bluuebunny/crossref_metadata_2025 huggingface dataset:
A STUDY ON IMPACT OF SOCIAL MEDIA USAGE ON SLEEP DISTURBANCES AMONG MEDICAL COLLEGE STUDENTS
Authors: Gowtham V. , Lincy T. , Kaleeswaran S.
Published: January 2023

Background: Sleep and circadian functioning are vital to promoting good health. Sleep disturbance and insufficient
sleep duration are associated with day time sleepiness and a range of poor health outcomes.The rapidly growing rate of
SM use in recent years raises concern that SM use may adversely affect sleep quality.The objective of the study is to find
the correlation between social media usage and sleep disturbance among medical college students. Methodology:
The study was conducted among 350 medical college students using a questionnaire and Pittsburgh sleep quality index
scale with the help of google forms. The data was downloaded as Excel and analysed using SPSS software. Results:
About 56% were using social media for 3 to 5 years,followed by 6-10 years usage (22.3%) and less than 2 years (20.6%).
About 81.4% were using social media for more than 60 minutes in a day and 18.6% were using social media for less than
60 minutes.About 71.1% had poor sleep quality index as per PSQI scale.It is found that those using social media longer
duration in a day had poor sleep quality, which is statistically significant. Conclusion: This study indicated that the
usage of social media at a greater extent will have an impact on one's sleep. One has to understand the impact of social
media on young adult's life and the proper and needy usage of social media has to be made in practice.
THE IMPORTANCE OF NUTRITIONAL COUNSELING FOR HYPERPHOSPHATEMIA IN MAINTENANCE HEMODIALYSIS PATIENTS
Authors: Luciana Carmen Nitoi
Published: January 2023

Aim: To assess the impact of dietetic intervention on the nutritional status and calcium–phosphorus metabolism in
maintenance hemodialysis (MHD) patients. Material and methods: Six-month longitudinal intervention study of 162
MHD patients selected from one dialysis unit in Romania. They were divided into 4 groups according to serum albumin
(SA) level and the comorbid condition of chronic liver disease (CLD). Clinical and biochemical parameters were
measured at baseline and 6 months after PNC (personalized nutritional counseling). Nutritional status was assessed by
mSGA (modified Subjective Global Assessment) and dietary calorie and protein intake by diet history with the help of 72
h recall method. Nutritional counselling and personalized diets were recommended by the dietician bimonthly for a
period of 6 months only to groups I and III (groups with hypoalbuminemia). Results: Comparison of data collected prior
PNC (T0) and 6 months after (T6) showed: phosphorus (P) level decreased significantly in all 4 groups: group I- T0 vs. T6
p=0.005, group II: T0 vs. T6 p= 0.002; group III: T0 vs. T6 p=0.001, and group IV T0 vs. T6 p=0.042; serum Ca followed a
similar trend; serum parathyroid hormone (PTH) remained stationary; SA level was significantly improved in both
nutrition counseling groups (group I: T0 vs. T6 p= 0.001, group III: T0 vs. T6 p=0.001, respectively). Conclusions: Our
study suggests that dietetic intervention focused on phosphate and albumin control in MHD patients with
hyperphosphatemia and hypoalbuminemia contributes to an improvement in important nutritional parameters and to a
positive calcium-phosphorus balance.
CONGENITAL NASOLACRIMAL DUCT OBSTRUCTION AND ITS MANAGEMENT PROTOCOL
Authors: Shakya Prachi , walia Shweta
Published: January 2023

PURPOSE: To determine management protocol in congenital nasolacrimal duct obstruction in age group of 3
months to 6 yrs . METHOD:A prospective interventional study was conducted on 30 patients with CNLDO within
the age group 3 months to 6 yrs from September 2020 to April 2022. The diagnosis was made based on a
history of epiphora since birth, or shortly after birth, in one or both eyes supported by objective evidence of
reduced lacrimal outflow using a fluorescein dye disappearance test (FDDT). Ocular examination was carried out
to exclude punctal stenosis or other abnormality. Patients with positive FDDT test were considered for various
treatment modalities. Patients with age < 1 year considered for criggler massage 8-10 times a day. Patients with
persistent epiphora and mucous discharge were considered for endoscopic assisted probing or DCR with
intubation under general anaesthesia. RESULTS: The study group comprised of 30 patients, out of which 40 %
were male and 60 % were female. On the basis of age of representation 60 % were between 12 months, 26 %
between 1 year – 4 year and 14 % more than 4 years. In this study all patients were prescribed crigler massage
but the patients not improved on massage and, 12 months - 4 years and more than 4 years were prescribed with
endoscopic assisted probing, and DCR with intubation respectively. In this study out of 30 patients of CNLDO 16
patients were improved by crigler massage (in age group of < 12 months ) ,9 patients were improved with
endoscopy assisted probing with 90 % of successful result in age group of 12 months - 4 years and 5 patients
improved from DCR with intubation depending upon age of patients . CNLDO is a relative CONCLUSIONcommon disorder in peadiatric population ( 5 - 20 % ) due to failure of canalisation of the distal end of
nasolacrimal duct leading to watery and mucoid discharge. Conservative management in the form of crigler
massage considered to be safest and effective with higher success rate. Patients with no improvement on crigler
massage and persistence of symptoms shows more effective outcome with endoscopic assisted probing or DCR
with intubation.
The Effect of Employee Motivation on Job Performance in the Banking Sector in Rwanda: Case of Bank of Kigali Headquarters
Authors: Nnadozie Regina , Singh Snarayan N.
Published: January 2023

