• Fully Printed VO<inf>2</inf> Switch Based Reconfigurable PIFA Antenna

      Su, Zhen; Vaseem, Mohammad; Yang, Shuai; Klionovski, Kirill; Shamim, Atif (2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, 2019-01-24) [Conference Paper]
      Frequency reconfigurable antennas are attractive as they can cover multiple bands as well as different wireless standards in different countries. Typically., these antennas utilize complex subtractive fabrication processes which result in higher costs. For switching to different bands., generally semiconductor based devices such as PIN diode switches or MEMS switches., etc. are used., which add to the cost and pose integration and reliability issues. The ideal approach would be to use low-cost additive manufacturing techniques., such as inkjet printing. This work presents., a novel fully inkjet printed frequency reconfigurable PIFA antenna., where the switch (based on vanadium dioxide (V02)) has also been printed. The switch operates through thermal activation and reconfigures the frequency band. In one mode of the switch., the antenna operates at 2.4 GHz band for WiFi., Bluetooth or Zigbee applications., and in the other mode., it operates at 3.5 GHz band for 5G communications. The antenna achieved 1.58 dBi gain at 3.5GHz.
    • 3D Printed Antenna-on-Package with Near-isotropic Radiation Pattern for IoT (WiFi Based) Applications

      Su, Zhen; Klionovski, Kirill; Bilal, Rana Mohammad; Shamim, Atif (2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, IEEE, 2019-01-24) [Conference Paper]
      Futuristic IoT applications demand antenna designs to fulfill a number of challenging performance metrics. The antennas for such applications must be small to be easily integrate-able with miniaturized devices, have near-isotropic radiation pattern to be able to communicate in an orientation insensitive way, provide sufficient bandwidth (4% for 2.4 GHz WiFi)requisite of concerned communication protocol and be low cost enough to be implemented in billions of devices. Also, as these antennas integrate with the devices in very small spaces, so the effect of components (such as battery, chips etc.)also require consideration in design. This paper presents for the first time, a WiFi 2.4GHz near-isotropic T -shaped monopole antenna additively manufactured on the package. The antenna is designed whilst taking battery and WiFi chip effect into consideration. The maximum gain is 1.78 dBi with a gain deviation of 6.84 dB. The VSRW=2 bandwidth is achieved from 2.4 to 2.7 GHz.
    • Mining top-k Popular Datasets via a Deep Generative Model

      Akujuobi, Uchenna Thankgod; Sun, Ke; Zhang, Xiangliang (2018 IEEE International Conference on Big Data (Big Data), IEEE, 2019-01-25) [Conference Paper]
      Finding popular datasets to work on is essential for data-driven research domains. In this paper, we focus on the problem of extracting top-k popular datasets that have been used in data mining, machine learning, and artificial intelligence fields. We solve this problem on an attributed citation network, which includes node content information (text of published papers) and paper citation relations. By formulating the problem as a semi-supervised multi-label classification one, we develop an efficient deep generative model for learning from both the document content and citation relations. The evaluation on a real-world dataset shows that our proposed model outperforms baseline methods. We then apply the model further to reveal the top-k frequently cited datasets in selected areas and report interesting findings.
    • Spatio-Temporal Attention based Recurrent Neural Network for Next Location Prediction

      Altaf, Basmah; Yu, Lu; Zhang, Xiangliang (2018 IEEE International Conference on Big Data (Big Data), IEEE, 2019-01-25) [Conference Paper]
      With the advances in technology and smart devices, more and more attention has been paid to model spatial correlations, temporal dynamics, and friendship influence over point-of-interest (POI) checkins. Besides directly capturing general user's checkin behavior, existing works mostly highlight the intrinsic feature of POIs, i.e., spatial and temporal dependency. Among them, the family of methods based on Markov chain can capture the instance-level interaction between a pair of POI checkins, while recurrent neural network (RNN) based approaches (state-of-the-art) can deal with flexible length of checkin sequence. However, the former is not good at capturing high-order POI transition dependency, and the latter cannot distinguish the exact contribution of each POI in a historical checkin sequence. Moreover, in recurrent neural networks, local and global information is propagated along the sequence through one bottleneck i.e., hidden states only.In this work, we design a novel model to enforce contextual constraints on sequential data by designing a spatial and temporal attention mechanisms over recurrent neural network that leverages the importance of POIs visited by users in given time interval and geographical distance in successive checkins. Attention mechanism helps us to learn which POIs bounded by time difference and spatial distance in user checkin history are important for the prediction of next POI. Moreover, we also consider periodicity and friendship influence in our model design. Experimental results on two real location based social networks Gowalla, and BrightKite show that our proposed method outperforms the existing state-of-the-art deep neural network methods for next POI prediction and understanding user transition behavior. We also analyze the sensitivity of parameters including context window for capturing sequential effect, temporal context window for estimating temporal attention and spatial context window for estimating spatial attention respectively.
    • Application of High Performance Asynchronous Acoustic Wave Equation Stencil Solver into a Land Survey

