Miracle-dz/UniFAR-FTUs huggingface dataset:
Noise Shaping for Phased Array Beamforming

Quantization of phase and/or amplitude has far-reaching effects on the radiation characteristics of the phased array, including gain, minor lobe level, and point deviation. Traditionally, one common method to address such a non-linear distortion is using random-phasing to interrupt the error periodicity. Here, we show that the distortion due to the quantization can be better remediated by spectrally shaping the error compared to the random-phasing (dithering) approaches. We adapted the method for phase-only and amplitude-phase synthesis of planar array designed based on analog beamforming. To do that, for the first time, 2-D real- and complex-coefficient minimum-phase digital FIR filters are designed based on the discrete Hilbert transform method. In particular, the digital filter design for phase-only synthesis is comprehensively investigated, respecting the error spectra in the beamspace domain. It is shown that by pushing the error out of the so-called visible region, the decrease of antenna directivity due to the quantization can be compensated to some extent, which provides a quite advantage over the uniform distribution of error. For some cases, pushing the error out of the visible region might be impossible. For such cases, we proposed using the spaced-notches filter. It is also shown that the method is on maximum efficacy when both phase and amplitude of excitation signal are controllable. Thus, complex-valued noise shaping can be exploited for the phase-amplitude synthesis of the phased array, showing quite promising performance.
Collaborative Impact of Compost and Beneficial Rhizobacteria on Soil Properties, Physiological Attributes, and Productivity of Wheat Subjected to Deficit Irrigation in Salt Affected Soil

Plant growth and crop productivity under unfavorable environmental challenges require a unique strategy to scavenge the severely negative impacts of these challenges such as soil salinity and water stress. Compost and plant growth-promoting rhizobacteria (PGPR) have many beneficial impacts, particularly in plants exposed to different types of stress. Therefore, a field experiment during two successive seasons was conducted to investigate the impact of compost and PGPR either separately or in a combination on exchangeable sodium percentage (ESP), soil enzymes (urease and dehydrogenase), wheat physiology, antioxidant defense system, growth, and productivity under deficient irrigation and soil salinity conditions. Our findings showed that exposure of wheat plants to deficit irrigation in salt-affected soil inhibited wheat growth and development, and eventually reduced crop productivity. However, these injurious impacts were diminished after soil amendment using the combined application of compost and PGPR. This combined application enhanced soil urease and dehydrogenase, ion selectivity, chlorophylls, carotenoids, stomatal conductance, and the relative water content (RWC) whilst reducing ESP, proline content, which eventually increased the yield-related traits of wheat plants under deficient irrigation conditions. Moreover, the coupled application of compost and PGPR reduced the uptake of Na and resulted in an increment in superoxide dismutase (SOD), catalase (CAT), and peroxidase (POX) activities that lessened oxidative damage and improved the nutrient uptake (N, P, and K) of deficiently irrigated wheat plants under soil salinity. It was concluded that to protect wheat plants from environmental stressors, such as water stress and soil salinity, co-application of compost with PGPR was found to be effective.
Data report: A revised composite depth record for Site 1077 based on magnetic susceptibility and XRF core scanner (CORTEX) data

The composite depth scale for Holes 1077A and 1077B (Shipboard Scientific Party, 1998) contains imperfections between 115 and 155 meters composite depth (mcd). The spliced magnetic susceptibility record shows discrepancies when compared to the record of Site 1075 at 120–125 and 140–150 mcd (Ocean Drilling Program [ODP] Site 1077 scale) around marine isotope Stages 22 and 34, respectively. In addition, the offsets applied to transform the standard meters below seafloor (mbsf) depths into composite depths cause overlaps between cores of the same hole at the transitions between Cores 175-1077A-12H and 13H, 175-1077B-12H and 13H, and 175-1077B-13H and 14H. These overlaps are supported neither by visual investigation of the lithology in the core photographs (see “Site 1077 Core Descriptions and Photographs” in Wefer, Berger, Richter, et al., 1998) nor by the pollen and dinoflagellate content. For these reasons, we have reassessed the Site 1077 composite depth scale.
Novel Mixed EWMA Dual-Crosier CUSUM Mean Charts without and with Auxiliary Information

