Efficient Coding Techniques Research Articles

The Exploration of Modelling for The Student Achievement Predictor

The project is rooted in the analysis of historical student data. It encompasses a comprehensive approach involving data observation, meticulous analysis, thorough comparison, systematic processing, and efficient coding techniques. The ultimate goal is to harness the power of machine learning to predict students' academic achievements and discern the key features that exert the most significant influence on their learning outcomes. In terms of the machine learning model, this study explored and assessed several machine learning algorithms, including but not limited to the K-Neighbors Classifier, Logistic Regression, and Decision Tree Classifier. These models are scrutinized and fine-tuned to ensure their suitability for the task at hand. Furthermore, a pivotal aspect of this project is identifying the features that wield the greatest impact on students' learning achievements. By employing feature selection techniques, this study aims to uncover the critical factors that can make a difference in educational outcomes. This information can guide educational institutions in designing targeted interventions to support student success. The experimental results obtained from this study demonstrated the effectiveness of the employed machine learning methods.

STBC-Assisted MDC-NOMA Image Transmission Scheme for Multi-Antenna Systems

As an efficient and interference-resistant coding technique, multiple description coding (MDC) is proposed with the aim to solve the transmission unreliability problem caused by packet errors, loss or blocking delays. The integration of MDC with non-orthogonal multiple access (NOMA) scheme (MDC-NOMA) can effectively boost the robustness and throughput of the underlying system. Additionally, space-time block coding (STBC) can further enhance the system reliability with increased diversity gain, as well as reduced decoding complexity. In this paper, we propose a novel framework referred to as MDC-NOMA-STBC, in which we apply Alamouti STBC integrated with MDC and NOMA to implement more reliable transmission. Specifically, NOMA signals are constructed by superimposing the descriptions from different users, then transmitted by the base station (BS) using Alamouti STBC. In order to substantiate the performance of the proposed framework, first, we derive closed-form expressions of both the outage probability and ergodic rate for each user in a two-antenna BS scenario. Second, for multi-antenna BS, we investigate different antenna selection strategies to further enhance the outage performance under the considered framework, whose analytical expression is provided wherever possible. Third, Monte Carlo simulation results are presented to validate our theoretical framework and to corroborate the superiority of the proposed MDC-NOMA-STBC over state-of-the-art MDC-NOMA scheme. Moreover, under realistic contexts with image transmission, it is confirmed that MDC-NOMA-STBC outperforms its counterpart MDC-NOMA in terms of the peak signal-to-noise ratio and the bit error rate.

A NEW TECHNIQUE FOR COMPRESSION AND STORAGE OF IMAGES

During the past decades we have been observing a permanent increase in image data, leading to huge repositories.[1]. This paper focuses on image compression and storage. We define methods to improve the efficiency and effectiveness of image compression. Image compression refers to represent an image with as few bits as possible while preserving the level of quality and intelligibility required for a particular application. The present work aims to develop an efficient algorithm for compression and storage of two-tone image. In this paper, an efficient coding technique is proposed and termed as line- skipping coding for two-tone image. The technique exploits 2-D correlation present in the image. This new algorithm is devised to reduce fifty to seventy five percentage of memory storage.

Optimized Reception Sensitivity of WBAN Sensors Exploiting Network Coding and Modulation Techniques in an Advanced NB-IoT

The sensitivity of the maximum useable data is the most significant characteristic that describes the quality of the Narrowband Internet of Things (NB-IoT) of Medical sensors (MS) receivers. It becomes the most important performance factor in mobile wireless communication networks, particularly wireless body area networks (WBAN). Our interest is in level sensitivity using modulation techniques and subcarrier spacing(SS) to achieve good Bit Error Rate (BER) performance, throughput, and power efficiencies for WBAN communication Systems in an advanced NB-IoT. We propose an efficient coding technique using Linear Network Coding (LNC) to improve sensitivity by considering several factors without affecting the human body. We also present an experimentally analyzed overview of the reception sensibility. Our research has revealed that the receiver sensitivity (minimum detectable signal level) and throughput of the proposed approach (PA) are much better than the conventional approach (CA), achieving more than 14.3% and 55%, respectively, compared to the CA. Also, the PA has improved the modulation types by approximately 45% to provide more throughput and reliability.

Binary Joint Network-Channel Coding for Reliable Multi-Hop Wireless Networks

The high and variable packet loss in wireless networks due to the unreliable nature of wireless channels, interference, link or router failure, fading, and shadowing wireless link are the main problems and challenges in implementing a reliable wireless network. Packet loss probability is the most important performance measure for real-time applications. Packet loss is due to errors, congestion in the queue because of high traffic, collision, hidden nodes, and link failures. In this paper, we focus on the links failure problem. To address this problem, improve the performance of wireless networks, and enhance and make the network survivability and availability more reliable, a new efficient binary joint network and channel coding (B-JNCC) technique is proposed. B-JNCC combines low-complexity parity-check (LCPC) channel coding and the wireless network erasure correcting with router code to detect lost packets to reduce the bit error rate and increase the packet delivery ratio over a wireless multi-access channel. B-JNCC is applied at the receiver node. Simulation results show that the proposed B-JNCC outperforms the binary symbol-wise JNCC, non-binary JNCC (NB-JNCC), and NB separate network-channel coding.