      Abdelkhalak, Rached; Akbudak, Kadir; Etienne, Vincent; Ltaief, Hatem; Tonellot, Thierry; Keyes, David E. (SPE Middle East Oil and Gas Show and Conference, Society of Petroleum Engineers, 2019-03-13) [Conference Paper]
      This paper describes the application of high performance asynchronous stencil computations for 3D acoustic modeling on a synthetic land survey. Using the Finite-Difference Time-Domain (FDTD) method, a parallel Multicore Wavefront Diamond-tiling (MWD) stencil kernel (Malas et al. 2015, Malas et al. 2017) drives the high performance execution using temporal blocking to maximize data locality, while reducing the expensive horizontal data movement. As absorbing boundary conditions, we use Convolutional Perfectly Matched Layer (CPML), which have to be redesigned to not interrupt the asynchronous execution flow engendered by the MWD stencil kernel for the inner-domain points. The main idea consists in weakening the data dependencies by moving the CPML computations into the inner-computational loop of the MWD stencil kernel (Akbudak et al. 2019). In addition to handling the absorbing boundary conditions, applying the asynchronous MWD with CPML kernels to a realistic land survey requires the extraction of the wavefield value at each receiver position. We revisit the default extraction process and make it also compliant with the overall asynchrony of the 3D acoustic modeling. We report performance improvement up to 24% against the standard spatial blocking algorithm on Intel multicore chips using the synthetic land survey, which is representative of an area of interest in Saudi Arabia. While these results concur with previous performance campaign assessment, we can actually produce and assess the resulting 3D shot gather accuracy. To our knowledge, this is the first time the effectiveness of asynchronous MWD stencil kernel with CPML absorbing boundary conditions is demonstrated in an industrial seismic application.
    • Enhancing the Near-Surface Image Using Duplex-Wave Reverse Time Migration

      Sindi, Ghada; Alkhalifah, Tariq Ali; Fei, Tong; Luo, Yi (SPE Middle East Oil and Gas Show and Conference, Society of Petroleum Engineers, 2019-03-13) [Conference Paper]
      Reverse time migration (RTM) involves zero-lag cross-correlation of forward extrapolated source function wavefields and backward extrapolated receiver wavefields. For a near surface with complex structures and velocity anomalies, forward propagating the source wavelet generates wavefields containing reflections, near-surface multiples, and scattered direct arrivals. The wavefields are recorded as upgoing arrivals contaminated by the same reflections, near-surface multiples, and scattered signals, which can be critical for imaging near-surface structures and scatterers. Here, we develop a new depth migration, duplex reverse time migration (DRTM) technique to improve imaging of complex near-surface structures. DRTM uses the direct arrival as a source to forward propagate and generate source wavefields, and reversely extrapolated recorded data in a zero-lag cross-correlation imaging condition to generate the final section. The interaction between the data components during cross- correlation can use primaries and multiples to image the near-surface structure correctly. Cross-talk artifacts may exist, but they are comparatively weak. DRTM is demonstrated on both synthetic and field data examples showing an enhanced image in areas with complex near-surface structures compared to conventional RTM imaging methods. The new algorithm can significantly enhance shallow imaging without additional computation costs compared with conventional RTM. It can produce an image with higher resolution and signal-to-noise (S/N) ratio by replacing the source wavelet with the recorded direct arrivals, which include near-surface information necessary to boost the image in areas with near-surface complexity. Since the direct arrivals are one of the most energetic events recorded, the resultant image is typically of high S/N. The wave can also illuminate shallow zones better than primaries in marine environments.
    • Detecting cyber-attacks using a CRPS-based monitoring approach

