Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithm to Pinpoint the Maximum Power Points on the Power-Voltage Curve of PV Arrays under Different Conditions

Photovoltaic (PV) cells convert sunlight directly into electricity as one way of renewable energy-based power generation, a key aspect of achieving energy sustainability for sustainable economic growth. The paper as part of this goal presents an algorithm to identify various maximum power points (MPPs) on different environmental conditions of group of PV arrays. Three series connected PV arrays of similar electrical properties are considered in this paper. The conditions are grouped under three main forms; uniform test conditions (UTC), partial shading conditions 1 (PSC1) and partial shading conditions 2 (PSC2) to simulate different environmental conditions. Results obtained showed that the algorithm was able to identify all the MPPs; global or local where applicable on power-voltage (P-V) curve. For example, a global MPP of 915.7W was pinpointed on the P-V curve under standard test condition scenario type of UTC based on open circuit voltage and short circuit current of 46.3V and 8.87A respectively of the PV model selected. The result obtained would provide aid for subsequent researches involving the MPP tracking algorithm and voltage converter designs for the PV arrays.
Toward Swarm Coordination: Topology-Aware Inter-UAV Routing Optimization

Swarm unmanned aerial vehicles (UAVs) is an approach to the coordination of multiple UAVs as a system, which has huge advantages on mission capabilities, such as cooperative search, border surveillance, and situation awareness. For better swarm coordination, a robust inter-UAV network, especially in ad hoc mode, is needed. Due to the dynamic nature of UAV networks owing to mobility and topology change, adapting routing quickly to topology changes is one of the key components of UAV networks. Based on investigating the relationship between the swarm formation control and the network topology, we propose a proactive topology-aware scheme to track the network topology change. Through simulations on Qualnet and real-world experiments with five quadrotors, the results confirmed that the proposed scheme reduces the average delay and improves routing performance significantly.
Interactive Robotic Systems as Boundary-Crossing Robots – the User’s View*

Social robots are receiving more attention through increased research and development, and they are gradually becoming a part of our daily lives. In this study, we investigated how social robots are accepted by robot users. We applied the theoretical lens of the boundary-crossing robot concept, which describes the role shift of robots from tools to agents. This concept highlights the impact of social robots on the everyday lives of humans, and can be used to structure the development of perceived interactions between robots and human users. In this paper, we report on the results of a web questionnaire study conducted among users of interactive devices (humanoid robots, animal robots, and smart speakers). Their acceptance and roles in daily life are compared from both functional and affective perspectives, with respect to their perceived roles as boundary-crossing robots.
On the Performance Evaluation of LoRaWAN with Re-transmissions under Jamming

This paper explores the possibility of having confirmed traffic in LoRaWAN networks under channel-oblivious jamming. Our results show that a LoRaWAN cell can handle up to 500 end-devices with a relatively good message success probability (∼ 0.8) if the network is strongly jammed (60% of the time) by using a maximum of 16 re-transmissions. We have also proved that, using a channel for downlink transmissions operating in the lowest SF is a major weakness in the LoRaWAN specification. Indeed, our results suggest that for a LoRaWAN cell with 600 end-devices the network goodput can be decreased by ∼ 53.06% when ACK transmissions on the second receive window are allowed. This was done by using an open-source network simulator that allows to evaluate many scenarios that can help LoRaWAN operators to better scale their networks in order to be more resilient against jamming attacks before actual deployments.
KalKi: A Software-Defined IoT Security Platform

Commercial IoT devices are increasingly being integrated into software systems. However, given the also increasing number of IoT vulnerability reports, there is a pressing need to enable organizations to achieve such integration with high assurance, especially for systems with high security and safety requirements. We present KalKi, a software-defined IoT security platform that moves security enforcement to the network to enable safe integration of IoT devices, even if the devices are not fully trusted or configurable. KalKi leverages software-defined networking (SDN) concepts and constructs, combined with a rich policy model that specifies both cyber and kinetic attacks, to create a safe, highly-dynamic and extensible IoT integration platform. Our experiments demonstrate high performance, scalability and resilience, even in the presence of a powerful attacker.
Design and Implementation of An Automatic Examination Timetable Generation and Invigilation Scheduling System Using Genetic Algorithm

