Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormal Detection to Big Data Using Deep Neural Networks

It is difficult to detect the anomalies in big data using traditional methods due to big data has the characteristics of mass and disorder. For the common methods, they divide big data into several small samples, then analyze these divided small samples. However, this manner increases the complexity of segmentation algorithms, moreover, it is difficult to control the risk of data segmentation. To address this, here proposes a neural network approch based on Vapnik risk model. Firstly, the sample data is randomly divided into small data blocks. Then, a neural network learns these divided small sample data blocks. To reduce the risks in the process of data segmentation, the Vapnik risk model is used to supervise data segmentation. Finally, the proposed method is verify on the historical electricity price data of Mountain View, California. The results show that our method is effectiveness.
A PubMedBERT-based Classifier with Data Augmentation Strategy for Detecting Medication Mentions in Tweets

As a major social media platform, Twitter publishes a large number of user-generated text (tweets) on a daily basis. Mining such data can be used to address important social, public health, and emergency management issues that are infeasible through other means. An essential step in many text mining pipelines is named entity recognition (NER), which presents some special challenges for tweet data. Among them are nonstandard expressions, extreme imbalanced classes, and lack of context information, etc. The track 3 of BioCreative challenge VII (BC7) was organized to evaluate methods for detecting medication mentions in tweets. In this paper, we report our work on BC7 track 3, where we explored a PubMedBERT-based classifier trained with a combination of multiple data augmentation approaches. Our method achieved an F1 score of 0.762, which is substantially higher than the mean of all submissions (0.696). Keywords—social media; named entity recognition; data augmentation; drug name detection
A Framework for Software Customization in Global Software Development (GSD)

Global Software Development (GSD) is an aspect of software engineering that requires the joint efforts of professional software from separate locations. The market is motivated to start GSD due to a lack of local software developers, inadequate resources, fixed budget, and time. Many companies have shifted to software development outsourcing because of the high availability of resources, which cost one-third less than onshore vendors, skilled and professional developers. Vendors improve their skills through outsourced project experience and learn new ways to satisfy client needs. However, many risks are involved in an outsourcing process. GSD becomes the latest and popular development in software engineering, brings a new opportunity to getting resource mobility, market speeding time, obtaining additional information, and also helps to increase operational efficiency. In this paper, we have presented a framework for software customization in global software development. We have divided our approach into two parts. In the first part, we have analyzed the current literature work on the requirement change management process to find the limitation, gaps, and issues of Requirement Change Management (RCM). Our focus is on proposing a framework for software customization in a distributed environment in the second part. In our framework, we overcome the gap between the client and teams and, with the help of a requirement graph, increase the understanding of change requests at the development site. We use the knowledge repository to save the record of a change request. To evaluate our research work, initially, we conducted a case study to evaluate our framework in a real-life context. We have applied the proposed framework on a case study of “Finance Automation” to prove the applicability of our proposed approach. Then we
Reconstruction of stress corrosion cracks using signals of pulsed eddy current testing

A scheme to apply signals of pulsed eddy current testing (PECT) to reconstruct a deep stress corrosion crack (SCC) is proposed on the basis of a multi-layer and multi-frequency reconstruction strategy. First, a numerical method is introduced to extract conventional eddy current testing (ECT) signals of different frequencies from the PECT responses at different scanning points, which are necessary for multi-frequency ECT inversion. Second, the conventional fast forward solver for ECT signal simulation is upgraded to calculate the single-frequency pickup signal of a magnetic field by introducing a strategy that employs a tiny search coil. Using the multiple-frequency ECT signals and the upgraded fast signal simulator, we reconstructed the shape profiles and conductivity of an SCC at different depths layer-by-layer with a hybrid inversion scheme of the conjugate gradient and particle swarm optimisation. Several modelled SCCs of rectangular or stepwise shape in an SUS304 plate are reconstructed from simulated PECT signals with artificial noise. The reconstruction results show better precision in crack depth than the conventional ECT inversion method, which demonstrates the validity and efficiency of the proposed PECT inversion scheme.
Probabilistic Model for Water Distribution Reliability

A two-stage methodology for assessment of reliability of water distribution networks recognizing uncertainties in nodal demands, pipe capacity, reservoir/tank levels, and availability of system components is proposed. In the first stage, the probability distribution functions for nodal heads are derived from a linearized hydraulic model on the basis of known probability distribution functions of the nodal demands, pipe roughnesses, and reservoir/tank levels. The effects of nonlinearity in the network hydraulic model are accounted for in this step by partitioning the nodal demands into a number of categories or intervals. The probability of supply failure calculated in this first stage assumes that the system state or configuration is fixed, e.g., certain pipes and pumps are specified as being out of operation; that the pipe capacity varies randomly; and that demands vary around a specified level. The second step involves combining this probability with the probabilities of different system configurations and demand levels to generate the overall reliability measures for the whole system or a particular area of the system.
Improved footwear comfort reduces oxygen consumption during running