      Harrou, Fouzi; Bouyeddou, Benamar; Sun, Ying; Kadri, Benamar (2018 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2019-02-28) [Conference Paper]
      Cyber-attacks can seriously affect the security of computers and network systems. Thus, developing an efficient anomaly detection mechanism is crucial for information protection and cyber security. To accurately detect TCP SYN flood attacks, two statistical schemes based on the continuous ranked probability score (CRPS) metric have been designed in this paper. Specifically, by integrating the CRPS measure with two conventional charts, Shewhart and the exponentially weighted moving average (EWMA) charts, novel anomaly detection strategies were developed: CRPS-Shewhart and CRPS-EWMA. The efficiency of the proposed methods has been verified using the 1999 DARPA intrusion detection evaluation datasets.
    • Monitoring land-cover changes by combining a detection step with a classification step

      Harrou, Fouzi; Zerrouki, Nabil; Sun, Ying; Hocini, Lotfi (2018 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2019-02-28) [Conference Paper]
      An approach merging the HotellingT 2 control scheme with weighted random forest classifier is proposed and used in the context of detecting land cover changes via remote sensing and radiometric measurements. HotellingT 2 procedure is introduced to identify features corresponding to changed areas. However, T 2 scheme is not able to separate real from false changes. To tackle this limitation, the weighted random forest algorithm, which is an efficient classification technique for unbalanced problems, has been successfully applied on features of the detected pixels to recognize the type of change. The performance of the algorithm is evaluated using SZTAKI AirChange benchmark data, results show that the proposed detection scheme succeeds to appropriately identify changes to land cover. Also, we compared the proposed approach to that of the conventional algorithms (i.e., neural network, random forest, support vector machine and k-nearest neighbors) and found improved performance.
    • Resource Allocation and Cluster Formation for Imperfect NOMA in DL/UL Decoupled HetNets

      Celik, Abdulkadir; Radaydeh, Redha Mahmoud Mesleh; Al-Qahtani, Fawaz S.; El-Malek, Ahmed H.Abd; Alouini, Mohamed-Slim (2017 IEEE Globecom Workshops (GC Wkshps), IEEE, 2018-01-25) [Conference Paper]
      Being capable of serving multiple users with the same radio resource, non-orthogonal multiple access (NOMA) can provide desirable performance enhancements in a fair and spectral efficient manner. In this paper, we investigate the resource allocation (RA) and cluster formation (CF) aspects of NOMA for downlink (DL) uplink (UL) decoupled (DUDe) heterogeneous networks (HetNets). A non-ideal NOMA scheme is considered with power disparity and sensitivity constraints (PDSCs), delay tolerance, and residual interference after cancellation. Taking the PDSCs into account, we analytically show that using the DL decoding order limits UL-NOMA performance by that of OMA, while employing an inverse order result in a performance gain that is mainly determined by the channel gain disparity of users. Thereafter, a generic CF method is proposed for any type of user graph, which iteratively forms clusters using Blossom algorithm. Finally, highly non-convex RA problem is converted into a convex form by employing geometric programming (GP) where power and bandwidth are optimized to maximize network sumrate and max-min fairness objectives.
    • Towards Early Detection of Red Palm Weevil Using Optical Fiber Distributed Acoustic Sensor

      Mao, Yuan; Ashry, Islam; Ng, Tien Khee; Ooi, Boon S. (Optical Fiber Communication Conference (OFC) 2019, OSA, 2019-02-25) [Conference Paper]
      Red palm weevil (RPW) is a severe danger to the dates farming. We use optical fiber distributed acoustic sensor (DAS) as a solution to the detection of RPW via sensing the RPW activities sound.
    • Numerical Modeling of Graphene Nano-Ribbon by DGTD Taking into Account the Spatial Dispersion Effects

      Li, Ping; Jiang, L. J.; Bagci, Hakan (2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama), IEEE, 2019-02-28) [Conference Paper]
      It is well known that graphene demonstrates spatial dispersion properties [1]-[3], i.e., its conductivity is nonlocal and a function of spectral wave number (momentum operator) q. In this work, to fully account for effects of spatial dispersion on transmission of high speed signals along graphene nano-ribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically-thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) [4] incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time domain SIBC model cannot be derived. To overcome this problem, the conductivity is approximated by its Taylor series in spectral domain under low-q assumption. This approach permits expressing the time domain SIBC in the form of a second-order partial differential equation (PDE) in current density and electric field intensity. To permit easy incorporation of this PDE with the DGTD algorithm, three auxiliary variables, which degenerate the second-order (temporal and spatial) differential operators to first-order ones, are introduced. Regarding to the temporal dispersion effects, the auxiliary differential equation (ADE) method [4] is utilized to eliminates the expensive temporal convolutions. To demonstrate the applicability of the proposed scheme, numerical results, which involve characterization of spatial dispersion effects on the transfer impedance matrix of GNR interconnects, will be presented.
    • Multi-stack Chirped InAs/InP Quantum-dash Structure as a Tunable Laser

