Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the Direction Movement of Financial Time Series Using Artificial Neural Network and Support Vector Machine

Prediction of financial time series such as stock and stock indexes has remained the main focus of researchers because of its composite nature and instability in almost all of the developing and advanced countries. The main objective of this research work is to predict the direction movement of the daily stock prices index using the artificial neural network (ANN) and support vector machine (SVM). The datasets utilized in this study are the KSE-100 index of the Pakistan stock exchange, Korea composite stock price index (KOSPI), Nikkei 225 index of the Tokyo stock exchange, and Shenzhen stock exchange (SZSE) composite index for the last ten years that is from 2011 to 2020. To build the architect of a single layer ANN and SVM model with linear, radial basis function (RBF), and polynomial kernels, different technical indicators derived from the daily stock trading, such as closing, opening, daily high, and daily low prices and used as input layers. Since both the ANN and SVM models were used as classifiers; therefore, accuracy and F-score were used as performance metrics calculated from the confusion matrix. It can be concluded from the results that ANN performs better than SVM model in terms of accuracy and F-score to predict the direction movement of the KSE-100 index, KOSPI index, Nikkei 225 index, and SZSE composite index daily closing price movement.
Modeling of skew using the flux-MMF diagram [of PM machines]

The flux-MMF diagram has recently been used to predict torque ripple in different electric machine types. This paper describes a simple and elegant method, based on this technique, for predicting the effect of skew on torque ripple in permanent-magnet machines. Although it is well known that skewing minimizes torque ripple, the paper quantifies the difference in the extent of minimization between the electromagnetic torque ripple and the cogging torque.
What to do when nothing has happened?

Often, during a layer of protection analysis (LOPA) or a quantitative risk analysis (QRA) study, historical information indicates no occurrences of a particular undesired event in the plant or system. The simple reply that the frequency or rate is zero because the event has never happened is sometimes heard by the analyst during review meetings. The analyst must then decide on an appropriate measure of the frequency of the undesired event. This article presents methods based on statistical tools for developing a measure of the frequency or failure rate of an event when the historical information includes no occurrences of the event. The article compares the various available statistical tools. Guidance is presented on methods to incorporate historical information of no failures into a LOPA or QRA study. Examples on the application of the recommended methods to deal with the problem are presented. © 2011 American Institute of Chemical Engineers Process Saf Prog, 2011
Research on UCD Precoding for MIMO System

This article mainly describes a new technique of multiple-input multiple-output (MIMO) communication systems based on the recent communication demand. This technique, by pre-coding CSI (the channel state information) at the transmitter, is based on UCD (Uniform Channel Decomposition) algorithm for MIMO system. By Uniform Channel decomposition of channel matrix, the algorithm can decompose a MIMO downlink channel into multiple identical sub-channels. The power allocation applied to each sub channel in MIMO system is identical, and the MIMO channel’s capacity isn’t reduce when the SNR (Signal Noise Ratio) is low. The simulations show that the UCD scheme has a better performance than GMD (Geometric Mean Decomposition) scheme even without the use of error-correcting codes, and the Symbol Error Rate (SER) of UCD algorithm is lower than GMD’s at the same SNR. Consequently, MIMO system gets a better interference performance by UCD algorithm.
Identifying the Driving Factors that Affect Judgments of Head-on Collisions

Head-on collisions result in a substantial number of fatalities. They occur more frequently on rural roads than urban roads, and more frequently on straight roads than curved roads. We investigated the effects of several factors on judgments about head-on collisions. Scenes depicted self-motion on a collision course with a car in the opposing lane. The scene ended before the collision occurred. Participants predicted whether a collision would occur. Results indicated that judgments were affected by the presence or absence of a centerline that divided the road, by the speed and distance of the oncoming car, and by how long the oncoming car was presented. The pattern of results suggests that head-on collisions on rural roads may decrease when a centerline is present, and when speed limits are reduced. However, collision-warning systems may be needed to reduce head-on collisions on roads with relatively high speed limits, especially during driver-distractions.
A NOVEL TELECOMMUNICATIONS-BASED APPROACH TO MATHEMATICAL MODELING OF HIV INFECTION

