bluuebunny/crossref_metadata_2025 huggingface dataset:
Different Market Segmentations of Dividend Policies: A Dynamic Panel Data Analysis
Authors: Shafai Nor Anis , Yusuf Noor Hafizha Muhamad , Shah Noor Sharida Badri , Bulot Norhisam
Published: April 2023

Objective - Despite much previous research on the issue, dividend policy remains an unsolved conundrum in corporate finance. By considering this, the goal of this research is to use the Generalized Method of Moments to examine dividend behaviour by identifying the key determinants of dividend policy in three different countries with different market microstructures: Singapore (developed market), Malaysia (developing market), and Saudi Arabia (emerging market).
Methodology/Technique –. The study uses data from each country's top 100 listed firms from 2007 until 2016. The results suggest that different determinants influence firms’ dividend policies for the three countries.
Findings - For Singapore as a developed market, profitability, and size are shown to be significantly and positively related to the dividend payout ratio, whereas leverage, business risk, and growth opportunities exert a significant negative effect. Meanwhile, for Malaysia (a developing market), only firm size is a significant and positive determinant. However, leverage and business risk are negatively and significantly associated with the dividend payout ratio. Conversely, for Saudi Arabia as an emerging market, firm size and leverage positively and negatively influence the dividend payout ratio.
Novelty - Therefore, this study employed the generalized method of moments (GMM) to uncover novel discoveries. The findings should motivate analysts, policymakers, institutional investors, and investors to investigate the dividend policy conundrum, mainly for three different market segmentations.
Type of Paper: Empirical
JEL Classification: G32, M14.
Keywords: Dividend behaviour, market microstructure, and Generalized Method of Moments.
Reference to this paper should be referred to as follows: Shafai, N.A; Yusuf, N.H.M; Shah, N.S.B; Bulot, N. (2023). Different Market Segmentations of Dividend Policies: A Dynamic Panel Data Analysis, Acc. Fin. Review, 7(4), 01 – 11. https://doi.org/10.35609/afr.2023.7.4(1)
Green Accounting and Firm Value
Authors: Alexander Nico
Published: April 2023

Objective - The environment is one of the more interesting issues to discuss, especially if it relates to companies' accounting issues. This study was conducted to determine the effect of green accounting implementation on firm value.
Methodology/Technique – Firm value is measured using Tobins-Q, and green accounting is measured by ratings based on PROPER. Multiple regression analysis was used, and 35 manufacturing companies were sampled in this study.
Findings - The results of this study show that green accounting can increase firm value. Companies that apply green accounting have a higher firm value because information about environmental costs is additional information for stakeholders when making decisions. If the company does not incur environmental costs, it is considered bad for investment.
Novelty - Green accounting is still new, so this study was conducted to provide an overview of green accounting and firm value. Companies implementing green accounting will increase their firm value and help preserve the environment. It is hoped that Indonesian accounting organizations will develop standards regarding green accounting.
Type of Paper: Empirical.
JEL Classification: F64, L50, M14, Q52, Q56
Keywords: Green Accounting; Firm Value; Green Investment; PROPER; Indonesia
Reference to this paper should be referred to as follows: Alexander, N. (2023). Green Accounting and Firm Value, Acc. Fin. Review, 7(4), 12 – 18. https://doi.org/10.35609/afr.2023.7.4(2)
EFFECTIVENESS OF VIRTUAL LABORATORY ON GRADE EIGHT STUDENTS’ SPATIAL ABILITY
Authors: Al-Duhani Fatma , Mohd Saat Rohaida , Abdullah Mohd Nor Syahrir
Published: April 2023

This study examines how virtual laboratory improves and enhances 8th grade students’ spatial ability to learn electricity-related subjects in the Sultanate of Oman. As for the instrument a quasi-experimental pre-test and post-test were used to analyse the data obtained from forty school girls aged 14-15. The findings demonstrate that the virtual lab, as opposed to the physical one, developed students' mental turning, spatial imagining and spatial skills. The results emphasise that by using the virtual laboratory, pupils are able to visualise non-perceptible phenomena and processes, and that the virtual lab, unlike the physical lab, develops higher level thinking skills, self-confidence and imagination of primary school students. The results are statistically significant for the experimental group, who actually learned and performed more quickly than the control group. The study recommends that a future study be conducted on how virtual laboratory effects 8th grade students’ cognitive and conceptual abilities in physics and electricity.
An Alternative Interpretation for the Origin of Black Shale in the Bakken Formation of the Williston Basin
Authors: Petty David M.
Published: April 2023

Recently, most researchers have argued for a deep-water origin for black shale in the Bakken Formation of the Williston basin based on sedimentology, paleontology and geochemistry characteristics that place black, laminated, sparsely fossiliferous, radiolarian, pyritic shale as the seaward lithology in an assemblage that originally transitioned landward into shallow-water facies. The shallow-water interpretation advocated in this paper is based on stratigraphic characteristics that include the absence of strata that represent a landward equivalent to the shale, gradual landward shale pinchouts, the restriction of Bakken strata to basinal areas, the Bakken onlap depositional style, and placement of a major maximum flooding surface near the base of the overlying Lodgepole.