      Alkhazraji, E.; Alias, Mohd Sharizal; Khan, Mohammed Zahed Mustafa (2018 Asia Communications and Photonics Conference (ACP), IEEE, 2019-01-18) [Conference Paper]
      Two-sectioned quantum dash laser is demonstrated as a monolithic, continuously electrically tunable source. Altering negative (positive) bias voltage on the absorber section showed a 4.2-nm blue-shift (4.5-nm red-shift) with a total broadband tunability of 8.7-nm.
    • Mathematical Modelling of Phenotypic Selection Within Solid Tumours

      Chaplain, Mark A. J.; Lorenzi, Tommaso; LORZ, ALEXANDER; Venkataraman, Chandrasekhar (Numerical Mathematics and Advanced Applications ENUMATH 2017, Springer International Publishing, 2019-01-05) [Conference Paper]
      We present a space- and phenotype-structured model of selection dynamics between cancer cells within a solid tumour. In the framework of this model, we combine formal analyses with numerical simulations to investigate in silico the role played by the spatial distribution of oxygen and therapeutic agents in mediating phenotypic selection of cancer cells. Numerical simulations are performed on the 3D geometry of an in vivo human hepatic tumour, which was imaged using computerised tomography. Our modelling extends our previous work in the area through the inclusion of multiple therapeutic agents, one that is cytostatic, whilst the other is cytotoxic. In agreement with our previous work, the results show that spatial inhomogeneities in oxygen and therapeutic agent concentrations, which emerge spontaneously in solid tumours, can promote the creation of distinct local niches and lead to the selection of different phenotypic variants within the same tumour. A novel conclusion we infer from the simulations and analysis is that, for the same total dose, therapeutic protocols based on a combination of cytotoxic and cytostatic agents can be more effective than therapeutic protocols relying solely on cytotoxic agents in reducing the number of viable cancer cells.
    • Imperfect D2D Association in Spectrum-Shared Cellular Networks under Interference and Transmit Power Constraints

      Radaydeh, Redha Mahmoud Mesleh; Al-Qahtani, Fawaz; Celik, Abdulkadir; Qaraqe, Khalid A.; Alouini, Mohamed-Slim (2018 IEEE International Conference on Communications Workshops (ICC Workshops), IEEE, 2018-07-05) [Conference Paper]
      This paper presents generalized modeling and analysis of the impact of imperfect device-to-device (D2D) association for direct D2D communication in spectrum-shared downlink cellular networks. It also addresses practical interference and energy constraints that are imposed on the underlying D2D communication network. Specifically, new decentralized schemes to identify and then establish point-to- point D2D communication links between well-identified groups of active devices when downlink cellular resources can be accessed by the underlying D2D network are proposed. Through the analysis, detailed characterization of devices that can serve others are first presented, wherein each of which is required to meet a specific transmit power constraint it can dedicate to serve others. Then, the downlink resources (i.e., physical channels) that can be used by serving devices to serve others via D2D communication links are identified cooperatively in the D2D network, while meeting an interference constraint per channel as imposed by the primary cellular network. The analysis then proceeds to analyze the proposed D2D association, which aims to simultaneously improve the desired link quality while minimizing the effect of interference at each served device, considering various practical but imperfect operating scenarios. Numerical results are presented to clarify some of the main outcomes of this work.
    • Power-dependent photoluminescence in strained In<inf>x</inf>Ga<inf>1−x</inf>N/GaN multiple-quantum wells: Simulations of alloying and interface-specific effects

