bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental approach for characterizing the nonlinear, time and temperature‐dependent constitutive response of open‐cell polyurethane foams
Authors: Tao Jialiang , Sun Xiangyu , Franck Christian
Published: May 2024

Elastomeric foams are composite materials comprising of a polymeric elastomer and interconnected gas‐filled pores, endowing them with exceptional compliance and the ability to undergo large, reversible deformations along with substantial volume change. These foams find extensive utility in contexts demanding compliance and compressibility, such as impact protection and cushioning, spanning a diverse range of applications. Changing temperature can dramatically alter foam stiffness, strength and deformation characteristics specifically around the material's glassy‐rubbery transition temperature (
). With the aim of informing new constitutive model developments for elastomeric foams, we conducted a comprehensive series of large deformation, homogeneous compression and tension tests across strain rates from 10−2 s−1 to 100 s−1 and ambient temperatures ranging from −10°C to 50°C covering an even range around the material's
of 20°C. To achieve precise control of ambient temperatures during mechanical testing, we constructed a custom‐designed environmental chamber for controlling the ambient temperature from −10°C to 50°C with a variation of less than 1°C. The obtained digital image correlation based stress‐strain data shows significant tension‐compression asymmetry as well as significant dependence on strain rate and ambient temperature, especially above and below the glass transition temperature. We provide full access to these data sets for the future development of rate‐ and temperature‐dependent constitutive models.
Memetics and the Parallel Architecture
Authors: Planer Ronald J.
Published: May 2024

The evolution of human communication and culture is among the most significant—and challenging—questions we face in attempting to understand the evolution of our species. This article takes up two frameworks for theorizing about human communication and culture, namely, Jackendoff's Parallel Architecture of the human language faculty, and the cultural evolutionary framework of Memetics. The aim is to show that the two frameworks uniquely complement one another in some theoretically important ways. In particular, the Parallel Architecture's account of the lexicon significantly expands the range of linguistic phenomena that are plausibly covered by Memetics (e.g., from words to constructions and pure rules of syntax). At the same time, taking a “meme's‐eye‐view” of the lexicon retools the Parallel Architecture's treatment of the origins and subsequent cultural evolution of language.
African continental free trade area and greenfield investment: Likely effect and transmission channels
Authors: Shingal Anirudh , Mendez‐Parra Maximiliano
Published: May 2024

We examine the likely effect of the African Continental Free Trade Area (AfCFTA) on African investment using data on announced greenfield investment. Departing from existing work on this subject, we add value by providing estimates based on a general equilibrium counterfactual analysis in a structural gravity framework. Results suggest that the stock of announced intra‐African greenfield investment in 2018 would have increased by 0.7 percent from a successful implementation of the AfCFTA in that year relative to the baseline scenario of no agreement, with considerable heterogeneity across source and destination countries. Moreover, the positive effect is found to increase with the depth of the negotiated agreement. Exploring possible transmission channels we find the trade elasticity of announced greenfield investment to be positive, especially for trade in intermediates in African host countries with strong governance indicators. This suggests that, by improving institutional quality and galvanising regional value chains, integration within Africa could also incentivise investment.
Financial Openness and Trade (Real) Openness: Should We Open up Both Markets?
Authors: Wai Chew Keong , Tang Tuck Cheong , Soon Siew Voon
Published: May 2024

This study examines the 'interdependence' between financial openness and trade (real) openness, as well as the macroeconomic determinants of such relationship from a general equilibrium perspective (viz. the balance of payments constraint). The macroeconomics factors are national income, exchange rate, and interest rate. The data cover 124 countries over a period spanning between 1970 and 2019. The 'interdependence' between financial and trade openness is captured by a positive Pearson correlation in most of the countries (i.e. between 60% and 79% of the countries). However, a more precise measure of a bidirectional causality between both openness exists in only 35% (44 countries) of 124 countries. The empirical results show that exchange rate explains negatively the estimated correlation coefficients between financial and trade openness, as well as for low income countries. While, the interest rate increases the likelihood of their bidirectional causality results. This study provides policy insights related to both the financial and real markets.
An edge-simplicity bias in the visual input to young infants
Authors: Anderson Erin M. , Candy T. Rowan , Gold Jason M. , Smith Linda B.
Published: May 2024

The development of sparse edge coding in the mammalian visual cortex depends on early visual experience. In humans, there are multiple indicators that the statistics of early visual experiences has unique properties that may support these developments. However, there are no direct measures of the edge statistics of infant daily-life experience. Using head-mounted cameras to capture egocentric images of young infants and adults in the home, we found infant images to have distinct edge statistics relative to adults. For infants, scenes with sparse edge patterns—few edges and few orientations—dominate. The findings implicate biased early input at the scale of daily life that is likely specific to the early months after birth and provide insights into the quality, amount, and timing of the visual experiences during the foundational developmental period for human vision.
Nucleobase adducts bind MR1 and stimulate MR1-restricted T cells
Authors: Vacchini Alessandro , Chancellor Andrew , Yang Qinmei , Colombo Rodrigo , Spagnuolo Julian , Berloffa Giuliano , Joss Daniel , Øyås Ove , Lecchi Chiara , De Simone Giulia , Beshirova Aisha , Nosi Vladimir , Loureiro José Pedro , Morabito Aurelia , De Gregorio Corinne , Pfeffer Michael , Schaefer Verena , Prota Gennaro , Zippelius Alfred , Stelling Jörg , Häussinger Daniel , Brunelli Laura , Villalta Peter , Lepore Marco , Davoli Enrico , Balbo Silvia , Mori Lucia , De Libero Gennaro
Published: May 2024

