Miracle-dz/UniFAR-FTUs huggingface dataset:
Terahertz Imaging of 3D Print Infill Structures

3D printed objects are usually not completely filled to reduce weight, printing time and costs. Instead, infill structures are used. These infill structures have a major influence on the strength of 3D prints. To non-destructively investigate such infill structures, our approach is the use of terahertz time-domain spectroscopy. This paper studies possible evaluation parameters for imaging an exemplary infill structure by using both transmission and reflection measurements. Thus, a non-destructive visualization of 3D print infill structures is enabled.
Cluster Synchronization of Fractional-Order Nonlinearly-Coupling Community Networks With Time-Varying Disturbances and Multiple Delays

This paper investigates the adaptive cluster synchronization of fractional-order complex networks with internal and coupling delays as well as time-varying disturbances via the fractional-order hybrid controllers. To be more practical, the unknown disturbances and dynamical behaviors of nodes are assumed to be nonidentical. Based on the properties of fractional calculus and the fractional-order comparison principle, sufficient conditions are derived to guarantee the cluster synchronization of two kinds of fractional-order nonlinear dynamical systems, which extends the results in existing literatures. Numerical simulations are presented to show the effectiveness of our theoretical results.
A Sidelobe Suppressed Huygens Dipole Array with High Aperture Efficiency

A sidelobe suppressed, high aperture efficiency X-band Huygens dipole array is reported. The Huygens array consists of four magnetic and four electric dipole radiators. A collinear set of magnetic dipoles (MDs) is formed from a TE0.5,0 mode open waveguide integrated with phase inverters. The electric dipoles (EDs) are produced by connecting two metallic plates to the aperture of the waveguide, one on each side of it and orthogonal to that vertical wall of the waveguide. The consequent pairs of MDs and EDs are orthogonally oriented and their phase difference is a natural 90°. These dipoles are excited by an electric pin probe inserted into the waveguide at its center through one vertical wall. The overlapped –10-dB impedance and 3-dB realized gain bandwidth is 800 MHz, covering 9.45 to 10.25 GHz. The sidelobe levels of the 1×4 array are significantly reduced to –23.3 dB thanks to the natural tapering of the amplitude distributions of the MDs and EDs from the center of the array to both of its ends. The peak realized gain value is 12 dBi. The aperture efficiency is 74%.
AFTM: An Adaptive Flow Table Management Scheme for OpenFlow Switches

Software-Defined Networking (SDN) is an emerging network platform, which decouples the control and data planes. As the most popular southbound protocol and standard, OpenFlow converts network forwarding policies to rule entries and stores them in the flow table. However, the capacity of the flow table is restricted, which can lead to table-overflow if the space is inefficiently used. In this paper, we propose an adaptive flow table management scheme (AFTM) on the control plane, which combines assigning dynamic timeout and proactive eviction to manage the limited flow table resources. The timeout assignment module and the proactive eviction module are not independent parts but work collaboratively. The timeout assignment module sets suitable timeouts for rule entries according to flow characteristics, so that entries of short-lived flows are quickly removed while entries of flows with large packet intervals are retained. When the table space is insufficient, the proactive eviction module removes rule entries to protect the flow table from table-overflow. In our design, the eviction thresholds and parameters in both modules can be adaptively adjusted according to the network load. Experimental results show that AFTM can effectively manage the flow table resource and reduce the number of packet drop rates by up to 81% compared with existing schemes.
Optically Controlled Reconfigurable NRI-TL Phase Shifter for 5G Antenna Applications

An optically-controlled reconfigurable NRI-TL metamaterial phase shifter operating at 3.6 GHz is proposed. A host transmission line with a fixed length loaded with series capacitors and shunt inductors is used to achieve reconfigurability, while the optical control is introduced by integrating highly resistive silicon switches within the shunt branches of the NRI-TL design. The two states of the phase shifter result in a phase shift of ±60° leading to a differential phase shift of 120° with an insertion loss of 1.3 dB and 1.8 dB respectively. The operational bandwidth of the phase shifter is between 3.45–3.75 GHz. The versatile optical control and the high-frequency response make the proposed NRI-TL phase shifter well suited for 5G antenna array applications.
Binary neural network based real time emotion detection on an edge computing device to detect passenger anomaly