Footwear comfort has been shown to have an influence on injuries, but it was unknown whether comfort was related to performance. The current study examined the effects of footwear comfort on running economy. Thirteen male participants rated five pairs of shoes on perceived comfort. Oxygen consumption was assessed during steady state runs in the least and most comfortable shoes at slightly above the aerobic threshold. A paired t-test was used to compare running economy in the most versus the least comfortable shoe conditions. The findings of the study indicated a significant improvement in running economy, 0.7% on average, in the most comfortable shoe condition. It is suggested that future study of kinematic and kinetic reactions to footwear of different comfort will help to understand the mechanism for the observed performance improvement.
Neural Dissociations between Magnitude Processing of Fractions and Decimals

Fraction and decimal magnitude processing are crucial for mathematic achievement. Previous neuroimaging results showed that fraction and decimal processing activated both overlapping and distinct neural substrates, but temporal dissociations between fraction and decimal processing remained unknown. This event-related potential (ERP) study explored differences in neural activities between magnitude processing of fractions and decimals, by examining the notation effect (fraction vs. decimal) and distance effect (far vs. close) on early components of P1/N1, P2 and N2. Results showed that decimals elicited larger N1 and smaller P1 than fractions at the parietal region. Fractions demonstrated the significant distance effect on fronto-central P2 while decimals showed the distance effect on left anterior N2. ERP results reflect distinct processing of identification and semantic access stages between fractions and decimals. Identification is located at the visual-related region with enhanced perception acuity and identification efficiency for decimals. Semantic access activates the fronto-central region associated with elaborative magnitude manipulation for fractions, while semantic access reflects automatic phonological retrieval for decimals. Our findings disintegrate the magnitude processing of fractions and decimals from identification to magnitude processing. It reveals that temporal discrepancies between fraction and decimal magnitude processing appear as early as post-stimulus 100 ms.
Membrane antenna array based on substrate integrated waveguide technology for 94 GHz communication systems

The design and the results of a single slot coupled substrate integrated waveguide (SIW)-fed membrane antenna and a 1 × 4 array is presented for 94 GHz communication system. The membrane antenna is designed using Ansys high frequency structure simulator and consists of six layers. The microstrip patch antenna placed on the top pyralux substrate layer is excited by means of a longitudinal rectangular slot placed over the SIW structure in the bottom pyralux substrate. The simulated antenna impedance bandwidth is found to be 5 GHz (91.5–96.5 GHz) for both single element and 1 × 4 array. Furthermore, the gain is found to be 7 and 13 dBi for the single element and the 1 × 4 array elements, respectively. The results are verified using Computer Simulation Technology (CST) Microwave Studio and are found to be in good agreement.
Drug Mention Recognition in Twitter Posts Using a Deep Learning Approach

—In an era where medicine and technology are closely intertwined, sources of patient-generated data such as social media content are being explored to extract important information for the study of public health and patient trajectories. Drug related mentions present in Twitter posts are a particular use case, as the process of automatically extracting drug related mentions from tweets can provide novel relevant information for pharmacoepidemiologic studies. In this paper, we describe the system developed by the BIT.UA team from the University of Aveiro during the participation in BioCreative VII Track 3 on automatic extraction of medication names in tweets. The system consists of an end-to-end deep learning architecture based on transformers, and was used in all three submitted runs for the challenge. Run 1 obtained the best results on strict evaluation (F 1 - score of 0.6810) whereas Run 3 performed better on overlapping evaluation (F 1 -score of 0.7700).
Non synonymous A803G Polymorphism of N-acetyltransferase 2 Gene and Impaired lipid profile in Egyptian Obese Children and Adolescents

