Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Frame Rate Limited Sub-Centimeter Localization System for Hybrid Radio-Optical Wireless Communications

Infrared optical wireless communication (IR-OWC) has received tremendous attention for the high-speed oriented applications. In consideration of issues like power budget and privacy, narrow-width and directional optical beams are commonly applied for IR-OWC. As only users located within specific areas can get the spatially confined optical signals, accurate localization (sub-)systems are required for the central controller to determine the beam-steering strategies. Image-based localization technologies have shown great accuracy performance. However, their localization speed is typically limited by the image transportation delays and processing time. Systematic studies for the phenomena and mechanisms behind the time relevant issues are desired but still rarely reported. Many real-time localization systems and complexity-reduced computation schemes have been published. However, most of the reported systems are performed under rather controlled (ideal) environmental conditions, and issues like deployments and data transportation are commonly neglected. In this paper, a real-time localization testbed for hybrid radio and optical wireless communications is studied. Novel two-stage processes combining quasi-synchronization and local user tracking processing are proposed to increase the localization speed. Comprehensive discussions for the time relevant issues are performed. The detected images are transported through WiFi; hence the localization systems can be flexibly deployed and be easily integrated with the IoT networks. The testbed is implemented under complex environmental conditions to more accurately reveal the practical performance. An overall localization delay of 39.3 ms, which is close to the camera frame rate limitation (29.2 ms), with 0.11 cm localization accuracy is demonstrated for a 1-cm-aperture user device (UD) 180 cm away from the camera.
Daily Energy Usage Estimation Using Regression Based Ensemble Methods

Providing uninterrupted supply energy flow is of in-valuable importance for today's humanity. Because almost every device used today need constant energy to operate flawlessly. However, correct and efficient use of energy is a point that humanity should pay attention to and is often overlooked. Thanks to the developments in technology, the problem of efficient use of energy, in other words, the prediction of energy usage, can now be transferred to computers, more specifically, machine learning methods. From this point of view, in this study, energy usage prediction was considered as a problem that can be solved with machine learning methods. Specifically, the problem was addressed as a regression problem and two powerful ensemble methods, namely Random Forest Regressor (RFR) and Extra Tree Regressor (ETR) methods were used to solve the problem. Both methods were evaluated from the perspective of estimator and maximum depth numbers. Energy data collected from households in the Sceaux region of France for 4 years were used in experiments. Results suggested that mentioned methods were capable of successfully estimating energy usage.
Extending YAGO4 Knowledge Graph with Geospatial Knowledge

We present an extension of YAGO4, the latest version of the YAGO knowledge graph, with qualitative geospatial information representing the administrative organization of Greece. To achieve this, we derive new geospatial information from the Greek Administrative Geography (GAG) dataset, an official source of the administrative divisions of Greece. Our goal has been to extend entities already existing in YAGO4 with geospatial information and add missing entities without introducing duplicate knowledge. Our study should be viewed as a demonstration of how YAGO4 can be extended with administrative geospatial information for the whole world. In addition, it has allowed us to uncover certain issues that exist with the representation and querying of geospatial information in schema.org and YAGO4 which we discuss in detail.
Hyperspectral Super-resolution Accounting for Spectral Variability: Coupled Tensor LL1-Based Recovery and Blind Unmixing of the Unknown Super-resolution Image

In this paper, we propose to jointly solve the hyperspectral super-resolution problem and the unmix-6 ing problem of the underlying super-resolution image using a coupled LL1 block-tensor decomposi-7 tion. We consider a spectral variability phenomenon occurring between the observed low-resolution 8 images. Exact recovery conditions for the image and mixing factors are provided. We propose two 9 algorithms: an unconstrained one and another one subject to non-negativity constraints, to solve 10 the problems at hand. We showcase performance of the proposed approach on synthetic and real 11 images.
An Architecture Smell Knowledge Base for Managing Architecture Technical Debt

Many software projects suffer from architecture erosion and archi-tecture technical debt. One challenge is to identify affected parts and prioritize them for refactoring. Architecture smells are indica-tors of potential architecture technical debt, but architecture smells are ambiguous and their impact is not always clear. To address this, we have built a knowledge base that improves understanding of architecture smells and identifies violated software design prin-ciples and affected quality attributes. The design principles help our understanding of what causes architecture smells, while the impaired quality attributes represent the consequences. We con-ducted a systematic literature review to identify these relations and built an architecture smell ontology. This ontology provides a knowledge base that architects can use to prioritize the smells according to the project's individual quality goals.
A Measurement Method for Determining Speed of High-Speed Rotating Parts