Black mud deposition in the Bakken is interpreted to have occurred in a low-relief, semi-enclosed, epeiric-lagoon environment with typical water depths of 0–30 m. It is theorized that a high-rainfall climate caused salinity stratification that produced bottom-water anoxia, which preserved organic material. Perhumid climate conditions (year-round rainfall) fostered thick soils and dense vegetation that limited sediment release and induced mud-dominated, sand-poor deposition. During middle Bakken deposition, an arid to semi-arid climate eliminated the bottom-water anoxic conditions and caused carbonate-siliciclastic deposition. The abrupt vertical transitions from black shale (lower Bakken), to carbonate-siliciclastic lithologies (middle Bakken), to black shale (upper Bakken) were caused by paleoclimate change.
Bayesian artificial intelligence for geologic prediction: Fracture case study, Horn River Basin
Authors: Agar S.M , Li W. , Goteti R. , Jobe D. , Zhang S.
Published: April 2023

A Bayesian Belief Network (BN) has been developed to predict fractures in the subsurface during the early stages of oil and gas exploration. The probability of fractures provides a first-order proxy for spatial variations in fracture intensity at a regional scale. Nodes in the BN, representing geologic variables, were linked in a directed acyclic graph to capture key parameters influencing fracture generation over geologic time. The states of the nodes were defined by expert judgment and conditioned by available datasets. Using regional maps with public data from the Horn River Basin in British Columbia, Canada, predictions for spatial variations in the probability of fractures were generated for the Devonian Muskwa shale. The resulting BN analysis was linked to map-based predictions via a geographic information system. The automated process captures human reasoning and improves this through conditional probability calculations for a complex array of geologic influences. A comparison between inferred high fracture intensities and the locations of wells with high production rates suggests a close correspondence. While several factors could account for variations in production rates from the Muskwa shale, higher fracture densities are a likely influence. The process of constructing and cross-validating the BN supports a consistent approach to predict fracture intensities early in exploration and to prioritize data needed to improve the prediction. As such, BNs provide a mechanism to support alignment within exploration groups. As exploration proceeds, the BN can be used to rapidly update predictions. While the BN does not currently represent time-dependent processes and cannot be applied without adjustment to other regions, it offers a fast and flexible approach for fracture prediction in situations characterized by sparse data.
Indonesian chitons of the genera Belknapchiton Sirenko, Saito et Schwabe, 2022 and Leptochiton Gray, 1847(Mollusca: Polyplacophora: Leptochitonidae)
Authors: Sirenko Boris I.
Published: April 2023

On the basis of the collections of the R/V Vityaz in the Banda Sea, Indonesia, a review of the chiton fauna of the genera Belknapchiton and Leptochiton was carried out. Leptochiton commandorensis , until now known only from the northern Pacific near the Commander Islands, is here added to the four known Indonesian deep sea species. This species turned out to be with juveniles in the pallial groove. A scanning electron microscope study of the collected specimens of B. giganteus made a corrected, supplemented description of this rare species possible. The age variability of the valves shape and shell sculpture of the two collected species was studied. Particular attention is paid to the age variability of the number of micraesthetes on the tegmentum grains and the position of the mucro.
Trust e sequestro preventivo: l’atto di disposizione delle partecipazioni sociali non incide sulla titolarità del patrimonio dell’ente (Cass. 22 settembre 2022, n. 35660)
Authors: Santangelo Alessandra
Published: April 2023

Massima
In caso di sequestro preventivo ex art. 321, comma 1, cod. proc. pen., che abbia a oggetto le quote sociali e il patrimonio della società, la disposizione di un blind trust sulle sole partecipazioni, ancorché totalitarie, non condiziona la titolarità delle componenti patrimoniali riferibili alla società e, per l’effetto, la legittimazione a impugnare il provvedimento cautelare.
Trustee soggetto passivo anche della TASI (CTP Roma, 7 luglio 2022)
Authors: Beraldo Andrea
Published: April 2023

Massima
La normativa disciplinante la fiscalità locale è priva di norme che regolano la casistica degli immobili dotati in trust: tuttavia, l’esame dei presupposti impositivi fondanti i tributi locali consente di individuare nel trustee il soggetto passivo della TASI, oltreché dell’IMU.
I disponenti sono comunque liberi di individuare nell’atto istitutivo del trust il soggetto tenuto a sostenere l’onere economico dei tributi: una tale disposizione non modifica la struttura dell’obbligazione tributaria, attribuendo soggettività passiva ad un soggetto diverso da quello individuato dal legislatore, poiché essa incide solo sul piano economico-finanziario del pagamento del tributo. Ne discende che il pagamento dei tributi locali eseguito da un terzo (nella specie, il disponente) determina l’estinzione dell’obbligazione tributaria, esplicando effetti anche a beneficio del soggetto passivo (ossia il trustee).
Il conferimento in trust della nuda proprietà di un immobile entro il quinquiennio dall’acquisto non determina la decadenza dall’agevolazione dei benefici 'prima casa' (CTP Firenze, 1 luglio 2022)
Authors: Cecci Maddalena
Published: April 2023

Massima
I disponenti i quali, prima del decorso del quinquennio dall’acquisto, conferiscano in trust la nuda proprietà dell’immobile relativamente al quale hanno goduto delle agevolazioni fiscali per l’acquisto della prima casa non decadono da dette agevolazioni, in quanto il conferimento in trust, non comportando un atto dispositivo in senso proprio, non integra il presupposto di atto traslativo rilevante ai fini della declaratoria di decadenza.
Il trust non sconta l’IVIE per i periodi di imposta anteriori al 2020 (CTP Benevento, 19 gennaio 2022)
Authors: Volontè Umberto
Published: April 2023