The Bank of Kigali was chosen as the case study to examine the effect of employee motivation on job performance. Findings showed that Intrinsic motivation has greatly enhanced job performance by a mean=3.5 and SD=1.219, and Style of management motivation had a positive effect on the degree of employee motivation by mean=3.5 and SD=1.289 while Extrinsic has a mean=3.39 and SD=1.267. Organizations make every effort to inspire their finest employees because they understand their crucial function and how it affects organizational success. Studies on motivation show that there are a number of ways to motivate employees. This study aims to offer explanations of why the employee of Bank of Kigali Rwanda do what they do, and examine to what level their activities affect job performance. Intrinsic motivation is a sort of internal incentive gained from the circumstance that propels workers to accomplish. This form of motivation develops because of the individual’s external effects received from environmental elements. These include good income, fringe benefits, empowering policies, and various types of supervision. Employers need to borrow a leaf from BK on what to do in extreme cases to sustain high productivity.
An Equity-based Model of Vandalism in Information and Communication for Development Tele-Centre’s: Reflections from the Siyakhula Living Laboratory, Dwesa-Cwebe, South Africa
Authors: Osah Umeoniso Joshua
Published: January 2023

This study looks at tele-center related vandalism from an equity-based lens. It is noticed that these uncivil acts are common occurrences in information and communication for development (ICT4D) related tele-centers around the globe. Paradoxically, there is very little investigation on the issue. Here an equity-based model of vandalism proposed by Fisher & Baron is used to investigate incidences of vandalism and theft in a rural based ICT4D initiative known as the Siyakhula Living Lab (SLL). The model provides explanation value for the empirical investigation. The study employs a qualitative abductive reasoning approach to gain insight from stakeholders of the ICT4D initiative. For this study four stakeholders of the ICT4D initiative are interviewed, with the help of a semi-structured interview guide. Their responses are thematically analyzed and as a result a narrative emerges about the relationship between inequity and vandalism in the SLL context. The findings reveal that noticed occurrences of vandalism to publicly installed ICT infrastructure as well as a theft incident to an SLL established tele-center, were highly likely as a result of perceived inequity by certain groups in the surrounding communities. It is revealed that due to their existing low level of control at the time of the study, these groups felt compelled to resort to vandalism and theft in order to address the perceived inequity. It is concluded that inequity can indeed spur acts of vandalism especially for groups that perceive themselves as disenfranchised and powerless.
Intuitive Understanding of Observing Reality: With Extension of the Game Theory
Authors: Yoon Jihyeon
Published: January 2023

By extending the context of the Game Theory to the understanding of P-NP Problem, fundamental principles of observation can be explained to the very limit of existence.
FARANE-Q: Fast Parallel and Pipeline Q-Learning Accelerator for Configurable Reinforcement Learning SoC
Authors: Sutisna Nana , Ilmy Andi M. R. , Syafalni Infall , Mulyawan Rahmat , Adiono Trio
Published: January 2023

This paper proposes a FAst paRAllel and pipeliNE Q-learning accelerator (FARANE-Q) for a configurable Reinforcement Learning (RL) algorithm implemented in a System on Chip (SoC). The proposed work offers flexibility, configurability, and scalability while maintaining computation speed and accuracy to overcome the challenges of a dynamic environment and increasing complexity. The proposed method includes a Hardware/Software (HW/SW) design methodology for the SoC architecture to achieve flexibility. We also propose joint optimizations on the algorithm, architecture, and implementation to obtain optimum (high efficiency) performance, specifically in energy and area efficiency. Furthermore, we implemented the proposed design in a real-time Zynq Ultra96-V2 FPGA platform to evaluate the functionality with an actual use case of smart navigation. Experimental results confirm that the proposed accelerator FARANE-Q outperforms state-of-the-art works by achieving a throughput of up to 148.55 MSps. It corresponds to the energy efficiency of 1747.64 MSps/W per agent for 32-bit and 2424.33 MSps/W per agent for 16-bit FARANE-Q. Moreover, the proposed 16-bit FARANE-Q outperforms other related works by an improvement of at least 1.23× in energy efficiency. The designed system also maintains an error accuracy of less than 0.4% with optimized bit precision for more than eight fraction bits. The proposed FARANE-Q also offers a speed up of processing time up to 1795× compared to embedded SW computation executed on ARM Zynq processor and 280× of computation of full software executed on i7 processor. Hence, the proposed work has the potential to be used for smart navigation, robotic control, and predictive maintenance.
Scalable and Resilient 360-degree-Video Adaptive Streaming over HTTP/2 against Sudden Network Drops
Authors: Nguyen Viet Hung , Truong Thu Huong , Truong Thang
Published: January 2023

