Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Erlang Distribution for Software Size Estimation

The Program Evaluation and Review Technique (PERT) model is one of the most popular methods for estimating software size and, sometimes, development effort. It mainly relies on expert judgment to estimate the ultimate size of a project. However, the basic assumption of this technique may be incorrect. The issue addressed in this paper concerns the weakness of the PERT model and proposes applying Erlang distribution to tackle this problem. An example has been included to show the effectiveness of this new model
Parallel Run-Time Verification

Run-time verification is a technique to reason about a program correctness. Given a set of desirable properties and a program trace from the inspected program as an input, the monitor module verifies that properties hold on this trace. As this process is taking place at a run time, one of the major drawbacks of run-time verification is the execution overhead caused by a monitoring activity. In this thesis, we intend to minimize this overhead by presenting a collection of parallel verification algorithms. The algorithms verify properties correctness in a parallel fashion, decreasing the verification time by dispersion of computationally intensive calculations over multiple cores (first level of parallelism). We designed the algorithms with the intention to exploit a data-level parallelism, thus specifically suitable to run on Graphics Processing Units (GPUs), although can be utilized on multi-core platforms as well. Running the inspected program and the monitor module on separate platforms (second level of parallelism) results in several advantages: minimization of interference between the monitor and the program, faster processing for non-trivial computations, and even significant reduction in power consumption (when the monitor is running on GPU). This work also aims to provide a solution to automated run-time verification of C programs by implementing the aforementioned set of algorithms in the monitoring tool called GPU-based online and offline Monitoring Framework (GooMF). The ultimate goal of GooMF is to supply developers with an easy-to-use and flexible verification API that requires minimal knowledge of formal languages and techniques.
Laser‐based SLAM automatic parallel parking path planning and tracking for passenger vehicle

Automatic parking system (APS) plays an important role in alleviating drivers' burden and improving vehicle safety. This study proposes a laser-based simultaneous localisation and mapping (SLAM) automatic parallel parking and tracking control scheme, which include environment perception and reconstruction, parking path planning, and path following. First, the proposed approach selects short-range lidar to enlarge its perceptron on parking environment and senses available parking space to build neighbourhood mapping with the help of simultaneous localisation. The test evaluation indicates that laser-SLAM has achieved good performance for recognising free spaces. Then, scene-dependent B-spline parallel parking path planning algorithm is proposed to optimise the parking path curve and makes the path meet vehicle kinematics model constrains well, in which vehicle actuator's dynamic performance and parking path smoothness are taken as key attributes. The experiment results indicate that the designed parallel parking path is better smooth. At last, a path following control method based on model predictive control (MPC) algorithm is proposed. The authors built an intelligent vehicle APS platform, and the results indicate that the designed MPC algorithms has excellent robustness and can minimise the tracking error. All the proposed scheme is quantitatively evaluated using different parking scene simulation with satisfactory performance.
Short-Circuit Constrained Power System Expansion Planning Considering Bundling and Voltage Levels of Lines

System expansion planning (SEP) models do not generally represent voltage levels, bundled conductors in transmission lines, and short-circuit limits. These modeling assumptions may result in suboptimal planning outcomes. To overcome this potential flaw, we propose a short-circuit constrained dynamic SEP (SC-SEP) that allows for investment decisions at different stages of the planning horizon and includes a detailed representation of voltage levels, alternative bundled conductor options per line and short-circuit limits. An effective linearization technique is used to transform the resulting mixed-integer nonlinear model into a mixed-integer linear one. The accuracy of the proposed model and the effectiveness of the proposed linearization technique are illustrated using the IEEE 39-bus system.
Research and Application of a Novel Hybrid Model Based on a Deep Neural Network for Electricity Load Forecasting: A Case Study in Australia

Electricity load forecasting plays an essential role in improving the management efficiency of power generation systems. A large number of load forecasting models aiming at promoting the forecasting effectiveness have been put forward in the past. However, many traditional models have no consideration for the significance of data preprocessing and the constraints of individual forecasting models. Moreover, most of them only focus on the forecasting accuracy but ignore the forecasting stability, resulting in nonoptimal performance in practical applications. This paper presents a novel hybrid model that combines an advanced data preprocessing strategy, a deep neural network, and an avant-garde multi-objective optimization algorithm, overcoming the defects of traditional models and thus improving the forecasting performance effectively. In order to evaluate the validity of the proposed hybrid model, the electricity load data sampled in 30-min intervals from Queensland, Australia are used as a case to study. The experiments show that the new proposed model is obviously superior to all other traditional models. Furthermore, it provides an effective technical forecasting means for smart grid management.
Methodology and decentralised control of modularised changeable conveyor logistics system