Massima
La sentenza n. 16 del 19 gennaio 2022 della CTP di Benevento è significativa poiché conferma che i trust fiscalmente riconosciuti non erano soggetti al pagamento dell’IVIE per i periodi di imposta antecedenti all’entrata in vigore della riforma recata dalla Legge di Bilancio 2020 (L. 27 dicembre 2019, n. 160). Inoltre, dalla decisione sembrerebbe possibile ritrarre anche taluni spunti di carattere generale sulla fiscalità dei trust autodichiarati o autodestinati, ed in particolare sulla possibilità che anche queste delicate figure di trust possano essere considerate valide ai fini fiscali, in assenza di prove, da parte dell’Amministrazione, in ordine all’effettiva sussistenza di elementi di interposizione.
Bad advice
Authors: Swadling William
Published: April 2023

The author’s view
This article is concerned with the situation where bad financial advice is given to an intending settlor to constitute a trust or to trustees in the exercise of their powers under an existing trust. When this advice turns out to have adverse financial consequences for the trust, are the settlor and trustees left to claims against the adviser for breach of contract, or can the settlement or exercise of the power be set aside?
Tesi
Questo articolo tratta il caso in cui chi sta per istituire un trust oppure il trustee che sta per esercitare un proprio potere riceve un parere professionale errato. Quando emerge che avere seguito questo parere ha prodotto effetti dannosi per il trust, il disponente o rispettivamente il trustee può solo agire contro il professionista che ha espresso il parere o può il negozio compiuto sulla base di quel parere essere dichiarato privo di effetti?
Una critica alla dichiarazione di nullità del trust liquidatorio c.d. anticoncorsuale (App. Napoli, 17 giugno 2022)
Authors: Manna Mario
Published: April 2023

Tesi
L’applicazione delle norme imperative che presiedono alla liquidazione concorsuale e alla tutela della par condicio creditorum, nel caso in cui un imprenditore, già versante in stato di insolvenza, istituisca un trust c.d. liquidatorio ivi trasferendo tutti i beni dell’impresa, non dovrebbe essere garantita tramite la dichiarazione di nullità dell’atto istitutivo del trust. Ciò poiché l’istituzione del trust in quanto tale non sottrae i beni alla procedura concorsuale né tantomeno lede la par condicio creditorum. Piuttosto, in coerenza con i rimedi previsti dall’ordinamento, il giudice dovrebbe procedere con la dichiarazione di revocabilità ex art. 2901 cod. civ. degli atti con cui il disponente ha trasferito i beni dell’impresa all’interno del trust, in quanto sono questi gli atti che distraggono i beni dalla procedura concorsuale.
The author’s view
In the event that an entrepreneur, already in a state of insolvency, establishes a so-called liquidation trust, transferring all the company’s assets to the trustee, the application of the mandatory rules governing insolvency procedures and the protection of creditors should not entail declaration of nullity of the trust deed. This is because the establishment of the trust as such does not subtract the assets from the insolvency procedure nor harm the creditors. Rather, in line with the remedies provided by the law, the judge should proceed with the declaration of revocability pursuant to art. 2901 of the civil code of the acts through which the settlor has transferred the assets of the company to the trustee, as these are the acts which have diverted the assets from the insolvency procedure.
The Degree of Smoking Based on the Brinkman Index and Insomnia
Authors: Purnawinadi I Gede
Published: April 2023

One of the human basic is the need to rest. Resting for humans is useful for restoring energy, repairing cells and resting the organs of the body which all day long activity. One way humans rest their bodies is by sleeping. Nicotine is a stimulant, and nicotine side effects can cause insomnia. The purpose of this study was to identify a significant relationship between the degree of smoking based on the Brinkman Index and insomnia through analytical survey research using cross sectional studies. The subjects of this study were people who smoked in Kaima village, Kauditan sub-district, North Minahasa district with a total sampling technique, which amounted to 80 respondents according to the results of the initial survey of researchers through direct interviews. Statistical test results show a significance value (p = 0.009 < 0.05) with a weak correlation coefficient ( r = 0.288) with a positive direction. There is a significant relationship between the degree of smoking and the incidence of insomnia. The community is expected to be able to change smoking behavior by reducing the number of cigarettes consumed or even stop smoking.
PENGARUH TERAPI BERMAIN MEWARNAI GAMBAR TERHADAP TINGKAT KECEMASAN ANAK USIA PRASEKOLAH AKIBAT HOSPITALISASI DI RSUP. PROF. DR. R. D. KANDOU MANADO
Authors: Gerungan Nova
Published: April 2023