Passenger safety in public transportation especially while riding in the form of shared cabs, and taxis are often ignored, and not much preventive protocols are devised. In the connected mobility world, emotion recognition from facial expressions is a possibility, however a faster processing and edge computing device to derive anomaly state inferences will be apt for further notifying about the safety of the passenger. FPGA implementation is a viable approach to not only implement in the embedded system automotive electronics, but also accelerate the inference results, hence making it as an ideal real time candidate for passenger anomaly state identification. For the same, a real time emotion detection system using facial features was implemented on FPGA. A Binary Neural Network (BNN) feeded by Local Binary Pattern (LBP) output was designed towards the development of an improved and faster emotion recognition system. LBP is configured as a preprocessing step to extract facial features that is passed on to the BNN layer for successful inference. The preprocessing method utilizes Viola-Jones (VJ) algorithm to extract facial data while removing other background information from the image. The LBP-BNN network is modelled using Facial Expression 2013 (FER-2013) data set for training. The custom hardware accelerator or the overlay is synthesized and the designed IP is implemented on FPGA for the inference. Inference is done using the trained model on FPGA to enable faster classified results. Emotion detection using facial expressions is classified to six states namely: angry, disgust, fear, happy, sad, and surprise. The LBP-BNN network is implemented in FPGA, to realize a real time facial emotion recognition by capturing the image of a person from a web camera interfaced to the FPGA acting as edge computing inference device, with acceptable accuracy. The image processing based emotion detection design is highly suitable for other applications including tracking of emotions for movement disorder patients in hospitals.
Towards a Crowdsourcing-Based EMF Exposure Monitoring: Evaluation of Smartphone Measurements Using Kriging

Conventional methods for exposure assessment cannot provide comprehensive and continuous monitoring. A crowdsourcing-based approach relying on the signal strength measurements of common smartphones could be a potential solution. This paper deals with the evaluation of measurement data collected with smartphones under conditions similar to crowdsourcing. Kriging is used to interpolate and smooth the noisy measurement data. The smartphone measurement data is analyzed for three LTE cells and compared with codeselective measurements of a field strength meter. It is shown that areas with high and low exposure can be distinguished and that local hot spots can also be detected. Furthermore, it becomes clear that at least a rough estimate of the electric field strength can be derived from the signal strength measurements, provided that enough smartphone readings are available for this area.
Large Signal RF Reliability of 45-nm RFSOI Power Amplifier Cell for Wi-Fi6 Applications

A power amplifier cell having a single n-channel transistor fabricated in 45-nm RFSOI technology is stressed using both DC drain voltage as well as RF power at 7GHz applied to the gate reproducing Wi-Fi6 like operating conditions. Impact of the stress is studied using both DC as well as RF metrics. Impact on impedance matching is also studied using small signal characteristics. Through this work, we attempt to explore differences in hot carrier degradation mechanisms between DC and RF stress conditions. Impact of hot carrier degradation on DC and RF parameters is also presented by analyzing the time slope exponent. Degradation in DC and RF performance (small and large signal) is compared under varying stress conditions (DC, RF, and DC+RF).
Fog Computing Security Assessment for Device Authentication in the Internet of Things

The Fog is an emergent computing architecture that will support the mobility and geographic distribution of Internet of Things (IoT) nodes and deliver context-aware applications with low latency to end-users. It forms an intermediate layer between IoT devices and the Cloud. However, Fog computing brings many requirements that increase the cost of security management. It inherits the security and trust issues of Cloud and acquires some of the vulnerable features of IoT that threaten data and application confidentiality, integrity, and availability. Several existing solutions address some of the security challenges following adequate adaptation, but others require new and innovative mechanisms. These reflect the need for a Fog architecture that provides secure access, efficient authentication, reliable and secure communication, and trust establishment among IoT devices and Fog nodes. The Fog might be more convenient to deploy decentralized authentication solutions for IoT than the Cloud if appropriately designed. In this short survey, we highlight the Fog security challenges related to IoT security requirements and architectural design. We conduct a comparative study of existing Fog architectures then perform a critical analysis of different authentication schemes in Fog computing, which confirms some of the fundamental requirements for effective authentication of IoT devices based on the Fog, such as decentralization, less resource consumption, and low latency.
Automatic Segmentation of Hippocampal Subfields MRI Based on FPN-DenseVoxNet