University timetabling is a highly constrained problem that requires considerable time and effort in the process. Stakeholders face a severe dilemma when coming up with a timetable manually as numerous clashes may arise. This necessitates the need for devising an efficient automated means of getting rid of the hectic and heavy tasks involved in examination timetable and Invigilation scheduling. Yusuf Maitama Sule University Kano is of no exception as several clashes were reported to examination office before the commencement of examinations. This paper proposed a solution to the problem of examination timetable and invigilation scheduling in Yusuf Maitama Sule University Kano, Nigeria. The paper employed Genetic Algorithm (GA) that provides an optimal solution by randomly and effectively selects a time slot for a particular course; a venue for such a course; and invigilators that suits particular teacher-student ratio of 1:40. The solution is implemented in Java with its Graphical User Interfaces (GUIs) designed using Java Swing and also use SQLite for database related activities (reading and writing of data).
Enhancing Electricity Network Efficiency in sub-Saharan Africa through Optimal Integration of Minigrids and the Main Grid

In the past two decades, grid extension and off-grid solutions, such as autonomous minigrids, have become main conduits for improving energy access in developing countries. Once universal energy access is mostly achieved in these countries, efficiency, reliability, quality of supply and flexibility will become increasingly prominent objectives in the planning and operation of their electricity networks. Some of these objectives, such as network efficiency, will be strongly influenced by the approach taken for the integration of the main grid and autonomous minigrids. This paper applies optimization techniques to investigate the impact of residual generation and load factor of an autonomous minigrid in the selection of an optimal point of grid connection to minimize energy losses.
Sub-Channel Allocation for Full-Duplex Access and Device-to-Device Links Underlaying Heterogeneous Cellular Networks Using Coalition Formation Games

This paper investigates a heterogeneous cellular network (HCN) topology, where multiple sub-6 GHz bands are available for access and device-to-device (D2D) links with the full-duplex (FD) mode, and an integrated millimeter-wave (mm-wave) band is added to the D2D links’ sub-channel resource options. D2D links share spectrum resources of cellular users or dedicated mm-wave sub-channel. Densely deployed small cells scenario provides an ideal platform to implement mm-wave, FD and D2D communications. With large bandwidths available, mm-wave has the potential to meet the expected extreme data rate demands. Leveraging highly directional beamforming, severe transmission loss and the blockage phenomenon of mm-wave can be alleviated. Theoretically, FD communications can double the spectral efficiency due to bi-directional communications with the same spectral and temporal resources. However, such benefit comes at the cost of residual self-interference (RSI). Multi-user interference (MUI) and RSI among network uplink, downlink and D2D links are the main challenges. In the paper, we formulate an optimization problem for FD access and D2D links sub-channel allocation underlaying HCNs combining sub-6 GHz and mm-wave bands to make the system transmission rate maximized. Then, a scheme based on the coalition formation game is proposed to deal with this challenging NP-complete optimization. Finally, performance evaluation investigates the suitable conditions for FD and HD operations. Under different network parameter settings, we quantify associated performance of proposed scheme.
A 20-30 GHz Compact PHEMT Power Amplifier Using Coupled-Line Based MCCR Matching Technique

This paper presents a 20–30 GHz differential power amplifier (PA) in 0.15-µm GaAs pHEMT process. Magnetically and capacitively coupled resonator (MCCR) is used to realize broadband matching networks. Coupled-line is used to constitute the MCCR in a compact size and the design procedure is also presented. The proposed PA achieves a measured saturated output power (Psat) of 23 dBm with 19.4% peak power added efficiency (PAE) at 26 GHz. The gain is higher than 19 dB over a wide frequency range from 20 to 30 GHz. This chip occupies a small area of only 1.05 mm2 thanks to the coupled-line based MCCR matching network.
Affective Touch Robots with Changing Textures and Movements

