Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Some Characteristics of Congested Flow

Recent German research has suggested that there may be two qualitatively different types of congested flow, referred to as “traffic jams” and “synchronized flow. ” The possible existence of synchronized flow raises a theoretical issue, since it is reported to be characterized by randomly sloped flow-density “transferences” (lines connecting adjacent points in the time series), and this may imply that there is no consistent wave direction in such flow. An analysis of flow-occupancy data from San Diego suggests that on the basis of the appearance of the data alone, two types of congested flow may be identified. These appear to be similar to, but not identical with, the two types reported in the German work; in particular, a region with positively sloped flow transferences was found. Further consideration of the data and the mechanics of congested flow suggests, however, that these two types of flow do not represent qualitatively different types of traffic behavior but rather are the result of random variations in average time gaps in the traffic stream and the relationship among speed, flow, density, and average time gap. In particular, predominantly positively sloped flow-concentration transferences do not necessarily imply that waves move downstream; rather they imply that, for data taken over short time intervals (30 s or 1 min), transferences are not a good indicator of kinematic wave speed.
Range-Doppler Spectrograms-Based Clutter Suppression of HF Passive Bistatic Radar by D-CycleGAN

As a new attempt to reject clutter in High Frequency Passive Bistatic Radar (HFPBR), the Cycle-Consistent Adversarial Network (CycleGAN)-based image domain clutter suppression algorithm works successfully by treating the clutter rejection problem as an image-to-image migration between the range-doppler spectrograms without and with clutter suppression. However, this algorithm also has some disadvantages such as too many calculation parameters, difficult model training and low clutter suppression rate. In this paper, a novel clutter suppression method based on an improved DenseNet CycleGAN (D-CycleGAN) is proposed. In this method, the ResNet block of the generator in the original CycleGAN network is replaced with the DenseNet block, to better extract clutter features. To better evaluate the clutter suppression performance of the deep learning network-based graph-relational method, a new index suitable for HF passive radar is introduced. Furthermore, the influence of the number of Dense blocks on the performance of the algorithm is also discussed. Finally, the performance of the proposed method is tested and verified on the measured data, compared with the traditional clutter suppression method and other popular image migration algorithms, such as Pix2pix. The results show that the D-CycleGAN-based method has better clutter suppression performance, stronger generalization ability, and better retained radar targets simultaneously.
Urban drainage in Ireland – embracing sustainable systems

The current approach to stormwater management in Ireland requires that outflows from new developments are restricted to greenfield values that would have occurred prior to development. This typically involved the use of holding tanks constructed within developments to attenuate stormwater from where it was released at a reduced rate via a control structure to a nearby drainage network or watercourse. Improved drainage policies now require that sustainable drainage systems (SuDS) are used to meet this objective. This study presents an evaluation of perceived issues that may impede the adoption of new policies. The findings are based on surveys and focus groups of practitioners involved with the planning and design of drainage systems. Although the study indicates that benefits of SuDS are reasonably well understood, their use, for many reasons, has remained less popular. Concerns with ongoing maintenance and long‐term responsibility of SuDS remain impediments to the embracing of these systems in drainage strategies.
SAP PRODUCT LIFECYCLE MANAGEMENT Manajemen Siklus Hidup Produk SAP

Dengan adanya teknologi menyebabkan inovasi sangat pesat, sehingga siklus hidup produk (product life cycle) menjadi semakin pendek. Semakin pendeknya siklus hidup produk, semakin memerlukan perencanaan yang matang atas keseluruhan pendapatan dan bisaya selama siklus hidup agar investasi yang dilakukan perusahaan untuk desain dan pengembangan produk dapat tertutup dari kas masuk bersih selama siklus hidup produk yang diperkirakan. Biaya pengembangan produk dan biaya logistic merupakan biaya yang cukup besar proporsinya dan berpengaruh terhadap kelangsungan hidup produk yang bersangkutan, sehingga perlu diperhitungkan dalam penetapan harga pokok produk sekaligus dapat menetapkan harga jual.
Lipid Phase Distribution and Acoustic Response of DSPE-based Microbubbles