This paper focuses on determining the speed of a high-speed rotating part, the gear of a starter motor, without disassembling the product. During the design process of the measurement method, the implementation of a machine vision system was chosen. Instead of using high-speed cameras, image acquisition was implemented by using line scan technology. Verification of the measurement data was performed using an asynchronous motor controlled by a frequency converter. The paper presents the measurement method based on image acquisition and summarizes the experiences gained during the testing process.
Examples of processing low-frequency oscillations in Russia and ways to improve the analysis

The current state of the synchrophasor measurement (SPM) technology opens up new possibilities for analyzing the operating modes of power systems. One of the most important applications of processing the SPM data is monitoring of the power system oscillatory stability. It includes the analysis of low-frequency oscillations (LFO). The problem of detecting the source of LFO is one of the most urgent. This paper considers the methods for detecting the LFO source. One of them estimates the quantity and direction of the flow of oscillation energy. Another one compares the amplitude-phase characteristics of the processed signals. Examples of real LFO in the Russian power system, given in the paper, illustrate various aspects of the analysis. The research proposes ways to improve the methods of analysis of the LFO based on the ideas about the structure of the phasor measurement units signals.
A Mixed E/E-Architecture for Interconnected Operating Tables Inspired by the Automotive Industry

The medical device industry faces new challenges in an increasingly connected environment. In addition, with interoperable medical devices, flexibility and adaptability are gaining more importance. Meanwhile, to support a higher degree of flexibility for adaptations during and after the development process, new communication paradigms are gaining practical importance in the automotive industry.In this paper, we compare the state-of-the-art measures from the automotive domain for requirements of future interconnected Operating-Room-Tables (OR-Tables). Based on these requirements, we propose a mixed architecture and present an Identity and Access Management (IAM) approach to improving the security of the system.
PCMCsim: An Accurate Phase-Change Memory Controller Simulator and its Performance Analysis

With the growing demand for technology scaling and storage capacity in data centers, phase-change memory (PCM) has garnered attention as a next-generation nonvolatile memory (NVM). However, an accurate simulator that includes the necessary hardware features for PCM is not available, lagging behind current PCM technology. In this study, a functional and cycle-accurate PCM controller simulator, called PCMCsim, is presented to revitalize the related research. The proposed simulator incorporates necessary features for current PCM products and the latest DDR5 specifications. Based on rigorous performance analysis, this study characterizes bottlenecks of the PCM subsystem by sweeping hardware parameters, providing important takeaway messages to designers. Furthermore, the latency is significantly reduced by introducing a dedicated prefetcher into the address translation module. The proposed simulator is validated against a command trace made by a PCM product developer. We release our simulator as open-source software, except for industry-confidential features.11https://github.com/harrylee365/pcmcsim-pub1ic
Comprehending the Use of Intelligent Techniques to Support Technical Debt Management

Technical Debt (TD) refers to the consequences of taking shortcuts when developing software. Technical Debt Management (TDM) becomes complex since it relies on a decision process based on multiple and heterogeneous data, which are not straightforward to be synthesized. In this context, there is a promising opportunity to use Intelligent Techniques to support TDM activities since these techniques explore data for knowledge discovery, reasoning, learning, or supporting decision-making. Although these techniques can be used for improving TDM activities, there is no empirical study exploring this research area. This study aims to identify and analyze solutions based on Intelligent Techniques employed to sup-port TDM activities. A Systematic Mapping Study was performed, covering publications between 2010 and 2020. From 2276 extracted studies, we selected 111 unique studies. We found a positive trend in applying Intelligent Techniques to support TDM activities, being Machine Learning, Reasoning Under Uncertainty, and Natu-ral Language Processing the most recurrent ones. Identification, measurement, and monitoring were the more recurrent TDM ac-tivities, whereas Design, Code, and Architectural were the most frequently investigated TD types. Although the research area is up-and-coming, it is still in its infancy, and this study provides a baseline for future research.
HyCo: A Low-Latency Hybrid Control Plane for Optical Interconnection Networks