ABSTRACT To comply with the trend of customised production, this paper proposes a novel methodology for a changeable logistics system on certain factory scenes. By modularising the traditional conveyor belt system and applying decentralised control to each module, the changeable conveyor system can quickly reassemble itself for different logistics routes and thus react to the changing requirements of new production plans. The logistics route transformation is organised in two stages while reassembling. First, the modules calculate their paths on their own towards the assigned positions using a modified Rapid-exploring Random Tree (RRT) algorithm with the introduction of orientation factor (α-factor) to increase path smoothness; then a sensor-based Artificial Potential Field (APF) algorithm is applied for real-time collision avoidance with the sensor orientation and data weight being specially arranged. Through these two stages, the proposed system can flexibly react to changing logistics demands and form various logistics routes in the factory layout according to customised production requirements. Simulations and comparisons are given to illustrate the performances of the method.
Stability Analysis of Grid-Connected Photovoltaic Systems with Dynamic Phasor Model

The typical layout of power systems is experiencing significant change, due to the high penetration of renewable energy sources (RESs). The ongoing evaluation of power systems is expecting more detailed and accurate mathematical modeling approaches for RESs which are dominated by power electronics. Although modeling techniques based on state–space averaging (SSA) have traditionally been used to mathematically represent the dynamics of power systems, the performance of such a model-based system degrades under high switching frequency. The multi-frequency averaging (MFA)-based higher-index dynamic phasor modeling tool is proposed in this paper, which is entirely new and can provide better estimations of dynamics. Dynamic stability analysis is presented in this paper for the MFA-based higher-index dynamical model of single-stage single-phase (SSSP) grid-connected photovoltaic (PV) systems under different switching frequencies.
Temperature Invariant Phenomenon in Dual Coil Eddy Current Displacement Sensor: Investigation, Verification and Application

To figure out the temperature drift problem in a dual coil eddy current displacement sensor (DC-ECDS) which is widely applied in food industry, the structure and working principle of DC-ECDS was descripted first. Then, the influence of the working temperature of the DC-ECDS on the difference signal from the dual coils was deeply investigated by the numerical simulation and experimental study. By the investigation, the temperature-invariant phenomenon (TIP) was found in the embedded DC-ECDS and non-embedded DC-ECDS. The interesting thing was that in the temperature invariant region (TIR), the impact of the working temperature on the difference signal could be neglected. Next, we found that the location of TIR was dependent of the excitation frequency and the geometric size of the electromagnetic shielding ring of the DC-ECDS. Finally, the TIP was applied in designing a novel eddy current limit switch, which exhibited the stable output regardless of working temperature change.
CeHRes roadmap utilization in development of eHealth technology solutions : a Scoping review

eHealth can be defined as health care field that is using Information and Communication Technologies. There is variety of different technologies that can be used in eHealth and the field is evolving via new inventions. Users in eHealth are coming from several user groups from health care professionals to patients and external users. Development of eHealth technology solutions can fill increasing demands of health care field that are caused by longer life expectancy. Despite all the benefits that utilization of eHealth technology can bring for health care sector, it has also some barriers that are delaying adoption of eHealth technology solutions. To overcome these barriers CeHRes Roadmap was created to support and guide eHealth technology development and it is meant for developers, researchers, policy makers, and for educational purposes. CeHRes Roadmap is visualizing Holistic framework and it is based on participatory development approach, persuasive design techniques, and business modelling. Objective of this master’s thesis is to identify, collect, and characterize all relevant research that is using CeHRes Roadmap in developing eHealth technologies published from year 2011 onwards. Research articles are analysed geographically, in terms of technology and medical domain, and characterizing and categorizing CeHRes Roadmap elements and attributes. Research method in this thesis was Scoping review that is literature review method that aim to map rapidly relevant literature and is suitable for broad topics. Literature search was done from Scopus, Web of Science, IEEE, PubMed, and Cinahl. Due to multidisciplinary nature of topic search was done for databases that contain material from Information processing science and/or medical science. 26 studies were identified to be relevant for this research. Results of this master’s thesis indicate that usage of CeHRes Roadmap has been most common in Netherlands, but it has been recognized and referenced in hundreds of studies. As the roadmap is not restricting usage to particular technology area, variety of used technologies were wide and several different medical domains using CeHRes roadmap were found. When analysing CeHRes Roadmap characteristics, participatory development was found to be the key characteristic that was visible in almost every selected study. This thesis provides inventory of studies that have used CeHRes Roadmap in development work and give insight how it has been used.
Conceptual Framework of Antecedents to Trends on Permanent Magnet Synchronous Generators for Wind Energy Conversion Systems