We explore how to design emotional expression using tabletop social robots with multiple texture modules. Previous studies in human-robot interaction have presented various designs for emotionally expressive robots without using anthropomorphic forms or cues. They revealed that haptic stimulation based on the textures and movements of the robots could evoke some emotions in users, although these were limited. In this work, we propose using a combination of textures and movements for richer emotional expression. We implemented tabletop robots equipped with detachable texture modules made of five different materials (plastic resin, aluminum, clay, Velcro, and cotton) and performed a user study with 13 participants to investigate how they would map the combinations of textures and movements to nine emotions chosen from Russell’s circumplex model. The results indicated that the robots could express various emotions such as excited, happy, calm, and sad. Deeper analysis of these results revealed some interesting relationships between emotional valence/arousal and texture/movement: for example, cold texture played an important role in expressing negative valence, and controlling the frequency of the movements could change the expression of arousal.
Step-up Ladder Resonant Switched-Capacitor Converter with Full-Range Regulation

A new modulation method for step-up Ladder RSCC is proposed to achieve full-range regulation for all loads. Furthermore, the proposed method for RSCC features advantages of ZVS turn-on for switches, ZCS turn-off for diodes, even switch voltage stress, even diode voltage stress, simple half-bridge gate driver with bootstrap circuit, small inductor, high power density and high efficiency. Experimental results of 3X step-up Ladder RSCC are presented.
Solid-State Membrane Sensors Based on Man-Tailored Biomimetic Receptors for Selective Recognition of Isoproturon and Diuron Herbicides

Solid-contact ion-selective electrodes (SC-ISEs) have shown great potential for routine and portable ion detection. The introduction of nanomaterials as ion-to-electron transducers and the adoption of different performance-enhancement strategies have significantly promoted the development of SC-ISEs. Herein, new solid-contact ion-selective electrodes, along with the implementation of multiwalled carbon nanotubes (MWCNTs) as ion-to-electron transducers and potassium tetrakis (p-chlorophenyl) borate (KTpClB) as lipophilic ionic additives, were presented for the detection of isoproturon (IPU) and diuron (DU) herbicides. Molecularly imprinted polymers (MIPs), with special molecule recognition properties for isoproturon (IPU) and diuron (DU), were prepared, characterized, and introduced as sensory recognition materials in the presented electrodes. Sensors revealed a near-Nernstian response for both isoproturon (IPU) and diuron (DU) with slopes of 53.1 ± 1.2 (r2 = 0.997) and 57.2 ± 0.3 (r2 = 0.998) over the linear ranges of 2.2 × 10−6–1.0 × 10−3 M and 3.2 × 10−6–1.0 × 10−3 M with detection limits of 8.3 × 10−7 and 1.4 × 10−6 M, respectively. The response time of the presented sensors was found to be <5 s and the lifetime was at least eight weeks. The sensors exhibited good selectivity towards isoproturon (IPU) and diuron (DU) in comparison with some other herbicides, alkali, alkaline earth, and heavy metal ions. The presented sensors were successfully applied for the direct determination of isoproturon (IPU) and diuron (DU) in real water samples.
How context shapes the appropriateness of a robot’s voice

Social robots have a recognizable physical appearance, a distinct voice, and interact with users in specific contexts. Previous research has suggested a ‘matching hypothesis’, which seeks to rationalise how people judge a robot’s appropriateness for a task by its appearance. Other research has extended this to cover combinations of robot voices and appearances. In this paper, we examine the missing connection between robot voice, robot appearance, and deployment context. In so doing, we asked participants to match a robot image to a voice within a defined interaction context. We selected widely available social robots, identified task contexts they are used in, and manipulated the voices in terms of gender, naturalness, and accent. We found that the task context mediates the ‘matching hypothesis’. People consistently selected a robot based on a vocal feature for a certain context, and a different robot based on the same vocal feature for another context. We suggest that robot voice design should take advantage of current technology that enables the creation and tuning of custom voices. They are a flexible tool to increase perception of appropriateness, which has a positive influence on Human-Robot Interaction.
Attenuation Characteristics of Bacterial-wilt-disease Biocontrol Strain Anti-8098A(Bacillus cereus ) to Ralstonia solanacearum

