Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Instrumentation Refinement for Empirical Performance Modeling

The analysis of runtime performance is important during the development and throughout the life cycle of HPC applications. One important objective in performance analysis is to identify regions in the code that show significant runtime increase with larger problem sizes or more processes. One approach to identify such regions is to use empirical performance modeling, i.e., building performance models based on measurements. While the modeling itself has already been streamlined and automated, the generation of the required measurements is time consuming and tedious. In this paper, we propose an approach to automatically adjust the instrumentation to reduce overhead and focus the measurements to relevant regions, i.e.,such that show increasing runtime with larger input parameters or increasing number of MPI ranks. Our approach employs Extra-P to generate performance models, which it then uses to extrapolate runtime and, finally, decide which functions should be kept for measurement. Also, the analysis expands the instrumentation, by heuristically adding functions based on static source-code features. We evaluate our approach using benchmarks from SPEC CPU 2006, SU2, and parallel MILC. The evaluation shows that our approach can filter functions of little interest and generate profiles that contain mostly relevant regions. For example, the overhead for SU2 can be improved automatically from 200% to 11% compared to filtered Score-P measurements.
A MEC-based Distributed Offloading Model for Ubiquitous and Time-constraint Offloading

The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-hungry applications that fundamentally changes the individual’s lifestyle. Although Cloud Computing technologies have already been leveraged to coordinate with the capability and battery-constraint mobile User Equipment (UE), the long-distance propagation delay downgrades the network QoS and user QoE. In this paper, we propose a queueing-based Mobile Edge Computing (MEC) model that concerns the offloading procedure, especially in the time-constraint scenarios. A queueing model is proposed for the offloading process, considering the dynamic network queueing delay. A heuristic scheduling model is designed to maximize the offloading energy and execution efficiency. A regression prediction model is implemented to achieve dynamic resource allocation. In the experiment, the proposed model is compared to the recent studies, and the results indicate that the proposed model can outperform the current studies in terms of execution time and energy reservation.
Broadband Dispersion Compensating Highly Nonlinear Square Photonic Crystal Fiber: Design & Analysis

An optimal design of photonic crystal fiber (PCF) in square lattice architecture with circular air-holes of three different diameters is proposed for dispersion compensation in optical transmission system. Finite element method (FEM) with perfectly matched layer boundary condition is applied to investigate the guiding properties of the proposed PCF. Simulation results affirm that the proposed PCF offers large negative dispersion coefficient of -1212 ps/(nm.km) and high nonlinear coefficient of 117.4 W−1Km−1 at 1. 55μm wavelength. Moreover, the structural parameter variation around the optimum value due to fabrication complexity is evaluated and reported. The proposed PCF will be very suitable for high bit rate optical transmission networks, sensing and nonlinear applications.
On Prerequisites for Revealing C. elegans Backward Crawling Mechanism through Computer Simulation of Key Involved Subsystems

Relatively simple and exceptionally well-studied invertebrate organism, Caenorhabditis elegans, is expected to become the first one for which a virtual ‘twin’ will be developed. Detailed biologically reasonable computational model of the organism, reproducing its neurophysiology, morphology and biomechanics, will allow to determine the gap between the real nervous systems and their current numerical models. This problem remains one of the key interdisciplinary challenges, requiring efforts both in neuroscience and information technologies. Moreover, even for C. elegans the entire nervous system remains too sophisticated (for current level of science and technology) to build its complete model, that's why here we focus on a separate part of C. elegans nervous system responsible for just one function (with still unknown mechanism) – backwards crawling movement. The choice was caused by the evidence of its ability to function independently from many other quite complex nervous system's parts and mechanisms, which is a big luck. Thus we propose a conception and strategy, based on integration of available experimental data, models and simulation software, which should lead to successful construction of backward crawling computational model, including neuronal level activity, muscular cells contraction and movement of the worm body interacting with virtual physical environment.
Generating Tests to Analyse Dynamically-Typed Programs

The increasing popularity of dynamically-typed programming languages, such as JavaScript or Python, requires specific support methods for developers to avoid pitfalls arising from the dynamic nature of these languages. Static analyses are frequently used but the dynamic type systems limit their applicability. Dynamic analyses, in contrast, depend on the execution of the code under analysis, and thus depend on the quality of existing tests. This quality of the test suite can be improved by the use of automated test generation but automated test generation for dynamically-typed programming languages itself is hard due to the lack of type information in the programs. The limitations of each of these approaches will be overcome by iteratively combining test generation with static and dynamic analysis techniques for dynamically-typed programs.
Robust Cell-Load Learning With a Small Sample Set