Realistic Virtual Reality is supported by 360° video, which provides viewers with an immersive watching experience. However, 360° video is bulky in size, while the transmission system has limited ability to provide bandwidth. As such, intelligent adaptive delivery solutions play a crucial role in enabling users to stream high-quality 360° video. In this research, we propose a novel approach for 360- degree video streaming over HTTP/2 that can provide consumers with a good watching experience (QoE) even in varying network circumstances and head-eye movements over time. The proposed method deploys the so-called BBAG algorithm (Buffer and Bandwidth Allocation Algorithm) using Scalable Video Coding to choose appropriate tile layers to resolve the trade-off between network and user adaptivity. With the support of HTTP/2’s stream termination capability, the delivery of late tile layers is terminated to handle abrupt interruptions. Our BBAG method is proven to improve QoE from 3.56% to 93.71% and the average viewport bitrate from 1.78% to 80.49% compared to state-of-the-art methods. 
Sample-Efficient Unsupervised Domain Adaptation of Speech Recognition Systems: A case study for Modern Greek
Authors: Paraskevopoulos Georgios , Kouzelis Theodoros , Rouvalis Georgios , Katsamanis Athanasios , Katsouros Vassilis , Potamianos Alexandros
Published: January 2023

Modern speech recognition systems exhibits rapid performance degradation under domain shift. This issue is especially prevalent in data-scarce settings, such as low-resource languages, where diversity of training data is limited.

In this work we propose M2DS2, a simple and sample-efficient finetuning strategy for large pretrained speech models, based on mixed source and target domain self-supervision. We find that including source domain self-supervision stabilizes training and avoids mode collapse of the latent representations. For evaluation, we collect HParl, a 120 hour speech corpus for Greek, consisting of plenary sessions in the Greek Parliament. We merge HParl with two popular Greek corpora to create GREC-MD, a test-bed for multi-domain evaluation of Greek ASR systems. In our experiments we find that, while other Unsupervised Domain Adaptation baselines fail in this resource-constrained environment, M2DS2 yields significant improvements for cross-domain adaptation, even when a only a few hours of in-domain audio are available. When we relax the problem in a weakly supervised setting, we find that independent adaptation for audio using M2DS2 and language using simple LM augmentation techniques is particularly effective, yielding word error rates comparable to the fully supervised baselines.
Effective Power Electronics Understanding Using Circuit Simulation
Authors: Surya Sumukh , Chhetri, Ahilya , Mudlapur Arjun , Williamson Sheldon
Published: January 2023

Learning power electronics circuits through simulation is one of the best ways for an Undergraduate and Postgraduate student to understand the subject effectively. This article aims to provide a panoramic view of different software tools used for simulating electrical circuits and enable students to have the best choice among various tools. A simple buck converter is considered for illustration and is realized using multiple approaches using MATLAB, Scilab, and LTspice software tools. As MATLAB and LTSpice software tools provide the open loop characteristics of any physical system, a detailed analysis of frequency response for constant voltage operation (Gvd) and average current operations (Gid) for the converter is carried out. Though Scilab is open-source software it provides the same accuracy as that of a licensed tool, such as MATLAB. However, slowness in simulation is observed while simulating complex systems. For a quick insight into the frequency response, the LTspice software tool provides a high-speed response compared to MATLAB.
CONSIP: Consistency Protocol for Hopping Function Exchange and Black listing in TSCH
Authors: Scanzio Stefano , Bitondo Federico , Cena Gianluca , Valenzano Adriano
Published: January 2023

The use of white and black listing techniques in Wireless Sensor Networks (WSN), and in particular those which are based on the Time Slotted Channel Hopping (TSCH) operating mode of IEEE 802.15.4, permits to improve reliability and latency by performing transmissions on the best channels. Techniques that operate on a per-link basis are deemed quite effective, but proper operation requires that the two end points involved in the communication agree on the channels to be used for transmission. On the contrary, communication in the network can be prevented, eventually leading, in the worst cases, to the disconnection of part of the nodes.

This paper presents CONSIP, a technique aimed to ensure strict consistency in the information exchanged between the nodes and used to drive communication, by preventing a prior the aforementioned problem from occurring. Results show a slight increase in energy consumption, due to the use of a backup cell, whereas communication latency does not worsen. The effectiveness of CONSIP was assessed by means of an experimental campaign, and the only drawback we found is that the backup cell, which is required to be reserved per link, may limit the number of nodes in dense networks.
Graphene oxide for electronic and photonic chips
Authors: Moss David
Published: January 2023