Kecemasan yang timbul pada anak selama dirawat di Rumah Sakit merupakan dampak dari hospitalisasi. Kecemasan dapat mengganggu tumbuh kembang anak dan proses penyembuhan pada anak. Terapi bermain mewarnai gambar merupakan salah satu teknik untuk menurunkan kecemasan yang di alami anak usia prasekolah akibat hospitalisasi. Penelitian ini bertujuan untuk mengetahui pengaruh terapi bermain mewarnai gambar terhadap tingkat kecemasan anak usia prasekolah akibat hospitalisasi. Desain penelitian yang digunakan dalam penelitian ini adalah pre-experimental dengan one-group pre-post test design. Teknik pengambilan sampel menggunakan purposive sampling dengan jumlah sampel 30. Teknik pengumpulan data menggunakan kuesioner. Hasil penelitian menunjukkan gambaran tingkat kecemasan pada anak sebelum diberikan terapi mewarnai gambar terdapat 4 (13.3%) responden pada tingkat kecemasan sedang dan 26 (86.7%) responden pada tingkat kecemasan berat. Sedangkan gambaran tingkat kecemasan sesudah diberikan terapi mewarnai terdapat 4 (13.3%) responden pada tingkat kecemasan ringan dan 26 (86.7%) responden pada tingkat kecemasan sedang. Hasil uji statistik menggunakan rumus wilcoxon test diperoleh nilai p=0.000 < 0.05 yang berarti ada pengaruh yang signifikan dari terapi bermain mewarnai gambar terhadap tingkat kecemasan anak usia prasekolah akibat hospitalisasi. Dapat disimpulkan bahwa terapi bermain mewarnai gambar dapat menurunkan tingkat kecemasan. Disarankan kepada institusi pelayanan kesehatan untuk dapat meningkatkan lagi pelayanan kesehatan terhadap anak usia prasekolah dengan memberikan terapi bermain mewarnai gambar untuk menurunkan tingkat kecemasan akibat hospitalisasi.
DAMPAK PANDEMI COVID-19 PADA PRESTASI BELAJAR MAHASISWA KEPERAWATAN TAHAP AKADEMIK
Authors: Purnawinadi I Gede
Published: April 2023

Latar belakang: Pandemi COVID-19 berdampak signifikan disemua bidang secara global, terlebih khusus pada dunia pendidikan secara nasional. Kegiatan pembelajaran tatap muka beralih pada proses pembelajaran daring (online) dalam upaya mencegah penularan virus corona. Transformasi pembelajaran ini tentunya mempunyai konsekuensi terhadap hasil belajar peserta didik baik tingkat menengah maupuan di perguruan tinggi. Penelitian ini bertujuan menganalisis prestasi belajar mahasiswa keperawatan tahap akademik melalui uji komparatif IPK pada semester sebelum dan saat pandemi. Metode: Data penelitian ini merupakan total sampling 1043 IPK mahasiswa keperawatan di salah satu perguruan tinggi swasta di sulawesi utara. Data dianalisis melalui uji komparatif non parametrik Mann Whitney karena tidak memenuhi kelayakan asumsi normalitas. Hasil: Hasil penelitian ini didapati bahwa terjadi peningkatan kategori prestasi belajar mahasiswa sebelum dan saat pandemi, sehingga ada berbedaan yang signifikan kategori prestasi belajar mahasiswa keperawatan pada semester sebelum dan saat pandemi COVID-19 dengan nilai signifikan 0,000 (p value < 0,05). Kesimpulan: Konsep merdeka belajar yang benar melalui penggunaan teknologi dalam proses pembelajaran memberikan peluang kepada para peserta didik dalam belajar dan mengembangkan diri secara mandiri, meskipun situasi pandemi menuntut kegiatan pembelajaran secara daring. Diskusi: Bagi institusi penyelenggara pendidikan diharapkan tetap mengembangkan manajemen pembelajaran daring dengan meningkatkan fasilitas dan sumber daya yang memadai.
Sparse Online Learning with Kernels using Random Features for Estimating Nonlinear Dynamic Graphs
Authors: Money Rohan , Krishnan Joshin P. , Beferull-Lozano Baltasar
Published: April 2023

An online nonlinear topology identification algorithm termed RFNL-TIRSO is proposed in the paper. The multivariate time series data received in sequential form is processed online to estimate time-varying nonlinear dependencies
Techno-economics of Fiber vs. Microwave for Mobile Transport Network Deployments [Invited]
Authors: Lashgari Maryam , Tonini Federico , Capacchione Massimiliano , Wosinska Lena , Rigamonti Gabriele , Monti Paolo
Published: April 2023

One of the challenges for network operators is to design and deploy cost-efficient transport networks (TNs) to meet the high capacity and strict latency/reliability requirements of today’s emerging services. Therefore, they need to consider different aspects, including the appropriate technology, the level of reconfigurability, and the functional split option. A crucial aspect of network design is assessing the impact of these aspects against the total cost of ownership (TCO), latency, and reliability performance of a given solution. For this reason, this paper proposes a framework to investigate the TCO, latency, and reliability performance of a set of fiber and microwave-based TN architectures. They are categorized based on their baseband functional split option and the reconfigurability capabilities of the equipment used. The results, based on real data from a non-incumbent operator, show that in most of the considered scenarios, a microwave-based TN exhibits lower TCO than a fiber-based one. The TCO gain may vary with the choice of the functional split option, geo-type, reconfigurability features, fiber trenching costs, and cost of microwave equipment, with a more significant impact in a dense urban geo-type, where for a low layer functional split option the fiber- and microwave-based architectures have a comparable TCO. Finally, it was found that the considered fiber and microwave architectures have almost similar average latency and connection availability performance. Both are suitable to meet the service requirements of 5G and beyond 5G services in most of the considered scenarios. Only in extreme latency-critical scenarios, a small number of the cells might not fully satisfy the latency requirements of a low layer split option due to multiple microwave hops in the microwave-based architecture.
Image Processing Results of Chlamydia Pneumonia X-Ray
Authors: Bansal Abhishek
Published: April 2023

