Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of an intelligent information resource model based on modern natural language processing methods

Currently, there is an avalanche-like increase in the need for automatic text processing, respectively, new effective methods and tools for processing texts in natural language are emerging. Although these methods, tools and resources are mostly presented on the internet, many of them remain inaccessible to developers, since they are not systematized, distributed in various directories or on separate sites of both humanitarian and technical orientation. All this greatly complicates their search and practical use in conducting research in computational linguistics and developing applied systems for natural text processing. This paper is aimed at solving the need described above. The paper goal is to develop model of an intelligent information resource based on modern methods of natural language processing (IIR NLP). The main goal of IIR NLP is to render convenient valuable access for specialists in the field of computational linguistics. The originality of our proposed approach is that the developed ontology of the subject area “NLP” will be used to systematize all the above knowledge, data, information resources and organize meaningful access to them, and semantic web standards and technology tools will be used as a software basis.
Proposing the Use of Hazard Analysis for Machine Learning Data Sets

There is no debating the importance of data for artificial intelligence. The behavior of data-driven machine learning models is determined by the data set, or as the old adage states: “garbage in, garbage out (GIGO). ” While the machine learning community is still debating which techniques are necessary and sufficient to assess the adequacy of data sets, they agree some techniques are necessary. In general, most of the techniques being considered focus on evaluating the volumes of attributes. Those attributes are evaluated with respect to anticipated counts of attributes without considering the safety concerns associated with those attributes. This paper explores those techniques to identify instances of too little data and incorrect attributes. Those techniques are important; however, for safety critical applications, the assurance analyst also needs to understand the safety impact of not having specific attributes present in the machine learning data sets. To provide that information, this paper proposes a new technique the authors call data hazard analysis. The data hazard analysis provides an approach to qualitatively analyze the training data set to reduce the risk associated with the GIGO.
Hazelnut-enriched diet effectively increases lipoproteins' resistance to oxidation in hypercholesterolemic subjects

Oxidative modifications of lipoproteins are crucial in the early stages of cardiovascular diseases (CVD) like hypercholesterolemia. The major aim is to determine the effects of hazelnut consumption on the resistance of low- and high-density lipoproteins to oxidation in hypercholesterolemic subjects. Fifteen hypercholesterolemic subjects (13 men, 2 women) who did not require drug treatment according to the National Cholesterol Education Program Adult Treatment Panel III criteria and had serum levels of TC˃200 mg/dL were included in the study. This study was designed as a dual control sandwich model intervention with a single group, isoenergetic three periods. The periods were; Control Diet I (30 days), Hazelnut-Enriched Diet (30 days), and Control Diet II (30 days). The susceptibility of LDL and HDL to copper-mediated oxidation was determined spectrophotometrically by following conjugated diene formation. The resistance of lipoproteins, mainly LDL, was increased by hazelnut consumption. It can be concluded that a hazelnut-enriched diet had protective effects against lipoprotein oxidation in hypercholesterolemic subjects. These changes may play important roles in reducing the development of the atherosclerotic process.
Kintamani Tourism Destinations: A Study Of Tourist Perceptions Milenial Generation

The purpose of this study is to examine the perceptions of the millennial generation towards Kintamani as a tourism destination from three aspects, namely attractions, facilities and accessibility. As a qualitative research, data analysis was carried out in a qualitative descriptive manner. The sample of this study was 99 people, determined by the Slovin method, consisting of 89 millennial generation domestic tourists and 11 millennial generation foreign tourists. The results showed that Kintamani Tourism Destinations for attractions were considered very good with an average value of 4.46; facilities are considered good with an average value of 3.67; and accessibility is considered good with an average value of 3.91. This study also recommends the need to improve the quality and quantity of supporting facilities for the Kintamani Tourism Destination such as tourism information centers, public toilets, street lighting, money changers, parking lots, and the quality of roads in the Kintamani Tourism Destination area.
Nature-Based Virtual Reality Feasibility and Acceptability Pilot for Caregiver Respite

Home-based informal caregivers (CGs), such as the family members and friends of cancer patients, often suffer averse emotional symptoms, such as anxiety and depression, due to the burden associated with providing care. The natural environment has been valued as a healing sanctuary for easing emotional pain, promoting calmness, relaxation, and restoration. The use of virtual reality (VR) nature experiences offers an alternative option to CGs to manage emotional symptoms and improve their quality of life. The aim of this mixed-method pilot was to evaluate the feasibility and acceptability of a nature-based VR experience for home-based CGs. Nine informal CGs participated in a 10 min nature-based VR session and completed feasibility, acceptability, and VR symptom measures in the laboratory. Semi-structured interviews with five of the CGs provided qualitative data regarding their experiences with VR. The CGs (mean age 64.78 years) were mostly female (n = 7). Our analysis showed high feasibility (15.11 ± 1.76; range 0–16) and acceptability (15.44 ± 1.33; range 0–16), as well as low VR Symptoms (1.56 ± 1.33; range 0–27). Participants primarily expressed positive perceptions regarding VR feasibility and acceptability during interviews. Our findings show promise for the use of VR nature experiences. In the next phase of the study, the intervention will be tested on home-based informal CGs of patients at end of life.
Impact of Institutional Agricultural Credit on Agriculture Sector Growth and Rural Unemployment in Pakistan