QoE‐Oriented Cooperative Broadcast Optimization for Vehicular Video Streaming

The popularity of online vehicular video has caused enormous information requests in Internet of vehicles (IoV), which brings huge challenges to cellular networks. To alleviate the pressure of base station (BS), Roadside Units (RSUs) and vehicle peers are introduced to collaboratively provide broadcast services to vehicle requesters where vehicles act as both service providers and service requesters. In this paper, we propose an efficient framework leveraging scalable video coding (SVC) technique to improve quality of experience (QoE) from two perspectives: (1) maximizing the data volume received by all requesters and (2) determining buffer action based on playback fluency and average playback quality. For (1), potential providers cooperate to determine the precached video content and delivery policy with the consideration of vehicular mobility and wireless channel status. If one provider fails, other sources will complement to provide requested content delivery. Therefore, their cooperation can improve the QoE and enhance the service reliability. For (2), according to buffer occupancy status, vehicle requesters manage buffer action whether to buffer new segments or upgrade the enhancement level of unplayed segment. Furthermore, the optimization of the data volume is formulated as an integer nonlinear programming (INLP) problem, which can be converted into some linear integer programming subproblems through McCormick envelope method and Lagrange relaxation. Numerical simulation results show that our algorithm is effective in improving total data throughput and QoE.

Technologies Assisting the Paradigm Shift from 4G to 5G

Due to exponential increase in the capacity demands raised by the smart devices and multimedia applications of new generations, existing cellular networks are facing significant burden. To provide a solution to the challenges faced by 4th generation (4G) networks, there is utmost need of improving existing technologies as well as developing new technologies to meet the key requirements of 5th generation (5G) networks as well as the Next Generation Mobile Networks (NGMNs). Networks having high capacity, low latency, faster data rates and better quality of service is the vision of 5G mobile networks. In order to achieve this, we will need wider bandwidths as offered by millimeter wave bands, more spatial diversity as offered by Massive multiple input multiple output technology, denser networks as designed in dense small cell deployment technology, new waveforms using efficient coding techniques such as filtered orthogonal frequency division multiplexing and filter bank multiple carrier, a new architecture supporting virtualization and advance computing techniques as in network function virtualization, software defined networks, cloud radio access networks. Many more technologies are yet to be introduced. This tutorial gives an insight to the candidate technologies proposed by researchers till date and the progress made, for defining the standards to meet the requirements of 5G and NGMNs. It explains the basic concept of the technology and the latest development in the industry to support this technology.

An Efficient Polar Coding Scheme for Uplink Data Transmission in Narrowband Internet of Things Systems

Narrowband Internet of Things (NB-IoT) is an emerging IoT cellular-based wireless technology that builds based on the existing LTE standard to extend its network coverage suited for Low Power Wide Area Network (LPWAN) connectivity. In the NB-IoT system, LTE turbo codes and Cyclic Redundancy Check (CRC) codes are adopted as the main channel coding technique for Narrowband Physical Uplink Shared Channel (NPUSCH). However, turbo codes require iterative decoding algorithm at the expense of high computation complexity of decoding hence is crucial to achieving the LPWAN requirement of NB-IoT systems. Polar codes are best suited in this regard due to its capacity approaching and complexity reduction in short block length code. In this paper, we proposed an efficient polar coding technique using the Belief Propagation (BP) decoding algorithm for uplink data transmission on the NPUSCH channel. Furthermore, the BP algorithm is incorporated with the CRC stoppage criterion to decrease the number of decoding iteration and reduce computational complexity. In this scheme, single-tone numerology of NPUSCH using 3.75 kHz and 15 kHz subcarrier spacing is adopted. Then, the encoded data is generated with different NPUSCH resources. The theoretical formulation and simulation demonstrate that the proposed scheme provides better error rate performance over the adopted LTE turbo codes and other polar decoding algorithms while reducing the computational complexity.

Towards a Low Complexity Scheme for Medical Images in Scalable Video Coding

Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio.