The classical cumulative SUM (CUSUM) chart is commonly used to monitor a particular size of the mean shift. In many real processes, it is assumed that the shift level varies within a range, and the exact level of the shift size is mostly unknown. For detecting a range of shift size, the dual-CUSUM (DC) and dual-Crosier CUSUM (DCC) charts are used to provide better detection ability as compared to the CUSUM and Crosier CUSUM (CC) charts, respectively. This paper introduces a new mixed exponentially weighted moving average (EWMA)-DCC (EDCC) chart to monitor process mean. In addition, AIB-based EWMA-DC (EDC) and EDCC charts (namely, AIB-EDC and AIB-EDCC charts) are suggested to detect shifts in the process mean level. Monte Carlo simulations are used to compute the run length (RL) characteristics of the proposed charts. A detailed comparison of the proposed schemes with other competing charts is also provided. It turns out that the proposed chart provides better performance than the counterparts when detecting a range of mean shift sizes. A real-life application is also presented to illustrate the implementation of the existing and proposed charts.
Day-ahead unit commitment model for microgrids

In this study, a heuristics-based optimisation methodology for a day-ahead unit commitment (UC) model in microgrids is proposed. The model aims to schedule the power among the different microgrid units while minimising the operating costs together with the CO2 emissions produced. A storage device is added where the charge and discharge schedule is calculated according to both objectives. In addition, as a part of the demand side participation strategy, a charging schedule was determined for the electric vehicles (EV) in order to increase the system security and further reduce the costs and emissions. A congestion management approach is also introduced, which eliminates congestions by effective unit scheduling according to congestion signals provided by the distribution system operators. The complete day-ahead time horizon is divided in 96 time steps (each with a 15 min time span), which makes the UC problem more complicated. The studied system includes renewable energy resources, a storage unit, two microturbines, a fuel cell and EVs. The results demonstrate that the proposed model is robust and is able to reduce the microgrid operating costs and emissions by optimal scheduling of the microgrid units, and is able to take into account local congestion problems.
H∞ control for a sensorless permanent-magnet synchronous drive

A robust two degrees of freedom speed controller for a permanent-magnet synchronous motor (PMSM) drive system without using shaft sensor is proposed. The feedback controller and the prefilter are designed in a simple way by extending the utility of the H∞ optimisation procedure. The feedback controller is designed to meet robust stability and disturbance rejection specifications by using the H∞ loop shaping design procedure. For the prefilter the free contractive parameter resulting in H∞ control is used to improve the robust model matching properties of the feedback system. A DSP-based sensorless PMSM drive under the field-oriented control framework is established for experimentally verifying controller performance.
Decision support for additive manufacturing deployment in remote or austere environments

Purpose Additive manufacturing (AM) can reduce the process supply chain and encourage manufacturing innovation in remote or austere environments by producing an array of replacement/spare parts from a single raw material source. The wide variety of AM technologies, materials, and potential use cases necessitates decision support that addresses the diverse considerations of deployable manufacturing. The paper aims to discuss these issues. Design/methodology/approach Semi-structured interviews with potential users are conducted in order to establish a general deployable AM framework. This framework then forms the basis for a decision support tool to help users determine appropriate machines and materials for their desired deployable context. Findings User constraints are separated into process, machine, part, material, environmental, and logistical categories to form a deployable AM framework. These inform a “tiered funnel” selection tool, where each stage requires increased user knowledge of AM and the deployable context. The tool can help users narrow a database of candidate machines and materials to those appropriate for their deployable context. Research limitations/implications Future work will focus on expanding the environments covered by the decision support tool and expanding the user needs pool to incorporate private sector users and users less familiar with AM processes. Practical implications The framework in this paper can influence the growth of existing deployable manufacturing endeavors (e.g. Rapid Equipping Force Expeditionary Lab – Mobile, Army’s Mobile Parts Hospital, etc.) and considerations for future deployable AM systems. Originality/value This work represents novel research to develop both a framework for deployable AM and a user-driven decision support tool to select a process and material for the deployable context.
Determination of Transmission and Reflection Parameters by Analysis of Square Loop Metasurface

In this present work, the transmission and reflection coefficients of the square loop metasurface structure are determined and analyzed by varying the different geometrical parameters of the structure. Initially, the block of 3X 3 square loop cells has been placed centrally in a waveguide and appropriate boundary conditions and excitations are applied. The simulation is carried out with a FEM based electromagnetic solver ‘High Frequency Structure Simulator (HFSS)’. The simulation results show that reflection coefficient relies on the different geometrical parameters and hence the value of reflection coefficient can be controlled from these parameters. Keywords— Square Loop, Metasurface, Reflection coefficient, Transmission coefficient.
Modeling and Applications of Dielectric Substrates at MM-Wave Frequencies and Realization of a New Class of Metamorphic Materials