This research article studies the impact of credit given by different financial institutions to farmers for agricultural development and its impact on rural unemployment rate covering the data sample from 1990 to 2021. Agriculture sector is the main sector of Pakistan’s economy. It provides employment to 43.7 % of total labor force and its contribution in GDP of Pakistan is 22%. This study analyze the impact of institutional agricultural credit provided by ZTBL, COP and CB, Infrastructure, GDP and total cropped area (TCA) on Rural Unemployment rate and agriculture sector and the impact of rural unemployment rate on agriculture sector growth. For this purpose, time series secondary data from 1990 to 2022 is used. ADF test estimate that RU, ZTBL, COP, CB, INFRA, GDP and TCA is stationary at First difference and AG is stationary at level. To estimate the impact of ZTBL, COP, CB, INFRA, GDP and TCA Toda and Yamamoto Technique is used and find out that all the variables individually as well as jointly has impact on RU. RU has unidirectional causality with CB, INFRA and TCA while the causality of RU with ZTBL, COP and GDP is bi-directional.
Robust iterative learning control via adaptive backstepping for oscillation displacement system of continuous casting mold driven by a servo motor

In order to solve the tracking problem of oscillation displacement system of continuous casting mold driven by a servo motor in the present of the time‐varying load, parameter uncertainties, unknown dynamics and external disturbances, a robust iterative learning control (ILC) via adaptive backstepping is proposed in this paper. Firstly, backstepping technique is used to design controller due to the mismatched disturbances. Secondly, the periodic component of the lumped disturbances is estimated by ILC method, while the aperiodic component is attenuated by switching term with adaptive gain. In addition, a time‐varying boundary layer approach is employed to overcome the identical initial condition limitation of the ILC. Through a proper composite energy function, the convergence of the closed‐loop system is analyzed. Finally, simulation and experimental results are given to illustrate the effectiveness of the proposed method.
The Concept of Total Leadership of Islamic Boarding Schools in KH Abdullah Syukri Zarkasyi’s Perspective (Case Study in Modern Islamic Boarding School Darussalam Gontor 1985-2020)

The existence of Kiai as a leader of Islamic boarding schools are very urgent and vital, because the success of Islamic boarding schools is largely from leadership factor of Kiai, so that he is the main pillar of leadership in realizing the progress of Islamic boarding schools, then KH Abdullah Syukri Zarkasyi saw that, leadership is the source of the benefit and problems of mankind. Even the problems of the people until now are about leadership. The aim of this study is to find out the Total Leadership Concept of Islamic Boarding Schools in KH Abdullah Syukri Zarkasyi’s Perspective who has had extraordinary experience in developing Darussalam Gontor Modern Islamic Boarding School from 1985-2020. In this study, researchers used qualitative research with a phenomenological approach, with field exploration and a theoretical orientation or theoretical perspective with a phenomenological approach. From the results of this study, it indicates that the concept of total leadership of Islamic Boarding School in KH Abdullah Syukri Zarksyi’s perspective is Priority, Focus and above personal interests, a leader must be willing and able to devote his time and thoughts to the interests of the Islamic boarding school above personal and family interests. Total leadership must be able to identify and solve all problems and solve them, either independently or delegated to the institution, he is a visionary leader, initiator, anticipatory inspirational, and has an analytical mind on every problem
Reproducing Kernel-Based Best Interpolation Approximation for Improving Spatial Resolution in Electrical Tomography

Electric tomography (ET) is an advanced visualization technique with low-cost, rapid-response, nonradiative, and nonintrusive advantages compared with other tomography modalities. The imaging resolution of ET, however, is significantly low providing the required measurements that are far less than the number of pixels in a detection field. Presented here is a reproducing kernel-based best interpolation (RKBI) method that can greatly increase the number of numeric measurements in the ET process. For a group of available measurements, RKBI has the smallest approximation error compared to the existing interpolation methods. Furthermore, the error of RKBI can be easily estimated with no additional hardware and the need for actual measurements. The optimality of RKBI is validated using both theoretical and experimental frameworks, demonstrating that RKBI really improves the spatial resolution and steadiness of ET images.
INVESTIGATING INDONESIAN EFL LEARNERS’ CRITICAL THINKING: CURRENT STATE AND FUTURE DIRECTIONS

