Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Complexity Beam Training for 5G Millimeter-Wave Massive MIMO Systems

We consider a 5G millimeter-wave (mmWave) massive MIMO system with subconnected hybrid structure, where each transceiver unit (TXRU) is connected to a subarray at the transmitter (TX) or the receiver (RX). Beam training is the first step for codebook-based beamforming in the absence of ideal channel state information (CSI). The complexity of the optimal exhaustive search beam training is exponentially increased with the number of TXRUs (or subarrays) at the TX and the RX, which is infeasible in practice. The conventional beam training schemes are mainly based on the idea of mathematical search algorithms and novel beam codebook designs. In this study, we explore a novel low-complexity beam training scheme by fully exploiting the sparse nature of the mmWave channel and the strong correlations of large-scale antenna arrays. Specifically, we propose a training scheme to reduce beam search space for 5G mmWave system, which consists of the following two key stages: 1) a beam subset optimization method from the perspective of array gain for capturing the energy of dominant channel propagation paths, and 2) a class of linear iterative beam search algorithms within the optimized beam subset utilizing the idea of limiting the degrees of freedom of the subarray indices during beam training. The range of the optimized beam subset size and linear search condition are also given. The performances of the proposed two algorithms, beam subset optimization-single subarray linear search and beam subset optimization-subarray pair linear search, are evaluated in a 5G mmWave system. Analysis has shown that the complexity of the proposed scheme is linear with the number of channel propagation paths, which can considerably reduce the complexity of conventional schemes. Simulation results have verified the near-optimal performance of the proposed schemes when compared with exhaustive search as well as other existing training methods.
Applying Deep Neural Networks (DNN) for Measuring Photometric Redshifts from Galaxy Images: Preliminary Study

In the cosmological and extragalactic study, distance to a galaxy is an important parameter, by knowing the distance, we can find any other physical parameter such as mass, luminosity, star formation rate, and metallicity. By applying the specific cosmological model, we can measure a distance from the redshift. The exact redshift can only measure by using the spectroscopic technique (Doppler effect), but spectroscopic observation limited to brighter objects and numbers of objects in a single field of view (FoV). While photometric observation can capture fainter objects and more objects in a single FoV. Measurements of photometric redshift could have done by comparing the SED curves of the elliptical galaxy with known spectroscopic redshifts from other elliptical galaxies which we want to find the photometric redshift. Another method is to do linear or non-linear regression, by assuming the redshift is a function of magnitude in each band-pass filter. Therefore, we propose a technique that using full galaxy images in each measured bands and machine learning method for measuring photometric redshift. We pass entire multi-band galaxy images into the machine learning architecture to get an estimated redshift. In this work, we use galaxies images at 0 ≤ z ≤ 1 from SDSS DR 10 as the datasets and we use DenseNet, one of the Deep Neural Networks (DNN) architecture.
The CrossSong Puzzle: Developing a Logic Puzzle for Musical Thinking

There is considerable interest in music-based games and apps. However, in existing games, music generally serves as an accompaniment or as a reward for progress. We set out to design a game where paying attention to the music would be essential to making deductions and solving the puzzle. The result is the CrossSong Puzzle, a novel type of music-based logic puzzle that integrates musical and logical reasoning. The game presents a player with a grid of tiles, each representing a mash-up of excerpts from two different songs. The goal is to rearrange the tiles so that each row and column plays a continuous musical excerpt. To create puzzles, we implemented an algorithm to automatically identify a set of song fragments to fill a grid such that each tile contains an acceptable mash-up. We present several optimisations to speed up the search for high-quality grids. We also discuss the iterative design of the game’s interface and present the results of a user evaluation of the final design. Finally, we present some insights learned from the experience which we believe are important to developing music-based puzzle games that are entertaining, feasible and that challenge one’s ability to think about music.
High-frequency electroporation for cancer therapy

The present invention relates to the field of biomedical engineering and medical treatment of diseases and disorders. Methods, devices, and systems for in vivo treatment of cell proliferative disorders are provided. In embodiments, the methods comprise the delivery of high-frequency bursts of bipolar pulses to achieve the desired modality of cell death. More specifically, embodiments of the invention relate to a device and method for destroying aberrant cells, including tumor tissues, using high-frequency, bipolar electrical pulses having a burst width on the order of microseconds and duration of single polarity on the microsecond to nanosecond scale. In embodiments, the methods rely on conventional electroporation with adjuvant drugs or irreversible electroporation to cause cell death in treated tumors. The invention can be used to treat solid tumors, such as brain tumors.
Let us complete the puzzle together: a jigsaw cooperative learning trial on optical graduate course