In view of the segmentation of multi-scale spatial structure of the human brain hippocampal subfields magnetic resonance image, this paper proposes a three-dimensional fully convolution DenseNet including a feature pyramid (Feature Pyramid Networks, FPN) structure, which is simply called FPN-DenseVoxNet. The network mainly integrates the FPN structure into a DenseNet with 3D convolution kernel, which better integrates the bottom and high-level features of the neural network to realize the full use of multi-level features. In the case of deep network layers, it could still restore shallow features and restore image details, thus could finally improve the accuracy of the subdivision of the hippocampus. It also contains self-attention blocks to recover more details. This paper compares the proposed method with the existing method on two public datasets. The experimental results show that the method proposed in this paper obtains a higher accuracy on the hippocampal subfields segmentation.
A Dynamic Distributed Multi-Channel TDMA Slot Management Protocol for Ad Hoc Networks

With the emergence of new technologies and standards for wireless communications and an increase in application and user requirements, the number and density of deployed wireless ad hoc networks is increasing. For deterministic ad hoc networks, Time-Division Multiple Access (TDMA) is a popular medium access scheme, with many distributed TDMA scheduling algorithms being proposed. However, with increasing traffic demands and the number of wireless devices, proposed protocols are facing scalability issues. Besides, these protocols are achieving suboptimal spatial spectrum reuse as a result of the unsolved exposed node problem. Due to a shortage of available spectrum, a shift from fixed spectrum allocation to more dynamic spectrum sharing is anticipated. For dynamic spectrum sharing, improved distributed scheduling protocols are needed to increase spectral efficiency and support the coexistence of multiple co-located networks. Hence, in this paper, we propose a dynamic distributed multi-channel TDMA (DDMC-TDMA) slot management protocol based on control messages exchanged between one-hop network neighbors and execution of slot allocation and removal procedures between sender and receiver nodes. DDMC-TDMA is a topology-agnostic slot management protocol suitable for large-scale and high-density ad hoc networks. The performance of DDMC-TDMA has been evaluated for various topologies and scenarios in the ns-3 simulator. Simulation results indicate that DDMC-TDMA offers near-optimal spectrum utilization by solving both hidden and exposed node problems. Moreover, it proves to be a highly scalable protocol, showing no performance degradation for large-scale and high-density networks and achieving coexistence with unknown wireless networks operating in the same wireless domain.
Traffic flow prediction based on JANet and attention mechanism

Time series prediction plays an increasingly important role in traffic analysis such as road situation awareness and dynamic route planning. However, there are some shortcomings in time series model, such as high time complexity and limited model representation ability, so that traffic flow data can not be fitted well. To address this problem, this paper proposes a JANet model that integrates attention. On the one hand, JANet reduces training time without affecting the accuracy of the model by simplifying the complex structure of the LSTM. On the other hand, the model focuses on features that are more meaningful to current predictions by introducing self-attention mechanisms. Experiments on multiple open datasets show that the JANet of fused attention outperforms existing mainstream LSTM, rnn models in terms of effect and speed.
Measurement of Millimeter-wave 3D MIMO Channel in Large Indoor Environment