Learning of the cell-load in radio access networks (RANs) has to be performed within a short time period. Therefore, we propose a learning framework that is robust against uncertainties resulting from the need for learning based on a relatively small training set. To this end, we incorporate prior knowledge about the cell-load in the learning framework. For example, an inherent property of the cell-load is that it is monotonic in downlink (data) rates. To obtain additional prior knowledge we first study the feasible rate region, i.e., the set of all vectors of user rates that can be supported by the network. We prove that the feasible rate region is compact. Moreover, we show the existence of a Lipschitz function that maps feasible rate vectors to cell-load vectors. With these results in hand, we present a learning technique that guarantees a minimum approximation error in the worst-case scenario by using prior knowledge and a small training sample set. Simulations in the network simulator NS3 demonstrate that the proposed method exhibits better robustness and accuracy than standard learning techniques, especially for small training sample sets.
A 2x2 Pixel Array Camera based on a Backside Illuminated Ge-on-Si Photodetector

This paper proposes a new concept of a Near-Infrared (NIR) micro-system camera with a backside illuminated Germanium-on-Silicon (Ge-on-Si) photodetector. The performance of this photodetector is analyzed and compared to frontside illuminated Ge-on-Si photodetectors. An enhanced responsivity of 0.4 A/W at 1310 nm for the backside illuminated diode is achieved, which is equal to commercial solutions. With the help of zero-biasing, the critical dark current density can be reduced by more than a factor of 80 000 compared to standard biasing with −1 V. By using a backside illuminated diode, reflections of the metal layer are eliminated and the pixel fill factor is increased. Additionally, a proof of concept micro-system with a 2 x 2 pixel array of Ge-on-Si backside illuminated photodetectors and a custom readout ASIC is demonstrated. This proves the functionality of the proposed photodetector and readout concept for NIR camera applications.
An Intelligent Scheduling of Non-Critical Patients Admission for Emergency Department

The combination of the progressive growth of an aging population, increased life expectancy and a greater number of chronic diseases all contribute significantly to the growing demand for emergency medical care, and thus, causing saturation in Emergency Departments (EDs). This saturation is usually due to the admission of non-urgent patients, who constitute a high percentage of patients in an ED. The Agent-based Model (ABM) is one of the most important tools that helps to study complex systems and explores the emergent behavior of this type of department. Its simulation more accurately reflects the complexity of the operation of real systems. Our proposal is the design of an ABM to schedule the access of these non-critical patients into an ED, which can be useful for the service management dealing with the actual growing demand for emergency care. We suppose that a relocation of these non-critical patients within the expected input pattern, provided initially by historical records, enables a reduction in waiting time for all patients, and therefore, it will lead to an improvement in the quality of service. It would also allow us to avoid long waiting times. This research offers the availability of relevant knowledge for Emergency Department managers in order to help them make decisions to improve the quality of the service, in anticipation of the expected growing demand of the service in the very near future.
High Frequency Gas Detection With an Uncoated CMUT Array by Impedance Resonant Frequency Measurement

This paper shows for the first time the ability to detect different gases by tracking the impedance of an uncoated silicon nitride capacitive micromachined ultrasonic transducer (CMUT) array at the anti-resonant frequency. The principle of this chemical detection is based on the influence of a physical property of the gas (the mass density) on the resonant properties of the CMUTs. In this paper, we present results for carbon dioxide and hydrogen detection. Potential applications of such sensor include long term gas monitoring or fast response gas sensing for gas leakage detection.
Comparative Study of Control Approaches Designed for a Quadrotor in a Visual Servoing Task without Observers

The performance and characteristics of four controllers applied to a quadrotor UAV are analyzed in this paper. The compared control approaches are: PID, Linearizing Feedback, Backstepping Approach and Sliding Mode based control. A suitable and efficient structure is proposed for control laws implementation. Standard sensors are used and need of observer is avoided by use of IBVS.The comparative analysis is done for the UAV in Visual Servoing Task. It is based on tracking errors during transients and at steady state, and on the performance and robustness with respect to plant model, to environment perturbations (in sensors and actuators) and uncertainties.
Active Cancellation Limitation Analysis for Full Duplex Systems with a Single Antenna

In this paper the performance limitations of the multi-PA / multi-LNA / single-antenna duplex RF transceiver architecture interconnected by a passive reciprocal electrical network are explored. It is shown that, if the antenna’s impedance is allowed to change, as is the case in real environment, either the influence of the PAs’ signal output on the SNR or the influence of the PAs’ thermal noise on the SNR can be canceled, but not both of them simultaneously. Additionally, it is demonstrated that, if the antenna’s impedance is fixed, then it is possible to design a system in which both the SNR impact of the PAs’ signals and the SNR impact of the PAs’ thermal noise are canceled. The constraint on the amount of the LNAs and the PAs required to achieve this cancellation is demonstrated as well.
Improving overall parallelism in AES accelerator using BRAM and multiple input blocks