This research aims to investigate the critical thinking skills of 86 Indonesian English as a Foreign Language (EFL) learners who are prepared to be English teachers using an adapted questionnaire measuring critical thinking skills. This research uses a descriptive quantitative research design to examine the critical thinking skills of Indonesian EFL learners. It reveals the ability of Indonesian EFL learners’ critical thinking skills through a diagnostic test which results in a moderate level, implying that the strategies to embed critical thinking in an EFL classroom setting need to be improved. This eventually might lead to a wide gap between the existing teacher's competence and the expected qualities. This research argues the diagnosis of critical thinking state in Indonesia’s pre-service English teachers and the future directions to leverage critical thinking skills.
A rotor initial position estimation method for sensorless field-oriented control of permanent magnet synchronous motor

In this paper, a new technique to improve initial rotor position detection at standstill of a permanent magnet synchronous motor (PMSM) is presented. Sensorless field-oriented control (FOC) of a PMSM at low speed remains a difficult task. In order to estimate the position and rotor speed, we proposed a novel structure of a full-order sliding mode observer (FO-SMO) in a sensorless FOC. At standstill, we used a voltage pulse sequence applied to the windings in order to detect the initial rotor position. With this technique, we managed to minimize the error on the estimated rotor position to 3.75° (electrical) compared with others. The validity of the proposed approach with a 1.1-kW low-speed PMSM sensorless FOC has been proved by experimental results.
Linear and Nonlinear Optics in a System of Massless Dirac Fermions

Graphene electrons possess linear energy dispersion relation, and thus behave as two-dimensional (2D) Dirac fermions. Consequently, compared with the conventional 2D electron gas systems (2DEG) found in MOSFETs and quantum wells, graphene exhibits a variety of electronic and optoelectronic properties that are characteristic of 2D Dirac fermions. Similar 2D Dirac fermions are found at the surface layer of 3D topological insulator, and they are topological protected from backscattering due to spin-orbital coupling and time reversal symmetry. We here calculate the linear and nonlinear optical response of graphene in strong magnetic and optical fields, using a quantum-mechanical density-matrix formalism. We show that graphene in a magnetic field possesses a giant midor far-infrared optical nonlinearity, perhaps the highest among known materials. The high nonlinearity originates from the unique electronic properties and selection rules near the Dirac point. As a result, even one monolayer of graphene gives rise to an appreciable nonlinear frequency conversion efficiency for incident infrared radiation. Inspired by the highly efficient four-wave mixing process in the 2D Dirac fermion systems, we further propose a new mechanism of generating polarization-entangled photons based on the parametric generation process in the third section of this dissertation. Unique properties of quantized electron states in a magnetized graphene and optical selection rules near the Dirac point give rise to a giant optical nonlinearity and a high rate of photon production in the midor far-infrared range. A similar mechanism of photon entanglement may exist in topological insulators where the surface states have a Dirac-cone dispersion and demonstrate similar properties of magneto-optical absorption.
Integrated Optics: Platforms and Fabrication Methods

Integrated optics is a field of study and technology that focuses on the design, fabrication, and application of optical devices and systems using integrated circuit technology. It involves the integration of various optical components, such as waveguides, couplers, modulators, detectors, and lasers, into a single substrate. One of the key advantages of integrated optics is its compatibility with electronic integrated circuits. This compatibility enables seamless integration of optical and electronic functionalities onto the same chip, allowing efficient data transfer between optical and electronic domains. This synergy is crucial for applications such as optical interconnects in high-speed communication systems, optical sensing interfaces, and optoelectronic integrated circuits. This entry presents a brief study on some of the widely used and commercially available optical platforms and fabrication methods that can be used to create photonic integrated circuits.
The development and use of adolescent mobile mental health (m-mhealth) interventions in low- and middle-income countries: a scoping review

Adult mental health challenges frequently stem from undiagnosed poor mental health earlier in life. With increasing levels of poor adolescent mental health and insufficient health care resources in low- and middle-income countries, mobile mental health may offer expanded service access. Little is known about mobile mental health interventions for adolescents in low- and middle-income countries. Our aim was to review the literature on mobile mental health intervention, development and use for low- and middle-income country adolescents. We searched APA PsycInfo, Web of Science, Psychiatry online, and Ebscohost databases using keywords and phrases. Screening of the 6953 retrieved articles, generated 6 articles that met the inclusion criteria. Arksey and O’Malley’s adapted framework was followed using rigorous inclusion criteria and screening by two reviewers. Studies showed high heterogeneity. Two studies used short message service text messaging platforms, one used phone call reminders, two used smartphone applications (WhatsApp or game-based), and one study compared different short message service, web-based and smartphone app offerings. Generally, adolescents had a positive perception of mobile mental health interventions. Helpline messages, peer group sessions, access to a counsellor and games set in real-life environments were some of the preferred contents of mobile mental health interventions. Noted barriers include low personal mobile phone ownership, leading to lack of confidentiality, data costs and limited internet access. While adolescents in low- and middle-income countries find mobile mental health interventions acceptable and supportive, challenges remain. Mobile mental health interventions can potentially overcome barriers associated with face-to-face care, such as high cost and stigma. However, more research is needed to overcome these challenges and build the evidence-base in low- and middle-income countries for this field to grow.
Change Detection of High-Resolution Remote Sensing Images Through Adaptive Focal Modulation on Hierarchical Feature Maps