As a derivative of graphene, graphene oxide (GO) was initially developed by chemists to emulate some of the key properties of graphene, but it was soon recognized as a unique material in its own right, addressing an application space that is not accessible to chemical vapor deposition based materials. Over the past decade, GO has emerged as a new frontier material with tremendous advances in its material fabrication and quality control over its properties. These in turn have led to rapid progress in GO based photonics, electronics, and optoelectronics concepts and devices, evoking new science and paving the way for many technological breakthroughs with exceptional performance. Here, we review the unique fundamental characteristics of GO, its thin film fabrication methods, patterning techniques, and mechanisms for tuning its material properties. This latter capability in particular has enabled novel advanced functional photonic, electronic, and optoelectronic devices. Understanding these insights is essential for designing and tailoring GO properties for state-of-the-art applications including solar energy harvesting, energy storage, medical diagnosis, image displays, and optical communications. We conclude by discussing the open challenges and exciting opportunities of this field, together with future prospects for major technological advancements and breakthroughs.
Comparative Modeling of Ethical Constructs in Autonomous Decision Making
Authors: Chhabra Janvi , Sama Karthik , Deshmukh Jayati , Srinivasa Srinath
Published: January 2023

Computational models for ethical autonomy, are crucial for building trustworthy autonomous systems. While different paradigms of ethical autonomy are pursued, comparing and contrasting these paradigms remains a challenge. In this work, we present SPECTRA (Strategic Protocol Evaluation and Configuration Testbed for Responsible Autonomy) a general purpose multi-agent, message passing framework on top of which, different models of computational ethics can be implemented. The paper also presents our implementation of four paradigms of ethics on this framework-- deontology, utilitarianism, virtue ethics and a recently proposed paradigm called computational transcendence. We observe that although agents have the same goal, differences in their underlying paradigm of ethics has a significant impact on the outcomes for individual agents as well as on the system as a whole. We also simulate a mixed population of agents following different paradigms of ethics and study the properties of the emergent system.
A quaternionic approach to kinematics for continuum manipulators
Authors: Prikhodko Victor
Published: January 2023

Quaternions have long been a powerful tool for describing the rotational motion of rigid bodies including conventional robotic manipulators. In this paper, we demonstrate that the quaternionic representation of kinematics for rigid link manipulators can be applied to continuum manipulators by passing to the limit as the link lengths tend to zero. Compact expressions are presented for forward kinematics that are based on the notions of distributed rotation quaternion and relative curvature. The robot’s pose in this formulation can be described by an arbitrary piecewise smooth function. Some simple closedform examples are discussed, and an approach to solving the inverse kinematics problem is outlined based on a modification of the cyclic coordinate descent algorithm.

This work has been submitted to the IEEE for possible publication.  Copyright may be transferred without notice, after which this version  may no longer be accessible. 
Transcranial Magnetic Stimulation Tech-nology with Freely Adjustable Pulse Shape and Sequence
Authors: Li Zhongxi , Zhang Jinshui , Peterchev Angel , Goetz Stefan
Published: January 2023

  

The temporal shape of a pulse in transcranial magnetic stimulation (TMS) influences which neuron populations are activated preferentially as well as the strength and even direction of neuromodulation effects. Furthermore, various pulse shapes differ in their efﬁciency, coil heating, sensory perception, and clicking sound. However, the available TMS pulse shape repertoire is still very limited to a few biphasic, monophasic, and polyphasic pulses with sinusoidal or near-rectangular shapes. Monophasic pulses, though found to be more selective and stronger in neuromodulation, are generated inefﬁciently and therefore only available in simple low-frequency repetitive protocols. Despite a strong interest to exploit the temporal effects of TMS pulse shapes and pulse sequences, waveform control is relatively inflexible and only possible parametrically within certain limits. Previously proposed approaches for flexible pulse shape control, such as through power electronic inverters, have signiﬁcant limitations: The semiconductor switches can fail under the immense electrical stress associated with free pulse shaping, and most conventional power inverter topologies are incapable of generating smooth electric ﬁelds or existing pulse shapes.

Leveraging intensive preliminary work on modular power electronics, we present a modular pulse synthesizer (MPS) technology that can, for the ﬁrst time, flexibly generate high-power TMS pulses (one-side peak ~ 4,000 V, ~ 8,000 A) with user-deﬁned electric ﬁeld shape as well as rapid sequences of pulses with high output quality. The circuit topology breaks the problem of simultaneous high power and switching speed into smaller, manageable portions, distributed across several identical modules. In consequence, MPS TMS can use semiconductor devices with voltage and current ratings lower than the overall pulse voltage and distribute the overall switching of several hundred kilohertz among multiple transistors. MPS TMS can synthesize practically any pulse shape, including conventional ones, with ﬁne quantization of the induced electric ﬁeld (≤ 17% granularity without modulation and ~300 kHz bandwidth). Moreover, the technology allows optional symmetric differential coil driving so that the average electric potential of the coil, in contrast to conventional TMS devices, stays constant to prevent capacitive artifacts in sensitive recording ampliﬁers, such as electroencephalography (EEG).