Microbubbles (MBs) are versatile ultrasound contrast agents that can be used for ultrasound molecular imaging and targeted drug delivery. However, a uniform and controlled response to ultrasound is essential for safe and effective use of targeted MBs in the clinic. It is suggested that the heterogeneous lipid distribution of currently available MB formulations causes variability in acoustic response. Hence, the objective of this study was to develop and characterize a new MB formulation with all coating components miscible and in the same lipid phase. MBs with 1,2-distearoyl-sn-glycero-3-phosphoethanolamine (DSPE) as main lipid were produced by probe sonication (MBprobe) or by amalgamation, with 10% (MBshake-10) or 30% (MBshake-30) propylene glycol (PG). The lipid phase distribution, shelf-life, and acoustic attenuation were investigated. MBprobe and MBshake-30 had a homogeneous lipid distribution, while MBshake-10 had circular condensed phase domains. For all MBs the condensed phase increased over time. The PG concentration also affected the size and concentration: MBshake-30 had the largest mean diameter 20 min after production, while MBshake-10 had a tenfold higher concentration. All types of MBs had a short shelf-life stability, decreasing in size during the first hour post-production. The coating composition had a more significant effect on size and concentration than the production method. The MBs had a size-dependent resonance behavior and MBshake-10 and MBshake-30 had the highest peak attenuation, revealing a stabilizing role for PG in these MB formulations. Even though the in vivo applications for the DSPE-based MBs may be limited because of the short shelf-life stability, the newly developed MB formulations are interesting candidates for further studies on the effect of lipid phase distribution on acoustic behavior of MBs.
WAVE-INDUCED MOTIONS OF MULTIPLE FLOATING BODIES

A prediction method for the wave induced motions of multiple floating bodies is presented. The hydrodynamic interactions among the bodies are taken into account in their exact form within the context of linear potential theory. The motions of the floating bodies, the diffraction forces due to waves and the radiation forces associated with the motions are solved simultaneously. Comparisons to experimental measurements show satisfactory agreements.The present method is also extended to examine the motions of floating bodies connected with each other by linear elastic structural members.
Coexistence and Interference Mitigation for WPANs and WLANs From Traditional Approaches to Deep Learning: A Review

More and more devices, such as Bluetooth and IEEE 802.15. 4 devices forming Wireless Personal Area Networks (WPANs) and IEEE 802.11 devices constituting Wireless Local Area Networks (WLANs), share the 2.4 GHz Industrial, Scientific and Medical (ISM) band in the realm of the Internet of Things (IoT) and Smart Cities. However, the coexistence of these devices could pose a real challenge—co-channel interference that would severely compromise network performances. Although the coexistence issues has been partially discussed elsewhere in some articles, there is no single review that fully summarises and compares recent research outcomes and challenges of IEEE 802.15. 4 networks, Bluetooth and WLANs together. In this work, we revisit and provide a comprehensive review on the coexistence and interference mitigation for those three types of networks. We summarize the strengths and weaknesses of the current methodologies, analysis and simulation models in terms of numerous important metrics such as the packet reception ratio, latency, scalability and energy efficiency. We discover that although Bluetooth and IEEE 802.15. 4 networks are both WPANs, they show quite different performances in the presence of WLANs. IEEE 802.15. 4 networks are adversely impacted by WLANs, whereas WLANs are interfered by Bluetooth. When IEEE 802.15. 4 networks and Bluetooth co-locate, they are unlikely to harm each other. Finally, we also discuss the future research trends and challenges especially Deep-Learning and Reinforcement-Learning-based approaches to detecting and mitigating the co-channel interference caused by WPANs and WLANs.
Non- invasive Serum Glucose Sensing Using a Double U-slot Antenna