Traditional lectures do hardly satisfy or benefit all of graduate students because of their diversity background, which might lead to inactive in the class, especially when the courses are professionally concentrated. Jigsaw cooperative learning (JCL), a student-centered learning method which engages all students and is beneficial in facilitating relationship-building, might be an alternative solution. A trial was made in an optical course “Optical Interferometric Measurement (OIM)”. However, the first trial we made is hardly counted as success. After thorough analysis on all factors that might cause the frustration, a new course plan is formed detailed. In this paper, we would like share our trials made in the course, both the unsuccessful one and the one work in progress.
Software Defined Networks Security: Link Failure Analysis in SDN

SDN is the new network technology. Although SDN still new, it is inseparable from the issue of a link failure. By using SDN, link failure scenario can be simulated and collection of data can be analysed. Before creating link failure scenario, several topologies were needed to show similarities with traditional network. There are many topologies that can be created by using SDN because SDN already provide virtual network devices. Each network device will be build inside virtual network topology. With use of desired topology then link failure scenario can be implemented. SDN also need a controller that acts a “brain” to the network. The controller will be provide a routing algorithm to control the behaviour of the network when one or more links become fail to connect with host or controller. One of suitable controller was Ryu which can adapt to any traffic handler and already provide application resemble to network behavior. All software components will be simulated inside Mininet emulator, one of realistic virtual network application.
Does artificial intelligence have any role in healthcare in low resource settings?

Artificial intelligence (AI) has revolutionized healthcare in the past few decades (1). Initially being used solely as a medical decision support system, it is anticipated that AI has a potential role in personalized medicine, patient monitoring and improve health service delivery and management (2). AI has penetrated the health care domain rapidly in high income settings where an estimated USD 150 million could be saved with such applications in the next 5 years (3). However, there is limited literature available on its use in low resource settings.
Performance Evaluation of SEPIC Based Single-Phase Seven-Level Inverter for Renewable Applications

Contemporary research in multilevel inverters (MLIs) is becoming famous for low power renewable applications. In this paper, therefore, a new configuration of SEPIC based single-phase seven-level inverter is presented with the advantages of lower parts count, size, and reduced cost. The front-end sepic inverter is used to boost the input voltage to the desired voltage and cascaded with a 1:2 multi-winding high-frequency transformer to generate V dc and 2V dc which is fed to the asymmetrical six switch multilevel inverter. The simulation work is carried out in Matlab/Simulink environment, and a laboratory prototype model is developed to validate the concept. The control pulses for the SEPIC inverter is built using TMS3202812 DSP in real time workshop(RTW), and the switching pulses for MLI are generated using a Spartan-6 FPGA Processor. The performance of the proposed topology evolved for the step change in input voltages, and the different loading conditions. A detailed comparison of various seven-level inverter topologies is also conducted.
A green approach for silver nanoparticles preparation by cell-free extract from Trichoderma reesei fungi and their characterization

Silver nanoparticles (AgNPs) exhibit unique optical, photochemical, electronic, photoelectrochemical properties and they are non-toxic to the mammalian cells at low concentrations. The biosynthesis of AgNPs is a green alternative to chemical and physical methods. The use of fungi is more efficient compared to other bio-alternatives because of the possibility for easy cultivation on a large scale and simple biomass harvesting. Trichoderma reesei fungi produce extracellular enzymes that can reduce silver ions (Ag+) to AgNPs. The present study describes an extracellular biosynthesis of AgNPs from AgNO3 solution by using cell-free water extract (CFE) of T reesei PF biomass. The impact of the components of the medium where the T. reesei PF were cultivated, the amount of biomass used for obtaining the CFE, the initial concentration of AgNO3 solution and the time for Ag+ reduction to AgNPs have been studied. It has been found that for all studied cultivation media the amount of biotransformed Ag+ increases with time and with the initial concentration of AgNO3. The higher amount of extracted wet biomass (i.e. the higher concentration of extracted metabolites) leads to a higher biotransformation of Ag+ to Ago. Having in mind the quantitative data from the ICP analysis of isolated and washed AgNPs produced at various experimental conditions, it could be concluded that the optimum formation of AgNPs was achieved when T reesei fungi were cultivated in media containing 0.1% corn steep liquor, 10% biomass extracted to obtain CFE and 10 mM concentration of the AgNO3 precursor was used. The formation of AgNPs was proved by XPS and TEM analysis. The HRTEM micrographs confirmed Ag metallic nanoparticles in crystal phase. The TEM images showed initial formation of AgNPs clusters with size 1–4 nm that increase further up to 15–25 nm. The NPs were stabilized by capping effect of the biomolecules, as the FTIR spectroscopy revealed. The small size, the particles’ narrow size distribution, nontoxicity, stability and the negative zeta potential which could facilitate attachment of biologically active substances render the produced AgNPs into suitable carriers of such substances.
A Framework for Turning Behavior Classification at Intersections Using 3D LIDAR