MR1T cells are a recently found class of T cells that recognize antigens presented by the major histocompatibility complex-I–related molecule MR1 in the absence of microbial infection. The nature of the self-antigens that stimulate MR1T cells remains unclear, hampering our understanding of their physiological role and therapeutic potential. By combining genetic, pharmacological, and biochemical approaches, we found that carbonyl stress and changes in nucleobase metabolism in target cells promote MR1T cell activation. Stimulatory compounds formed by carbonyl adducts of nucleobases were detected within MR1 molecules produced by tumor cells, and their abundance and antigenicity were enhanced by drugs that induce carbonyl accumulation. Our data reveal carbonyl-nucleobase adducts as MR1T cell antigens. Recognizing cells under carbonyl stress allows MR1T cells to monitor cellular metabolic changes with physiological and therapeutic implications.
Supplemental Material: U-Pb calcite ages date oblique rifting of the Arctic–North Atlantic gateway
Authors: Haaland Linda C. , al. et
Published: May 2024

Descriptions of U-Pb calcite dating methods, and detailed description of samples and interpretations of U-Pb data.  
Is it all too much?
Authors: McCrory P
Published: May 2024

This article has been retracted. See the retraction notice for details. The PDF is retained for transparency.
Optimized Improved Random Forest-Fostered Glaucoma Detection from Fundus Retinal Images
Authors: Pandeeswari B. , Alice K.
Published: May 2024

Glaucoma is a major cause of irreversible blindness caused by optic nerve damage. The ophthalmologist uses retinal examination of the dilated pupil to diagnose this disease. Since this diagnosis is a manual and laborious procedure, an automated technique is required for faster diagnosis. Automated retinal image processing is deemed a competitive research field owing to its lower accuracy results, complication and improper effects related with it. Therefore, Optimized Improved Random Forest fostered Glaucoma Detection from Fundus Retinal Images (IRF-MOSOA-GD) is proposed in this paper. Here, Images are acquired through the datasets of DRISHTI-GS, ORIGA and RIM_ONE and given to the pre-processing. The pre-processing is carried out utilizing the Savitzky–Golay Denoising technique for eliminating the noise at the input images. Then the pre-processed image is given to the feature extraction phase. In the feature extraction phase, the region features are extracted with the help of the Fuzzy color and Texture histogram (FCTH), Edge histogram and Pyramid Histograms of Orientation Gradients (PHOG) method. Then, the extracted feature is fed to the Improved Random Forest (IRF) classifier for categorizing the normal and Glaucoma images. The hyperparameter of the IRF classifier is tuned with a Multi-Objective Squirrel Optimization Algorithm (MOSOA) to attain better categorization of normal and glaucoma images. The proposed technique is implemented in Java and its efficiency is analyzed under some metrics, like accuracy, F-scores and computational time. The IRF-MOSOA-GD method attains higher accuracy in the DRISHTI-GS dataset at 23.6%, 27.55% and 24.98% higher accuracy compared with existing techniques.
Enhancing the Segmentation Accuracy of the Otsu Method for Calculating Blood Vessel Rupture Volumes in CT-Scan Images
Authors: Guslendra  , Yuhandri  , Defit Sarjon
Published: May 2024

The precise quantification of cerebral hemorrhage volume assumes paramount significance, given its consequential impact on subsequent medical interventions. While antecedent scholarly endeavors have undertaken cerebral hemorrhage volume computations, the attendant accuracy remains amenable to refinement. The main contribution to this research is the development of a rectangle algorithm using the Otsu method, which can be used to calculate the total volume of brain hemorrhage in CT-Scan images of the human brain. The present investigation seeks to augment the segmentation paradigm inherent to the Otsu method, thereby advancing the precision of cerebral hemorrhage volume assessments. The Otsu method is conceived with the purpose of automating the segmentation of the hemorrhagic domain through the determination of threshold values. The refinement of the Otsu method’s accuracy is effectuated by the formulation of an algorithm aimed at maximizing the mean discrepancy between object and background intensities within the object image, predicated upon the ascertained threshold values. These determined thresholds subsequently govern the transformation of grayscale images into binary format, achieved through the quotient of the threshold value and the mean variance, thereby amplifying segmentation precision. The incorporation of variance and mean values in the binarization of grayscale images affords adaptability in threshold modulation commensurate with the intensity spectrum of the image. The research corpus leverages CT-Scan images sourced from RSUP M. Djamil Padang, West Sumatra, encompassing a compendium of 100 image slices culled from a quintet of patients. Empirical findings attest to the fortification of the Otsu method in the segmentation milieu, substantiating the augmentation of threshold value accuracy. This enhancement is conspicuously manifest in the outcomes of segmentation tests, underscoring the superior efficacy of the Otsu method in discerning between objects and backgrounds. The corollary effect is a discernibly more accurate computation of volumes employing the Otsu-T methodology. The import of this research rests in its successful establishment of automated threshold values and the concomitant elevation of segmentation precision.
Meixner random variables and their quantum operators
Authors: Obata Nobuaki , Stan Aurel I. , Yoshida Hiroaki
Published: May 2024