It is well known that biological systems utilize communication in some form, one prolific example of this is the propagation of HIV (Human Immunodeficiency Virus) in the human body. By modeling HIV infection as a communication system, we hope to gain a unique insight into HIV and biological communication systems in general. Such a model would provide researchers a platform for experimenting and simulating various biological communication systems. We have previously developed a layered communication protocol for interpreting biological communication systems using telecommunications paradigms and will apply said model to HIV proliferation. We will also demonstrate the effectiveness of the model by formulating a telecommunications-based mathematical model, and by implementing a simulation of HIV infection based on direct interpretation of this layered protocol. iii DEDICATION I would like to thank my advisers Drs. Tadeusz and Beata Wysocki who have been the driving and creative force behind my work and my family Tim, Cindy, and Andrew for their continued unconditional support. Thank you.
INFLUENCES ON ENGAGEMENT IN E-COMMERCE IN AGRIBUSINESS: AN EMPIRICAL STUDY

Shirley Gregor Australian National University Australia John Rolfe Central Queensland University Australia Don Menzies Australian National University Australia Gregor, Professor Shirley Australian National University, Canberra ACT 0200 email: Shirley.Gregor@anu.edu. au Rolfe, Associate Professor John Central Queensland University Rockhampton QLD 4702 email: j.rolfe@cqu.edu. au Menzies, Mr Don Australian National University C/- Capgrains Cooperative PO Box 5826
Characterization of serum N-glycome alterations in seasonal allergic rhinitis using MALDI-TOF-MS: A pilot study

Abstract Seasonal allergic rhinitis (SAR) is an inflammatory process. In this pilot study, matrix assisted laser desorption ionization-mass spectrometry (MALDI-MS)-based analyses were conducted to investigate the effects of SAR on serum N-glycome in a small dataset (n = 10 for both SAR patients and controls). It was detected that two N-glycan compositions (H6N5E2L1 and H6N5E1L2) were down-regulated in SAR patients. Additionally, five tri-antennary N-glycan traits, including both galactosylated and sialylated (A3GS and A3GL) and non-fucosylated (A3F0GE, A3F0GL, A3F0GS) ones, were decreased. Furthermore, three high-antennary and fucosylated N-glycan traits (A3F, A3EF and A4F) were increased in SAR patients compared to controls. Graphical Abstract
Cell type–specific analysis by single-cell profiling identifies a stable mammalian tRNA–mRNA interface and increased translation efficiency in neurons

The correlation between codon and anticodon pools influences the efficiency of translation, but whether differences exist in these pools across individual cells is unknown. We determined that codon usage and amino acid demand are highly stable across different cell types using available mouse and human single-cell RNA-sequencing atlases. After showing the robustness of ATAC-sequencing measurements for the analysis of tRNA gene usage, we quantified anticodon usage and amino acid supply in both mouse and human single-cell ATAC-seq atlases. We found that tRNA gene usage is overall coordinated across cell types, except in neurons, which clustered separately from other cell types. Integration of these data sets revealed a strong and statistically significant correlation between amino acid supply and demand across almost all cell types. Neurons have an enhanced translation efficiency over other cell types, driven by an increased supply of tRNAAla (AGC) anticodons. This results in faster decoding of the Ala-GCC codon, as determined by cell type–specific ribosome profiling, suggesting that the reduction of tRNAAla (AGC) anticodon pools may be implicated in neurological pathologies. This study, the first such examination of codon usage, anticodon usage, and translation efficiency resolved at the cell-type level with single-cell information, identifies a conserved landscape of translation elongation across mammalian cellular diversity and evolution.
Multicomponent incremental dynamic analysis considering variable incident angle