Turning behavior classification of oncoming vehicles is a critical step toward high-level scene understanding and motion planning tasks for autonomous vehicles. In this paper, we propose a new method for classifying an oncoming vehicle's turning behavior at intersection using 3D LIDAR, i.e., a Velodyne HDL-64E LIDAR, which collects rich point clouds from the surrounding environment. First, the vehicle pose is measured via a novel rectangle-based multi-frame fitting method applied to the vehicle point cloud extracted by a data pre-process procedure. Then, a Kalman filter integrates these measured vehicle poses to estimate and update vehicle kinematic parameters. Next, a hidden Markov model and Bayesian filtering are combined to recognize the vehicle's turning behavior using the heading angle and the acceleration components of the kinematic model. Real point clouds from intersection environments are used to train and validate the proposed turning behavior classification algorithm in the experiments. The results of the performance analysis and classification time measurements confirm that the proposed method can recognize the behavior of the oncoming vehicle at intersections correctly at an early stage of entering an intersection.
Throughput Enhancement for Dual-Function Radar-Embedded Communications Using Two Generalized Sidelobe Cancellers

In this paper, we develop a novel approach for a joint platform of radar and communication systems. The previous approaches for dual-function radar-communication systems focused only on the simultaneous transmission of radar and communications in radar active mode. To increase the throughput of communications without affecting the radar operation, we enable communication during the whole pulse repetition interval by using two generalized sidelobe cancellers. We propose two different operational modes of the dual-function radar-communications system. In active mode, the radar function is achieved through the mainlobe, and communications are achieved through the sidelobes. In active mode, only one generalized sidelobe canceller is functional. In rest mode, both the generalized sidelobe cancellers are functional. The first generalized sidelobe canceller has the mainlobe and sidelobe levels as in active mode, and the second generalized sidelobe canceller has the same mainlobe level but double the power in the sidelobes. The output is the difference between the two, in which the mainlobe is canceled, while the sidelobes have the same power, as in the case of active mode. The effectiveness of the proposed scheme is investigated in terms of the bit error rate. Moreover, the proposed system allows communication during the whole pulse repetition interval, thus, enhancing the throughput tremendously.
SeC‐SDWSN: Secure cluster‐based SDWSN environment for QoS guaranteed routing in three‐tier architecture

Software defined wireless sensor network (SDWSN) is a recent evolution in networking that improves network performance and scalability. However, Quality of Service (QoS) and security are major the issues in SDWSN due to inefficient route selection (traffic load minimization algorithm) and insecure cryptography scheme (homomorphic algorithm). This paper proposes novel three‐tier architecture for secure cluster‐based SDWSN (SeC‐SDWSN) environment to ensure QoS and security for WSN using SDN. In the first tier, sensor nodes are segregated into multiple clusters by secure hash tree‐based clustering (SHTC) algorithm. Within each secure cluster, data transmission is performed through optimal route selected by adaptive spider monkey optimization (ASMO) algorithm in which two new fitness factors (F1, F2) are formulated by multiple QoS metrics. For data security, parallel advanced encryption standard with cipher block chaining (PAES‐CBC) algorithm is proposed. Aggregated ciphertext is transmitted to optimal switch in the second tier by using fuzzy weighted technique for order preference by similarity to ideal solution (FW‐TOPSIS) algorithm according to selection criteria. Switches forward the data to sink node based on flow rules deployed by SDN controllers in the third tier. SDN controllers provide global view on the entire network and deploy flow rules on switches in accordance to network status and security level. Extensive simulation in ns‐3 shows that the proposed three‐tier architecture achieves 5% throughput improvement, 7.8% PDR improvement, and 16% energy consumption improvement.
Local-remote transparency framework for passing mutable objects to remote operations

This paper focuses on the fact that a developer should not be concerned whether his application will be distributed or not. Because the current remoting infrastructures use serialisation to pass parameters, synchronisation problems exist. We will elaborate on a transparent framework to pass mutable objects to remote operations, in the same way as they are passed to local operations. A number of solutions will be proposed to provide this transparency. Finally, a solution based on a caching mechanism will be implemented using annotations.
Adsorption and transport behavior of arsenate on saline-alkali soils of tidal flat of Yellow Sea, Eastern China

