AN EFFICIENT ADAPTATION OF UHD VIDEO STREAMING OVER INTERNET

The main challenge of multimedia applications is how to transmission the Ultra-High Definition (UHD) video streaming in real time over the internet. The real time video streaming suffer from difficulties to be flexible and efficiency cause the wide variation of the available internet bandwidth. To avoid the problems that introduces with internet, in this work the HEVC with required video network adaptive streaming are proposed and tested using different six levels of three UHD video (4K, FHD, 720p, 4CIF, CIF and QCIF). From different experiments that applied find the optimal configuration of H.265 encoding features for six levels to obtain the required PSNR with range (32-38 dB). The important part in this project is a controller that worked incorporate with the encoder (H.265) to obtain the video streaming adaptation on the available bandwidth of the channel. The controller continuously reads the status of channel buffer, then choosing the proper level of video to be transmitted over the channel. The work architecture is content two parts: First, the H.265 codec that apply on the three raw videos with optimal parameters configuration to compress them and get videos with lower bit rate and acceptable quality. Second, the compressed videos, based to controller.....

HIGH QUALITY LOW BITRATE VOICE CODEC FOR TRANSMISSION OVER ADVANCED LTE

In mobile communication systems bit-rate reductions while maintaining an acceptable voice quality are necessary to achieve efficiency in channel bandwidth utilization and users satisfaction. As Long-Term Evolution(LTE) converging towards all-IP solutions and supporting VOIP service, the voice signals are converted into coded digital bit-stream and sent over the network. This paper proposes the implementation of codebook excited linear prediction (CELP) voice codec algorithm based on two source-rates of low 9.6Kbps and medium 16Kbps for achieving a perceptible level of voice quality, while efficiently using available bandwidth during the transmission over advanced LTE. The architecture of proposed CELP codec model is implemented to decompose the voice signal into a set of parameters that characterize each particular frame at the encoder part, these parameters are quantized and encoded for transmission to the decoder. The investigation showed that the configuration of the link and the applied CELP codec mode mainly influence on the obtained voice capacity and quality. The quantifying also shows that the voice quality can be traded for the enhanced capacity, since the low rate codec will produce lower voice quality than higher rate codec. Also, this paper is achieved, during theconfiguration of the system with higher channel quality indicator (CQI) index, increasing in the capacity gain to a saturated value of about 500 and 1000 users per cell over 5MHz bandwidth for transmit diversity (TD) and Open-Loop Spatial Multiplexing (OLSM) respectively and up to 1000 and 2000 users per cell over 10MHz channel bandwidth for TD and OLSM respectively.

CHAOTIC COMPRESSIVE SENSING OF TV –UHF BAND IN IRAQ USING CHEBYSHEV GRAM SCHMIDT SENSING MATRIX

Cognitive radio (CR) is a promising technology for solving spectrum sacristy problem. Spectrum sensing is the main step of CR. Sensing the wideband spectrum produces more challenges. Compressive sensing (CS) is a technology used as spectrum sening in CR to solve these challenges. CS consists of three stages: sparse representation, encoding and decoding. In encoding stage sensing matrix are required, and it plays an important role for performance of CS. The design of efficient sensing matrix requires achieving low mutual coherence . In decoding stage the recovery algorithm is applied to reconstruct a sparse signal. İn this paper a new chaotic matrix is proposed based on Chebyshev map and modified gram Schmidt (MGS). The CS based proposed matrix is applied for sensing real TV signal as a PU. The proposed system is tested under two types of recovery algorithms. The performance of CS based proposed matrix is measured using recovery error (Re), mean square error (MSE), and probability of detection (Pd) and evaluated by comparing it with Gaussian, Bernoulli and chaotic matrix in the literature. The simulation results show that the proposed system has low Re and high Pd under low SNR values and has low MSE with high compression.

DETECTION OF THE DSSS SIGNAL WITH VARIABLE PN CODES USING THE ANN

- Direct sequence spread spectrum systems appeared and are used to protect the transmitted data DSSS Systems might be one of the solutions for reliable and secured communications. Also, it is one of the approaches used by signals for transmitting bandwidth larger compared to the satisfied frequency related to the original information. The communication systems of SS were vital to suppress interference, complicating the detection and processing of secure communications, the technology of spread spectrum (DSSS) has been initially created for military applications. In a traditional DSSS system, the PN code is the primary key to make the receiver recover the transmitted data. In this paper, by using the MATLAB R2020a is used to simulate the proposed system, it is considered that the transmitter sends data bits and wants to protect the sent data by making each bit send with a PN code consisting of 127 bits randomly without informing the receiver of that. here the artificial neural network (ANN) was used as a tool to find the PN code for each initial value of 7 flip-flops. so, the receiver could detect the transmitted data with BER =0.

LIFETIME MAXIMIZATION OF A MOBILE WSN USING ZRP-FUZZY CLUSTERING PROTOCOL BASED ON ANT-LION OPTIMIZER

Wireless Sensor Networks require energy-efficient protocols for communication and data fusion to integrate data and extend the lifetime of the network. An efficient clustering algorithm for sensor nodes will optimize the energy efficiency of WSNs. However, the clustering process requires additional overhead, such as selection of cluster head, cluster creation, and deployment. This paper prepared a modified ZRP for mobile WSN clustering scheme and optimization using ant-lion optimization algorithm and so far named as mobility cluster head fuzzy logic based on the zone routing protocol (ZRP-FMC-ALO). Which proposed fuzzy logic approach based on three descriptors node for the selection of the CH nodes such as, residual energy, the concentration, and the centrality of the node and also exploited the concept of the mobility of the Base Station (BS) to prolong the life span of a WSN. The performance of the proposed protocol compared with the famous protocol such as LEACH. Using the MATLAB simulator and the result shows that it outperforms in terms of the WSN network lifetime, the average remaining-consuming energy, and the number of a live node.