In this paper, we find the position–momentum decomposition of the quantum operators of the classic Meixner random variables. The position–momentum decomposition involves translation operators, which are used to give a new characterization of the Meixner random variables.
Hidden quantum Markov processes
Authors: Accardi Luigi , Soueidi El Gheteb , Lu Yun Gang , Souissi Abdessatar
Published: May 2024

Starting from the notion of algebraic hidden processes introduced in Ref.9, we propose a definition of quantum hidden Markov process which extends the notion of quantum Markov chain (QMC) in the same sense in which classical hidden Markov processes (HMPs) extend classical Markov chains. We give several structure theorems for this new family of quantum states which shares with the QMCs the unique property that the finite dimensional joint expectations are explicitly given without these states being linearly equivalent to product states (as the Gaussian ones). The special feature of this new class of quantum states is best exemplified by looking at their restrictions to diagonal sub-algebras: we prove that they lead to a new family of classical stochastic processes that generalize in a non-trivial way the classical HMPs.
Cohen–Macaulay binomial edge ideals in terms of blocks with whiskers
Authors: Saha Kamalesh , Sengupta Indranath
Published: May 2024

For a graph [Formula: see text] and the binomial edge ideal [Formula: see text] of [Formula: see text], Bolognini et al. have proved the following: [Formula: see text] is strongly unmixed [Formula: see text][Formula: see text] is Cohen–Macaulay [Formula: see text][Formula: see text] is accessible. Moreover, they have conjectured that the converse of these implications is true. Accessible and strongly unmixed properties are purely combinatorial. We give some motivations to focus only on blocks with whiskers for the characterization of all [Formula: see text] with Cohen–Macaulay [Formula: see text]. We show that accessible and strongly unmixed properties of [Formula: see text] depend only on the corresponding properties of its blocks with whiskers and vice versa. We give a new family of graphs whose binomial edge ideals are Cohen–Macaulay, and from that family, we classify all [Formula: see text]-regular [Formula: see text]-connected graphs, with the property that, after attaching some special whiskers to it, the binomial edge ideals become Cohen–Macaulay. To prove the Cohen–Macaulay conjecture, it is enough to show that every non-complete accessible graph [Formula: see text] has a cut vertex [Formula: see text] such that [Formula: see text] is accessible. We show that any non-complete accessible graph [Formula: see text] having at most three cut vertices has a cut vertex [Formula: see text] for which [Formula: see text] is accessible.
Conformal and projective tractors from 2-frame bundles by the dressing field method
Authors: Marsot L. , Lazzarini S.
Published: May 2024

This paper is devoted to the study of conformal and projective structures, and especially their connections, in the language of 2-frames, or [Formula: see text]-structures of second order. While their normal Cartan connections are well-known, we use the dressing field method to obtain their local, mostly gauge invariant, connections. Lastly, we recall how to obtain the tractor bundle from conformal structures, and then show that we can define a projective tractor bundle using the same kind of construction.
About the solutions of Modified Lorenz system
Authors: Zlatanovska Biljana , Dimovski Dončo , Kocaleva Vitanova Mirjana
Published: May 2024

A Modified Lorenz system is a system of three differential equations. The third differential equation in the Lorenz system is replaced with a fifth-order linear homogeneous differential equation with constant coefficients. In the paper [B. Zlatanovska and D. Dimovski, A modified Lorenz system: Definition and solution, Asian-Eur. J. Math. 13(08) (2020) 2050164], the Modified Lorenz system is defined by offering a solution, but without solving the fifth-order linear homogeneous differential equation with constant coefficients. This differential equation is solved by solving the characteristic equation of fifth degree. A formula for solving the algebraic equation of the fifth degree does not exist. Therefore, solutions for the special cases of the characteristic equation of fifth degree will be offered. The solution of the Modified Lorenz system will be completed using these forms of the characteristic equation of the fifth degree.
A Quick, High-Yield Biogenic Synthesis of Antibacterial AgNPs (Silver Nanoparticles) via Carica papaya Seeds
Authors: Singh Anshu , Singh Vishwajeet , Bharadwaj Alok , Gaur Ridhima , Agarwal Smita , Wahi Nitin
Published: May 2024

