Miracle-dz/UniFAR-FTUs huggingface dataset:
H1-Control of an Ensemble of Half-Spin Systems Replacing Rabi Pulses by Adiabatic Following

This work considers the control of an ensemble of non-interacting half-spin systems (Bloch equations) in a vertical static field B0 subject to a pair of controlled radiofrequency inputs (u1(t),u2(t)) acting on the horizontal plane. The state M(t,ω) ∈ S2 belongs to the Bloch sphere S2, and it is indexed by the Larmor frequency ω ∈ (ω∗,ω∗). Previous works have constructed a local stabilizing feedback based on a Lyapunov functional which is essentially a convenient H1-norm of a Sobolev space H1((ω∗,ω∗),S2) (see Beauchard, Pereira da Silva and Rouchon [3]-[4]). This feedback assures local L∞ convergence of the initial state M0(ω) to −e3. However, the control law of that paper is a sum of a (infinite dimensional) state feedback with a T-periodic comb of π-Rabi pulses (Dirac impulses). The present work shows that one may replace this comb of Dirac pulses by adiabatic pulses. It is shown in the paper that, if ${\left\| {{M_0}(\omega ) + {e_3}} \right\|_{{H^1}}}$ is small enough, our control strategy assures, for any ε > 0, the existence of a pair (T,ℓ) where T ∈ ℝ and ℓ ∈ N such that ${\left\| {M\left({\ell T,\cdot}\right) + {e_3}} \right\|_{{L^\infty }}} \leq \varepsilon $. Simulations has shown that this new strategy produces faster convergence than the one that is based on the comb of Rabi pulses. The new method seems to work well even for initial conditions such that ${\left\| {{M_0}(\omega ) + {e_3}} \right\|_{{H^1}}}$ is "relatively big".
Steganography in DNA Sequence on the Level of Amino acids

The increasing advancements in bioinformatics have recently attracted many pieces of research in the field of cryptography and steganography. We are proposing a steganographic algorithm that aims at preserving the properties of a DNA sequence (carrier) based on the distribution of DNA codons upon amino acids in the standard genetic code table. The algorithm hides a secret message inside a DNA sequence while preserving its biological properties and another algorithm extracts back the secret message using the secret key. The paper is considered a way to minimize the gap between DNA computing and Digital computing and proves this relation through applications. We have compared our algorithm to other related DNA-based steganographic algorithms and proved that our algorithm is robust, has advanced utilization storage and invulnerable to several types of possible attacks.
Compositional Semantics Network With Multi-Task Learning for Pun Location

A pun is always humorous and has strong interactive value in people’s daily communication. It creates a humorous effect in a certain context, in which a word implies two or more meanings by using polysemy (homographic pun) or phonological similarity to another word (heterographic pun). Pun location is a task to identify the pun word in a given text, which is of great significance to understand humorous texts. Existing methods generally adopt single long sequence structure but cannot well capture the rich semantics of pun words in sentences. We present an approach that considers long-distance and short-distance semantic relations between words simultaneously. For the long-distance semantic relation, we introduce multi-level embeddings to represent the most relevant aspects of the data. For the short-distance semantic relation, we exploit the complex-valued model with a self-adaptive selection mechanism based on multi-scale of input information. Meanwhile, we propose a new classification task to distinguish the homographic pun and heterographic pun. We introduce it as an auxiliary to jointly train the original pun location task, which first learns the location of different types of puns together. Experiment results show that the latest state-of-the-art results can be achieved through our model.
37,000 Human-Planned Robotic Grasps With Six Degrees of Freedom