Author(s): Papio Toda, Anna | Advisor(s): De Flaviis, Franco | Abstract: The millimeter-wave frequency band spectrum represents a great opportunity for ultrahigh-speed, short-range wireless communications and a wealth of new applications such as target positioning or tracking. However, a number of challenges remain for this spectrum to be a viable solution for high-volume consumer applications.One challenge is the determination of the electromagnetic properties of dielectric substrate packaging materials and metamorphic structures. This is vital for the optimal and robust design of beamforming mm-wave systems. In this thesis we present "The Covered Transmission Line Method", a new method to determine the complex permittivity of printed circuit and packaging materials at the mm-wave frequencies. This method is relevant in that it allows for testing of a variety of materials without changes on the setup and with minimal sample processing. Some applications however, require more advanced materials, called metamorphic materials, which are able to change their response to electromagnetic waves. We present in here a unique electromagnetically metamorphic material that can undergo four distinct electromagnetic states (Perfect Electric Conductor, Perfect Magnetic Conductor, Perfect Amplification and Perfect Absorption). Fundamental mathematical and electromagnetic analysis has been used to obtain a full wave analytical model of the scattering properties of this novel composite material. For the first time, a truly metamorphic surface that can precisely be tuned to any electromagnetic state has been fabricated and tested. This is achieved by loading the basic elements (printed circular rings) of the surface with active devices (tunnel diodes) that can sweep their terminal resistance from a high negative to a high positive value. The combination of small wavelength and large available bandwidth make mm-wave target positioning systems a viable option to achieve the desired accuracy. However, such systems require the use of beamforming mm-wave antenna systems to mitigate the high path losses (there are 21 dB more path losses at 60 GHz than at 5 GHz). In this work, we present a novel high-gain beam selection 60 GHz band Grid Array antenna that fulfills the requirements of beamforming, low-cost and small size for integration with mobile devices.Regarding target positioning applications, we study the impact of using beamforming mm-wave antenna systems on the location precision of multiple targets in a realistic indoor environment. The positioning error is assessed when omnidirectional antennas are used at the receiving sensors and when they are substituted by beamforming antennas.
Hardware implementation of deception detection system classifier

Non-verbal features extracted from human face and body are considered as one of the most important indication for revealing the deception state. The Deception Detection System (DDS) is widely applied in different areas like: security, criminal investigation, terrorism detection …etc. In this study, fifteen features are extracted from each participant in the collected database. These features are related to three kinds of non-verbal features these are: facial expressions, head movements and eye gaze. The collected databased contain videos for 102 subjects and there are 888 clip related to both lie and truth response, these clips are used to train and test the system classifier. These fifteen features are placed in a single vector and applied to Support Vector Machine (SVM) classifier to classify input feature vectors into one of two classes either liar or truth-teller class. The detection accuracy of the proposed DDS based on SVM classifier was equal to 89.6396%. Finally, the hardware implementation for SVM classifier is done using the Xilinx block set. The design requires 136 slices and 263 of 4 input LUTs. Moreover, the designed classifier doesn’t require any use of both flip-flops and MULT18X18SIOs. The selected hardware platform (FPGA kit) for implementing the SVM classifier is Spartan-3A 700A.
Transfer and Reuse of Knowledge from the Service Phase of Complex Products

The reuse of knowledge generated during the different phases of a product‘s lifecycle is crucial for a company in order to achieve competitive advantage. This thesis investigates knowledge transfer within the service phase and between service and design phases through case studies from the oil industry. Knowledge generated during the service phase was analyzed from the point of view of service engineers and engineering designers. Furthermore, the mechanisms involved in the transfer of knowledge within the service phase and between service and design were investigated. Both service engineers and engineering designers were interested in knowledge about changes, issues and improvements generated during service; however, engineering designers were more orientated towards knowledge of the equipment at a component level while service engineers were interested in obtaining an overview of the systems. The study showed that knowledge transfer between the service and design departments was not systematic and consisted primarily of knowledge pushed by service engineers to engineering designers. The issues that posed a barrier to a systematic reuse of service knowledge were taken into consideration whilst developing a model for managing the knowledge generated during the service phase. The core of this model, called the RSK model, is the analysis phase, in which information from service cases is evaluated and integrated into existing documentation. The RSK model has been developed based on the case studies from the oil industry, however an auxiliary case study from the aerospace industry indicated it is also suitable to answer the needs of the variant design industry.
Radio propagation into buildings at 912, 1920, and 5990 MHz using microcells

Continuous wave (CW) propagation experiments were conducted at 912, 1920, and 5990 MHz simultaneously using a narrowband system consisting of a fixed transmitter and a mobile receiver. The goal of the experiments was to quantify building penetration losses at various frequencies to determine the viability of indoor coverage using street microcells with base antenna heights below the roof level of nearby buildings. Statistical analysis included the computation of mean building penetration losses, standard deviations, cumulative probability distribution functions, and correlation coefficients. <<ETX>>
Role of indigenous knowledge systems in the conservation of the bio-physical environment among the Teso community in Busia County-Kenya