Carica papaya seeds were used in this research for the synthesis of AgNPs. The production of silver nanoparticles was characterized using UV–Vis spectroscopy, FTIR, XRD and SEM-EDX analysis. The antibacterial activity of the prepared AgNPs was evaluated by the Kirby–Bauer disc diffusion method with the antibacterial activity of different compounds against Bacillus aerogenes. UV–Vis spectral peaks are found at 8–18 nm. SEM and TEM analysis revealed several spherical structures between 10 nm and 50 nm. XRD analysis also confirmed its 50 nm size. Experimental data revealed that AgNPs inhibited bacterial growth. This study shows that papaya seed extract contributes to the bioreduction and stabilization of the synthesized silver nanoparticles.
CLIMATE POLICY UNCERTAINTY AND CARBON PRICE: EVIDENCE FROM FREQUENCY AND QUANTILE PERSPECTIVE
Authors: WANG KAI-HUA , WEN CUI-PING , TAO RAN , LI JIANZENG , DONG XIAOTIAN
Published: May 2024

Changes in climate policy are posing enormous challenges to carbon markets. However, the intricate link and time-frequency features between climate policy uncertainty (CPU) and carbon emission price (CEP) have not been extensively explored in the current literature. This paper aims to reveal the dynamic relationship between the two under different time frequencies and quantiles by using a wavelet-based quantile-on-quantile regression (QQR) method. Nine sets of variable pairs with various temporal frequencies are constructed, such as short-term CPU and long-term CEP. The results demonstrate that their coefficients would change from positive to negative or irrelevant, or conversely, under different quantiles and frequencies. China has been a global focus and an interesting case since its relentless efforts towards addressing climate change and constructing a carbon market, which makes one of the contributions of this paper. Additionally, time frequencies combined with different quantiles are employed to explore the connection between CPU and CEP, revealing nonlinear and asymmetric features between variables, and enriching the theoretical influencing mechanisms. Therefore, the government should avoid drastic policy changes, and make full use of policy guidance effect. Besides, top-design and market-oriented reforms for the carbon market are needed.
Radiation Awareness and X-Ray Use in Cardiology: An International Independent Web-Based Survey
Authors: Ballatore Andrea , Casella Michela , Moscoso Costa Francisco , Giaccardi Marzia , Haim Moti , Ingimarsdóttir Inga Jóna , Mewton Nathan , Van Ofwegen-Hanekamp Clara , Ollitrault Pierre , Pawlak Agnieszka , Sultan Arian , Tokmakova Mariya , Varounis Christos , Weberndörfer Vanessa , Zemrak Filip , Anselmino Matteo
Published: May 2024

Background. Cardiologists are today exposed to a growing dose of ionising radiation in their practice. Radiation awareness and correct management of X-ray use are the cornerstone to comply with the principles of exposure optimization and justification. Methods and Results. An investigator-initiated international voluntary-based survey including 28 questions was conducted across 19 European countries. 228 cardiologists participated in the survey. Invasive cardiology subspecialties were the most represented (83.6%). Radiation exposure is the cause of personal protective equipment-related orthopaedic injuries (personally or in coworkers) or anxiety in 68.5% and 62.9% of cases, respectively. 38.4% of participants have encountered difficulties in having their institutions recognizing periods off work for exceeding radiation exposure limit (16.3% usually and 22.1% on rare occasions). Gender was not associated with any difference in the answers. Age older than 40 years old was associated with an increased knowledge of personal dosimeter data (71.6% vs. 51.3%, p=0.008). Invasive cardiologists more frequently suffer from orthopaedic injuries (73.0% vs. 44.8%, p=0.006) and show greater participation to radioprotection courses (78.4 vs. 27.6%, p<0.001). Conclusion. European cardiologists show appropriate awareness of the risks associated with X-ray use in medical practice and of the principles guiding a proper management of radiation hazard. However, there is still room for improvement, and institutions should promote risk education policies, which are the basis for the creation and diffusion of a community consciousness on radiation hazard.
Motion Accuracy of Pneumatic Stepper Motor-Driven Robotic System Developed for MRI-Guided High-Intensity Focused Ultrasound Treatment of Prostate Disease
Authors: Seo Hyunkwan , Hwang Sung Kwan , Kim Hee-Won , Lee Kyu Chan
Published: May 2024

The latest advancement in high-intensity focused ultrasound (HIFU) treatment technology integrates magnetic resonance imaging (MRI) guidance for precise treatment of prostate disease. As conventional electromagnetic motors are not applicable for utilization within MRI scanners, we have developed a prototype robotic system driven by pneumatic stepper motors to control the movement of the HIFU transducer within an intrarectal probe during MRI-guided HIFU treatment procedures. These pneumatic stepper motors were constructed entirely from MRI-compatible plastic materials. Assessment of the robotic system’s MRI compatibility was conducted utilizing a 3.0T MRI scanner, revealing no discernible MRI image distortion with a minor decrease in the signal-to-noise ratio (2.8%) during the motor operation. The robotic system enabled the transducer to move inside the probe with two degrees of freedom, allowing both linear and rotational motion. The positional accuracy of the transducer movement was assessed, yielding ±0.20 and ±0.22 mm accuracies in the forward and backward linear movements, respectively, and ±0.79° and ±0.74° accuracies in the clockwise and counterclockwise rotational motions, respectively. Emulation of authentic HIFU procedures involved creating a two-dimensional array of thermal lesions in a tissue-mimicking phantom, achieving positional accuracy within ±1 mm for the generated HIFU focal spots. The prototype robotic system incorporating pneumatic stepper motors fabricated entirely from MRI-compatible plastic materials has demonstrated the requisite positional accuracy necessary for effective HIFU treatment of prostate disease, indicating substantial promise for future clinical application.
Perceived Conjunctival Foreign Material Egress in Morgellons Disease: A Case Study
Authors: Ghiam Sean , Sojitra Badal , Reiff Collin , M. Sears Connie , N. Karlin Justin
Published: May 2024

