Dimensional Indexes

Abstract: Scanning and filtering over multi-dimensional tables are key operations in modern analytical database engines. To optimize the performance of these operations, databases often create clustered indexes over a single dimension or multi-dimensional indexes such as R-Trees, or use complex sort orders (e.g., Z-ordering). However, these schemes are often hard to tune and their performance is inconsistent across different datasets and queries. In this paper, we introduce Flood, a multi-dimensional in-memory read-optimized index that automatically adapts itself to a particular dataset and workload by jointly optimizing the index structure and data storage layout. Flood achieves up to three orders of magnitude faster performance for range scans with predicates than state-of-the-art multi-dimensional indexes or sort orders on real-world datasets and workloads. Our work serves as a building block towards an end-to-end learned database system.

MIMO antennas with diversity and mutual coupling reduction techniques: a review

Abstract: Multiple input multiple output (MIMO) antenna is at core of the presently available wireless technologies. The design of MIMO antennas over a limited space requires various approaches of mutual coupling reduction, otherwise gain, efficiency, diversity gain, and radiation patterns will be severely affected. Various techniques have been reported in literature to control this degrading factor and to improve the performance of the MIMO antennas. In this review paper, we have carried out an extensive thorough investigation of diversity and mutual coupling (correlation) reduction techniques in compact MIMO antennas.