This paper presents the collection of 154 new images and results, obtained after performing many known image processing algorithms and digital image transformations techniques like adding noises namely Gaussian with variances, Poisson and speckle with variances; double precision, methods of Sobel, Prewitt and Robert; de- hazing algorithm, pixel intensities, vector quantization, k-means clustering, fuzzy logic and morphological segmentation. Images used in this paper are two X-Rays having the lateral and Posterior to Anterior (PA) views of the patient’s lungs who was diagnosed from Chlamydia Pneumonia which is a lung infection caused by bacteria of family Chlamydiaceae and order Chlamydiales, which causes respiratory tract infections and illness by damaging the lining of the respiratory tract including the throat, windpipe, and lungs. Chlamydia pneumoniae is a small gram-negative bacterium (0.2 - 1 μm). All results are included in the paper as well as separate images have also been uploaded on the open-access page. The data has been analyzed with histogram and mathematical polynomial fitting equations and matrices have been also submitted which can used in the digital testing of machines or computer diagnostic solutions. As these results reveal certain patterns, these further processed X-Ray results can help researchers or doctors in understanding ailment or diagnosing and to pharmacologists in making medicine or machine/therapy.
Personality Classification of text through Machine learning and Deep learning: A Review (2023)
Authors: Perera Himaya , Costa Lakshan
Published: April 2023

Personality classification from text is a very popular domain of research among the domain of natural language processing. Personality of an individual has been found to be a very important characteristic when analyzing an individual for a particular purpose. Especially in fields such as e-recruitment, personality is a determining factor of if an individual has a placement at a particular workplace. The author aims to explore various personality classifications such as ‘The Big Five’ and the “Myer Briggs Type Indicator’ and various approaches in which text classification when it comes to detecting personality. Both machine learning and deep learning approaches are examined and their inner workings, benefits and limitations are detailed as well. We expect that this article will provide a thorough insight to personality classification of text by a numerous number of approaches.
A Simplified Guide To Rocket Science and Beyond – Understanding The Technologies of The Future
Authors: Bhattacharjee Deep , Roy Sanjeevan Singha
Published: April 2023

Rocket science has always been fairly complex. Its not because, it deals only the properties of rocket dynamics, attitude control, propulsion systems but the complexity arises mostly as a result of its payload, whether its manned or unmanned, how to make that payload reaches to orbit? How to assemble them in orbit to make giant structures like space stations? And most importantly, the mechanisms and aerodynamics of the shuttle associated with the lifting of the rocket. This paper, not only helps to make ease out the complex terminology, rigorous mathematics, pain stroking equations into a simplified norms, like a non-fiction for the general readers but also, no pre-requisite knowledge in the field is needed to study this paper. However, every possible attempt have been make to simplify the dynamics of rocket sciences and control mechanisms to the most easier way that one can imagine, still, there are some complex terminologies but pictures are provided deliberately with facts and histories to boost up the way of understanding the subject much more better than before. It has been deliberately proved in this paper that rockets along with orbital mechanics, Kessler’s syndrome, Lunar and Martial landing of the Apollo and the Curiosity rovers, is not the future of the humanity to reach out to the stars. Therefore, to eliminate time completely, to warp the space in a new way, to make the gravity constant at 1g Earth gravity, physics of Electrohydrodynamics – Or, the physics beyond the rocket propulsion by harnessing the Anti-Gravity is discussed in details with various types of engines and experiments carried out throughout the globe. Just as a rocket become incapable of taking humans to some exoplanets millions of light years apart, Electrohydrodynamics have shown humanity hopes that, this can be achieved by applying clever physics by eliminating the hindrances of time, gravity, acceleration and fuels. Thus arrives the need to consider a totally different form of propulsion technology unknowingly discovered by Tesla and later put forward by Thomas Townsend Brown. The technology of the super-intelligent humans that the Earthmen have gathered by reverse engineering the crashed Unidentified Flying Objects which involves the perpetual motion mechanism of Anti-Gravity governed by Semi-Quantum Kinetics.
HASP: Hierarchical Asynchronous Parallelism for Multi-NN Tasks
Authors: Li Hongyi , Ma Songchen , Wang Taoyi , Zhang Weihao , Wang Guanrui , Song Chenhang , Qu Huanyu , Lin Junfeng , Ma Cheng , Pei Jing , Zhao Rong
Published: April 2023

The rapid development of deep learning has propelled many real-world artificial intelligence (AI) applications. Many of these applications integrate multiple neural network (multi-NN) models to cater to various functionalities. Although a number of multi-NN acceleration technologies have been explored, few can fully fulfill the flexibility and scalability required by emerging and diverse AI workloads, especially for mobile. Among these, homogeneous multi-core architectures have great potential to support multi-NN execution by leveraging decentralized parallelism and intrinsic scalability. However, the advantages of multi-core systems are underexploited due to the adoption of bulk synchronization parallelism (BSP), which is inefficient to meet the diversity of multi-NN workloads. This paper reports a hierarchical multi-core architecture with asynchronous parallelism to enhance multi-NN execution for higher performance and utilization. Hierarchical asynchronous parallel (HASP) is the theoretical foundation, which establishes a programmable and grouped dynamic synchronous-asynchronous framework for multi-NN acceleration. HASP can be implemented on a typical multi-core processor for multi-NN with minor modifications. We further developed a prototype chip to validate the hardware effectiveness of this design. A mapping strategy that combines spatial partitioning and temporal tuning is also developed, which allows the proposed architecture to promote resource utilization and throughput simultaneously.
Assessing the Performance of Reinforcement Learning on Passive RRAM Crossbar Array
Authors: Tyagi Arjun , Sahay Shubham
Published: April 2023