Wind Energy Conversion System (WECS) plays an inevitable role across the world. WECS consist of many components and equipment’s such as turbines, hub assembly, yaw mechanism, electrical machines; power electronics based power conditioning units, protection devices, rotor, blades, main shaft, gear-box, mainframe, transmission systems and etc. These machinery and devices technologies have been developed on gradually and steadily. The electrical machine used to convert mechanical rotational energy into electrical energy is the core of any WECS. Many electrical machines (generator) has been used in WECS, among the generators the Permanent Magnet Synchronous Generators (PMSGs) have gained special focus, been connected with wind farms to become the most desirable due to its enhanced efficiency in power conversion from wind energy turbine. This article provides a review of literatures and highlights the updates, progresses, and revolutionary trends observed in WECS-based PMSGs. The study also compares the geared and direct-driven conversion systems. Further, the classifications of electrical machines that are utilized in WECS are also discussed. The literature review covers the analysis of design aspects by taking various topologies of PMSGs into consideration. In the final sections, the PMSGs are reviewed and compared for further investigations. This review article predominantly emphasizes the conceptual framework that shed insights on the research challenges present in conducting the proposed works such as analysis, suitability, design, and control of PMSGs for WECS.
Numerical Investigation of Flow through a Valve during Charge Intake in a DISI -Engine Using Large Eddy Simulation

Apart from electric vehicles, most internal combustion (IC) engines are powered while burning petroleum-based fossil or alternative fuels after mixing with inducted air. Thereby the operations of mixing and combustion evolve in a turbulent flow environment created during the intake phase and then intensified by the piston motion and influenced by the shape of combustion chamber. In particular, the swirl and turbulence levels existing immediately before and during combustion affect the evolution of these processes and determine engine performance, noise and pollutant emissions. Both the turbulence characteristics and the bulk flow pattern in the cylinder are strongly affected by the inlet port and valve design. In the present paper, large eddy simulation (LES) is appraised and applied to studying the turbulent fluid flow around the intake valve of a single cylinder IC-engine as represented by the so called magnetic resonance velocimetry (MRV) flow bench configuration with a relatively large Reynolds number of 45,000. To avoid an intense mesh refinement near the wall, various subgrid scale models for LES; namely the Smagorinsky, wall adapting local eddy (WALE) model, SIGMA, and dynamic one equation models, are employed in combination with an appropriate wall function. For comparison purposes, the standard RANS (Reynolds-averaged Navier–Stokes) k- ε model is also used. In terms of a global mean error index for the velocity results obtained from all the models, at first it turns out that all the subgrid models show similar predictive capability except the Smagorinsky model, while the standard k- ε model experiences a higher normalized mean absolute error (nMAE) of velocity once compared with MRV data. Secondly, based on the cost-accuracy criteria, the WALE model is used with a fine mesh of ≈39 millions control volumes, the averaged velocity results showed excellent agreement between LES and MRV measurements, revealing the high prediction capability of the suggested LES tool for valve flows. Thirdly, the turbulent flow across the valve curtain clearly featured a back flow resulting in a high speed intake jet in the middle. Comprehensive LES data are generated to carry out statistical analysis in terms of (1) evolution of the turbulent morphology across the valve passage relying on the flow anisotropy map, (2) integral turbulent scales along the intake-charge stream, (3) turbulent flow properties such as turbulent kinetic energy, turbulent velocity and its intensity within the most critical zone in intake-port and along the port length, it further transpires that the most turbulence are generated across the valve passage and these are responsible for the in-cylinder turbulence.
Design of a new balun bandpass filter with single‐band balance and dual‐band filtering characteristics