The attenuation characteristics of bacterial-wilt-disease biocontrol Bacillus cereus strain ANTI-8098A caused by culture, physical, chemical factors, and other bacteria were compared. The attenuation index to distinguish the pathogenicity for Ralstonia solanacearum (Rs) was based on the TTC cultural medium and the infection mortality to the host. The Rs virulent strain was recognized by the index less than 0.60 and the Rs avirulent strain by that higher than 0.80. The culture activity could not make the Rs attenuated in 120 h within 10 generations. The similar attenuation indexes and infection mortality were persisted in the Rs virulent strains after treating with ultrasonic in different times, indicating no attenuation activity happened by the physical factor. The streptomycin as a chemical factor could inhibit the Rs strain without attenuation activity happened by the physical factors. Fifteen bacterium strains were used in the test of attenuating the Rs virulent strain, only two of Bacillus cereus ANTI-8098A and Bacillus sphaercus showed the attenuation activitiy to change the Rs virulent strain into the Rs avirulent strain in 24 h. The other 13 strains had not the characteristic. It was concluded that the biocontrol strain ANTI-8098A had the attenuation characteristics to make Rs avirulent in 24 h, of which the activity significantly differed from that caused by culture, physical and chemical factors.
A theorem on the polarization of null-free antennas

This paper presents an extension of previous works by Mathis and Saunders, who showed that one will always find both linear polarization and polarization other than linear on the far-field sphere of a null-free antenna. It is shown in this paper that a null-free radiation pattern must contain all axial ratios (ratio of semiminor to semimajor axes) of elliptical polarization ranging from -1 (circular polarization of one sense), through zero (linear polarization), to +1 (circular polarization of the opposite sense). It is also demonstrated that the results of Mathis and Saunders are easily recaptured by this proof.
Vision-Based Building Seismic Displacement Measurement by Stratification of Projective Rectification Using Lines

We propose a new flexible technique for accurate vision-based seismic displacement measurement of building structures via a single non-stationary camera with any perspective view. No a priori information about the camera’s parameters or only partial knowledge of the internal camera parameters is required, and geometric constraints in the world coordinate system are employed for projective rectification in this research. Whereas most projective rectifications are conducted by specifying the positions of four or more fixed reference points, our method adopts a stratified approach to partially determine the projective transformation from line-based geometric relationships on the world plane. Since line features are natural and plentiful in a man-made architectural building environment, robust estimation techniques for automatic projective/affine distortion removal can be applied in a more practical way. Both simulations and real-recorded data were used to verify the effectiveness and robustness of the proposed method. We hope that the proposed method could advance the consumer-grade camera system for vision-based structural measurement one more step, from laboratory environments to real-world structural health monitoring systems.
Genetic diversity analysis amongst GIFT strains of Oreochromis niloticus using microsatellites

[Objective]The experiment was conducted to assess the genetic diversity of a new selected GIFT strain of Oreochromis niloticus in order to evaluate and preserve this strain as a germplasm resource. [Method]Genetic diversity of the newly bred F16 population of GIFT strain Nile tilapia obtained from Guanghui Farm Limited Company, Huangzhou (Guangdong, China) was analyzed using microsatellite markers. [Result]A total of 44 alleles were detected in the population by using 8 microsatellite primers, and the number of allele at each locus ranged from 3 to 8 with an average of 5.5. The mean number of effective allele was 4.77. The size of allele fragment ranged from 118 to 256 bp. The average observed heterozygosity was 0.8058 and the average expected heterozygosity was 0.7292. The average gene diversity between individuals within populations was 0.7044, and the mean fixation index coefficient of population was -0.2261. The average polymorphism information content (PIC) was 0.7044. All of the 8 detected loci were in a high polymorphism degree (PIC0.5000). [Conclusion]There was rich polymorphism information content and wide genetic diversity in the population of GIFT strain of Oreochromis niloticus. This selected GIFT strain population still has wide selection potential and can be used as a base population for further breeding.
Human Tracking and Vital Sign Monitoring with a Switched Phased-Array Self-Injection-Locked Radar