ABSTRACT The adsorption of arsenic plays an important role in the mobility of this toxic element in the saline-alkali soil environment. The adsorption and transport of arsenate [As(V)] in saline-alkali soils were investigated in this study. The results of kinetic experiments indicated that the rate of As(V) adsorption was initially rapid and then became slow, which were modeled well with the pseudo-second-order rate model. The adsorption isotherms were best fitted by the Langmuir and Freundlich sorption equation. The maximum adsorption capacity of soil L1was the lowest (202.8 mg/kg), and that of soil D1 was the highest (686.6 mg/kg). The difference in adsorption capacity in five soils was mainly due to the CaCO3 content. The CaCO3 enhanced As(V) adsorption due to the adsorption and coprecipitation of calcium with As(V). The column experiments demonstrated that the transport of As(V) in soils was detained and the degree of detainment increased with decreasing As(V) concentration.
Locally Presentable And Accessible Categories

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Know Your Crowd: A Case Study in Digital Collection Marketing

ABSTRACT Digitized special collections and institutional repositories present unique challenges to libraries struggling to identify marketing strategies that will entice patrons to these services. These collections, which do not have the same mass appeal as full-text articles or author book readings, still must attract use. This case study explores an academic library’s attempts to actively market its digital special collections. They advertised their collections via published marketing materials, a library services fair, and a photography contest. The results were that high-quality, intense, marketing for a general population does not work for specialized digital collections because the subject areas are too narrow for general interest. The scope of the audience was also misplaced since the collections had a greater market outside the university than with the local students. The authors looked at digital special collections that were successful to see what worked to market collections to outside users. They found that collections that were connected to external resources that were affiliated with different interest groups were successful with minimal marketing. The method of linking collections to Wikipedia was identified as a simple and effective method that was more effective than linking the collection to more niche sites. The authors conclude that academic libraries should utilize more focused, community-connecting approaches in order to engage the specialized patrons of digital special collections.
Antioxidant and antibacterial activities of Ischaemum indicum leaves extracted using different solvents

The aim of this study was to evaluate antioxidant and antibacterial activities of Ischaemum indicum leaves extracts based on different polarity solvents: water, methanol, ethyl acetate, dichloromethane, and n-hexane. The antioxidant activity was evaluated using ABTS and DPPH methods, while the antibacterial activity was determined by broth dilution method against Pseudomonas aeruginosa and Bacillus subtilis. The results showed that water and methanol extracts of I. indicum gave the highest antioxidant activity in ABTS assay with an IC50 73.80 and 46.32 µg/mL, respectively. On the other hand, The IC50 on DPPH assay for water extracts was 117.51 µg/mL, this value was higher than that of methanol extract with no inhibition. Methanol and water extracts showed the antibacterial activity against B. subtilis with inhibition of 48.62 and 45.11%, whereas inhibition of P. aeruginosa were 31.95 and 30.31%, respectively. This study denoted that I. indicum is a new potential candidate as antioxidant source.
Firefly-Inspired Time Synchronization Mechanism for Self-Organizing Energy-Efficient Wireless Sensor Networks: A Survey

Perceptions of lifelike marvels are viewed as the best data source of unconstrained synchronization. Such synchronization is imperative for the best possible coordination of intensity cycles for wireless sensor network (WSN) energy conservation. Fireflies, which have a comparative structure to WSN, utilize the guideline of pulse-Coupled Oscillators (PCOs) for light blaze outflow to pull in mating accomplices. This conduct can be impersonated for the improvement of WSNs and have decentralized energy efficiency conduct. In any case, a fascinating component of WSNs is that the PCO is utilized by the firefly synchronization to pull in mating accomplices; however, it cannot be utilized in genuine sensor networks. This is because of the failure of the sensor nodes to get data packets utilized by the first PCO model because of deafness. Subsequently, energy utilization turns out to be high and a large portion of the data is lost. For most situations, the PCO model is not appropriate for sensor networks because of high packet collision since WSNs cannot bear the cost of transmission and gathering data concurrently. It likewise expands energy utilization because the battery substitution is unthinkable upon the fatigue of a node battery energy strategy. Accordingly, this paper broadly surveys and talks about the algorithms developed to address the difficulties and the systems of incorporating energy-efficient firefly inspired time synchronization over WSNs and the properties of transmission state inside the deafness and packet collision. In particular, it is an exhaustive audit incorporating instrument, points of interest and detriments of past related work inside the transmission state. The paper helps scientists to (1) keep away from deafness that happens in the transmit state in WSNs, (2) prevent packet collision for the time of transmission in WSNs, and (3) increment the data gathering all through the transmission states in WSNs. It additionally features the recommendation of a few appropriate open issues as proposals for future research.