Performance-based earthquake engineering (PBEE) is the current trend in designing earthquake-resistant structures. The implementation of the PBEE framework requires the assessment of the structural capacity in multiple earthquake hazard levels. Incremental dynamic analysis (IDA) is considered to be one of the most efficient computational tools for estimating structural capacity; therefore, it is often incorporated into the PBEE framework. Most real world reinforced concrete (RC) buildings can only be represented accurately with three-dimensional (3D) models; hence, a multicomponent incremental dynamic analysis (MIDA) is required in order to carry out an IDA-based PBEE framework. In this work, the implementation of IDA studies in 3D structures is examined, where a two-component seismic excitation is applied, and a new procedure for performing MIDA is proposed. According to the proposed procedure, the MIDA is performed over a sample of record-incident angle pairs that are generated using Latin hypercube sampling (LHS).
Composite generation and transmission system adequacy assessment with time varying loads using a contingency enumeration approach

Adequacy evaluation of composite generation and transmission system can be performed in a variety of ways. In general, these techniques can be categorized as being either a Monte Carlo simulation approach or based on a contingency selection/evaluation procedure. This paper illustrates the development of an annual chronological load curve for each load bus in a composite generation and transmission system. These load curves are then utilized in composite system adequacy assessment using the analytical or contingency enumeration approach.
Promoting Kaohsiung Air-Sea Port Integration with Identity-Oriented Pervasive Networks

Reliable communications and spatial connection are essential to critical operations. A reclamation area close to Kaohsiung coastal plants was proposed for replacing the 1990s-established international airport. An alternative is suggested to reliably connect new runways with the original terminal by (underground) passages, offering airport development flexibilities and neighboring plants' operational justices. To assure services and security, optimal-degree spider-web networks are prototyped in the surveillance-control networks along these and city critical passages to benefit coping with detection-unavailability, radio interference. The inherent radial-ring road configuration of Kaohsiung and other cities is mathematically evidenced having connecting robustness. Such configurations can offer integrated response capabilities even if two paths being attached with the surveillance-control networks are destroyed. Hence, including radio frequency identification (RFID) applications, the dedicated short range communications (DSRC) linked as the aforementioned surveillance-control network along roads can provide more reliable mobile business (m-business), tourism development, and logistic services incorporated with multi-modal transportation.
Damping techniques for grid-connected converters with LCL filter: an overview

Distributed generation systems, based on renewable energy sources, are typically connected to the main grid by a voltage-source inverter with a low-pass filter. The need for improved efficiency led to the use of third order low-pass filters, such as the LCL configuration, which has resonant behavior. In order to meet energy quality requirements and ensure the systems stability it is necessary to suppress the LCL filters resonance through damping techniques. Therefore, this paper presents an overview of some damping strategies found in literature and its design procedure, applied to a simulated single-phase grid-tied inverter. The comparison of each presented damping methodology characteristics is described, with analysis of advantages and drawbacks for each case.
A novel active region concept for highly efficient GaSb-based optically in-well pumped semiconductor disk lasers

A novel active region concept for GaSb-based optically pumped mid-infrared vertical external cavity surface emitting lasers (VECSELs, also referred to as optically pumped semiconductor disk lasers - OPSDLs) is presented. The concept is based on GaxIn1-xAsySb1-y type-I quantum wells (QWs) embedded between AlAs0.08Sb0. 92 barrier layers designed for optical in-well pumping where the pump absorption at pump wavelengths between 1 μm and 2 μm takes place exclusively in the active QWs. This concept provides several advantages such as a high modal gain, the suppression of thermal leakage currents, and an improved thermal conductivity of the active region compared to a conventional GaInAsSb/AlGaAsSb active region design. Using the novel design approach an in-well pumped VECSEL emitting at 2.24 μm has been realized, yielding at a heat sink temperature of 20°C in continuous-wave operation a power slope efficiency of more than 32% and an absorption of the 1.96 μm pump light of more than 50% without pump recycling, These data constitute a significant improvement in device performance compared to previously reported data on in-well pumped GaSb-based VECSELs.
HIERARCHICAL CONTROL SYSTEM SYNTHESIS FOR ROTORCRAFT-BASED UNMANNED AERIAL VEHICLES