Much recent work in grasp planning has focused on data-driven approaches, using deep learning to map from images to gripper configurations. However, this approach typically fails about once per ten attempts, limiting its practicality. We sought to better understand the degree to which such failures can be attributed to hardware versus control. To this end, we developed a naturalistic grasp demonstration system in which a gripper was fitted with a handle and moved by a human operator, while its trajectory was recorded with a motion tracker. The gripper's fingers were controlled with a joystick. We recorded roughly 37 K grasp demonstrations with this system. These grasps were almost always successful. In contrast with planar grasp planners that perform only top-down grasps by design, many of the human-planned grasps used a horizontal approach rather than a top-down approach. We analysed robustness of a subset of these human-planned grasps, and found that many were robust to gripper rotations of about $\pi /8$ radians and translations of 3 cm (depending on the object). Consistent with past work, human operators tended to align the gripper aperture with objects’ principal axes. We also tested robustness of grasps in which the gripper aperture was aligned exactly with the principal axes, and found that these heuristic grasps were even more robust than human-planned grasps. This suggests that humans used a partly symbolic grasp planning strategy, with somewhat imprecise control.
How Much Training Data is Enough? A Case Study for HTTP Anomaly-Based Intrusion Detection

Most anomaly-based intrusion detectors rely on models that learn from training datasets whose quality is crucial in their performance. Albeit the properties of suitable datasets have been formulated, the influence of the dataset size on the performance of the anomaly-based detector has received scarce attention so far. In this work, we investigate the optimal size of a training dataset. This size should be large enough so that training data is representative of normal behavior, but after that point, collecting more data may result in unnecessary waste of time and computational resources, not to mention an increased risk of overtraining. In this spirit, we provide a method to find out when the amount of data collected at the production environment is representative of normal behavior in the context of a detector of HTTP URI attacks based on 1-grammar. Our approach is founded on a set of indicators related to the statistical properties of the data. These indicators are periodically calculated during data collection, producing time series that stabilize when more training data is not expected to translate to better system performance, which indicates that data collection can be stopped. We present a case study with real-life datasets collected at the University of Seville (Spain) and a public dataset from the University of Saskatchewan. The application of our method to these datasets showed that more than 42% of one trace, and almost 20% of another were unnecessarily collected, thereby showing that our proposed method can be an efficient approach for collecting training data at the production environment.
Discrete-time Maximum Hands-Off Control with Minimum Switches

Maximum hands-off control provides energy-saving bang-off-bang control signals. However, it does not restrict the number of changes in the control signal. As the use of a control signal that has fewer adjustments is often preferred, this paper considers the problem of maximum hands-off control with minimum switches. For the class of discrete-time nonlinear control-affine systems, the problem is formulated as a sparse optimization based on the l0 norm, then relaxed to l1 norm optimization. For the special case of linear single-input single-output systems, some properties of l0 optimization and its l1 relaxation are discussed and we present an efficient numerical algorithm to solve l1 relaxation based on the proximal splitting method. A numerical example illustrates that the proposed formulation effectively reduces the number of switches.
Analyzing Two Stage CMOS LNA for Wireless Interconnect

Sooner or later the conventional interconnects used nowadays in high speed performance computing systems are going to put serious performance constraints. As the proportion of CMOS technology scaling and interconnect length scaling differs largely, the interconnect length poses drastic speed limitations on the systems. Hence as technology node scales from 14nm to 7nm shows high improvement on speed on paper but is barely achieved in reality compared to node scaling from 130nm to 90nm. As the speed of operation for HPC systems is in Gb/sec, the power consumption due to conventional interconnect will be higher. The solution to this problem is to use wireless interconnects. The wireless interconnect may be fabricated with on chip wireless transceiver. The on chip antenna and router based architecture may help in reducing those routing delays and also saving chip area. The first block in wireless receiver of wireless interconnect is Low Noise Amplifier (LNA), and this work focuses to design and analyse a CMOS LNA operating at 60 GHz, As most of the HPC systems operate at about 60 GHz. The designed LNA’s are compared on the basis of figure of merits.
On Trade-offs Between Computational Complexity and Accuracy of Electrochemistry-based Battery Models