Diabetes is a chronic disease where the body does not produce sufficient insulin hormone to control glucose levels. To prevent health complications arising, diabetics must continuously monitor their blood glucose. Currently, blood glucose levels are mainly monitored using invasive methods which can discourage regular testing. This paper proposes a non-invasive double U-slot patch antenna system to monitor blood glucose levels. COMSOL was used to simulate the port impedance and resonant frequency shifts for varying glucose blood vessel concentrations. The impact of sensor placement, relative to the blood vessel, on glucose level sensitivity was explored considering the relationship between blood glucose concentration and RF-based predictors. Results demonstrate that the lumped port magnitude resonant frequency shift correlates with the range of glucose concentrations investigated. The sensitivity is better at lower frequencies for the designed sensor, and the sensor is relatively insensitive to rotation shifts and horizontal shifts, while vertical shifts, representing more fatty tissue impact the sensitivity.
A longitudinal analysis of the use of videoconferences in the Spanish company: its potential for virtual training

Videoconferencing has become the most used resource in the field of virtual education in the 2020-21 academic year, at all levels, from primary to secondary education and at the University. Something similar has happened in the corporate world. In this work we analyze through a longitudinal survey carried out in 2001, 2011 and 2021 the use of videoconferencing in Spanish companies since it is a resource that is used on a massive scale in the business environment. We propose that this tool be used for employee training.
Optimal Mid-Course Modifications of Ballistic Missile Trajectories

Abstract : The problem of finding optimal mid-course modifications of ballistic missile trajectories is investigated. A single velocity impulse is applied at the point of transfer from the original orbit to the modified trajectory. This limits the modified trajectory to one which intersects the original trajectory. Optimization of a weighted function of transfer velocity impulse and the time to impact after the modification occurs is accomplished. The function can be weighted to accommodate trade-offs between both components. The study is divided into two parts. Elliptical orbits for a non-rotating, atmosphere free earth are investigated, and then trajectories for an oblate, rotating earth with atmospheric reentry are examined.
Accurate Bus Arrival Time from Linear and Non-Linear Route Parameters Using Hybrid Predictors

Nowadays, public transportation plays a major role in various countries. Utilizing public transport is one of the important factors which indicates the quality of transportation department. The essential features of a quality public transport is providing precise information on bus departure and arrival schedules at bus stations. Accurate arrival time can be more helpful for the passengers to schedule their journey more comfortably. In this work, a new technique is presented to accurately predict bus arrival time at bus stops. Hybrid predictors are used in this work to perform the prediction process based on the route parameters. Route parameters are divided into linear and nonlinear to perform an independent prediction process. An extreme learning machine is used to perform prediction from nonlinear parameters. Also, a Support Vector Machine (SVM) predictor for processing linear route parameters. The proposed technique is tested on a local route and finds highly accurate result when compared to conventional techniques. This work achieved higher performance 0.05 of MAE, 5.5 of MAPE and 96.33 % of accuracy.
Analytical Review on OMA vs. NOMA and Challenges Implementing NOMA

The increasing number of devices and high data speed requirements are putting a challenge. To address these problems 5G is implemented. The Orthogonal Multiple Access (OMA) schemes are not sufficient for the implementation of the 5G. One of the promising Multiple Access Technique is Non Orthogonal Multiple Access Technique (NOMA). In NOMA the entire users use the same resource so there will be interference from the others users. In order to transmit data and recover it correctly, this research work utilizes the Successive Interference Cancellation (SIC), which will increase the receiver complexity but has the benefit of high connectivity and spectral efficiency. This paper has analysed different variants in NOMA and presented the most prominent works and compared NOMA with OMA. The challenges for implementing NOMA commercially have also been addressed elaborately.
Monitoring Automation Failures: Effects of Single and Multi-Adaptive Function Allocation