Reinforcement learning is a promising approach that can allow machines to acquire knowledge and solve problems without the intervention of humans. However, the current implementation of reinforcement learning algorithms on standard complementary metal-oxide-semiconductor based platform constraints the performance due to von Neumann architecture, which leads to increased energy consumption and latency. To this end, in this work, we propose an extremely area- and energy-efficient implementation of Monte Carlo learning on passive resistive random access memory (RRAM) crossbar array considering the non-ideal hardware artifacts such as device-to-device variation, noise and endurance failure. To illustrate the capabilities of our implementation, we considered the classical control problem of cart-pole. Our results indicate that the proposed passive RRAM crossbar-based implementation of Monte Carlo learning not only outperforms prior digital and active 1 Transistor - 1 RRAM (1T1R) crossbar-based implementation by more than five orders of magnitude in terms of area but is also robust against spatial and temporal variations and endurance failure of RRAM devices.
Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study
Authors: Liu Yinqiu , Du Hongyang , Niyato Dusit , Kang Jiawen , Xiong Zehui , Kim Dong In , Jamalipour Abbas
Published: April 2023

A paper with 8 pages and 5 figures
A Software-Defined Deterministic Internet of Things (IoT) with Artificial Intelligence (AI) for Quantum-Safe Cyber-Security
Authors: Szymanski Ted
Published: April 2023

The next-generation Internet of Things (IoT) will enable Industry 4.0 and Smart Cyber-Physical Systems, including Smart Cities and Smart Manufacturing. These Smart Systems require: (i) ultra-low latencies, and (ii) immunity from cyber-attacks. This paper explores a "Software-Defined Deterministic IoT", with Artificial Intelligence (AI) for Cyber-Security. It introduces a new sub-layer (3a) of "Software Defined Wide Area Networks (SD-WANs)", using simple and secure deterministic packet switches (ie low-cost FPGAs). A "Software Defined Networking" (SDN) control-plane uses collaborative AI systems to implement Zero Trust Architectures (ZTAs) and Guaranteed Intrusion Detection Systems (IDSs), to control access to all critical resources. The SD-WANs can support millions of Deterministic Virtual Private Networks (DVPNs).The approach has many benefits: (i) All interference, congestion, and Distributed Denial-of-Service (DDOS) attacks are eliminated; (ii) End-to-end delays are determined by the speed of light in fiber; (iii) The SD-WANs provide hardware support for the US NIST ZTA and Post Quantum Cryptography (PQC); (iv) All communications within a DVPN are encrypted with PQC, and are immune to attacks from Quantum Computers; (v) The expected number of a successful cyber-attacks per year against a nation's critical infrastructure from external cyber-attackers is zero, when using Quantum-Safe ciphers; (vi) Total cost savings are estimated at $100s of Billions USD per year.

 
Novel HRV Metrics using Analytic Signal Representation of Interbeat Intervals for New Insights on Cardiac Dynamics
Authors: Pratiher Sawon , Srivastava Apoorva , Acharya Mrinal , Ghosh Nirmalya , patra amit
Published: April 2023

This work has been submitted to the IEEE Journal of Biomedical and Health Informatics for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. 
Efficient Privacy-Preserving Framework for Federated and Blockchain Networks
Authors: Khordadpour Peyman
Published: April 2023

Machine learning (ML) models, at the core of Artificial intelligence (AI), are widely applied in our digital world. To build these models, huge amounts of data must be collected, and many assets must be protected under privacy law. Data privacy is a critical issue when training and testing ML models. For privacy concerns to be adequately addressed in today’s ML systems, there needs to be considered privacy gaps in ML, as trained ML models can be vulnerable to adversarial attacks. In this regard, federated learning and blockchain networks are the new paradigms that have emerged with the promise of privacy-preserving by design while utilizing ML models. The new paradigms have promising privacy-preserving potential; however, they neglect several fundamental privacy and security issues the fact that adversaries can exploit shared gradients and global parameters, and the parameter server may drop gradients that have been mistakenly or deliberately updated. Also, enough data is available to train models. The proposed research addresses privacy concerns in federated and distributed environments. This is a general overview to establish a privacy-preserving framework that can provide privacy in federated and blockchain-based networks while address to fundamental privacy and security issues.
Application of Kernel Principal Component Analysis for Optical Vector Atomic Magnetometry
Authors: McKelvy James , Novikova Irina , Mikhailov Eugeniy E. , Gonzalez Mario , Fan Isaac , Li Yang , Wang Ying-Ju , Kitching John , Matsko Andrey
Published: April 2023