Next-generation multiprocessor systems point to the integration of a large number of cores (e.g., processing and memory) where electrical networks-on-chip (eNoCs) can improve the communication performance. As the number of integrated cores increases, metallic interconnect in eNoCs becomes a bottleneck, leading to communication performance degradation and increased power consumption. Optical interconnection networks (OINs) have emerged to outperform the communication infrastructure in multiprocessor systems. Nevertheless, OINs’ full capability is curbed by high latency electrical controllers required to orchestrate and (re)configure the underlying photonic components, realizing a path between sending and receiving cores. Control techniques impose a high latency to perform the network routing, limiting the full utilization of OINs. In this paper, we design a novel low-latency Hybrid Controller (HyCo) that employs acceleration techniques to reduce its execution time. HyCo is developed based on integrating centralized and distributed control techniques as well as by using pre-calculated network routes and a Bloom filter, all of which result in a considerable reduction in HyCo’s latency. Simulation and prototyping results for networks up to 64×64 indicate a latency smaller than 50 ns, in the worst-case scenario.
Integrated energy scheduling under uncertainty in a micro energy grid

It is expected that different energy infrastructures and resources to be operated and planned simultaneously in the future smart energy systems. Recently, the concept of energy hub and its corresponding management systems has been proposed in multi-carrier energy systems. The presented study develops a two-stage stochastic mixed-integer linear programming model for a day-ahead energy scheduling of a multi-carrier energy system, considering the time-varying energy price signals and volatility feature of renewable energy resources. In the framework of the proposed method, the objective is set to minimise the energy hub's total cost, while finding the optimal values for decision variables. A set of valid scenarios is considered for the uncertainties of loads and solar energy resources. Finally, the proposed stochastic day-ahead optimisation is tested in a case study situation. In the process of minimising the operational cost, an energy hub operator is able to fix some decisions such as energy exchange with the main grid and unit commitment, before the actual realisation of the uncertain parameters is observed. The unit commitment results also are compared with those produced by a deterministic model for the case in which the electricity flow is bidirectional.
Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.
Optimum design and machining parameters of a permanent magnet brushless DC linear motor as a CNC feed drive

OPTIMUM DESIGN AND MACHINING PARAMETERS OF A PERMANENT MAGNET BRUSHLESS DC LINEAR MOTOR AS A CNC FEED DRIVE by William Tereshkovich A new heuristic has been developed to determine optimal operating parameters applied to a permanent magnet brushless DC linear motor (PMBDCLM) as a CNC feed drive. An FEA model has been developed utilizing an electromagnetic postprocessor to provide performance output of a PMBDCLM and DC servomotor. Based on the developed FEA models, velocity results have been utilized to provide feedrate levels for design of experiments (DOE). DOE has been conducted to provide force, tolerance, and surface finish . data necessary for the performance comparison of a DC servo motor/ballscrew equipped CNC vertical milling machine and a PMBDCLM equipped CNC vertical milling machine. Based on the DOE, a knowledge base has been developed using force, tolerance, and surface finish data. Relationships between force, and spindle speed and feedrate with tolerance and surface finish indices were determined. A heuristic has been developed which represents a guide of applying a set of decisions through the knowledge base to provide a set of operating parameters that will meet user specified tolerance and surface finish requirements for given surfaces. Application of the developed heuristic to a milled part is illustrated. A PMBDCLM CNC retrofit for a conventional ballscrew feed drive system has also been developed to improve machine performance and cost. Copyright © 2000 by William Tereshkovich ALL RIGHTS RESERVED OPTIMUM DESIGN AND MACHINING PARAMETERS OF A PERMANENT MAGNET BRUSHLESS DC LINEAR MOTOR AS A CNC FEED DRIVE by William Tereshkovich A Dissertation Submitted to the Faculty of New Jersey Institute of Technology In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Industrial Engineering Department of Industrial and Manufacturing Engineering
Marketing plan for Neustile roof tile for CPAC Roof Tile Co., Ltd. (Thailand)

Roof tile products play a significant role in the market of Thailand. The CPAC Roof Tile Co., Ltd., a member company of the Siam Cement Group, is Thailand's original and largest manufacturer of concrete roof tiles, which are sold as CPAC Monier brand name products. The company is now engaged in a joint venture with LAFARGE, a global leader in concrete roof tile production technology. This thesis is divided into five chapters. The first chapter structures the joint venture by introduction including company background, problem statement, purpose of the project, benefits of the project, and limitation of the project. The second chapter reviews the literature focusing on marketing definition, marketing concept, the scope of marketing, the product life cycle, marketing mix, SWOT analysis, customer analysis, marketing plan, marketing strategy, industrial market, and industry in Thailand market. The third chapter discusses the methodology of the thesis by focusing on instrumentation and data preparation. The fourth chapter contains results and analysis of the study. They include current situation, marketing objective, marketing strategy, product personality and brand positioning, selling point, segment analysis, target group and influencer, and product
The Corpus Based Approach to Sentiment Analysis in Modern Standard Arabic and Arabic Dialects: A Literature Review