Three-dimensional (3D) multiple-input multiple-output (MIMO) and millimeter wave (mm-wave) are key technologies for the future wireless communication. This paper proposes a channel measurement method for millimeter wave 3D MIMO channel. Using the uniform rectangular array (URA) and vector network analyzer (VNA), measurement of 3D MIMO channel is carried out in a large conference hall. Subsequently, the power angle delay profile (PADP) of line-of sight (LOS) and non-line of sight (NLOS) is extracted from the measured data. The analysis is extended to a multi-user scenario in which virtual URA is used as the base station to work with users at different altitudes under LOS and NLOS conditions. Measurement results shows that the multipath resolution can be improved when the antenna height is close to each other. These findings can provide valuable experimental basis for 3D MIMO channel modeling of massive antenna elements.
Design of Compact SIW Cavity Backed Self-triplexing Planar Slot Antenna for Triple Band Application

A novel design technique of planar triple band self-triplexing Substrate Integrated Waveguide (SIW) cavity backed slot antenna is presented. The proposed antenna uses three separate feeding ports to excite three SIW cavity modes into the proposed design. A dumbbell shaped slot antenna placed at top metallic plate is excited by these modes to radiate at corresponding resonant frequencies in C (4-8 GHz), X (8-12 GHz) and Ku (12-18 GHz) band. The behaviour of the proposed SIW cavity modes are analyzed with the help of half mode theory to predict the resonant frequencies of the proposed antenna. The fabricated prototype of the antenna resonates at 6.76 GHz, 8.62 GHz and 13.33 GHz and exhibits unidirectional radiation pattern with a gain of 3.78 dBi, 4.46 dBi, 5.6 dBi and front-to-back ratio (FTBR) of 14 dB at three resonant frequencies respectively. The proposed antenna maintains a high isolation of better than 15 dB between its three excitation ports while retaining its compact configuration which makes it attractive for high frequency on chip antenna applications.
Organometallic materials: Ferroceno[c]thiophenes and 1,2-Bisthienylmetallocenes

OF DISSERTATION ORGANOMETALLIC MATERIALS: FERROCENO[C]THIOPHENES AND 1,2-BISTHIENYLMETALLOCENES Development of synthetic routes toward two general organometallic frameworks was undertaken. The first project involved synthetic attempts of substituted and unsubstituted ferroceno[c]thiophene while the second one was the synthesis of 1,2dithienylmetallocenes. The long-term goal of this work is to lay the foundations for study of electronic, electrochromic, redox, and optical properties of thiophene-based materials integrated with organometallic systems such as ferrocene, ruthenocene and cymantrene. The synthetic pathway for the target molecule in the first project involved converting 1,2bis(hydroxymethyl)ferrocene to 1,2-bis(thiouroniummethyl)ferrocene with thiourea under acidic conditions. Refluxing the salt in base followed by acidification resulted in 1,2bis(mercaptomethyl)ferrocene, which is oxidized to the cyclic ferroceno[d]-1,2-dithiane. Ring contraction of cyclic dithiane gave the thioether, ferroceno[c]-2,5-dihydrothiophene. Periodate oxidation of the thioether gave ferroceno[c]-2,5-dihydrothiophene-S-oxide (1), a potential precursor for ferroceno[c]thiophene via Pummerer dehydration. Attempts to dehydrate 1 and to trap the resulting thiophene in situ indicated instability of the target compound. Synthesis of ferroceno[c]thiophene with electron-donating as well as electronwithdrawing substituents at the 2,5-positions of the thiophene ring was attempted. 1,2–Dithienylethenes and their derivatives have gained increased attention due to their exceptional photochromic property. They tend to be thermally irreversible but photochemically reversible, which is a vital for their potential use in optical memories, switches and other optoelectronic applications. Inspiration of the second project was that incorporation of 1,2-dithienyl systems into metallocenes would enhance the general properties of the molecule, including stability, fatigue resistance, solid-state reactivity and higher sensitivity. 1,2-Dithienylferrocene was successfully synthesized. The synthetic pathway for 1,2-dithienylferrocene involved the reaction of α-bromo-3-acetyl-2,5dimethylthiophene (1) with ethyl 4-(2,5-dimethylthiophen-3-yl)-3-oxobutanoate (2) to give 2,3-diarylcyclopent-2-en-1-one (3). Compounds 1 and 2 were synthesized following literature methods. Compound 3 was then converted to its cyclopentadienide form by first reducing the ketone to alcohol using LAH, followed by dehydration and then deprotonation of the substituted cyclic diene using butyllithium to give 1,2-bis(2,5-dimethylthiophene)-2,4-cyclopentadien-1-yl)lithium (4). [Fe(fluorenyl)(Cp)] was then used as a transfer reagent and reacted with 4 to yield the target compound.
Effect of Taro (Colocasia esculenta) Enrichment on Physicochemical and Textural Properties of Cake