In this paper, we propose several simplifications to the so-called Doyle-Fuller-Newman (DFN) model, which is a popular electrochemistry-based battery model. This simplified DFN (SDFN) model allows for a computationally very efficient implementation. The simplifications are a result of several assumptions, which will be justified for two different parameter sets. Finally, the SDFN model proposed is compared to the DFN model as well as an implementation of the single-particle model, for the two parameter sets. This will show that by making specific assumptions, simplifications can be made that have no significant impact on the model accuracy, while the computation time can be drastically decreased. This leads to a simulation time of over 3600 times faster than real-time.
Sliding Mode Control of Discrete-Time 2-D Roesser Systems Via Event-Based Scheme

This paper is concerned with the problem of sliding mode control (SMC) of discrete-time two-dimensional (2-D) systems in Roesser type via an event-triggered scheme. For the 2-D Roesser system, an event-triggered scheme (ETS) is first proposed, followed by introducing some linear sliding surface functions. It is shown that the introduced sliding surface functions are existent under some sufficient conditions thus derived. Furthermore, the reaching law approach is utilized to construct the event-triggered sliding mode controllers so as to force the state trajectories of the closed-loop 2-D system into a bounded region and keep them inside it thereafter. Computer simulation results illustrate the capableness of the proposed event-triggered SMC scheme for 2-D Roesser systems.
Constructive Interference based Co-operative NOMA Full Duplex Downlink System

Non-orthogonal multiple access (NOMA) is the promising candidate to improve the spectral efficiency and system throughput in fifth-generation (5G) mobile communication networks. In this paper, we consider a co-operative non-orthogonal multiple access (CR-NOMA) system with dual users. The user closer to the base station (BS) acts as a full-duplex (FD) relay to assist the information transmission to the cell edge user. Instead of mitigating self-interference in FD systems, we propose to use the knowledge of Data information (DI) and the channel state information (CSI) at the BS to exploit the self-interference constructively rather than to suppress it. For Constructive interference based (CI) FD NOMA system, we derive an exact analytical expression for the outage probability of both users and system throughput. Numerical results are carried out to investigate the proposed CI FD-NOMA system and compared with the state of art HD and FD NOMA scenarios. It is observed that the proposed system performs better than the conventional HD/FD NOMA system.
Particle Swarm Based Service Migration Scheme in the Edge Computing Environment

With the development of Mobile Edge Computing (MEC), it has become a key technology to realize the vision of the Internet of Things. In MEC, users can upload tasks to edge nodes for faster processing speed and lower local energy consumption. However, as the mobility of users and the limited resources of the edge nodes, some edge nodes cannot provide high-quality services. In this case, we study service migration strategy in the MEC system to migrate services from the initial nodes to other edge nodes that can provide services to meet the needs of users. By making service migration decision and allocating computation resource, our work minimizes the delay and the energy consumption caused by finishing tasks. Specifically, we set up an efficient service migration model and formulate the service migration problem as a non-linear 0-1 programming problem. To solve this problem, we design a Particle Swarm based Service Migration scheme (PSSM) which includes Queuing Delay Prediction algorithm (QDP), Delay-aware Computation Resource Allocation algorithm (DCRA), and Modified Quantum Particle Swarm algorithm (MQPS). For evaluating the performance of the proposed PSSM, we conduct simulation in a practical scenario. The results demonstrate that our scheme not only can effectively reduce delay and energy consumption, but also improve the processing capability of servers.
Vulnerability Mapping of Tsunami Inundation Hazard at The Tourism Area of Pangandaran, West Java