MPS TMS can enable the optimization of stimulation paradigms for more sophisticated probing of brain function as well as stronger and more selective neuromodulation, further expanding the parameter space available to users.
Analysis of optical wireless communication links in turbulent underwater channels with wide range of water parameters
Authors: Ata Yalçın , Kiasaleh Kamran
Published: January 2023

In this study, the performance of underwater optical wireless communication links is investigated by taking into account turbulence, absorption and scattering effects. Weak turbulent channel is modeled using log-normal distribution while moderate and strong turbulence channels are modeled using gamma-gamma distribution. Rytov variance of Gaussian beam is derived analytically for oceanic turbulence optical power spectrum. Subsequently, scintillation index is calculated using the computed Rytov variance. Moreover, the closed-form expression of bit-error-rate (BER) for underwater wireless optical communication (UWOC) systems using intensity-modulated/direct detection (IM/DD) implementation and on-off-keying (OOK) modulation scheme is obtained. Results show that the performance of wireless optical communication link between two platforms in underwater medium is degraded significantly due to turbulence, absorption and scattering. In fact, as the turbulence level increases, its effect becomes quantitatively comparable to those of absorption and scattering effects. The variation of both scintillation index and BER performance are presented for various underwater medium and communication system parameters, such as chlorophyll concentration, average temperature, average salinity concentration, temperature and dissipation rates, wavelength, link length and receiver aperture size. Optical network and internet of underwater things (IoUT) applications, which are growing day by day and requiring high data rates, will benefit from the results of this study. 
Agent-Based Cloud Simulation Model for Resource Management
Authors: Dong Dapeng
Published: January 2023

Driven by the successful service model and growing demand, cloud computing has evolved from a moderate-sized data center consisting of homogeneous resources to a heterogeneous hyper-scale computing ecosystem. This evolution has made the modern cloud environment increasingly complex. Large-scale empirical studies of essential concepts such as resource allocation, virtual machine migration, and operational cost reduction have typically been conducted using simulations. This paper presents an agent-based cloud simulation model for resource management. The focus is on how service placement strategies, service migration, and server consolidation affect the overall performance of homogeneous and heterogeneous clouds, in terms of energy consumption, resource utilization, and violation of service-level agreements. The main cloud elements are modeled as autonomous agents whose properties are encapsulated. The complex relationships between components are realized through asynchronous agent-to-agent interactions. Operating states and statistics are displayed in real time. In the evaluation, the efficiency of the simulator is studied empirically. The performance of various resource management algorithms is assessed using statistical methods, and the accuracy of server energy consumption models is examined. The results show that agent-based models can accurately reflect cloud status at a fine-grained level.
YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation
Authors: Lin Li , Peng Linkai , He Huaqing , Cheng Pujin , Wu Jiewei , Wong Kenneth Kin-Yip , Tang Xiaoying
Published: January 2023

Weakly-supervised learning (WSL) has been proposed to alleviate the conflict between data annotation cost and model performance through employing sparsely-grained (i.e., point-, box-,  scribble-wise) supervision and has shown promising performance, particularly in the image segmentation field. However, it is still a very challenging task due to the limited supervision, especially when only a small number of labeled samples are available. Additionally, almost all existing WSL segmentation methods are designed for star-convex structures which are very different from curvilinear structures such as vessels and nerves. In this paper, we propose a novel sparsely annotated segmentation framework for curvilinear structures, named YoloCurvSeg. A very essential component of YoloCurvSeg is image synthesis. Specifically, a background generator delivers image backgrounds that closely match the real distributions through inpainting dilated skeletons. The extracted backgrounds are then combined with randomly emulated curves generated by a Space Colonization Algorithm-based foreground generator and through a multilayer patch-wise contrastive learning synthesizer. In this way, a synthetic dataset with both images and curve segmentation labels is obtained, at the cost of only one or a few noisy skeleton annotations. Finally, a segmenter is trained with the generated dataset and possibly an unlabeled dataset. The proposed YoloCurvSeg is evaluated on four publicly available datasets (OCTA500, CORN, DRIVE and CHASEDB1) and the results show that YoloCurvSeg outperforms state-of-the-art WSL segmentation methods by large margins. With only one noisy skeleton annotation (respectively 0.14%, 0.03%, 1.40%, and 0.65% of the full annotation), YoloCurvSeg achieves more than 97% of the fully-supervised performance on each dataset. Code and datasets will be released at https://github.com/llmir/YoloCurvSeg.
KK Theory and K Theory for Type II Strings Formalism
Authors: Bhattacharjee Deep , Sadhu Riddhima , Behera Ashis Kumar , Roy Sanjeevan Singha , Das Saptashaw
Published: January 2023

Type-II emphasizing Type-II(B) in Ramond–Ramond Sector has been analyzed and computed from the Atiyah–Hirzebruch spectral sequence taking E_i sheets for the concerned values of i = 4=∞ and for E_n^(p,q) for n=1,2,3; several varieties of K–Theories where a transitive approach has been shown from the KK–Theory to K–Theory to String Theory concerning Fredholm modules of Atiyah–Singer Index Theorem and the Baum–Connes conjecture with respect to the Hilbert–A, Hilbert–B module and c*-algebras also in the reduced form taking Morita equivalence and the Kasparov composition product where extended relations has been provided between the equivalence of noncommutative geometry and noncommutative topology channelized through Poincaré Duality, Thom Isomorphism and Todd class.
Differentiable Image Data Augmentation and Its Applications: A Survey
Authors: Shi Jian , Ghazzai Hakim , Massoud Yehia
Published: January 2023