CNN-Based Macropixel-Level Up-Sampling for Plenoptic Image Coding

Plenoptic imaging has emerged as a representative approach for recording richer visual information from the real world. With the insertion of a microlens array, plenoptic cameras can record both angular and spatial information of a scene on a plenoptic image. However, the large amount of data calls for efficient coding techniques for both transmission and storage. In this paper, we propose a convolutional neural network (CNN)-based macropixel-level up-sampling method for plenoptic image coding. First, a macropixel-based down-sampling method, which performs the down-sampling in the units of macropixels, is developed for reducing the block resolution. Then, an up-sampling CNN is carefully designed to achieve resolution recovery and quality enhancement for down-sampled blocks. The experimental results show that the proposed method achieves considerable bitrate reduction compared with the HEVC/H.265 format SCC extension profile.

Efficient coding techniques for ADO-OFDM in IM/DD systems

Optical wireless communication (OWC) is an age-long technology, which is based on optical data transmission through free space, and it can be implemented in both indoor and outdoor applications. As...

Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks

Random network coding (RNC) for Error Correction have been the subject of intense research lately. However, in wireless sensor networks (WSNs) the correlation between the received symbols, from the same cluster head (CH), provoke the column correlation on the generator matrix of array Low-Density Parity-Check (LDPC) codes, whereby many columns of this matrix do not offer any additional information, thus the most important properties are lost despite the fact that the generator matrices are more easily dispersed. In this paper, the authors describe each step of the problem-solving algorithm employing efficient coding techniques focusing on improvement planning at Bit-error rsate (BER) vs signal-to-noise ratio (SNR) curves, in dense WSN, between CHs and the base station (BS) node. They use efficient coding techniques approach based on RNC and LDPC codes using the Time Division Multiple Access (TDMA) method. They generalize the notion of RNC-LDPC, study their properties and formulate the main steps of the proposed algorithm reconstruction method. The simulation results demonstrate that this approach is more effective in improving the BER using the proposed algorithm. Moreover, subsequently ameliorate the technical properties offered by this codification type.

MIMO Network and the Alamouti, STBC (Space Time Block Coding)

In the present world, the spectrum efficiency along with the capacity and coverage of wireless networks are being improved by wireless specialists. Wireless link performance could be enhanced and improved by using multiple antenna technology called Space time wireless technology. There exists some advancement in the present MIMO techniques which could further improve the overall wireless Local Area Network (LANs) and Wide Area Network (WANs). In Multipath fading performance gain is very important which could be achieved by using an efficient Space-Time Coding (STC) technique. This Space Time coding along with Alamouti Scheme is a very vibrant research topic. In the forthcoming generation of mobile communication there will be a need of high data rate, reliable communication link and vast multimedia capabilities, STBC is the one solution for these. This paper presents the Space-Time Block Codes (STBC) for wireless networks using Alamouti Scheme in which multiple antennas are being used at both transmitter and receiver. The simulations have been done in MATLAB.

Invasive Weed Optimization Algorithm for Minimizing Total Weighted Earliness and Tardiness Penalties on a Single Machine under Aging Effect

In this paper, minimizing total weighted tardiness and earliness criteria on a single machine is considered. Job processing time is a linear function of its starting time and each job has a distinct due date. In this study an Invasive Weed Optimization (IWO) algorithm is proposed for machine scheduling problem. Because the local search operator in IWO algorithm is designed for continuous problem only, a simple and efficient coding and decoding technique is applied to map the discrete feasible space of the permutation to a number. Then, this number is used to produce the solution. The computational results show that the performance of the proposed algorithm is much better than the GA algorithm for this problem in finding the best solutions.

Novel Block Matching Reduced Complexity Motion Estimation and Compensation Algorithm for Mobile Domain: DBTSSDS

Communication between ends have dramatically increased by the expansion in wired (Hard) and wireless networks (soft wire). The user end machines have constrained capability. The availability of power/computation capability/storage and processing buffer/registers along with display. This necessitate the processing or preprocessing of information before transmitting in processed, compressed form. The bottleneck is to transmit the data through the channel with constrained capacity, in error free and acceptable quality. The data is enormously increases with HD content further necessitate effective and vigorous video processing procedures to permit error free real-time encoding and decoding. The real-time conferencing and events generates large sets of data which demands maximum level of compression and very high quality of reception. Even though latest standards like 3G /4G/5G along with efficient coding techniques the available channel has significantly increased but still processing is needed to adjust and accommodate more information in terms of numbers and quality. Numerous methodology had been proposed for compressing the Video but Block Matching methodology(BM) remains the most acceptable. BM is also commonly known as Motion Estimation and compensation(ME) techniques had been utilized for reducing the computational complication of the coding process. BM algorithms is important for accomplishing the effectual and reasonable compression. The block matching algorithm dictates the total computation cost and actual bit budget. Lately various fast search algorithms for video coding have also been proposed. This paper presents a method built on the extension and adjustment of research work MTSSDS block matching algorithm. The proposed algorithm utilizes the concept of logical dead blocks. The projected algorithm is labeled as DBTSSDS which expands to include and manipulate Dead Block on Modified Three steps and Diamond Search (DS) Block Matching Algorithm for the active block based motion estimation for mobile domain. It has been found that from the original (3SS/TSS) and DS, the PSNR value (thus quality) has increased slightly and the significant lowering of computations and thus computation time (faster) has been reduced significantly. The investigational fallouts utilizing various video sequences with different environment are utilized for validating and equate the benefits of projected motion estimation technique.

