Ikram Syed - Profile on Academia.edu (original) (raw)

Papers by Ikram Syed

Computers, Materials & Continua

This article presents a novel modified chuck wagon dinner bell shaped millimeter wave (mm-wave) a... more This article presents a novel modified chuck wagon dinner bell shaped millimeter wave (mm-wave) antenna at 28 GHz. The proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of 2.2. The design consists of T shaped resonating elements and two open ended side stubs. The desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed structure. The maximum achieved single element gain at the desired resonance frequency is 3.45 dBi. The efficiency of the proposed design over the operating band is more than 88%. The impedance bandwidth achieved for −10 dB reference value is nearly 2.9 GHz. The proposed antenna is transformed into four element linear array which increases the gain up to 10.5 dBi. The fabricated prototype is tested for the measured results. It is observed that measured results closely match the simulated results. By considering its simple structure and focused radiation patterns, the proposed design is well suited for IoT (Internet of Things), mmWave microwave sensing, 5G and future RF (Radio Frequency) frontends.

Delay analysis of IEEE 802.11e EDCA with enhanced QoS for delay sensitive applications

2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC)

The performance of IEEE 802.11e enhanced distributed channel access (EDCA) mechanism effects by t... more The performance of IEEE 802.11e enhanced distributed channel access (EDCA) mechanism effects by the network loads. It is observed that when the number of users increases in each access category, the delay significantly increased in EDCA algorithm. The performance improvement in EDCA algorithm in fluctuating network load is a challenging task. To improve the performance of EDCA algorithm for delay sensitive services, we propose an adaptive contention window algorithm, which adjusts the contention window with the number of user in each access category. We introduce a simple but novel model for delay analysis based on EDCA mechanism. The proposed model analyzes the quality of service for the delay-sensitive applications such as voice and video. The simulation result verifies the significance of the proposed model compared to the EDCA model.

FPL-An End-to-End Face Parts Labeling Framework

2018 24th International Conference on Automation and Computing (ICAC), 2018

Face parts labeling is the process of assigning class labels to each face part. A face parts labe... more Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method FPL which divides a given image into its constitutes parts is proposed in this paper. In most of the previously proposed methods this division is based on three or some time four classes. In the proposed work a given face image is divided into six classes (skin, hair, back, eyes, nose and mouth). A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. Testing phase is performed with two semantic segmentation methods i.e., pixel and super-pixel based segmentation. In pixel based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixels only – as a result same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel b...

IEEE Access

Medium Access Control (MAC) is the sub-layer of data link layer in the communication OSI model, w... more Medium Access Control (MAC) is the sub-layer of data link layer in the communication OSI model, whose basic function is to control the hardware that interacts with the transmission medium. In Wireless sensor network, the communication is done without any wired connectivity and the sensor nodes get energy through batteries. MAC layer protocol is classified as contention based and contention free. Over the years, these protocols have served efficiently in controlling the data transmission, yet they have some compromising and challenging issues, and data collision is one of them. Contention based protocols are reported to be more vulnerable to collisions, as they allow sharing of channels among transmitting nodes. Collisions result in message delay, data loss and retransmissions, resultantly demanding more energy. Researchers are trying their best to reduce the collisions during transmission. This research is aimed to evaluate the priority-based collision control in contention-based protocol. We present a new technique Energy efficient Collison mitigation MAC (ECM-MAC) protocol to handle the QoS and energy constraints for variety of applications. ECM-MAC uses different contention window and node priority mechanism to get the overall performance of the network. Nodes with most important data or with least residual energy will be allowed to transmit first, thereby minimizing the chances of collisions and maximizing the lifespan of the network. In case of high level of collision, the data traffic will be intelligently reduced to minimize the collisions. A contention-based MAC protocol is evaluated to compare the impacts of suggested mechanism with the standard protocol. It will be useful for designers to develop a better collision avoiding contention-based protocol. In wireless Sensor Networks (WSNs), a sensor node is typically comprising detection unit, transceiver unit (to send and receive the data packets), processing unit and an energy supply unit for energy provisioning. Enhancement in network lifetime is an important and major challenge in WSNs. Since the transceiver unit has more impact on the energy consumption of the node and its reduction results in significant improvement on network lifetime. In our work, we propose an efficient mechanism that prioritized the nodes to get the high performance in quality of service. MAC protocol is targeted to achieve this, as MAC layer has the authority access to the transmission channel. We prioritize the nodes with lower energy to increase the chances of that node to get access of the transmission channel before their power and battery ran out. Our proposed strategy outperforms other protocols in terms of content retrieval Time, retransmissions and energy efficiency.