Data augmentation is an effective method to improve model robustness and generalization. Conventional routines of data augmentation pipeline are used as a preprocessing modules for neural networks with predefined heuristics and restricted differentiability. Some recent works indicated that the differentiable data augmentation (DDA) could effectively contribute to the training of neural networks and the augmentation policy searching strategies. This survey provides a comprehensive and structured overview of the advances in DDA, with a focus on fundamental elements including differentiable operations, operation relaxations, and gradient estimations. We then categorize existing DDA works accordingly. Afterwards, the survey investigates the utilization of DDA in selected of practical applications, specifically neural augmentation and differentiable augmentation search. Finally, we discuss current challenges of DDA and some promising future research directions.
Structural and SCOAP features based approach for hardware Trojan detection using SHAP and Light Gradient Boosting model
Authors: Sharma Richa , Sharma G.K. , Pattanaik Manisha , Prashant VSS
Published: January 2023

Hardware Trojan (HT) is the most critical threat due to outsourcing of Integrated circuit designing phases. Therefore, a new technique is proposed that utilizes structural and SCOAP features to detect HT from the gate-level netlist using Light Gradient Boosting (Light GBM). Further, a model agnostic Shapley additive explanations (SHAP) is employed to identify each feature global and local impact on model prediction. Moreover, a quartile-based feature selection method is proposed, which uses SHAP to identify the optimal feature set by keeping low retraining rounds. Experimental results show that the proposed technique accurately detects always-on-Trojans and HT nets from Trust-Hub, DeTrust, and DeTest benchmarks.
On the Use of a Metasurface Lens Over a Large-Element-Spacing Antenna Array for Grating Lobe Suppression and Gain Enhancement
Authors: Ge Yuehe
Published: January 2023

The large-element-spacing (LES) antenna arrays have the advantages of low cost and less structural complexity but generally suffer from high-level grating lobes. In this paper, we propose a new method to address the issue. By placing a metasurface lens above such an LES array at an appropriate height to adjust and compensate for the phases of the near fields generated by the array, the grating lobes can be suppressed or eliminated without increasing the design complexity. Theoretical analyses, calculations from an efficient numerical method, simulations, and experiments are carried out to validate the proposed method. A complete study of the radiation performance of the proposed antenna configuration is also conducted using the above different ways. All the results demonstrate that the grating lobes from an LES antenna array can be suppressed and the gain can be improved by the proposed method at the cost of a slight increase in the antenna array profile or volume. The novel approach can be applied to any LES antenna arrays, with either large or small sizes, uniform or non-uniform spaces, and periodic or aperiodic structures. 
Development and Application of 3D Hyperspectral Scanning System for Underground Mine and Tunnel Exploration
Authors: Baik Hyunseob , Son Young-Sun , Kim Kwang-Eun
Published: January 2023

A hyperspectral scanning system was developed for three-dimensional (3D) surface mapping in underground spaces, such as mine shafts and tunnels. A hyperspectral line-scanning camera was mounted on the rotating driver unit coaxial with the tunnel to image both the mine wall and the ceiling. Uniform light was illuminated on the target surface to be imaged using a halogen lamp rotating together with the hyperspectral imaging sensor. A stereo camera, Light Detection and Ranging (LIDAR), and Inertial Measuring Unit (IMU) were also attached to the sensor unit together with the hyperspectral camera so that geometric information could be acquired simultaneously during imaging. All sensor and controller units were mounted on a cart-type platform for easy movement in the tunnel, and a battery mounted on the platform supplied power for system operation and the halogen light source. The developed scanning system was tested in an actual mine, and 3D hyperspectral images of the internal surface of the mine shaft were successfully obtained.
Applications for optical frequency microcomb chips
Authors: Moss David
Published: January 2023

Optical microcombs represent a new paradigm for generating laser frequency combs based on compact chip-scale devices, which have underpinned many modern technological advances for both fundamental science and industrial applications. Along with the surge in activity related to optical micro-combs in the past decade, their applications have also experienced rapid progress ‒ not only in traditional fields such as frequency synthesis, signal processing, and optical communications, but also in new interdisciplinary fields spanning the frontiers of light detection and ranging (LiDAR), astronomical detection, neuromorphic computing, and quantum optics. This paper reviews the applications of optical microcombs. First, an overview of the devices and methods for generating optical microcombs is provided, which are categorized into material platforms, device architectures, soliton classes, and driving mechanisms. Second, the broad applications of optical microcombs are systematically reviewed, which are categorized into microwave photonics, optical communications, precision measurements, neuromorphic computing, and quantum optics. Finally, the current challenges and future perspectives are discussed.
Non-interference patterns evolving to interference patterns --- Universal phenomena of single slit, double slit, cross double slit, triple slit, disc ring, 1D grating and 2D grating experiments
Authors: peng hui
Published: January 2023

Young’s double slit (and Arago spot) experiments revived the wave theory of light. The standard interpretation is that the light behaves as waves before and after passing through the double slit. 