Adaptive function allocation has been proposed to allow the advantages of task automation to be realized without some of the disadvantages of “static” automation. However, few empirical studies of the efficacy of adaptive allocation have been reported. The effects of adaptive function allocation on monitoring for automation failure during multi-task flight simulation were examined in two experiments. The first study examined the use of two methods of adaptive function allocation as a possible counter-measure to automation-induced monitoring problems. Subjects were required to perform a tracking and fuel management task while monitoring an automated system monitoring task for possible failures. For the “model-based” and “performance-based” adaptive groups, a single 10-minute block of fully manual performance on the monitoring task was allocated to subjects in the middle of a session. For the control group system monitoring was automated throughout all sessions. All three groups had low probabilities of detection of automation failures for the first 40 minutes spent with automation, before the adaptive function allocation change. However, detection probabilities were higher for both adaptive groups than for the control group following the function allocation change. The second study found that multiple adaptive changes (repeated function allocation) sustained these performance benefits over a longer automation period. These results clearly indicate that adaptive function allocation can improve detection of automation failures and that the improvement can be sustained over long periods of automation cycles.
CTL-Based Dynamic IoT Service Composition

The collaboration of contiguous Internet of Things (IoT) devices is envisioned to satisfy complex applications which are beyond the capacity of single devices. The functionalities of IoT devices are encapsulated as IoT services, and their collaboration is implemented in terms of IoT service composition. Considering the capacity occupancy, release, and consumption caused by the implementation of IoT services, their composition is challenging in capacity-dynamically fluctuating IoT networks. This paper proposes a dynamic IoT service composition mechanism with inter-service dependencies adopted to capture the dynamic changes of IoT devices, and this change is specified by various Quality-of-Service factors. IoT service composition is formalized under Computation Tree Logic specification with certain composite structures and dynamic dependencies, and this composition is formally achieved by an optimized model checking method. Extensive experiments are conducted on publicly available datasets, and evaluation results show that our technique outperforms the state-of-the-art's approaches in relevant performance metrics.
A Deep Learning Signal-Based Approach to Fast Harmonic Imaging

High resultant image contrast and quality have caused tissue harmonic imaging to become a valuable tool in ultrasound imaging. Amplitude Modulation (AM) is one of the most commonly used nonlinear pulsing schemes in tissue harmonic imaging. However, its need for at least two consecutive firings continues to be a hindering factor for a faster imaging process. In this work, deep learning concepts are exploited to introduce an alternative approach for ultrasound tissue harmonic imaging using a single firing. This is achieved by implementing an asymmetric convolutional autoencoder network to estimate the low-harmonic component content from a received echo signal. The network is trained on the full-amplitude harmonic content IQ echo comprising the network's input and its corresponding low-amplitude harmonic IQ echo representing the network's output. The proposed approach yielded high contrast harmonic images with comparable contrast to noise ratio and contrast ratio to the conventional checkerboard apertures amplitude modulation technique, yet at approximately three times the frame rate. Moreover, less clutter is observed in the proposed approach reconstructed images in contrast with the ground truth images. These results open the door for the implementation of harmonic imaging with comparable quality to the conventional AM techniques, yet with an increased framerate and reduced motion artifacts.
SonoVue Microbubbles as Ultrasound Pressure Sensors in a Dynamic Flow Phantom