Mathematics

This paper presents the design and realization of a compact printed ultra-wideband (UWB) antenna ... more This paper presents the design and realization of a compact printed ultra-wideband (UWB) antenna with notching characteristics for compact devices using a genetic algorithm. The antenna is capable of mitigating an adjacent sub-band ranging from 3.75 to 4.875 GHz, mainly used by many applications and standards such as WiMAX, WLAN and sub-6-GHz. The notch band functionality is achieved by etching out two symmetrical slots from the pentagonal radiating element. The simulation and measured results demonstrate that the proposed antenna overperformed compared with state-of-the-art antennas in terms of compactness with an overall size of 20 mm×15 mm×0.508 mm. Moreover, the proposed design shows a large bandwidth in the UWB region with a fractional bandwidth of 180% with respect to the center frequency of 5.25 GHz. The antenna also presents omnidirectional radiations all over the operation band and a good return loss performance.

Sensors

Human face image analysis is an active research area within computer vision. In this paper we pro... more Human face image analysis is an active research area within computer vision. In this paper we propose a framework for face image analysis, addressing three challenging problems of race, age, and gender recognition through face parsing. We manually labeled face images for training an end-to-end face parsing model through Deep Convolutional Neural Networks. The deep learning-based segmentation model parses a face image into seven dense classes. We use the probabilistic classification method and created probability maps for each face class. The probability maps are used as feature descriptors. We trained another Convolutional Neural Network model by extracting features from probability maps of the corresponding class for each demographic task (race, age, and gender). We perform extensive experiments on state-of-the-art datasets and obtained much better results as compared to previous results.

A framework for head pose estimation and face segmentation through conditional random fields

Signal, Image and Video Processing

This paper explores the usefulness of conditional random fields through the idea of semantic face... more This paper explores the usefulness of conditional random fields through the idea of semantic face segmentation in the challenging task of head pose estimation. A multi-class face segmentation algorithm based on conditional random fields is implemented to develop a model for each discrete pose. When a new test image is given as input to the face segmentation framework, the trained model predicts probabilities for each face part. These probabilities are then used for estimation of head pose. The proposed framework is evaluated on four standard databases, namely Pointing’04, AFLW, BU and ICT-3DHPE. Two standard metrics, mean absolute error and pose estimation accuracy are used for evaluation of the head pose estimation part. Pixel labeling accuracy is used to assess the segmentation results. The experimental results show that better results are obtained as compared to state-of-the-art.

Entropy

Accurate face segmentation strongly benefits the human face image analysis problem. In this paper... more Accurate face segmentation strongly benefits the human face image analysis problem. In this paper we propose a unified framework for face image analysis through end-to-end semantic face segmentation. The proposed framework contains a set of stack components for face understanding, which includes head pose estimation, age classification, and gender recognition. A manually labeled face data-set is used for training the Conditional Random Fields (CRFs) based segmentation model. A multi-class face segmentation framework developed through CRFs segments a facial image into six parts. The probabilistic classification strategy is used, and probability maps are generated for each class. The probability maps are used as features descriptors and a Random Decision Forest (RDF) classifier is modeled for each task (head pose, age, and gender). We assess the performance of the proposed framework on several data-sets and report better results as compared to the previously reported results.

Symmetry

Automatic gender classification is challenging due to large variations of face images, particular... more Automatic gender classification is challenging due to large variations of face images, particularly in the un-constrained scenarios. In this paper, we propose a framework which first segments a face image into face parts, and then performs automatic gender classification. We trained a Conditional Random Fields (CRFs) based segmentation model through manually labeled face images. The CRFs based model is used to segment a face image into six different classes—mouth, hair, eyes, nose, skin, and back. The probabilistic classification strategy (PCS) is used, and probability maps are created for all six classes. We use the probability maps as gender descriptors and trained a Random Decision Forest (RDF) classifier, which classifies the face images as either male or female. The performance of the proposed framework is assessed on four publicly available datasets, namely Adience, LFW, FERET, and FEI, with results outperforming state-of-the-art (SOA).