In this article, a new type of balun bandpass filter with single‐band balance and dual‐band filtering function is presented. For this purpose, a novel compact dual‐mode open loop resonator with short‐circuited stubs and interdigital capacitors is proposed. Two identical resonators are coupled to two output ports in order to obtain 180° phase difference between the output ports. By means of the changes in the short‐circuited stubs and interdigital capacitors, control of the passbands at two output ports can be achieved. In addition, as the short‐circuited stubs are located at the same wave traveling paths, phase difference cannot be obtained in the first passband and only the second passband has balun function. The designed balun bandpass filter was fabricated and tested for the experimental verifications. Phase difference and magnitude imbalance have been measured within 180° ± 2° and 0.5 dB, respectively. The measured results exhibit a very good agreement with the predicted results.
Metal Additive Manufacturing Cycle in Aerospace Industry: A Comprehensive Review

Additive Manufacturing (AM) is the forefront of advanced manufacturing technologies and has the potential to revolutionize manufacturing, with a dramatic change in the design and project paradigms. A comprehensive review of existent metal AM processes, processable materials, respective defects and inspection methods (destructive and non-destructive) is presented in a succinct manner. Particularly, the AM design optimization methodologies are reviewed and their threats and constraints discussed. Finally, an aerospace industry case study is presented and several cost-effective examples are enumerated.
Complexity Analysis of the Kramers–Kronig Receiver

We propose a low-complexity digital implementation of the Kramers–Kronig receiver and analyze its performance and complexity. In simulations and experiments, we find that a relatively small number of filter taps is sufficient to achieve a reasonably high accuracy for the phase retrieval and for the reconstruction of the complex field. We show that the Kramers–Kronig receiver performance strongly depends on details of the system design. Unnecessarily broad optical filters decrease the reception quality, because additional noise makes the violation of the minimum-phase condition more likely. Narrow optical filters, however, impose high local oscillator laser stability and reduce the flexibility of this kind of receiver architecture. Further, we demonstrate Kramers–Kronig reception of 16 QAM signals at a net data rate of 267 Gbit/s after transmission over 300 km of standard single-mode fiber. We compare the performance with a conventional intradyne receiver. In a back-to-back setting, we increase the net data rate to 300 Gbit/s.
An analysis of strengths and weaknesses of SCM strategies in medical technology OEMs: a perspective from German manufacturers

Original Equipment Manufacturers (OEMs) in the German Medical Technology (MT) sector are facing a strong competition from low-wage countries developing, manufacturing, and distributing high-quality products globally. For this reason, organisations in this sector require orientation in the implementation of SCM policies to reduce operating cost and to create value for their customers. A multiple case study was conducted to identify SCM issues and best practices in this sector. This study contributes to healthcare operations management literature with a tailor-made assessment tool. Its findings offer new priorities for managers, particularly if they are contemplating a re-engineering of their SCM strategies.
Approximate loop unrolling

We introduce Approximate Unrolling, a compiler loop optimization that reduces execution time and energy consumption, exploiting code regions that can endure some approximation and still produce acceptable results. Specifically, this work focuses on counted loops that map a function over the elements of an array. Approximate Unrolling transforms loops similarly to Loop Unrolling. However, unlike its exact counterpart, our optimization does not unroll loops by adding exact copies of the loop's body. Instead, it adds code that interpolates the results of previous iterations.
Strength and stability studies of ring-stiffened circular cylindrical shells using self-organising maps (SOM) and data mining analysis

ABSTRACT Ring-stiffened circular cylindrical shells are commonly used in many engineering applications. In the present study, the strength and stability characteristics of ring-stiffened circular cylindrical shells are investigated using self-organising map (SOM) technique and multivariate approaches. Stress and critical pressure analysis of ring-stiffened circular cylindrical shells under hydrostatic pressure are obtained from the design guide. Design of experiment (DOE) technique is employed for generating design samples. The information behind these design samples can be studied by the self-organising map (SOM) approach. Multivariate analysis is adopted for post- processing of SOM's results. The clustering of samples can be obtained from the codebook of SOM with the help of multivariate analysis. The samples in different clusters would have their own characteristics. The variable significance in each cluster is examined. The dimensionality reduction approach is used for finding the structure of the data set. A useful visualisation approach, parallel coordinate plot with clustering information, is proposed for visualisation of design samples. Correlations and clustering of variables are also studied by the hierarchical method. The ranking of samples is conducted by minimising the distance to an ‘ideal’ solution in the data set. A final compromises sample is obtained. A numerical example is provided for the illustration of the present analysis.
Classical Descriptive Set Theory

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