An unsupervised machine learning algorithm utilizing nonlinear dimensionality reduction has been developed to interface with spectroscopic measurements from an atomic rubidium optical magnetometer. The magnetometer uses Electromagnetically Induced Transparency (EIT) optical spectroscopy with atomic vapor cells in order to observe magneto-sensitive spin transitions of the 87Rb atom. The Rb EIT measurements result in the observation of seven transmission peaks associated with the available two-photon resonances between the Rb D1 line Zeeman sublevels. The developed algorithm correlates the waveform of the EIT spectra and the directionality of the local magnetic field using kernel principal component analysis (KPCA). The analysis, implemented with a radial basis function (RBF) kernel trick, was found to neatly cluster the EIT spectra according to the direction of the local magnetic field in the reduced dimensional feature space. The KPCA projections demonstrated a smooth curve in a three-dimensional feature space, and the resulting curve was modeled with a support vector regression (SVR) machine. We found that if the direction of the magnetic field is undefined initially, the measurement accuracy is better than 3 degrees in both azimuthal and longitudinal angles with respect to the real direction of the magnetic field. If the magnetometer is configured so that the azimuthal angle of the field is defined, the KPCA- SVR algorithm is capable of predicting the longitudinal angle of the local magnetic field within 1 degree of accuracy. These results suggest that the dimensionality reduction methods may be a powerful tool for approaching regression problems in optical spectroscopy. 
Application of Kernel Principal Component Analysis for Optical Vector Atomic Magnetometry
Authors: McKelvy James , Novikova Irina , Mikhailov Eugeniy E. , Gonzalez Mario , Fan Isaac , Li Yang , Wang Ying-Ju , Kitching John , Matsko Andrey
Published: April 2023

 An unsupervised machine learning algorithm utilizing nonlinear dimensionality reduction has been developed to interface with spectroscopic measurements from an atomic rubidium optical magnetometer. The magnetometer uses Electromagnetically Induced Transparency (EIT) optical spectroscopy with atomic vapor cells in order to observe magneto-sensitive spin transitions of the 87Rb atom. The Rb EIT measurements result in the observation of seven transmission peaks associated with the available two-photon resonances between the Rb D1 line Zeeman sublevels. The developed algorithm correlates the waveform of the EIT spectra and the directionality of the local magnetic field using kernel principal component analysis (KPCA). The analysis, implemented with a radial basis function (RBF) kernel trick, was found to neatly cluster the EIT spectra according to the direction of the local magnetic field in the reduced dimensional feature space. The KPCA projections demonstrated a smooth curve in a three-dimensional feature space, and the resulting curve was modeled with a support vector regression (SVR) machine. We found that if the direction of the magnetic field is undefined initially, the measurement accuracy is better than 3 degrees in both azimuthal and longitudinal angles with respect to the real direction of the magnetic field. If the magnetometer is configured so that the azimuthal angle of the field is defined, the KPCA- SVR algorithm is capable of predicting the longitudinal angle of the local magnetic field within 1 degree of accuracy. These results suggest that the dimensionality reduction methods may be a powerful tool for approaching regression problems in optical spectroscopy. 
Integrated Sensing, Localization, and Communication in Holographic MIMO-enabled Wireless Network: A Deep Learning Approach
Authors: ADHIKARY APURBA , Munir Md. Shirajum , Raha Avi Deb , Qiao Yu , Han Zhu , Hong Choong Seon
Published: April 2023

The impending sixth-generation wireless communication networks are anticipated to guarantee mass connectivity, high integration, and lower power consumption for generating the required beamforming. To achieve these goals, an artificial intelligence (AI) framework is proposed by utilizing holographic MIMO-assisted integrated sensing, localization, and communication. The proposed AI framework ensures lower power consumption to activate the minimum number of grids from the holographic grid array for the generation of holographic beamforming. An optimization problem is formulated to maximize the signal-to-interference-plus-noise ratio received by the users, which in turn maximizes the utility function for sensing considering the user distances, beampattern gains, sensingcommunication loss, and dense locations controlling parameter. A novel AI-based framework is proposed to solve the formulated NP-hard optimization problem by decomposing it into two subproblems: the sensing problem and the communication resource allocation problem. First, a variational autoencoder (VAE) based mechanism is devised to solve the sensing problem mitigating the disputes to obtain the users’ exact location. Second, a sequential neural network-based scheme is utilized to allocate the communication resources to the heterogeneous users for generating the desired beamforming based on the findings of the VAE-based mechanism. Moreover, an extreme case power allocation strategy is presented once a large number of users enter the system. The extreme case power allocation strategy applies when the total power prediction exceeds the total system power for allocating the communication resources to the users. Finally, simulation results validate that the proposed AI-based framework outperforms the long short-term memory method with a cumulative power savings of 34.02% taking the ground truth power into account. Therefore, the proposed AI framework generates effective beamforming to serve the communication users.
Picture Segmentation using changing Artifacts Identification and Bias Modification
Authors: Sakimalla Girija , Chilukuri Pranathi , Jamuna Anusha , oruganti pranavasri , bedadha nithesh
Published: April 2023