Background: Childhood overweight and obesity remains an important public health concern. The prevlance of obesity and overweight among children and adolescents aged 5-19 years has risen dramatically from 4% to over 20%. The aim of the present study was to assess A803G polymorphism in the NAT2 gene in Egyptian obese children and adolescents and to detect the relation between this gene mutation and impaired lipid profile in them. Patients and methods: this cross sectional study included 100 obese children and adolescents divided into two groups according to their HbA1c results : group 1(pre-diabetic obese children and adolescents) and group 2 (Nondiabetic obese children and adolescents) , both groups are compatible as regard age and sex and had equal numbers (50). Whole blood samples were collected and underwent genotyping todetect NAT2 A803G gene polymorphism using Taqman allelic discrimination assay. Results: There was highly statistically significant higher total cholesterol, triglycerides and LDL among Group 1 than Group 2. But regarding HDL, it was highly statistically significant higher among Group 2 than Group 1. Heterozygous A allele of Group 1 group had the worst lipid profile characteristics (higher cholesterol, triglycerides and LDL and lower HDL) but this difference was statistically significant only regarding LDL while regarding otherpararmeters, they were not statistically significant. While, heterozygous G allele of Group 2 had the worst lipid profile characteristics (higher cholesterol, triglycerides and LDL and lower HDL) but this difference was statistically significant only regarding LDL while regarding other parameters, they were not statistically significant. Conclusion: Our study concluded that Egyptian obese children and adolescents who carrying the NAT2 A803 allele might be at a high risk of impaired lipid profile and consequent increased future risk to develop secondary metabolic diseases.
PPG-Based Respiratory Rate Monitoring Using Hybrid Vote-Aggregate Fusion Technique

In this work, we present a low-complexity photoplethysmography-based respiratory rate monitoring (PPG-RRM) algorithm that achieves high accuracy through a novel fusion method. The proposed technique extracts three respiratory-induced variation signals, namely the maximum slope, the amplitude, and the frequency, from the PPG signal. The variation signals undergo time domain peak detection to identify the inter-breath intervals and produce three different instantaneous respiratory rate (IRR) estimates. The IRR estimates are combined through a hybrid vote-aggregate fusion scheme to generate the final RR estimate. We utilize the publicly available Capnobase data-sets [1] that contain both PPG and capnography signals to evaluate our RR monitoring algorithm. Compared to the reference capnography IRR, the proposed PPG-RRM algorithm achieves a mean absolute error (MAE) of 1.44 breaths per minute (bpm), a mean error (ME) of 0.70±2.54 bpm, a root mean square error (RMSE) of 2.63 bpm, and a Pearson correlation coefficient r = 0.95, p < . 001.
MOS sine function generator using exponential-law technique

A novel circuit configuration for generating the sine function in MOS integrated circuit technology is proposed. It is based on the exponential-law of MOS transistors operating in the subthreshold region. An experimental MOS sine generator and PSPICE simulations show that the MOS sine function generator achieves a total harmonic distortion of 0.71% over an angular range of ±360°. Typical power consumption is less than 1 μW and the bandwidth is greater than 100kHz.
Role of the Project Management Office in University Research Centres

University Research Centres (URCs) have become a primary organisational structure in universities for bringing together a critical mass of multidisciplinary research interests that can compete for large, funded research projects and create breakthrough research results. Some of the more successful URCs are now developing specialised project management offices (PMOs) that can coordinate key activities, from proposal development to project execution, and ensure that research results are disseminated. A key challenge for URCs is to define what roles, functions, and competencies such a PMO should have. This research identifies a number of key attributes of PMOs that meet the unique challenges of URCs. This paper presents an initial conceptualisation of roles and functions developed from a literature review and that are later tested via a detailed survey among 370 URC participants involved in collaborative R&D projects worldwide. The study suggests that there are three PMO maturity stages: ‘basic’, ‘intermediate’, and ‘advanced’. The resulting conceptualisation highlights six functions for a ‘basic’ PMO stage, an additional ten functions for an ‘intermediate’ PMO stage, and a further ten functions for ‘advanced’ PMO. The research presented provides guidance and decision support to URCs when selecting the role that a PMO should play for achieving tangible and intangible project benefits. Although the study suggests a lengthy list of functions, none of these should be considered in isolation. Most of the functions interact with each other and affect the PMOs’ impact within the URC in various ways. The paper contributes to the transformative and evolutionary nature of PMOs, and illustrates that universities are receptive and even demanding of the need to create an effective PMO to improve the operation of major R&D projects and programs and create greater societal impact by URCs.
Compact, tunable Wilkinson power divider using tunable synthetic transmission line

A very compact and frequency tunable Wilkinson power divider is suggested and demonstrated for the first time.By replacing λ/4 section lines in a conventional Wilkinson power divider with varactor tunable, lumped‐element synthetic transmission lines, dramatical size reduction and frequency tunability has been achieved. The prototype circuit fabricated shows excellent performance. For tunable frequencies from 0.71 to 0.99 GHz, the insertion loss is less than 3.52 dB, whereas the return loss and isolation are greater than 20 dB. Yet, the size of this voltage controllable Wilkinson power divider is only 4 mm by 8 mm, which occupies less than 3% area of original Wilkinson power divider structure. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1434–1436, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25181
Income Versus Prices: How Does The Business Cycle Affect Food (In)-Security?