With the design of custom architecture of a hardware for user applications in FPGAs, throughput, power and latency can be optimized. Accelerators deployed in FPGAs can be used to accelerate user applications and later on reprogrammed to run another application. Availability of huge amount of resources, high parallelism and re-programmability of FPGAs, it is found to be useful as accelerators in cloud infrastructure. Communication speed between main processor and accelerator should not pull down the acceleration process speed. Usage of BRAMs for increasing the communication speed and improved pipelining, thereby speeding up of acceleration process is discussed here. Input is divided into blocks are continuously passed to BRAM which is read by AES accelerator and improving overall parallelism by pipelining multiple input blocks. After processing, output is passed to another BRAM without waiting the user process to read from accelerator. Result shows 32% decrease in number of clock cycles while using BRAM with pipelining than without using BRAM with pipelining.
Improve the Accuracy of SenseComp in Thai Consumer’s Review Using Syntactic Analysis

Thai sentiment analysis can be analyzed in multiple dimensions: product, price, and shipping. The scores from sentiment analysis can be considered as multi-dimensional trust score of e-vendor which affects the purchase decision of the consumer. A consumer’s review that has different sentiments describing the same dimension in the sentence leads to the incorrect scoring problem in SenseComp – the method to automatically analyze Thai sentiment in the consumer’s review in multiple dimensions with sentiment compensation technique. In this paper, SenseComp using syntactic analysis method (SenseComp2) is proposed in order to improve the accuracy of the original SenseComp. Thai syntactic structure in the consumer’s review is analyzed before the scores in multiple dimensions are given. The results show that SenseComp2 increases the accuracy of the original SenseComp up to 31.88% in the sentiment analysis of Thai consumer’s review when there are multiple dimensions and various sentiments in the same sentence.
Can the Exchange Rate Be Used to Predict the Shanghai Composite Index?

Stock index price forecasting is a consistent focus of business intelligence. Various factors influence stock index price forecasting, such as technical indicators, financial news, business status, and the macroeconomics situation. In addition, many studies have shown that the exchange rate is related to the stock index price; however, no study has examined whether the exchange rate can be used to forecast stock index prices. Therefore, this paper focuses on this topic and uses exchange rate to predict China stock index price for the first time. Firstly, we compare the association of China stock index price with different data sources to illustrate the feasibility of using the exchange rate to predict stock index prices. Then, we generate some additional technical features of the exchange rate and propose a strategy to predict the stock index price. Finally, we compare the forecast results of China’s stock index price based on four data sources, i.e., technical indicators, exchange rate data, US market index data and finance news data from January 3, 2017 to March 20, 2019. Experimental results demonstrate that the performance of exchange rate data for stock index prediction is comparable to other popular data sources and that, in some prediction periods, the exchange rate outperforms such data sources. The results confirm that the exchange rate could be used for forecasting the Shanghai Composite Index prices.
An Adaptive Droop Control Strategy for Islanded Microgrid Based on Improved Particle Swarm Optimization

In an islanded microgrid with multiple distributed generations (DGs), the difference in line impedance may cause local voltage deviation, which leads to a series of problems such as lower power allocation accuracy and bus voltage drop under traditional droop control. In this respect, a method for optimizing the droop control using an improved particle swarm optimization (IPSO) is proposed. Firstly, the microgrid structure and influence of line parameters on traditional droop control strategy is analyzed. Then, an improved particle swarm optimization is proposed. Based on the basic particle swarm optimization (PSO) algorithm, a fuzzy inference system (FIS) is introduced to dynamically adjust the particle swarm optimization, which can effectively improve the global search ability and local search ability of the algorithm. After that, the improved algorithm is applied to the droop controller, simultaneously, the range of stable operation of the system is determined by small signal analysis. Finally, the simulation and experiment results show that the proposed improved droop control strategy can achieve accurate allocation of active and reactive power effectively while maintaining bus voltage and system frequency stability, enhance the dynamic performance and transient stability of the microgrid system.
Practical Issues with Unloaded Resonant Inductive WPT Link Operating in Load-Independent Regime

The paper reveals practical issues present in series-series compensated unloaded inductive wireless power transfer system operating in load-independent regime. It was recently shown, that due to existence of parasitic resistances, corresponding output voltage is not completely load-independent. Based on time-domain analysis, DC voltage gain of an unloaded system was predicted for a wide range of operation frequencies. However, parasitic lumped capacitance of the receiving coil was not taken into account. It is therefore shown that parasitic oscillations appearing in an unloaded secondary impose significant overvoltage at DC output, which may cause safety issues. Two possible solutions are discussed, allowing damping the oscillations thus making the unloaded operation feasible. The presented analysis is well-verified by simulation results and experiments of a 400V, 1kW inductive wireless power transfer link.
Interference Model of Two Time-Of-Flight Cameras