This paper introduces the development of multiple number of Unmanned Arial Vehicle (UAV) system as a part of BErkeley AeRobot (BEAR) project, highlighting the recent achievements in the design and implementation of rotorcraft-based UAV (RUAV) control system. Based on the experimental flight data, linear system model valid near hover condition is found by applying time-domain numerical methods to experimental flight data. The acquired linear model is used to design feedback controller consisting of inner-loop attitude feedback control, mid-loop velocity feedback control and the outer-loop position control. The proposed vehiclelevel controller is implemented and tested in Berkeley UAV, Ursa Magna 2, and shows superior hovering performance. The vehicle level controller is integrated with higher-level control using a script language framework to command UAV.
One OCDMA PON System with 2D Multi-Length Two-Weight CHPCs

One OCDMA PON system is discussed in this paper. Multi-length Two-Weight Carrier Hopping Prime Codes is selected as encoder scheme, encoded information is transmitted through Optical fiber. Hard Limiter is utilized in receiver terminal to ensure lower bit error rate. Simulation shows that it can be used for large capacity optical networks.
Proactive Detection for Countermeasures on Port Scanning based Attacks

Defending a cyber asset from a targeted attack based on port scanning is a challenging task because attackers exploit protocol behavior essential for productive use of applications. For instance, TCP or UDP ports opened for applications such as file transfer or video can be exploited to launch denial of service attacks. There is a need for proactive methods that can detect port scanning based attacks at their initial stage so that countermeasures can be initiated before the attack impact is disruptive on a cyber asset. This paper presents methods to counteract the initial stages of network attacks involving TCP and UDP port scanning. Our methods analyze outgoing traffic to identify ICMP 3.3 and TCP RST response packets that indicate the beginning of an attack launch. We specifically describe two countermeasures based on software-defined networking controller (at the network level) and Linux utility (at the host level) modules we developed. To validate the effectiveness of our proactive detection based methodology, we set up a testbed with a scheme of a polygon and conducted experiments related to distortion of the port status of attacks. Our results demonstrate that our approach is effective and the accuracy of determining open TCP ports did not exceed 15%, and it did not reach 2% for the remaining ports (closed TCP, UDP of any type).
Multi-Focus Image Fusion Using Curvelet Transform

Curvelet transform is a new muiti-scale geometic analysis, which has the characteristics of anisotropy. It is more suitable for the analysis of image curve edge characteristics than wavelet. Thus, in this paper it is applied to multi-focus image fusion, and used fusion rules that suitable for the characteristics of multi-focus image fusion.
GNSS Spoofing Detection Based on Receiver C/No Estimates

A perceived emerging threat to GNSS receivers is posed by a standoff spoofing transmitter that emulates authentic signals but with randomized code phase and Doppler over a target area extending over several hundred meters in radius. The victim GNSS receiver computes the navigation solution based on these counterfeit signals which are subsequently passed on to the location services application layer as being reliable with potentially damaging consequences. An effective spoofing detection technique is developed in this paper, based on signal power measurements that can be readily applied to present consumer grade GNSS receivers with minimal firmware changes. While the average authentic satellite signal power is uniform in the target area, the spoofer average signal power is highly affected by pathloss which can be used to discriminate between the authentic and the spoofer signals. The proposed technique utilizes C/N0 measurements to detect a spoofing threat and is effective in minimizing the affected area to an annulus in range. An extensive statistical analysis is carried out based on formulating a multi-hypothesis detection problem. Expressions are developed to devise a set of thresholds required for signal detection and identification. The statistical analysis supports the effectiveness of the proposed spoofing detection technique under various multipath conditions.
A Binary Translator to Accelerate Development of Deep Learning Processing Library for AArch64 CPU