A Proficient Algorithm for Compression and Storage of Two-Tone Image

Since 1990s , there has be a swift, increase in computers, storage media and digital image taking devices, which enables a large number of digital information and store in computer readable formats. Image compression is an important issue in internet, mobile communication, digital library and other applications. Image compression refers to represent an image with as few bits as possible while preserving the level of quality and intelligibility required for a particular application. The present work aims to develop an efficient algorithm for compression and storage of two-tone image. In this paper, an efficient coding technique is proposed and termed as line- skipping coding for two-tone image. The technique exploits 2-D correlation present in the image. This new algorithm is devised to reduce fifty to seventy five percentage of memory storage.

시간적 예측 구조와 움직임 벡터의 특성을 이용한 움직임 추정 기법

Efficient multi-view coding techniques are needed to reduce the complexity of multi-view video which increases in proportion to the number of cameras. To reduce the complexity and maintain image quality and bit-rates, an motion estimation method and temporal prediction structure are proposed in this paper. The proposed motion estimation method exploits the characteristic of motion vector distribution and the motion direction and motion size of the block to place search points and decide the search patten adaptively. And the proposed prediction structure divides every GOP to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experiment results show that the complexity reduction of the proposed temporal prediction structure and motion estimation method over hierarchical B pictures prediction structure and TZ search method which are used in JMVC(Joint Multi-view Video Coding) reference model can be up to 45∼70% while maintaining similar video quality and bit rates.

Motion Hooks for the Multiview Extension of HEVC

MV-HEVC refers to the multiview extension of High Efficiency Video Coding (HEVC). At the time of writing, MV-HEVC was being developed by the Joint Collaborative Team on 3D Video Coding Extension Development (JCT-3V) of International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) Moving Picture Experts Group and ITU-T VCEG. Before HEVC itself was technically finalized in January 2013, the development of MV-HEVC had already started and it was decided that MV-HEVC would only contain high-level syntax changes compared with HEVC, i.e., no changes to block-level processes, to enable the reuse of the first-generation HEVC decoder hardware as is for constructing an MV-HEVC decoder with only firmware changes corresponding to the high-level syntax part of the codec. Consequently, any block-level process that is not necessary for HEVC itself but on the other hand is useful for MV-HEVC can only be enabled through so-called hooks. Motion hooks refer to techniques that do not have a significant impact on the HEVC single-view version 1 codec and can mainly improve MV-HEVC. This paper presents techniques for efficient MV-HEVC coding by introducing hooks into the HEVC design to accommodate inter-view prediction in MV-HEVC. These hooks relate to motion prediction, hence named motion hooks. Some of the motion hooks developed by the authors have been adopted into HEVC during its finalization. Simulation results show that the proposed motion hooks provide on average 4% of bitrate reduction for the views coded with inter-view prediction.

Interframe coding of feature descriptors for mobile augmented reality.

Streaming mobile augmented reality applications require both real-time recognition and tracking of objects of interest in a video sequence. Typically, local features are calculated from the gradients of a canonical patch around a keypoint in individual video frames. In this paper, we propose a temporally coherent keypoint detector and design efficient interframe predictive coding techniques for canonical patches, feature descriptors, and keypoint locations. In the proposed system, we strive to transmit each patch or its equivalent feature descriptor with as few bits as possible by modifying a previously transmitted patch or descriptor. Our solution enables server-based mobile augmented reality where a continuous stream of salient information, sufficient for image-based retrieval, and object localization, is sent at a bit-rate that is practical for today's wireless links and less than one-tenth of the bit-rate needed to stream the compressed video to the server.

H.264‐based hierarchical two‐layer lossless video coding method

An efficient lossless coding technique is very important for storage and transmission applications of error sensitive information such as medical, seismic and digital artistic data. In this study, the authors proposed an H.264-based advance video coding (H.264/AVC)-based hierarchical lossless coding method, where the input video will be firstly encoded by H.264/AVC coder with a quantisation parameter (QP) selector in the base layer and the coded error is encoded by a QP-adaptive Rice coder in the enhancement layer. To reduce encoding time, the QP selector can be simplified to select the nearly optimal QP. Simulation results show that the proposed hierarchical lossless coding architecture achieves better compression ratio than the traditional H.264/AVC-based lossless coding systems. Since the proposed system could provide both lossy and lossless coding services at the same time, the proposed lossless video coding system has advantages of efficiency and flexibility for practical applications. Experimental results show that the proposed coding system can provide less coding bits and reduce coding complexity compare with H.264-differential pulse code modulation.