Indonesia is located in and surrounded by areas that have active plate movements, making its coastal and marine areas prone to tsunami, and creating negative impacts, such as damage to properties and increase in death rates. One of these areas is the coastal area in Pangandaran Regency, West Java. This study aimed to analyze the level of building vulnerability and impact of losses as a result of tsunami. The research method combined data of buildings that have been classified based on their type and uses with data of inundation caused by tsunami and coefficient of Damage Ratio. The study results showed that the type of buildings in the tourism area of Pangandaran Regency is dominated by 1-story permanent buildings (P1), in which 2,050 out of 3,103 buildings were identified as residences and businesses. In general, based on the coefficient of Damage Ratio in the tourism area of Pangandaran Regency, vulnerability level of buildings is within 51%–70%, which is considerably high and indicates that the buildings could suffer heavy damage if they are hit by tsunami. The tourism industry in the area lost 700 million rupiahs and fisheries industry lost 6.055 billion rupiahs due to the 2016 tsunami. Eight hotel/resort buildings have been recommended as temporary evacuation sites or shelter in the event of a tsunami.
Performance Analysis of IMC based PID Controller for a Twin Rotor MIMO System

Twin Rotor Multi Input Multi Output system has become more popular in the research community in view of designing new controllers for many real world systems such as aircraft and helicopter systems. However, because of the external disturbances, model uncertainties and inherent cross-coupling effects, designing a suitable controller for such system becomes a challenging task. In this paper, an Internal Model Control (IMC) based PID controller is designed for the TRMS with One degree of freedom (1-DOF). Its performance is compared with that of conventional PID and LQR-LMI based PID controller. From the obtained results, it is confirmed that IMC based PID controller exhibits superior performance than the other two PIDs, in terms of improved attitude angle tracking and disturbance rejection ability.
AI-Powered Image-Based Tomato Leaf Disease Detection

The development of Artificial Intelligence over few decades had been incredible, where it converts every segment of the global economy, including agriculture. The traditional approach of the agricultural industry is experiencing a vital revolution. With requiremesnts of better crop yield, AI has been developed as a powerful tool to permit farmers in monitoring and detecting the crop diseases. In addition, farmers can easily identify the crop diseases in early stage by using AI. As traditional plant disease identification includes expertise and high processing time, AI is integrated with image processing with an objective of providing accurate, fast, efficient and inexpensive solution for disease detection. In this paper, novel tomato leaf disease detection is proposed which comprises of four different phases that includes image preprocessing, segmentation, feature extraction and image classification. RGB to grayscale conversion, thresholding, GLCM and random forest classifier are the various algorithms that are used for implementation of the proposed method. The results indicate that the proposed method classifies the diseases with an accuracy of 94.1%.
Article Detection on the Web using DOM and text based features

Web pages are constantly getting flooded with dis-tractive content like ads, popups, etc. which take away the focus from the main article of the page. Compared to desktops, smartphones—whose usage for browsing online has been on a steep upward trend—have a smaller screen size thereby compounding the problem. To give the user a good browsing experience on phone and hence increase their engagement with the browser, it is imperative to provide a clutter-free experience to him. Existing techniques do this in two phases—phase one detects if there is an article on a given Web page and phase two proceeds to extract the article in order to display it, removing unwanted elements of the Web page. In this paper, we propose to use a random forest model for article detection in Web pages using DOM and text-based features. With this model, we were able to achieve a precision of 0.91 and a recall of 0.92 which beats the state of the art techniques which are being used by major Android browsers in the market today.
PAPR and Spectrum Analysis of 4G and 5G Techniques

GFDM is a method of wireless communication that produces ISMCI which will influence the performance of Symbol Error Rate when contrasted with an Orthogonal Frequency Division Multiplexing. In GFDM a single cyclic prefix (CP) is embedded for the whole block, but in case of OFDM cyclic prefix embedded for each transmitted symbol. It will boost the system spectral efficiency. Additionally, in Wavelet based GFDM, there is no need of cyclic prefix, that will further boost up the efficiency of spectrum. GFDM is better technique because it has low PAPR, which helps in low power consumption. Power spectral density (PSD) of GFDM is less this shows GFDM provides lesser leakage of energy on the side lobes which helps in reduction of OOB radiation. Wavelet based GFDM is good method for the needs of future wireless communication. Meyer wavelet has overall better spectral efficiency and low PAPR as compared to other techniques.
Design and Analysis of Improved IGBT with Embedded p+ in N-Buffer Layer