This paper presents a switched phased-array (SPA) radar that uses self-injection-locking (SIL) and digital beamforming (DBF) technologies to provide high sensitivity of vital sign detection and accurate azimuthal tracking of a mobile person. Advantageously, the complexity of RF transmission and reception in the proposed SPA radar is very low compared to the conventional phased array radar. In the experiment, a prototype SPA-SIL radar was implemented to operate in the 2.4 GHz ISM band. This radar can automatically track the azimuth angle of a subject and successfully detect his vital signs over a wide azimuth and distance range,
Multimodal MRI Synthesis Using Unified Generative Adversarial Networks.

PURPOSE Complementary information obtained from multiple contrasts of tissue facilitates physicians assessing, diagnosing and planning treatment of a variety of diseases. However, acquiring multiple contrasts magnetic resonance images (MRI) for every patient using multiple pulse sequences is time-consuming and expensive, where, medical image synthesis has been demonstrated as an effective alternative. The purpose of this study is to develop a unified framework for multimodal MR image synthesis. METHODS A unified generative adversarial network consisting of only a single generator and a single discriminator was developed to learn the mappings among images of four different modalities. The generator took an image and its modality label as inputs and learned to synthesize the image in the target modality, while the discriminator was trained to distinguish between real and synthesized images and classify them to their corresponding modalities. The network was trained and tested using multimodal brain MRI consisting of four different contrasts which are T1-weighted (T1), T1-weighted and contrast-enhanced (T1c), T2-weighted (T2), and fluid-attenuated inversion recovery (Flair). Quantitative assessments of our proposed method were made through computing normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR), structural similarity index measurement (SSIM), visual information fidelity (VIF), and naturalness image quality evaluator (NIQE). RESULTS The proposed model was trained and tested on a cohort of 274 glioma patients with well-aligned multi-types of MRI scans. After the model was trained, tests were conducted by using each of T1, T1c, T2, Flair as a single input modality to generate its respective rest modalities. Our proposed method shows high accuracy and robustness for image synthesis with arbitrary MRI modality that is available in the database as input. For example, with T1 as input modality, the NMAEs for the generated T1c, T2, Flair respectively are 0.034±0.005, 0.041±0.006, and 0.041±0.006, the PSNRs respectively are 32.353±2.525 dB, 30.016±2.577 dB, and 29.091±2.795 dB, the SSIMs are 0.974±0.059, 0.969±0.059, and 0.959±0.059, the VIF are 0.750±0.087, 0.706±0.097, and 0.654±0.062, and NIQE are 1.396±0.401, 1.511±0.460, and 1.259±0.358, respectively. CONCLUSIONS We proposed a novel multimodal MR image synthesis method based on a unified generative adversarial network. The network takes an image and its modality label as inputs and synthesizes multimodal images in a single forward pass. The results demonstrate that the proposed method is able to accurately synthesize multimodal MR images from a single MR image.
Multi-Band All-Digital Transmission for 5G NG-RAN Communication

This paper explores multi-band all-digital transmitter architecture suitable for 5G next-generation radio access network (NG-RAN). In NG-RAN, most of the radio frequency (RF) layer functions are moved to a distributed unit (DU) in the digital domain so that a low cost and small size remote radio unit (RRU) can be developed. This paper presents a delta-sigma modulation (DSM) technique implemented in the field-programmable gate array (FPGA) for DU which is further interfaced with a power amplifier in RRU through feeder cable. A single bit 1st and $2^{\mathrm{n}\mathrm{d}}$ order low-pass DSM is implemented in FPGA of DU. An IQ sequencing block and high-speed serializer multiplexer are used to digitally up-convert the baseband signals to the different carrier frequencies in DU. The proposed scheme is validated with transmission of long-term evolution (LTE) signal of 5 MHz bandwidth for single as well as multi-band operation. The performance of the transmitter is measured in terms of signal to noise distortion ratio (SNDR) and error vector magnitude (EVM).