The purpose of this report is to present a case of a 63-year-old man with orbital Morgellons disease. A 63-year-old man presented reporting 15 years of daily egress of different foreign bodies apparently found in the superior fornices of both eyes, exhibiting a classic manifestation known as the matchbox sign. He described the symptoms starting after a facial trauma. The patient stated that at several points over the 15-year course of his condition, he was so distressed that he had contemplated suicide. On multiple exams by a range of ophthalmic professionals, there was no evidence of foreign body. Further investigation involving MRI and plain radiographs demonstrated similar lack of findings. A trial of gabapentin was performed without improvement in symptoms. He discontinued care 5 months later. Morgellons disease is a poorly understood condition, particularly ophthalmic presentations of the disease. Despite extensive investigation, the exact cause of Morgellons disease remains unclear, and there is no definitive treatment for the condition. We highlight the importance of empathetic listening in building trust, as a means of helping the patient to seek psychological help.
Efficient and scalable multitenant placement approach for in-memory database over supple architecture
Authors: Shah Arpita , Patel Narendra
Published: May 2024

Of late Multitenant model with In-Memory database has become prominent area for research. The paper has used advantages of multitenancy to reduce the cost for hardware, labor and make availability of storage by sharing database memory and file execution. The purpose of this paper is to give overview of proposed Supple architecture for implementing in-memory database backend and multitenancy, applicable in public and private cloud settings. Backend in-memory database uses column-oriented approach with dictionary based compression technique. We used dedicated sample benchmark for the workload processing and also adopt the SLA penalty model. In particular, we present two approximation algorithms, multi-tenant placement (MTP) and best-fit greedy to show the quality of tenant placement. The experimental results show that MTP algorithm is scalable and efficient in comparison with best-fit greedy algorithm over proposed architecture.
On the performance of switching methods in space division multiplexing based optical networks
Authors: Iyer Sridhar
Published: May 2024

In the current work, for space division multiplexing based optical networks (SDM-b-OTNs), we investigate the performance of various switching methods with a variation in traffic evolution over different time frame periods. Initially, comparison of the existing methods viz., independent switching (InSw), frequency switching (FqSw), and space switching (SpSw) demonstrates that (i) over longer periods of time frame, FqSw provisions low network usage and (ii) SpSw offers low network usage for shorter periods of time frame; however, as time frame increases to longer periods, SpSw starts to outperform InSw. Next, we investigate a hybrid switching (HySw) method which begins by implementing InSw and then shifts to the use of SpSw after the activation of specific numbers of space channels. The simulation results demonstrate that HySw provisions substantial savings on the costs incurred for switching, and with lower space channel values it also offers a balance in the trade-off which occurs between the costs associated for activating the space channels and that incurred for switching.
High security mechanism: fragmentation and replication in the cloud with auto update in the system
Authors: Khobragade Shrutika , Bhosale Rohini , Jiwane Rahul
Published: May 2024

Cloud computing makes immense use of internet to store a huge amount of data. Cloud computing provides high quality service with low cost and scalability with less requirement of hardware and software management. Security plays a vital role in cloud as data is handled by third party hence security is the biggest concern to matter. This proposed mechanism focuses on the security issues on the cloud. As the file is stored at a particular location which might get affected due to attack and will lost the data. So, in this proposed work instead of storing a complete file at a particular location, the file is divided into fragments and each fragment is stored at various locations. Fragments are more secured by providing the hash key to each fragment. This mechanism will not reveal all the information regarding a particular file even after successful attack. Here, the replication of fragments is also generated with strong authentication process using key generation. The auto update of a fragment or any file is also done here. The concept of auto update of files is done where a file or a fragment can be updated online. Instead of downloading the whole file, a fragment can be downloaded to update. More time is saved using this methodology.
Model of emergence evacuation route planning with contra flow and zone scheduling in disaster evacuation
Authors: Dedy Hartama  , Herman Mawengkang  , Muhammad Zarlis  , Rahmad Widia Sembiring
Published: May 2024