SUMMARY To accelerate deep learning (DL) processes on the super-computer Fugaku, the authors have ported and optimized oneDNN for Fugaku’s CPU, the Fujitsu A64FX. oneDNN is an open-source DL processing library developed by Intel for the x86 64 architecture. The A64FX CPU is based on the Armv8-A architecture. oneDNN dynamically creates the execution code for the computation kernels, which are implemented at the granularity of x86 64 instructions using Xbyak, the Just-In-Time (JIT) assembler for x86 64 architecture. To port oneDNN to A64FX, it must be rewritten into Armv8-A instructions using Xbyak aarch64, the JIT assembler for the Armv8-A architecture. This is challenging because the number of steps to be rewritten exceeds several tens of thousands of lines. This study presents the Xbyak translator aarch64. Xbyak translator aarch64 is a binary translator that at runtime converts dynamically produced executable codes for the x86 64 architecture into executable codes for the Armv8-A architecture. Xbyak translator aarch64 eliminates the need to rewrite the source code for porting oneDNN to A64FX and allows us to port oneDNN to A64FX quickly.
Stabilization and tracking control of an x-z type inverted pendulum system using Lightning Search Algorithm tuned nonlinear PID controller

Abstract Inverted pendulum systems (IPSs) are mostly used to demonstrate the control rules for keeping the pendulum at a balanced upright position due to a slight force applied to the cart system. This paper presents an application for nonlinear control of an x-z type IPS by using a proportional-integral-derivative (PID) controller with newly established evolutionary tuning method Lightning Search Algorithm (LSA). A single, double and triple PID controller system is tested with the conventional and the self-tuning controllers to get a better understanding of the performance of the given system. The mathematical modelling of the x-z type IPS, the theoretical explanation of the LSA and the simulation analysis of the x-z type IPS is put forward entirely. The LSA algorithm solves the optimization problem of PID controller in an evolutionary way. The most effective way of making comparisons is evaluating the performance results with a well-known optimization technique or with the previous accepted results. We have compared the system’s performance with particle swarm optimization and with a classical control study in the literature. According to the simulation results, LSA-tuned PID controller has the ability to decrease the overshoot better than the conventional-tuned controllers. Finally, it can be concluded that the LSA-supported PID can better stabilize the pendulum angle and track the reference better for non-disturbed and the slightly disturbed systems.
A DC Fluctuation Suppression Control Strategy for Isolated DC Microgrids Based on Linear Active Disturbance Rejection Control (LADRC)

This paper introduce a control strategy based on liner active disturbance rejection control to reduce the DC fluctuation in DC microgrid. A brief introduction of DC microgrid is presented, and the advantage of isolated storage port is claimed. Later, this paper illuatrates the small signal model of dual active bridge(DAB) port. The basic working principle of LADRC is analyzed, the mathematical expression of extended state observer(ESO) is explained. Combining the small signal model of DAB, a simulation in Matlab/Simulink verifies the advantage of the proposed control strategy.
Optimal Meter Placement for Water Distribution System State Estimation

Real-time state estimates (SEs) of nodal demands in a water distribution system (WDS) can be developed using data from a supervisory control and data acquisition (SCADA) system. These estimates provide information for improved operations and customer service in terms of energy consumption and water quality. The SE results in a WDS are significantly affected by measurement characteristics, i.e., meter types, numbers, and topological distributions. The number and type of meters are generally selected prior to a SCADA layout. Thus, selecting measurement locations is critical. The aim of this study is to develop a methodology that optimally locates field measurement sites and leads to more reliable SEs. An optimal meter placement (OMP) problem is posed as a multiobjective optimization form. Three distinctive objectives are formulated: (1) minimization of nodal demand estimation uncertainty; (2) minimization of nodal pressure prediction uncertainty; and (3) minimization of absolute error between demand estimat.