Sentiment Analysis, is the analysis of ideas, emotions, evaluations, values, attitudes and feelings about products, services, companies, individuals, tasks, events, titles and their characteristics. With the increase in applications on the Internet and social networks, Sentiment Analysis has taken a considerable place in the field of text mining research and has since been used to explore the opinions of users about various products or topics discussed over the Internet. When the literature on Sentiment Analysis is examined, it is seen that the natural language of the Internet information sources that form the basis of the analysis is mostly English. Developments in the fields of Natural Language Processing and Computational Linguistics have contributed positively to Sentiment Analysis studies made from natural languages other than English. The purpose of this study is to examine the literature of Sentiment Analysis conducted in Arabic internet information sources. The literature review includes studies based on the corpus approach, which is made up of Arabic Internet information sources. Studies are being carried out on the works which constitute their own corpora for both Modern Standard Arabic and Arabic dialects and on which sentiment analysis is performed.
Enhanced Voltage Stability Assessment Index Based Planning Approach for Mesh Distribution Systems

This paper offers an enhanced voltage stability assessment index (VSAI) and loss minimalize condition (LMC) centered integrated planning approach. The proposed method aims at the simultaneous attainment of voltage stability, loss minimizations and various other related objectives with the employment of multiple distributed generation (DG) units, in mesh distribution systems (MDS). The approach presents two enhanced VSAI expressions based on a multiple-loops configured equivalent MDS model. The main objective of each VSAI expression is to find the weakest buses as potential candidates for single and multiple DG placements with initial optimal DG sizes for aimed objectives attainment in MDS. Later, mathematical expressions for LMC have been presented, based on equivalent MDS model. The LMC aims to achieve significant loss minimization with optimal DG sizes and attain negligible voltage difference across tie-line branches via reduction of respective loop currents. The proposed integrated VSAI-LMC based planning approach is employed with two computation variants and tested on two well-known, 33-Bus and 69-Bus, test distribution systems (TDS). The performance analysis of each TDS is conducted with two cases and respective scenarios, across various performance evaluation indicators (PEIs). The paper also offers a comparative analysis of achieved numerical outcomes of the proposed planning approach with the available research works found in the literature. The numerical results attained have better performance in comparison with the presented literature data and thus shows the effectiveness and validity of the proposed planning approach.
Understanding and predicting the electronic and dynamic behavior of nanoscale magnetic random access memory (MRAM) cells using micromagnetic modelling and simulation

In recent years, micromagnetic simulation has evolved into a vital tool for understanding and optimizing the electronic and dynamic properties of magnetic structures on the nanometer scale. The main focus of current research has moved from establishment of correct models and simulation tools to understanding the results furnished by such tools, with the exception of two major fields that are currently given much attention. The first is the study of the interaction between the magnetization or spin of a ferromagnetic material with electric currents, and secondly the study of the dynamic properties in such nanomagnets when switching between different magnetization states, e.g., spin wave modes, damping, etc. We have adapted an existing simulation code by optimizing its performance for dynamic simulations, integrated a feature that computes one type of current-spin interaction, and computed the Fourier transformation into frequency space thus revealing the spin wave modes of typical nanomagnetic structures. In this paper, we present the fundamental equations and methods implemented in the simulation of current-spin interactions and in the calculation of spin wave modes, as well as results from these simulations and computations.
Design of compact wideband bandpass filter with broad stopband using hybrid HMSIW and open‐circuit tri‐section stepped impedance resonators

A compact wideband bandpass filter (BPF) with broad stopband using hybrid half‐mode substrate integrated waveguide (HMSIW) resonator and open‐circuit tri‐section SIRs (OTSIRs) is proposed. A BPF with 3 transmission poles (TPs) and 3 transmission zeros is obtained by cascading the HMSIW resonator and OTSIRs using J and K inverters. A demonstrated wideband BPF with the stopband up to 4.4 times the designed center frequency for a 20 dB rejection level is designed, fabricated and measured. The measured results verify the predicted attractive features.