The last decade bore witness to increased development of time-of-flight (ToF) camera hardware, algorithms, and applications, particularly 3-D measurement in the fields of human-robot collaboration. Their advantage is in faster digital 3-D image target representation from efficient signal computations. ToF cameras emit modulated light, measuring the round-trip time from its illumination source to its sensor, deriving a distance image. A disadvantage of using multiple ToF cameras is light interference with other cameras’ 3-D measurements. Commonly, adopting an access protocol called frequency division multiple access (FDMA) minimizes interference-related errors but does not eliminate them. The quantification of this distance error has remained a challenging research problem. This paper presents an interference model for two time-of-flight cameras, quantitative analysis, and mathematical modeling to determine the interference-related distance error when using FDMA.
Waveform Coding Techniques in Large Scale Antenna Systems

Scale Antenna System consist of several number of antennas and are used at the transmitter side as well as the receiver side to reduce interferences for obtaining low Bit Error Rate (BER) and high throughput of the signals during transmissions. In Large Scale Antenna Systems, an increased Cell Sites will reduces the interferences for obtaining high throughput of the signals. The Cell Sites consists of many number of antennas which transmits and receives the signals are placed at the fixed place and are used to communicate with the users or mobile phones. The better spectral containment per subcarrier can be achieved with the help of Filter Bank Multi Carrier (FBMC) technique. The cyclic prefix will not be used in FBMC, and so it increases the bandwidth efficiency. The aim of this system is to increase the throughput and to decrease the Bit Error Rate (BER) of the signals of FBMC technique in Large Scale Antenna System using different detection methods. The detection methods used in our proposed system are Maximal Ratio Combining, Zero Forcing.
High-Accuracy Off-Line Map-Matching of Trajectory Network Division Based on Weight Adaptation HMM

In this paper, an accurate off-line map-matching (OM2) system is designed for complex trajectory networks. It is difficult to complex trajectories input into the hidden Markov model (HMM) directly. OM2 includes three key modules that are pre-processing, map-matching based on weight adaptation HMM (WA-HMM), and post-processing. The pre-processing module divides complex multi-trajectory into single-trajectory sets based on the self-defined trajectory division model (TDM) of crossroads. Another core module is the WA-HMM based on Boxplot, which is used to balance efficiency and accuracy of off-line map-matching. The post-processing is used to map the points of the crossroads so as to further improve the map-matching accuracy. OM2 employs the actual GPS trajectories of the internet company and road map of Sichuan province police GIS (PGIS). Our evaluation results show that the accuracy is about 98%, which is suitable for off-line map-matching and solves the problem of complex trajectory network matching being difficult and time-consuming.
New Assembly Technology for VCSEL arrays comprising ultra-thin diodes

Objective of this paper is the development of an assembly technology for VCSELs 360 micron by 360 micron in size and a thickness of 72 micron with high positioning accuracy for automated production. Due to special customer requirements, a final thickness of the conductive glue of about 50 micron is necessary. For highest reliability, gold wire bonding of the top side contact of the VCSEL to a silicon substrate with gold metallization and printing gold-based conductive glue have been used. One VCSEL array contains 512 diodes. Special design features of the VCSEL secure that the relatively high thermal resistance of the cured conductive glue layer does not impair the optical properties or the life time of the VCSELs. Die bonding has been carried out with a Datacon EVO machine. The singulated laser chips were picked from a blue tape. For the interconnection of the top side contact we used gold wire and a Stand-Off Stich Bond process with special loop geometry. With an optimized screen printing process we did get a reproducible height of the conductive glue of about 50 micron with low standard deviation, as required, and no shorts at the silicon substrate. The position tolerance of the VCSELs meets the customer requirements. Gold wire bonding delivered excellent results, meeting the customer specification. For the first prototypes we did get a total yield of 99.9%. The optical spectrum of the VCSELs and other measurements indicate that the assembly processes do not harm the diodes or their optical properties.
A Review on Microgrids with Distributed Energy Resources

In association with increasing in penetration of distributed generation sources (DGs) into power systems, and their power management of different DGs and the grid has elevated as a major concern. Though, Microgrid (MG) is the extensively an accepted concept for the association of DGs in power system networks. Integrating renewable energy sources (RESs), which are often connected via power electronic interfaces into the power grid, can sometimes be a stimulating task just from a purely technical point of view. Thus, the MG is a promising option for future power system interfaces. Evolving the challenges has taken place in terms of the power system control, power quality improvement, reliability, and energy management. The MG operational performance, stability, basic control issues and, concept of MGs are presented in this paper.