Feynman called the double slit experiment the only mystery in quantum mechanics. In this article, we postulate and experimentally confirm the precise rules of convex lenses. Based on those Postulates, we study the evolution of the patterns of single slit, double slit, triple slit, cross-double slit, disc ring, 1D-grating and 2D-grating experiments. The experiments show, for the first time, the novel universal phenomena: (1) Within a certain macroscopic distance from the diaphragm (Zone-1), light behaves as photons and produces a non-interference pattern, while near the screen (the far field, Zone-3), the photons produce an interference pattern, while between Zone-1 and Zone-3 (Zone-2), the photons produce an non-interference pattern; namely the nature and characteristics of the pattern are distance dependent; (2) The non-interference pattern evolves to the interference pattern gradually in the same experiment; (3) The convex lens stops the evolution of the patterns. The experiments provide profound phenomena/data for further theoretical development of optics and for understanding the nature of light. We suggest that a complete theory should be able to interpret the non-interference pattern in Zone-1, the non-interference pattern in Zone-2, and the interference pattern in Zone-3; and the evolution from one pattern to another. 
A Survey on STAR-RIS: Use Cases, Recent Advances, and Future Research Challenges
Authors: Wahid Abdul , Ahmed Manzoor , Laique Sayed Shariq , Khan Wali Ullah , Ihsan Asim , Xu Fang , Chatzinotas Symeon , Han Zhu
Published: January 2023

The recent development of metasurfaces, which may enable several use cases by modifying the propagation environment, is anticipated to have a substantial effect on the performance of 6G wireless communications. Metasurface elements can produce essentially passive sub-wavelength scattering to enable a smart radio environment. STAR-RIS, which refers to reconfigurable intelligent surfaces (RIS) that can transmit and reflect concurrently (STAR), is gaining popularity. In contrast to the widely studied RIS, which can only reflect the wireless signal and serve users on the same side as the transmitter, the STAR-RIS can both reflect and refract (transmit), enabling 360-degree wireless coverage, thus serving users on both sides of the transmitter. This paper presents a comprehensive review of the STAR-RIS, with a focus on the most recent schemes for diverse use cases in 6G networks, resource allocation, and performance evaluation.

We begin by laying the foundation for RIS (passive, active, STAR-RIS), and then discuss the STAR-RIS protocols, advantages, and applications. In addition, we categorize the approaches within the domain of use scenarios, which includes increasing coverage, enhancing physical layer security (PLS), maximizing sum rate, improving energy efficiency (EE), and reducing interference. Next, we will discuss the various strategies for resource allocation and measures for performance evaluation. We aimed to elaborate, compare, and evaluate the literature in terms of setup, channel characteristics, methodology, and objectives. In conclusion, we examine the open research problems and potential future prospects in this field.
Tranched Tokenised Revenue Streams as a Tool for Renewable Energy Financiers and Electrical Offtakers
Authors: de Villiers Almero , Byrne Julie , Cuffe Paul
Published: January 2023

Renewable energy generation is non-dispatchable and notably unpredictable. Furthermore, a volatile electricity spot market means vulnerability to both price and volumetric risk for generation firms. As such, project financiers may be hesitant to invest in renewable energy projects. Electrical offtakers purchase from the same spot market, and thus also suffer its uncertainty. Ideas from the world of blockchain and decentralised finance may present solutions for these cases. This paper proposes tokenised revenue streams \textit{(RevToks)} as a novel mechanism for the electricity industry. A RevTok allows the owning party to directly claim a share of a specific generator's revenue stream. This is combined with tranching, a technique from finance where priority on a revenue flow is divided based on seniority. Project financiers hold this senior RevTok that entitles them to precedence on generator incomes, ensuring loan repayments. A case study using real-world generation, pricing, and consumption data is formulated. A market simulation is performed in the form of optimisation problem to establish an idea market equilibrium. Junior tranch RevToks can be purchased by electrical offtakers to decrease their budget variance by offsetting fluctuations in their monthly energy bill. The tranched revenue profiles of generators are demonstrated visually. For offtakers, monthly variance is universally decreased. The case study market simulations shows evidence that tranched revenue sharing arrangements show benefits for generators, financiers, and offtakers.
Zero-effort Continuous Two-factor Authentication
Authors: AlQahtani Ali Abdullah S.
Published: January 2023

Traditional two-factor authentication (2FA) systems often require users to enter a code or use a physical token, which can be inconvenient or inconvenient. In this paper, we propose a novel zero-effort 2FA system that utilizes the characteristics of ambient access points (APs) visible to users’ devices to authenticate them without requiring user interaction. The proposed system is flexible and adaptable, allowing for the adjustment of various parameters such as the range of acceptable distances between the user’s devices and the minimum number of APs required for authentication. It is also robust, with features to handle situations where there may be a lack of APs in the user’s environment or the user does not have access to their mobile device. Additionally, the proposed system takes user privacy into consideration by limiting the storage of sensitive information and purging data related to a user’s session after it is complete. The proposed system is a secure and user-friendly solution for 2FA that can be easily implemented in various settings. Finally, the proposed system was tested and evaluated, and the results showed that it is effective in authenticating users while maintaining a high level of security.
Differential derivation method for high accuracy calculation of the refractive index curves
Authors: Li Wenjuan , Wang Nan , Jia Luyuan , Zhu Hongyu , Zhang Lei
Published: January 2023