In this paper, the superjunction IGBT with embedded p+ in N-Buffer layer is proposed along with the gate engineering technique. The hybrid p+ section in N-Buffer layer, provides extra injection of the minority charge carriers in the drift region in order to modulate collector current density (JC). This enhancement in JC is further improved by the thin gate oxide near n-source region, results in enhanced electric field and hence improving the conductivity. 11% improvement in JC is observed for proposed device with respect to the conventional one hence reducing specific ON-resistance by 10%. In addition to this, broad oxide layer is also provided at the bottom side of the gate, which reduces the extra charge carrier accumulation closed to bottom gate surface and helps the proposed device to turn-off quickly. The improved turn-off time and delay time minimizes the energy losses (Eoff , Eon) of the proposed device. The reduction in Eoff and Eon is obtained as 33.23% and 35.42%, respectively, at 1.36V of on-state voltage drop (Von). Additionally, proposed device also shows the improvement in Baliga’s Figure of merit (BFOM) and industrial FOM (FOM1) by 13% and 115% as compared to conventional device.
Research of Dual-band Dual Circularly Polarized Wide-angle Scanning Phased Array

A dual-band dual circularly polarized wide-angle scanning array, operational in the K/Ka bands is presented. A stacked-patch element, which is excited by two ports to provide left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP) for TX and RX, respectively, is connected with active modules as part of a co-aperture phased array system. A sub-array composed of 2×2 sequentially rotated elements is designed to improve array's polarization purity and symmetry of radiation pattern. A 36-element (3×3 subarray) array prototype has been fabricated, which measured results exhibits good agreements with simulations. The circularly polarized bandwidths of the array are 7.8% at frequency point in first band and 5.3% at frequency point in second band, respectively. A maximum of 60° wide-angle scanning is also achieved at Dual-band frequency bands.
Incidence and determinants of change of initial HAART regimen among outpatient HIV infected adults at the University of Teaching Hospital in Lusaka, Zambia

Introduction: Durability of the first highly active antiretroviral therapy (HAART) regimen is a major key to long term access, scalability and sustainability of an HIV treatment program. It is important to know the incidence rate of initial HAART regimen change, the reasons and factors associated with change of the initial HAART regimen in Zambia. This study was designed to determine the incidence rate and factors associated with change of initial HAART regimen at the University Teaching Hospital (UTH) from 1st January 2008 to 31st December 2011. Methodology: This research was a hospital based retrospective cohort study of adult HIV/AIDS patients who were initiated on HAART from 1st January 2008 to 31st December 2011 at UTH adult outpatients ART clinic. Medical charts were reviewed for demographic information, change or no change of initial HAART regimen, type of initial HAART regimen, date of initiation, date of change, and reasons or factors of change. The incidence rate of change of initial HAART regimen was calculated. We assessed characteristics of patients who changed their initial HAART regimen and reasons for change. Cox proportional hazard models were performed to analyze factors associated with change of initial HAART regimen. Results: Incidence rate of change and factors associated with change of initial HAART regimen was obtained from 341 medical charts. 154/341 (45.2%) of patients had their initial HAART regimen changed. The incidence rate of change was 17.5 per 100 person-years. The proportion of change due to treatment failure was 1.8%. The most common reasons for change of initial HAART regimen were drug unavailability (stocks out and drugs cost) 46.1%, non-adherence 19% and renal toxicity 5.2%. The type of initial HAART regimen was significantly associated with change of initial HAART regimen. Conclusions: It is important to evaluate reason-specific trends in the incidence of change of initial HAART regimen in order to better understand the determinants of changes. Given the findings that drug unavailability was responsible for nearly half of all changes of initial HAART regimens, better health systems need to be implemented to ensure steady supply of drugs to patients. Also there is a need for research that helps to develop better screening modalities for renal toxicity, considering that tenofovir is part of the recommended first line regimen in Zambia.