Mobile Information Systems, 2016

The performance improvement in IEEE 802.11 WLANs in widely fluctuating network loads is a challen... more The performance improvement in IEEE 802.11 WLANs in widely fluctuating network loads is a challenging task. To improve the performance in this saturated state, we develop an adaptive backoff algorithm that maximizes the system throughput, reduces the collision probability, and maintains a high fairness for the IEEE 802.11 DCF under dense network conditions. In this paper, we present two main advantages of the proposed ABA-CW algorithm. First, it estimates the number of active stations and then calculates an optimal contention window based on the active station number. Each station calculates the channel state probabilities by observing the channel for the total backoff period. Based on these channel states probabilities, each station can estimate the number of active stations in the network, after which it calculates the optimal CW utilizing the estimated active number of stations. To evaluate the proposed mechanism, we derive an analytical model to determine the network performance...

Journal of Applied Research and Technology, 2014

In this paper we proposed a method for geometric calibration of a projector. This method makes us... more In this paper we proposed a method for geometric calibration of a projector. This method makes use of a calibrated camera to calibrate the projector. Since the projector works inversely with a camera i.e., it projects the image instead of capturing it, so it can be considered as a reverse camera. The projector is calibrated with the help of a calibrated camera using two types of chessboard, a printed chessboard and a projected chessboard by the projector. The object points of the projected chessboard pattern are measured with the help of calibrated camera and the image points are directly acquired from the chessboard pattern to be projected. Then using these object points and image points the projector is calibrated. Once the projector calibration is done, the transformation matrices (from projector to screen, from camera to screen and from camera to projector) are determined which are used for the reconstruction of the 3D geometry.

A Secure Registration Scheme for Femtocell Embedded Networks

Lecture Notes in Electrical Engineering, 2013

Recently, femtocell received a signification interest to improve the indoor coverage and provide ... more Recently, femtocell received a signification interest to improve the indoor coverage and provide better voice and data services. Lots of work has been done to improve the femtocell security, but still there are some issues which need to be addressed. Our contribution to the femtocell security is to protect secure zone (femtocell coverage area within macrocell) from unauthorized (non-CSG) users. In this paper, we propose a secure registration scheme for femtocell embedded network. In this scheme, only Closed Subscriber Group (CSG) users are allowed to access both the femtocell and macrocell services within the secure zone. By prioritizing the femtocell over macrocell within the secure zone, every user will try to camp on femtocell and invoke location registration to the femtocell as the user enters to the femtocell coverage area. If the user is within the allowed users list, the femtocell will allow the user otherwise femtocell will send a reject message to the user and also send the user information to the core network.

Event Information Based Optimal Sensor Deployment for Large-Scale Wireless Sensor Networks

IEICE Transactions on Communications, 2012

Performance Improvement of QoS-Enabled WLANs Using Adaptive Contention Window Backoff Algorithm

IEEE Systems Journal

Quality of service (QoS) is one of the critical aspects for real-time applications in wireless lo... more Quality of service (QoS) is one of the critical aspects for real-time applications in wireless local area networks (WLANs). To provide QoS, WLANs use the enhanced distributed channel access (EDCA) with a fixed backoff range without considering the network load for estimating the backoff time. When the number of stations (STAs) increases in each access category (AC), the collision among STAs also increases; this leads to increased delay and decreased network throughput. In this paper, we aim to improve the QoS for WLANs and achieve better network performance in terms of high throughput, low collision rate, and small mean frame delay in delay-sensitive applications. To achieve this objective, we propose an adaptive contention window backoff mechanism that improves the QoS by adjusting the backoff time according to the active STAs in each AC. First, we estimate the number of STAs in each AC and then calculate the optimal contention window size based on the estimated STAs in each AC. We derived an analytical model for the proposed scheme and then conducted simulations to validate analytical model results. The simulation results show that the proposed scheme outperforms EDCA in terms of throughput and delay in different traffic scenarios.