A differential derivation method is demonstrated to high-accurately calculate the refractive index curves by solving the mode coupling problems in theoretical calculations. Because of the existence of mode coupling, the finite element method cannot lock the calculator in the interested mode, especially at the crossing part of two refractive index curves. Either imaginary crossing or real crossing will result in an inaccurate calculation of the refractive index curve. The calculation accuracy in the crossing parts is improved by using the differential derivation method, and the effectiveness is verified by calculating the refractive index curves for the HE11, HE12, TE01, and EH11 modes of a custom-designed fiber.
Importance of Accurate Zref Estimation for Transmission Line Characterization based on 2x-thru Calibration
Authors: Chou Chiu-Chih
Published: January 2023

The 2x-thru calibration is frequently used in the characterization of printed circuit board (PCB) transmission lines. Since the reference impedance of the calibrated S parameters are exactly given by the characteristic impedance, ZLINE, of the trace at the center of THRU, accurate estimation of this impedance becomes crucial to the accuracy of the renormalized S parameters. In this paper, we compare three different methods of estimating ZLINE: the mid-point TDR method, the initial-value TDR method, and the analytic model fitting method. Through a simulation test case, it is demonstrated that (i) the initial-value method gives accurate high-frequency responses, but inaccurate low-frequency and time-domain responses, (ii) the mid-point TDR gives inaccurate results in both time and frequency domains, and (iii) the analytic model method produces the most accurate results. 
Trajectory Generation for Space Manipulators Capturing Moving Targets Using Transfer Learning
Authors: Sze Hon Yin , Chhabra Robin
Published: January 2023

In a debris mitigation mission, a crucial phase of the proximity operation for a space manipulator is chasing a capture point on a noncooperative target satellite. Knowing the uncertain position and velocity of the target, a learning-based online trajectory planner offers a robust solution to the chasing problem. This paper uses the concept of transfer learning to develop an online trajectory generator for the task of capturing a moving target with an uncertain space manipulator. We divide this complex task into multiple sub-tasks and order them based on their difficulty level. We employ the Deep Deterministic Policy Gradient (DDPG) algorithm to learn each sub-task individually. The DDPG is a deep reinforcement learning approach that provides the ability to work with continuous states and actions by approximating the action-value function and the policy with neural networks. We propose a novel method to transfer the knowledge gained in an easier sub-task to a more difficult one in the form of expert policy and transition memories. State and action representation has a crucial impact on learning performance, which is comprehensively studied in this paper for the task of capturing a moving target. Considering the learning performance, we show the existence of an optimal state representation, which is not necessarily the minimal representation of the system. We compare different action representations of a manipulator, i.e., joint space and workspace velocities, and demonstrate the superiority of the workspace actions. Finally, the developed transfer learning approach is implemented on a planar space manipulator with an onboard 2-link arm to generate trajectories that can capture a target randomly moving with the maximum speed of the manipulator’s end effector. To show the efficacy of the approach, its results are compared with the case where the agent learns the task from scratch.
Thin Shell Model of a Coated Conductor with a Ferromagnetic Substrate
Authors: Prigozhin Leonid , Sokolovskiy Vladimir
Published: January 2023

Thin shell model of a coated conductor with a ferromagnetic support, efficient spectral method for numerical simulations
Privacy-Cost Optimization of Smart Meters Using URLLC and Demand Side Energy Trading
Authors: Hossain Mohammad Belayet , Pokhrel Shiva , Choi Jinho
Published: January 2023

The work is related to the privacy of smart meter and the benifits of using URLLC in smart grid network.
Causal inference on the impact of nutrition policies using observational data
Authors: Mazzocchi Mario , Capacci Sara , Biondi Beatrice
Published: January 2023

We discuss the state-of-the-art in the application of quasi-experimental methods to estimate the impact of nutrition policies based on observational data. This field of application is less mature compared to other settings, especially labour and health policy, as food economists have started to implement widely counterfactual methods only over the last decade. We review the underlying assumptions behind the most prominent methods, when they can be regarded as credible and if/when they can be tested. We especially focus on the problem of dealing with unobserved confounding factors, emphasizing recent evidence on the limitations of propensity score methods, and the hard task of convincing reviewers about the quality of instrumental variables. We discuss the application of Difference-in-Difference, with an emphasis on its potential in consumer panel data applications, and how results from Regression Discontinuity Design studies should be interpreted. Finally, we cover the estimation of counterfactual outcomes using structural methods and provide an overview of recent developments and current gaps.
Acknowledgements
Authors: AAVV AAVV
Published: January 2023

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