We study how two aspects of food insecurity - caloric insufficiency and diet composition - are affected by aggregate economic fluctuations. The use of cross-country panel data allows us to adopt a global prospective on the identification of the macroeconomic determinants of food insecurity. Income shocks are the most relevant driver of food insecurity, displaying high elasticities at the early stages of economic development. The role of food price shocks is more limited. Social protection has a direct effect and mitigates the impact of income shocks. Effects are highly heterogeneous across a range of structural characteristics of the economy, highlighting the role of distributional aspects and of food import dependency.
Leader Tolerance of Ambiguity: Implications for Follower Performance Outcomes in High and Low Ambiguous Work Situations

Individuals high in tolerance of ambiguity (TOA) are comfortable with, desire, and strive to manage ambiguous situations. We predicted leader TOA would be associated with better follower performance outcomes, depending on the level (Study 1) and nature (Study 2) of follower role ambiguity. Data were collected from employees (Study 1, n = 423) and managerial employees (Study 2, n = 326) who rated their leader on three facets of TOA and provided self-reports of their own performance outcomes. Positive implications of leader TOA for follower learning goal orientation and job performance (Study 1) were most pronounced when followers perceived low role ambiguity and, in the prediction of situational coping (Study 2), when ambiguous work situations were categorized as challenges (unexpected events requiring problem-solving) compared to hindrances. Findings have theoretical implications for understanding when TOA in leaders is optimal and have practical relevance for leaders seeking to adapt to the situational needs of their followers.
Study on the Formation Control Methods for Multi-Agent Based on Geometric Characteristics

Multi-agent formation control is the process in which the teams formed by multiple agents move to specific target or specific direction. The formation method of the linear formation and circular formation are given in this paper, based on the geometric characteristics of the formation formed by multi-agent. The process in which 5 agents arrived at the designated target point and formed a linear formation is achieved through simulation; and 4 agents formed a circular formation and cooperated to carry heavy weights. The result of the three-dimensional simulation shows the feasibility of the method to form multi-agent formations in different environments and different tasks.
Performance of beacon safety message dissemination in Vehicular Ad hoc NETworks (VANETs)

Currently, there is a growing belief that putting an IEEE 802.11-like radio into road vehicles can help the drivers to travel more safely. Message dissemination protocols are primordial for safety vehicular applications. There are two types of safety messages which may be exchanged between vehicles: alarm and beacon. In this paper we investigate the feasibility of deploying safety applications based on beacon message dissemination through extensive simulation study and pay special attention to the safety requirements. Vehicles are supposed to issue these messages periodically to announce to other vehicles their current situation and use received messages for preventing possible unsafe situations. We evaluate the performance of a single-hop dissemination protocol while taking into account the quality of service (QoS) metries like delivery rate and delay. We realize that reliability is the main concern in beacon message dissemination. Thus, a new metric named effective range is defined which gives us more accurate facility for evaluating QoS in safety applications specifically. Then, in order to improve the performance, the effects of three parameters including vehicle’s transmission range, message transmission’s interval time and message payload size are studied. Due to special characteristics of the safety applications, we model the relationship between communication-level QoS and application-level QoS and evaluate them for different classes of safety applications. As a conclusion, the current technology of IEEE 802.11 MAC layer has still some challenges for automatic safety applications but it can provide acceptable QoS to driver assistance safety applications.
Assessment of organisational involvement in implementing empowerment

This paper presents initial findings of ongoing research that is developing a best practice framework for the implementation of empowerment within construction organisations. Data obtained from 53 construction and manufacturing organisations are analysed. Findings confirm 62 empowerment activities, specifically, their respective influence at four organisational levels (strategic, general, operational, and direct work), and the roles of operatives and management, in effectively performing them. It is shown that almost all levels of an organisation have a significant contribution to play in efficiently performing empowerment activities, whilst senior management (at strategic, general, and operational levels) has greatest influence. The investigation also demonstrates that necessary resources and a suitable environment are crucial for successful empowerment implementation.
Nondestructive techniques for investigating semi-insulating gallium arsenide as initial material for direct implantation

The analysis of the effect of initial semi-insulating gallium arsenide quality on microwave ion-implanted metal- semiconductor field-effect transistors (MESFETs) parameters has been carried out. The leakage current method, `photofield-effect transistor with bias on substrate' technique for MESFET structures on GaAs wafers, Hall measurements, optical absorption, photoluminescence, ellipsometry have been used for evaluating semi-insulating gallium arsenide quality. The criteria for sorting initial semi-insulating gallium arsenide as material applicable to direct ion implantation in the process of microwave MESFETs and integrated circuits fabrication have been developed. The possibilities of prognosticating MESFET parameters and their thermal stability are defined by the compensation scheme taking into consideration the presence of deep impurity levels, deep level concentration and peculiarities of their distribution along ingot length and along wafer diameter as well as deep level redistribution during annealing.