 Picture segmentation is a crucial task in  computer vision that involves dividing an image into multiple  regions or segments based on various criteria, such as color,  texture, or edge characteristics. Changing artifacts  identification involves identifying and removing artifacts that  are present in the image and affecting the accuracy of segmentation. Artifacts can be caused by various factors, such  as noise, lighting conditions, or image compression.  Identifying and removing these artifacts can improve the  accuracy of segmentation algorithms. Bias modification  involves adjusting the biases present in segmentation  algorithms to improve their accuracy. These biases can lead  to errors in segmentation, such as over-segmentation or  under-segmentation. Bias modification can involve adjusting  the algorithm's parameters or using different training data to  improve its performance. The use of changing artifacts  identification and bias modification can significantly improve  the accuracy of picture segmentation. By identifying and  removing artifacts and adjusting biases, segmentation  algorithms can more accurately identify and classify objects  in an image, leading to better object detection and  classification. This model is expected to be useful for  damaged images and applications where artifacts and bias are  actual features of interest, such as lesion detection(problem  within medical imaging analysis) and bias field correction in  medical imaging, e.g., Magnetic resonance imaging (MRI). 
150 GHz High-Power Photodiode by Flip-Chip Bonding
Authors: Xie XIAOJUN
Published: April 2023

We report high-power modified uni-traveling carrier photodiodes with 150-GHz bandwidth. To improve the RF output power, the photodiode chips are flip-chip bonded on diamond submounts with high thermal conductivity to enhance heat dissipation. Measured 3-dB bandwidths of 4-μm, 6-μm, 8-μm, and 10-μm diameter photodiodes reach 150 GHz, 129 GHz, 117 GHz, and 105 GHz, respectively. RF output power with 12.7 dBm at 90 GHz, 11.3 dBm at 100 GHz, 8.5 dBm at 110 GHz, -3 dBm at 150GHz, and -5.7 dBm at 165GHz are achieved. 
Waveguide-Floquet Mapping Based on Surface Susceptibilities for Metasurface Unit Cell Characterization
Authors: Kundu Debidas , Emara Mohamed K , Rufail Leandro M. , Gupta Shulabh
Published: April 2023

A simple method is proposed to characterize metasurface unit cells using rectangular waveguide. The method maps the S-parameters obtained using a dominant-mode waveguide to the S-parameters of fundamental Floquet mode for a plane wave incident at any desired angle. The mapping between the dominant waveguide mode and the fundamental Floquet mode is executed by extracting the equivalent surface susceptibilities of the metasurface unit cell. The results obtained from the proposed method show good agreement with the full-wave simulation results of the metasurface unit cell.
A Computationally Efficient Model Predictive Control for Cascaded H-Bridge STATCOM in Unbalanced Distribution Grids
Authors: Li Yufei , Diao Fei , Zhao Yue
Published: April 2023

Computationally Efficient MPC for STATCOM
The Brand Personality of World Heritage Sites: Text Mining the Perceptions of UNESCO Experts and Visitors
Authors: Hassan Mohamed Abdalla Elsayed , Zerva Konstantina , Aulet Silvia
Published: April 2023

World Heritage (WH) is acknowledged as a prominent tourism brand. However, research on the intangible relationship between World Heritage sites (WHSs) and outstanding universal values (OUVs) is lacking. This study employed advances in text mining, using digital textual data, and Brand
Personality (BP) lexical methods to explore descriptions of WHSs. Although existing BP dictionaries are useful for measuring the personalities of destinations and attractions, they need further development. This is due to the perception that the current BP dictionary is limited to capturing
distinct brand cultural meanings from large digital texts. Additionally, a BP dictionary construction technique is still necessary to enable BP analysis using substantial online text. The necessity to specifically identify the WHSs personality categorization dictionary as microelements of
destination that may have significance for affecting visitor preference is still needed. Using 13,741 postexperience visitor-generated TripAdvisor reviews, and 1,121 WH center website descriptions, a natural and cultural WHSs personality dictionary was developed. Significant differences in
the way UNESCO experts and visitors perceive WHSs are explored and practical and managerial implications are discussed.
EFFECT OF SKEWED DISTRIBUTIONS ON SHEWHART CONTROL CHART COEFFICIENTS
Authors:   National Research Technological University ", Shper V.L. ,   MISiS"
Published: April 2023

In this paper, we discuss the influence of asymmetric distribution functions on the values of the coefficients of Shewhart control charts (CCS) of the x-mR and -R types. It is argued that for distribution functions (DF) that are very different from the normal law, this influence should be taken into account. The level of such a change in the CCF coefficients, which should be taken into account, is discussed. The simulation results are presented, and an algorithm for applying the CCS in practice is proposed, taking into account the law of data distribution. An example is also given of how the deviation of the FR of data from the normal law changes the boundaries of the KCS for real
Study on Mechanical Properties and Fracture Mechanisms of Lignin Fiber/epoxy Resin Composites
Authors: Zhe Wu , Qingnan Wang , Shuai Zhao , Yang Zhang , Bo Xue
Published: April 2023

Lignin fiber/epoxy resin compositeused for energy absorbing was prepared by atmospheric stirring method. Quasi-static compressive mechanics tests were implemented by using the electronic universal mechanics tester (WDW-100KN) under ambient conditions to analyze the compressing behavior of the matrix material and composite at the strain rate of 10-2s-1 .Scanning electron microscope (SEM) was used to observe the microstructure of the composite after quasi-static compression damage. The results showed that when the ratio of epoxy resin and curing agent was 3:1, the internal structure of the matrix material was more uniform with smoother cross-section, which represented better mechanical properties. It was found that the addition of lignin fiber changed the compression characteristics of the matrix material, resulting in a strengthening stage appeared. At the same time, when the lignin fiber content was 2% or 3%, the composite could absorb more impact energy and delay crack generation, which met the performance requirement of energy absorbing materials.