Evacuation is characterized by rapid movement of people in unsafe locations or disaster sites to safer locations. The traffic management strategy for commonly used evacuations is the use of Shoulder-Lane, contra flowing traffic and gradual evacuation. Contra flowhas been commonly used in traffic management by changing traffic lanes during peak hours. To implement the contra flowoperation, there are two main problems that must be decided, namely optimal contraflow lane configuration problem (OCLCP) and optimal contraflow scheduling. Within the OCSP there are two approaches that can be used: zone scheduling and flow scheduling. Problem of contra flow and zone scheduling problem is basically an emergence evacuation route planning (EERP) issue. This research will discuss EERP with contraflow and zone scheduling which can guarantee the movement of people in disaster area to safe area in emergency situation.
Design and simulation of high-swing fully differential telescopic Op-Amp
Authors: Zahra Pezeshki
Published: May 2024

This article describes the process of design and simulation of a high-swing fully differential telescopic operational amplifier (Op-Amp). Due to the common gate-common source (CG and CS) cascode structure, the gain is very high. To maximize this gain, the load must also be selected such as two current sources. This circuit has the higher voltage in output than current Op-Amps in accordance with desirable characteristics. The loss of power of this operating amplifier are very low and in milliwatts. With use of a power supply of 1.8 V, it achieves a high-swing 1.2 V, a differential gain of 76.333 dB, ωuGB of 412 MHz, and >50 dB CMRR. This new design through the simulations and analytically shows that the high-swing fully differential telescopic Op-Amp retains its high CMRR even at high frequencies.
Realtime monitoring for groundwater level and local climate based on universal communication system
Authors: Rony Teguh  , Hepryandi Usup
Published: May 2024

The groundwater level and weather patterns and climate conditions are several of the very significant factors which influence the quality of livelihood and the other activity of the tropical peatland environment. The current method of groundwater level and meteorological information aggregate build the use of certain expensive weather station devices, prominent to a lack of vast monitoring suitable to cost barriers and disturbance in some countries. In this research, we have developed and implemented a hardware module based on an Arduino microcontroller and mobile communication, which measures the groundwater level and meteorological data, including air temperature, air humidity, and soil temperature, and humidity, rainfall in peatland area. The data groundwater level is received by a specially developed application interface running on an internet of things (IoT) connected through a global mobile system (GSM) communication. In this work, our proposed system is a model system that can able to generate alerts based on the real-time groundwater level and data weather as potential peat fire in Indonesia. It provides online and data real-time monitoring. In this works, we have resulted in a system to monitor the groundwater level and data weather alert, condition mapping, and warn the people from its disastrous effects.
Hancitor malware recognition using swarm intelligent technique
Authors: Laheeb M. Ibrahim  , Maisirreem Atheeed Kamal  , AbdulSattar A. Al-Alusi
Published: May 2024

Malware is a global risk rife designed to destroy computer systems without the owner's knowledge. It is still regarded as the most popular threat that attacks computer systems. Early recognition of unknown malware remains a problem. swarm intelligence (SI), usually customer societies, communicate locally with their domain and with each other. Clients use very simple rules of behavior and the interactions between them lead to smart appearance, noticeable, individual behavior and optimized solution of problem and SI has been successfully applied in many fields, especially for malware ion tasks. SI also saves a considerable amount of time and enhances the precision of the malware recognition system. This paper introduces a malware recognition system for Hancitor malware using the gray wolf optimization (GWO) algorithm and artificial bee colony (ABC) algorithm, which can effectively recognize Hancitor in networks.
Classification of mammograms based on features extraction techniques using support vector machine
Authors: Enas Mohammed Hussein Saeed  , Hayder Adnan Saleh  , Enam Azez Khalel
Published: May 2024

Now mammography can be defined as the most reliable method for early breast cancer detection. The main goal of this study is to design a classifier model to help radiologists to provide a second view to diagnose mammograms. In the proposed system medium filter and binary image with a global threshold have been applied for removing the noise and small artifacts in the pre-processing stage. Secondly, in the segmentation phase, a hybrid bounding box and region growing (HBBRG) algorithm are utilizing to remove pectoral muscles, and then a geometric method has been applied to cut the largest possible square that can be obtained from a mammogram which represents the region of interest (ROI). In the features extraction phase three method was used to prepare texture features to be a suitable introduction to the classification process are first Order (statistical features), local binary patterns (LBP), and gray-level co-occurrence matrix (GLCM), Finally, support vector machine (SVM) has been applied in two-level to classify mammogram images in the first level to normal or abnormal, and then the classification of abnormal once in the second level to the benign or malignant image. The system was tested on the MAIS the mammogram image analysis society (MIAS) database, in addition to the image from the Teaching Oncology Hospital, Medical City in Baghdad, where the results showed achieving an accuracy of 95.454% for the first level and 97.260% for the second level, also, the results of applying the proposed system to the MIAS database alone were achieving an accuracy of 93.105% for the first level and 94.59 for the second level.
Visualisation for ontology sense-making: A tree-map based algorithmic approach
Authors: Kaneeka Vidanage  , Noor Maizura Mohamad Noor  , Rosmayati Mohemad  , Zuriana Abu Bakar
Published: May 2024