      Tit, Nacir; Mishra, Pawan; Ng, Tien Khee; Ooi, Boon S. (2018 5th International Conference on Renewable Energy: Generation and Applications (ICREGA), IEEE, 2018-04-18) [Conference Paper]
      Combined experimental and theoretical efforts are focused to study hexagonal InGaN/GaN[0001] multiple-quantum wells (MQWs). Plasma-assisted molecular-beam epitaxy (PA-MBE) is used to grow high-quality MQWs with multiplicity of 1, 3 and 5. Characterizations methods based on scanning tunneling electron microscopy (STEM) and photoluminescence (PL) indicated that each period is composed of 10 nm GaN barrier and 2.5 nm InGaN well with x ≤ 0.12. Usually, these MQWs have radiations with the blue region. However, in power (from 0.008 mW to 8 mW) dependent micro-photoluminescence (PL), measured at room temperature, blue shifts of about 11.11 nm, 11.94 nm and 14.94 nm were observed corresponding to the single-quantum well (1-QW), 3-MQW, and 5-MQW, respectively. While in literature such shift is speculated to be attributed to so-called
    • Mobile user association for heterogeneous networks using optimal transport theory

      Ghazzai, Hakim; Tembine, Hamidou; Alouini, Mohamed-Slim (2017 Sixth International Conference on Communications and Networking (ComNet), IEEE, 2018-02-12) [Conference Paper]
      This paper investigates the mobile user association problem for heterogeneous networks. More specifically, it applies the optimal transport (OT) concept to determine the cells corresponding to each base station (BS) that minimize the total transmit power consumption of orthogonal frequency-division multiple access (OFDMA) cellular networks. This is performed by respecting the network quality of service and by taking into account the resource limitation per BS (e.g., power budget and number of resource blocks). Starting from given BS locations and user distributions, a fixed point algorithm is employed to find the optimal solution for the formulated problem. Selected numerical results investigate various practical scenarios with different user distributions and show that the cell boundaries obtained using OT solution provide a significant energy saving compared to the classical Voronoi cell boundaries.
    • Delay analysis of new-flow setup time in software defined networks

      Alghadhban, Amer Mohammad JarAlla; Shihada, Basem (NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, IEEE, 2018-07-09) [Conference Paper]
      Software Defined Networking (SDN) provides network engineers with a high-level of abstraction to manage network traffic and control the associated network resources. Unfortunately, the data-plane devices communicate with the controller for every new flow, which adds an extra overhead and causes excessive delays. Such communication relies on the probability called matching probability. In this work, we propose a mathematical model for the SDN flow-setup process with the consideration of all factors that contribute into the matching probability, such as proactive/reactive flow setup modes. Finally, we attempt at deriving the overall system capacity and blocking probability.
    • DNA Profiling Methods and Tools: A Review

      Alamoudi, Emad; Mehmood, Rashid; Albeshri, Aiiad; Gojobori, Takashi (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer International Publishing, 2018-07-21) [Conference Paper]
      DNA typing or profiling is a widely used practice in various forensic laboratories, used, for example, in sexual assault cases when the source of DNA mixture can combine different individuals such as the victim, the criminal, and the victim’s partner. DNA typing is considered one of the hardest problem in the forensic science domain, and it is an active area of research. The computational complexity of DNA typing increases significantly with the number of unknowns in the mixture. Different methods have been developed and implemented to address this problem. However, its computational complexity has been the major deterring factor holding its advancements and applications. In this paper, we review DNA profiling methods and tools with a particular focus on their computational performance and accuracy. Faster interpretations of DNA mixtures with a large number of unknowns and higher accuracies are expected to open up new frontiers for this area.
    • Quasi-1D High-Speed Raman/Filtered Rayleigh Scattering for Combustion Dynamics Applications

      Magnotti, Gaetano; Krishna, Yedhu (Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP), OSA, 2018-06-18) [Conference Paper]
      Raman/Rayleigh scattering is a powerful diagnostics technique to measure temperature, species and their gradients in non-sooting jet flames, but it is typically limited to repetition rates of 10 Hz or lower. Here we introduce a novel approach to extend sampling rates to 10 kHz and enable access to enclosed combustors, while maintaining accuracy and precision levels adequate to experimental datasets intended for validation of numerical combustion models.
    • Photo-induced THz Plasmonics in Black Silicon

      Peters, L.; Gongora, J.S. Totero; Tunesi, J.; Pasquazi, A.; Fratalocchi, Andrea; Peccianti, M. (Advanced Photonics 2018 (BGPP, IPR, NP, NOMA, Sensors, Networks, SPPCom, SOF), OSA, 2018-06-28) [Conference Paper]
      We experimentally investigated a novel form of photo-induced plasmonic response, in nanostructured silicon, at THz frequencies which can be employed to precisely control the full-wave properties, i.e. amplitude and phase, of the generated THz pulse.