DESIGNING A SECURE NETWORK SOLUTION AGAINST DHCP ATTACKS

DHCP is an important aspect in small and large networks, since it facilitates the IP configuration of computers. However, DHCP is vulnerable to different attacks; therefore, the essential objective of this paper is to propose solutions against DHCP attacks. The paper gives an explanation about how DHCP works and understand the handshake mechanism and give a brief summary about DHCP attack, how they occur and how they affect the security of the enterprise since a leakage of sensitive Information could happen, which threatens the enterprise's security or a denial of service that immobilizes the network. Three effective countermeasures are looked up and tested against DHCP attacks, and each one successfully prevented the attack.

PERFORMANCE EVALUATION OF FILTER BANK MULTI-CARRIER MODULATION IN MULTIPATH FADING CHANNELS

Filter Bank Multi-Carrier (FBMC) modulation is one of the most significant enablers for future 5G technologies. It is a modulation technique for resolving inter-carrier and inter-symbol interference using two possible methods: Frequency Spreading (FS) and Poly Phase (PP) implementation. Cyclic prefixes are used in OFDM for signal robustness, but they have some disadvantages in orthogonal frequency division multiplexing. FBMC is used to solve the disadvantages of OFDM and save a bandwidth. In this paper, performance comparisons in terms of symbol error rate between OFDM and FBMC systems in AWGN and multipath fading channels are presented. The obtained results show that FBMC over performs OFDM in multipath fading channels and the improvement margin is increased as the number of subcarriers decreased.

HEART DISEASE PREDICTION SYSTEM USING MACHINE LEARNING ALGORITHM

Abstract—Information decision support systems are becomingmore in use as we are living in the era of digital data andrise of artificial intelligence. Heart disease as one of the mostknown and dangerous is getting very important attention, thisattention is translated into digital and prediction system thatdetects the presence of disease according to the available dataand information. Such systems faced a lot of problems since thefirst rise, but now with the deveolopment of machine learnigfield we are using them in developing new models to detect thepresence of this disease, in addition to algorithms data is veryimportant which also form the heart of the predicton systems,as we know prediction algorithms take decisions and thesedecisions must be based on facts, and these facts are extractedfrom data, as a result data is the starting point of every system.In this paper we propose a Heart Disease Prediction Systemusing Machine Learning Algorithms, in terms of data we usedCleveland dataset, this dataset is normalized then divided intothree scnearios in terms of traning and testing respectively,80%-20%, 50%-50%, 30%-70%. In each case of dataset ifit is normalized or not we will have these three scenarios.We used three machine learning algorithms for every scenarioof the mentioned before which are SVM, SMO and MLP, inthese algorithms we’ve used two different kernels to test theresults upon that. These two types of simulation are added tothe collection of scenarios mentioned above to become as thefollowing we have at the main level two types normalized andunnormalized dataset, then for each one we have three typesaccording to the amount of training and testing dataset, thenfor each of these scenarios we have two scenarios according tothe type of kernel to become 30 scenarios in total, our proposedsystem have shown a dominance in terms of accuracy over theother previous works.

MALWARE DETECTION SYSTEM BASED ON DEEP LEARNING TECHNIQUE

In this paper, we propose a malware classification and detection framework using transfer learning based on existing Deep Learning models that have been pre-trained on massive image datasets, we applied a deep Convolutional Neural Network (CNN) based on Xception model to perform malware image classification. The Xception model is a recently developed special CNN architecture that is more powerful with less overfitting problems than the current popular CNN models such as VGG16, The experimental results on a Malimg Dataset which is comprising 9,821 samples from 26 different families ,Malware samples are represented as byteplot grayscale images and a deep neural network is trained freezing the convolutional layers of Xception model adapting the last layer to malware family classification , The performance of our approach was compared with other methods including KNN, SVM, VGG16 etc. , the Xception model can effectively be used to classify and detect malware families and achieve the highest validation accuracy than all other approaches including VGG16 model which are using image-based malware, our approach does not require any features engineering, making it more effective to adapt to any future evolution in malware, and very much less time consuming than the champion’s solution.

RECONFIGURABLE MONOPOLE ANTENNA DESIGN BASED ON FRACTAL STRUCTURE FOR 5G APPLICATIONS

a reconfigurable antenna design for 5G applications is presented. It is based on monopole antenna and fractal structure. The design structure is consisted of (monopole) feedline, ground plane, L-shape reflector, fractal structure and PIN diodes. The antenna is printed on (25×29×1.6 mm3) FR-4 substrate of εr=4.3 and tanδ =0.001. The antenna shows a resonant frequency at 4.1 GHz with S11=-11.4 dB and Omni-direction pattern of 1.21 dB gain. The L-shaped reflector is used to maintain the radiation pattern in a specific direction. Moreover, the proposed fractal structure is found to operate as a circuit to give another resonant frequency and enhance the antenna performance. Where it is used to give more manipulation in the antenna performance including: frequency resonance and radiation patterns. The PIN-diodes are used to give many cases for more current manipulation. moreover, the authors used RF (50 SMA port) between monopole antenna and right side of ground plane to optimize directing radiation pattern and to eliminate the problems of interference between AC and DC current that produced from using PIN diode. This manipulation leads to change the resonant frequency and radiation pattern to the desired direction.So all parts are printed on a single side of FR4 substrate