The indigenous knowledge systems are a significant resource which would contribute to the increased efficiency, effectiveness and sustainability in environmental conservation among rural communities of developing countries in particular. They form the basis for community-level decision making in areas pertaining to food security, human and animal health, education and more important in natural resource management. However, despite their critical role in the conservation of the bio-physical environment, these practices and technologies are being marginalized or even forgotten among rural communities in different parts of the world. To ascertain the role played by these traditional practises on the biophysical environment, this paper identified and established the Teso community indigenous environmental practices and assessed changes in these knowledge systems from the time of Kenya’s pre-independence to the 2000s era. Data were collected using various social science methods such as the questionnaire and focused group discussions. The results showed that the use of totems, protection of sacred places, prohibitions and gender and age restraints declined by 41.3, 68, 41.8 and 38.2%, respectively. The evident decline in the use of the indigenous environmental knowledge systems has negatively impacted on the state of the bio-physical environment exemplified by the Chi-square Pearson (P) values of 0.00 between decline in the use of age and gender restraints and the deterioration in land fertility and only a few elders using the knowledge systems and reduction in the number of rivers, streams and wetlands as exemplified by the Chi-square Pearson (P) value of 0.02. In view of the above, it is recommended that rekindling, recording and preservation of indigenous environmental best practices among local communities such as the Teso for sustainable natural resources management be re-invigorated and integrated in conventional environmental management plans. This also calls for participatory decision-making between policy makers, implementers and actual resource users. Key words: Indigenous knowledge systems, conservation, bio-physical environment
Dynamic load applied to shear pin and motion prediction of flexible hose

A flexible hose that is unwound along with fiber-optic cables from a mother ship helps prevent interference with the mother ship during the unwinding of the fiber-optic cable. Because the density of fiber-optic cables is close to the fluid density, if there is no flexible hose, the fiber-optic cable is more likely to interfere with the mother ship because of the motion of underwater vehicles or mother ships. Hence, it is necessary to prevent the interference of fiber-optic cables by using flexible hoses made of stainless steel. Flexible hoses unwound as an underwater vehicle moves are coupled to the vehicle by shear pins, and once all flexible hoses are unwound, the underwater vehicle continues to move forward as the pins fracture. Here, a dynamic load applied on the shear pin for connection in the early stages of the unwinding of the flexible hose is an important factor that controls the position, which should be accurately predicted, prior to the motion of the underwater vehicle. Further, it is essential that the shear pin of the connection part be designed to fracture under the selected load so that underwater vehicle can continue to move forward as the pin breaks. In this study, analysis results based on loading information measured in real experiments were compared and verified, and based on the findings, an analytical model that can predict loads applied on the shear pin was developed.
Multiscale Partial Symbolic Transfer Entropy for Time-Delay Root Cause Diagnosis in Nonstationary Industrial Processes

Nonstationary characteristics and lack of time delays analysis remain two large obstacles to diagnosing fault root cause in industrial processes. However, ignoring these two issues, many traditional methods tend to introduce some spurious or indirect causal relationships that interfere with root cause judgments. In this article, multiscale partial symbolic transfer entropy (MPSTE) is proposed to handle the above-mentioned problems. On the one hand, a multivariate multiscale filter module of MPSTE is designed to estimate the information transfer on multiple time scales and detect time delays while considering the indirect causality of the multivariate industrial system. On the other hand, to capture the causal information from the nonstationary processes, MPSTE introduces a segmental symbolization procedure and maps time series into finite rank vectors, overcoming the limitation of stationarity. Moreover, two causal criteria for MPSTE are constructed to identify the direction and significance level of causality correspondingly. MPSTE can thus provide sufficient information for causal relationships and exclude spurious causality. Finally, a causal diagram construction strategy with time delay based on MPSTE is established to diagnose the root cause and trace the fault propagation path. The results of experimental verification in a coal mill rig prove the effectiveness of the proposed strategy.
Current and future perspectives on biomaterials for segmental mandibular defect repair

Abstract Segmental mandibular defects are a common problem in head and neck surgery. Osseous free flap transfer has revolutionized mandibular reconstruction; however, donor site morbidity remains a significant problem. Bone tissue engineering (BTE) employs strategies for reconstructing critical-sized bone defects, improving the patients’ quality of life. Scaffolds employed for BTE must be mechanically stable, osseointegrate with neighboring bone, and promote osteogenesis. The need for modified, hybrid constructs with a diversity of favorable characteristics is essential. This review focuses on the recent progresses in modulating the physiochemical properties and applications of biomaterials in BTE in the context of mandibular segmental defect repair. Graphical Abstract