One of the major challenges in the change detection (CD) of high-resolution remote sensing images is the high requirement for computational resources. Besides, to get the best change detection result, it must spot only the important changes while omitting unimportant ones, which requires learning complex interactions between multi-scale objects on the images. Despite Convolution Neural Network (CNN) efficiently extracting features from such images, it has a limited receptive field resulting in sub-optimal representation. On the other hand, Vision Transformer (ViT) can capture long-range dependencies. Still, it suffers from quadratic complexity concerning the number of image patches, especially for high-resolution images. Furthermore, both approach can not model the interactions among multi-scale image patches, which is essential for a model to fully understand the natural images. We propose FocalCD, a CD method based on a recently proposed focal modulation architecture capable of learning short and long dependencies to solve this problem. It is attention-free and does not suffer from quadratic complexity. Also, it supports learning multi-scale interaction by adaptively selecting the discriminator regions from multi-scale levels. Besides the efficient yet powerful encoder, FocalCD has an effective multi-scale feature fusion and pyramidal decoder network. FocalCD achieves strong empirical results on various CD datasets, including CDD, LEVIR-CD, and WHU-CD. It reaches F1 scores of 0.9851, 0.952, and 0.9616 on datasets CDD, LEVIR-CD, and WHU-CD outperforming state-of-the-art CD methods while having comparable or even lower computation complexity.
Influence of Jet Parameters on the Aero Engine Cleaning Flow Field

Engine blades will be contaminated during operation, On-line cleaning is the main method to solve blade fouling. In order to study the effect of jet parameters on the flow field of aero-engine cleaning, a low-pressure first-stage rotor flow channel model of a CFM56-7B engine was established, and the changes in the parameter of the cleaning flow field were analyzed under different incident pressures. The results showed that as the jet pressure increased, the average pressure along the blade height increased, whereas the average pressure along the cross section at 50% blade chord length decreased. The vorticity along the blade height cross section increased first and then decreased as the jet pressure increased, whereas the vorticity along the blade chord length cross section remained basically unchanged after the jet pressure reached 3 bar. Comparing experimental results, when the pressure is maintained at 3 bar, better cleaning effect can be obtained. The research provides a theoretical basis for the on-line cleaning.
A Torque Control Strategy for a Robotic Dolphin Platform Based on Angle of Attack Feedback

Biological fish can always sense the state of water flow and regulate the angle of attack in time, so as to maintain the highest movement efficiency during periodic flapping. The biological adjustment of the caudal fin’s angle of attack (AoA) depends on the contraction/relaxation of the tail muscles, accompanying the variation in tail stiffness. During an interaction with external fluid, it helps to maintain the optimal angle of attack during movement, to improve the propulsion performance. Inspired by this, this paper proposes a tail joint motion control scheme based on AoA feedback for the high-speed swimming of bionic dolphins. Firstly, the kinematic characteristics of the designed robot dolphin are analyzed, and the hardware basis is clarified. Second, aiming at the deficiency of the tail motor, which cannot effectively cooperate with the waist joint motor during high-frequency movement, a compensation model for the friction force and latex skin-restoring force is designed, and a joint angle control algorithm based on fuzzy inference is proposed to realize the tracking of the desired joint angle for the tail joint in torque mode. In addition, a tail joint closed-loop control scheme based on angle of attack feedback is proposed to improve the motion performance. Finally, experiments verify the effectiveness of the proposed motion control scheme.
A DIPLOID GENETIC ALGORITHM WITH EXOGENOUS RECOMBINATION FOR BREAKING MERKLE-HELLMAN KNAPSACK

Cryptanalysis is the science and study of methods of breaking cryptographic techniques. Cryptanalytic attack on Merkle-Hellman knapsack using Genetic Algorithm (GA) was done by Spillman. Then Garg et al improved the Spillman GA. The objective of this paper is to harness the power of GA used by Garg et al. to get more reliable results and in less computation time. This paper utilizes a GA , known as diploid GA with exogenous recombination scheme for translating each number in ciphertext into the correct ASCII code for the plaintext characters. Our results are compared with Garg et al. result and they proved that diploid GA with exogenous recombination scheme is more efficient and highly successful in finding the correct bit pattern for the hard knapsack sum.