Ontology sense-making or visual comprehension of the ontological schemata and structure are vital for cross-validation purposes of the ontology increment during the process of applied ontology construction. Also, it is important to query the ontology in order to verify the accuracy of the stored knowledge embeddings. This will boost the interactions between domain specialists and ontologists in applied ontology construction processes. Hence existing mechanisms have numerous of deficiencies (discussed in the paper), a new algorithm is proposed in this research to boost the efficiency of usage of tree-maps for effective ontology sense making. Proposed algorithm and prototype are quantitatively and qualitatively assessed for their accuracy and efficacy.
Design and testing of systolic array multiplier using fault injecting schemes
Authors: Kurada Verra Bhoga Vasantha Rayudu  , Dhananjay Ramachandra Jahagirdar  , Patri Srihari Rao
Published: May 2024

Nowadays low power design circuits are major important for data transmission and processing the information among various system designs. One of the major multipliers used for synchronizing the data transmission is the systolic array multiplier, low power designs are mostly used for increasing the performance and reducing the hardware complexity. Among all the mathematical operations, multiplier plays a major role where it processes more information and with the high complexity of circuit in the existing irreversible design. We develop a systolic array multiplier using reversible gates for low power appliances, faults and coverage of the reversible logic are calculated in this paper. To improvise more, we introduced a reversible logic gate and tested the reversible systolic array multiplier using the fault injection method of built-in self-test block observer (BILBO) in which all corner cases are covered which shows 97% coverage compared with existing designs. Finally, Xilinx ISE 14.7 was used for synthesis and simulation results and compared parameters with existing designs which prove more efficiency.
Remote-control of multi appliances based latching circuit and DTMF
Authors: Jabbar Shatti Jahlool
Published: May 2024

There are multiple technologies used to remotely control electric appliances like Wi-Fi, Bluetooth, global system for mobile (GSM), and dual-tone multi-frequency (DTMF), but these technologies contain limitations, whether by coverage distance or by the number of devices that are controlled remotely. In this paper, these restrictions were overcome with the use of DTMF and digital latching devices, which doubles the number of remote-controlled electrical appliances compared to other research using the same intended technology DTMF. Using the proposed mechanism in this paper enables the users to effectively control several electric remote devices equal to the standard number of mobile keypad buttons, so in this way, can control 12 devices. This is via the mobile phone by sending commands in the form of analog tones through calling to auto-answer remote control panel phone (RCPP). An interesting feature of this research, each keypad key of the owner mobile (OM) using to control one remote electric device to switch it ON or OFF, so that the first pressing will cause to switch it ON and the second pressing caused to switching it OFF. This method is used instead of using two keypad keys, one for ON and the other for OFF. The proposed idea working is the same as manually switching but here remotely and electronically. This feature is achieved by using a D-latch digital circuit. The work is implemented and tested by using Proteus simulation program.
Prediction of mango firmness by near infrared spectroscopy tandem with machine learning
Authors: Sri Agustina  , Ramayanty Bulan  , Agustami Sitorus
Published: May 2024

The firmness of the mango fruit is one of the internal physical properties that can show its quality. Unfortunately, non-destructive methods to measure this are not yet available. In the current study, we develop a calibration model using near infrared spectroscopy to predict the physical properties (firmness) of the mango cultivar Arumanis (Mangifera indica cv. Arumanis) via machine learning. Spectral data were acquired using the fourier transform near-infrared (FTNIR) benchtop with a wavelength range of 1000 to 2500 nm. Multivariate spectra analysis based on machine learning, including principal component regression (PCR), partial least squares regression (PLSR), and support vector machine regression (SVMR), was utilized and compared to estimate the firmness of fresh mangos. The results obtained show that the prediction of machine learning by PLSR is better than that of SVMR and PCR for the prediction of mango firmness. The coefficient correlation of calibration (rc) and validation (rcv), the root means square error of calibration (RMSE-C) and validation (RMSE-CV), and the ratio of prediction to deviation (RPD) were 0.941, 0.382 kgf, 0.920, 0.472 kgf, and 2.556, respectively. The general results satisfactorily indicate that near infrared spectroscopy technology integrated with an appropriate machine learning algorithm has optimistic results in determining the firmness of mango non-destructively.
Pakistan sign language to Urdu translator using Kinect
Authors: Saad Ahmed  , Hasnain Shafiq  , Yamna Raheel  , Noor Chishti  , Syed Muhammad Asad
Published: May 2024

The lack of a standardized sign language, and the inability to communicate with the hearing community through sign language, are the two major issues confronting Pakistan's deaf and dumb society. In this research, we have proposed an approach to help eradicate one of the issues. Now, using the proposed framework, the deaf community can communicate with normal people. The purpose of this work is to reduce the struggles of hearing-impaired people in Pakistan. A Kinect-based Pakistan sign language (PSL) to Urdu language translator is being developed to accomplish this. The system’s dynamic sign language segment works in three phases: acquiring key points from the dataset, training a long short-term memory (LSTM) model, and making real-time predictions using sequences through openCV integrated with the Kinect device. The system’s static sign language segment works in three phases: acquiring an image-based dataset, training a model garden, and making real-time predictions using openCV integrated with the Kinect device. It also allows the hearing user to input Urdu audio to the Kinect microphone. The proposed sign language translator can detect and predict the PSL performed in front of the Kinect device and produce translations in Urdu.
A preliminary empirical study of react library related questions shared on stack overflow
Authors: Kurniaji Ganno Tribuana , Nugroho Yusuf Sulistyo , Islam Syful
Published: May 2024