Cardiac catheterization is the gold standard for assessing cardiac pressures. However, this is an invasive and costly procedure. An alternative may be to use the subharmonic signal of microbubble ultrasound contrast agents to estimate pressure using echocardiography. The aim of this work was to investigate the subharmonic response of the ultrasound contrast agent SonoVue (Bracco Spa, Milan, Italy) to dynamic pressures in a flow phantom. SonoVue was circulated through a silicone tube using a peristaltic pump. The ULtrasound Advanced Open Platform (ULA-OP) was used with a cardiac phased array transducer to transmit a pulse-inversion sequence at 2.1 MHz. Radiofrequency data were recorded at five acoustic pressures (71–228 kPa peak-negative) to investigate the effects of pulse length (7-, 12- and 16-cycle pulses) and flow rate (150, 200 and 375 mL/min). The subharmonic (1.05 MHz) amplitude of SonoVue was calculated over a 40% bandwidth. A solid-state catheter recorded ground-truth pressures. Increasing pulse length improved the correlation coefficient between the subharmonic signal of SonoVue and pressure (r = 0.74 ± 0.14, 0.79 ± 0.06 vs. 0.86 ± 0.04 for 7-, 12- and 16-cycle pulses, respectively; $n$ = 3 at optimal acoustic pressure). The strong correlations with 16-cycle pulses persisted at different flow rates ($r > 0.8$). This is the first report showing the ability of SonoVue to track pressure cycles five times faster than the average resting heart rate (376 cycles/min at 375 mL/min flow rate). SonoVue may potentially be used to assess diastolic and pulse pressures using ultrasound instead of cardiac catheterization.
Improving Students' Mathematical Computational Thinking Using Scratch Program through Project Based Learning: A Development Research during Pandemic Covid-19

This study aims to examine the development of Project Based Learning kits using Scratch program to improve students' mathematical computational thinking skills in statistics content. The research method used is Research and Development (R & D) approach which refers to Four-D model: Define, Design, Develop, and Disseminate. In the initial stage, researchers conducted preliminary research through literature studies, school surveys, and draft designs. The study produces Project Based Learning kits using Scratch program consist of student's worksheet, lesson plans, and an instrument of mathematical computational thinking. The design of the model was then revised by the expert trial subject. The subjects of the expert test were mathematics learning experts and several mathematics school teachers. The field Pre-Test and Post-Test were conducted in a Junior High School in Tangerang Selatan on mathematical computational thinking instruments, consisting of four essay test (8 question items). The collected data were analyzed using qualitative and quantitative techniques. In validity aspects, all the three learning kits are valid. From the aspect of effectiveness, the Project Based Learning model intervention can improve students' mathematical computational thinking skills. In terms of practicality, students' responses to the developed worksheets are positive.
Empowering Women for Economic Self Sufficiency and Social Action through Self Help Group

The present study was carried out to see the influence of SHG membership on the economic and social aspects in the life of a tribal woman. Both quantitative and qualitative methods were used to generate information from 57 SHG leaders and 153 SHG members. The NGOs are the major SHG promoters. It also reveals that there is change for better in the credit facilities and monthly income. The fact that they are able to have savings in their own name is an indication of independence to a certain level. Majority of the SHG members have been capacitated on various topics and feel self confident as it has made them aware about, aside from other themes, on bank procedures. In terms of their social standing in family and society, an overwhelming percentage agreed that it has indeed improved. The SHG members have involved themselves in many issues that are choking their society. It is obvious how the pro active involvement of women in society is necessary to bring sustainable development and just peace. The NGOs who promoted these SHGs have done a commendable job in empowering these women.
On the Anthropogenic Heat Fluxes Using an Air Conditioning Evaporative Cooling Parameterization for Mesoscale Urban Canopy Models

An air conditioning evaporative cooling parameterization was implemented in a building effect parameterization/building energy model (BEP + BEM) to calculate the magnitude of the anthropogenic sensible and latent heat fluxes from buildings released to the atmosphere. The new heat flux formulation was tested in New York City (NYC) for the summer of 2010. Evaporative cooling technology diminishes between 80% and 90% of the anthropogenic sensible heat from air conditioning systems by transforming it into latent heat in commercial (COMM) areas over NYC. Average 2-m air temperature is reduced by 0.8 °C, while relative humidity is increased by 3% when cooling towers (CTs) are introduced. Additionally, CTs introduce stable atmospheric conditions in the urban canopy layer reducing turbulence production particularly during dry days.