Taro is a plant widely produced in tropical areas for its underground corms and it is used mainly as a vegetable. Its physicochemical, sensory properties and health benefits led to its use in value-added products. The cake is a high value-added bakery product and it needs a lower amount of gluten protein, therefore, taro flour (TF) was supplemented in wheat flour (WF) at different levels (10, 20, 30 and 40%). In connection with this, the incorporation of taro flour into wheat-based products has been reported to increase their nutritional and textural quality. The taro-supplemented cake showed higher mineral and fiber content, however, reduced caloric value. It was observed that taro supplementation reduced gluten and protein content and had higher oil and water binding capacity, therefore suitable for cake preparation. Taro cake had improved texture and sensory characteristics in comparison to wheat cake. It can be concluded that addition of taro for cake preparation improves nutrition and quality characteristics, therefore, it can be recommended to use taro for cake preparation.
The Effect of Dietary Habbit of Phosphorus Intake in Chronic Kidney Disease Patients on Hemodialysis

Background: Phosphorus is an essential nutrient required for multiple physiological functions, recent researches found that high phosphorus intake could have detrimental effects on health. Hyperphosphatemia is one of the most important risk factors for morbidity and mortality for chronic kidney disease (CKD) patients. High phosphorus intake can cause vascular and renal calcification, renal tubular injury, and premature death in multiple animal models. Limited data exist linking high phosphorus intake directly to adverse clinical outcomes. Small studies in human suggest that high phosphorus intake may result in positive phosphorus balance and correlate with renal calcification and albuminuria.Further prospective studies are needed to determine whether phosphorus intake is a modifiable risk factor for kidney disease. Aims & Objectives: To study the effect of dietary habits on dietary phosphorous intake in chronic kidney disease patients on hemodialysis. To study the prevalence of hyperphosphatemia in patients of CKD on maintenance hemodialysis. To see the impact of dietary control of phosphorus in CKD patients. Original Research Article Mogal et al.; AJRN, 4(1): 1-8, 2021; Article no.AJRN. 64311
Using Multi-Objective Bat Algorithm for Solving Multi-Objective Non-linear Programming Problem

Human beings are greatly inspired by nature. Nature has the ability to solve very complex problems in its own distinctive way. The problems around us are becoming more and more complex in the real time and at the same instance our mother nature is guiding us to solve these natural problems. Nature gives some of the logical and effective ways to find solutions to these problems. Nature acts as an optimized source for solving the complex problems. Decomposition is a basic strategy in traditional multi-objective optimization. However, it has not yet been widely used in multi-objective evolutionary optimization. Although computational strategies for taking care of Multi-objective Optimization Problems (MOPs) have been accessible for a long time, the ongoing utilization of Evolutionary Algorithm (EAs) to such issues gives a vehicle to tackle extremely enormous scope MOPs. MOBATD is a multi-objective bat algorithm that incorporates the dominance concept with the decomposition approach. Whilst decomposition simplifies the MOP by rewriting it as a set of Tchebycheff Approach, solving these problems simultaneously, within the BAT framework, might lead to premature convergence because of the leader selection process which uses the Tchebycheff Approach as a criterion. Dominance plays a major role in building the leaders archive, allowing the selected leaders to cover less dense regions while avoiding local optima and resulting in a more diverse approximated Pareto front. The results from 5 standard MOPs show that the MOBATD outperforms some developmental methods based on decomposition. All the results were achieved by MATLAB (R2017b).