React is a JavaScript library to develop user interfaces for single-page applications. Developers utilize react to build large web apps that allow users to update data without refreshing the page. Despite its benefits, many developers face react-related issues in the implementation. To find a solution, developers commonly shared and discussed their issues on stack overflow (SO). Although recent studies have demonstrated the benefits of utilizing react in web development, the trends of the users’ attentions remain unknown. In this study, we conducted a preliminary empirical study of react library-related questions shared on SO. We applied an exploratory data analysis technique to investigate the distribution of problems shared by the developers. The findings reveal that although the quantity of react-related topics on SO has risen over time, community interest is beginning to decrease. This is shown by the increase of the unsolved questions and the decrease of the number of views per year. Regarding the react users’ activity, most of them are more active in providing answers rather than commenting and providing scores. The findings of this study might point to future research that recommends approaches to assist the react community in overcoming issues while using react in the early phases.
The effect of segmentation on the performance of machine learning methods on the morphological classification of Friesien Holstein dairy cows
Authors: Siregar Amril Mutoi , Purwanto Yohanes Aris , Wijaya Sony Hartono , Nahrowi
Published: May 2024

Many classification algorithms are in the form of image pattern recognition; the approach to the complexity of the problem should be a feature of feasibility for representing images. The morphology of dairy cows greatly affects their health and milk production. The paper will apply several classification methods based on the morphology of Holstein Friesian dairy cows. To improve the accuracy of the model used, the segmentation process is the right step. In this paper, we compare several machine learning algorithms to get optimal accuracy. The algorithm used a support vector machine (SVM), artificial neural networks, random forests and logistic regression. Segmentation methods used are mask region-based convolutional neural network (R-CNN) and Canny; optimal accuracy is expected to create intelligent applications. The success of the method is measured with accuracy, precision, recall, and F1 Score, as well as testing by conducting a training-testing ratio of 90:10 and 80:20. This study discovered an artificial neural network optimal model with Canny with an accuracy of 82.50%, precision of 87.00%, recall of 79.00%, F1-score of 81.62%, and testing ratio of 90:10. While the models with the highest 80:20 ratio achieved 84.39% accuracy, 88.46% precision, 80.47%, and 83.00% F1-score with mask RCNN with logistic regression.
Exploring application portfolio management in Indonesia: a case study of the Indonesia agency for the assessment and application of technology
Authors: Kusumarani Riri , Pramesti Raden Putri Ayu
Published: May 2024

Due to rapid information and communication technology (ICT) growth, government agencies must manage more digital apps to support public service operations and administration. In Indonesia, at least 400,000 applications have been received by various ministries and government agencies. This amount will hurt the ICT budget’s investment and waste if no approach is employed. Problems can be solved with application portfolio management (APM). Indonesian government agencies’ AMP implementation is unclear. APM is applied at the government research institute agency for the assessment and application of technology (BPPT) in this study. BPPT was chosen due to APM’s lack of ICT investment management. This research examined 41 submissions from the 2019 digital transformation initiative. APM selected two mapping models. The outcome indicates how APM may offer ICT strategies for current applications to government entities. This analysis mapped existing applications into two models: McFarlan’s strategic grid and gartner’s TIME model. Mapping findings from these two models-technical health evaluations and regulatory compliance-may be used for application sustainability suggestions. 11 treatments were advised for maintenance and investment, while 4 applications were recommended for removal. This research helps us understand how the Indonesian government institute maintains its application portfolio and how APM might be a valuable method for application management.
The observed preprocessing strategies for doing automatic text summarizing
Authors: Juna Muhammad Farhan , Hayaty Mardhiya
Published: May 2024

It is challenging for humans to keep up with the rapid creation of digital information due to the explosion of digital information. A written document can be analyzed to extract meaningful information using automatic text summarization. This research proposes 16 different experimental settings in which the model developed by IndoBERT will be applied in order to answer the question of how much of an impact preprocessing has on the quality of summaries produced by automatic text summarization. In order to answer this question, the researchers have devised this study. In this study, we will explicitly talk about preprocessing strategies by conducting tests with different combinations of preprocessing techniques. These techniques include data cleansing, stopwords, stemming, and case folding. After that, the recall-oriented understudy for gisting evaluation (ROUGE) assessment will be used to conduct the measurement of the research results. According to the findings of this research, the optimal level of performance may be accomplished by combining the processes of data cleaning and case folding with scores of 0.78, 0.60, and 0.68 for ROUGE-1, ROUGE-2, and ROUGE-L respectively