bluuebunny/crossref_metadata_2025 huggingface dataset:
Controlled Redundancy Schemes in Collaborative IoT by Smartphones
Authors:   Benha Faculty of Engineering, Benha University, Egypt, Marzouk Mohamed A. , Hassan Ayman M. , Zekry Abdelhalim A.
Published: October 2022

Internet of Things (IoT) operators tend to utilize smartphones in establishing reliable and sustainable communication links for their services. Collaborative IoT (CIoT) is a concept where the smartphones are utilized as a mobile gateway (GW) that connects sensors to the cloud. CIoT scheme has many challenges including the redundancy in transmissions of sensor readings. As the same sensor data is sent by many uncoordinated users, this leads to consuming network resources and degrading Quality of Services (QoS) for primary users. This paper has three main contributions: First, four metrics for evaluating redundancy and its effects in CIoT network are defined and explained. Second, a novel redundancy control scheme (Fresh-List redundancy control) is proposed and evaluated against well-known probabilistic transmission schemes using the proposed metrics. Finally, a simulation setup for CIoT environment is implemented using a computer equipped with Bluetooth network card. The setup simulates many CIoT users with different scenarios of random entry, departure, and dwelling times. Results show the ability of Fresh-List method to reduce redundancy order and increase efficiency compared to non-controlled redundancy. It is also shown that a mix between probabilistic transmission and Fresh-List methods provide even more better redundancy control at an acceptable increase at the average packet delivery delay.
Improving Interference Cancellation in Spatial Division Multiplexing Using a Combination of the Channel Coding and QR-Successive Interference Cancellation
Authors:   Benha Faculty of Engineering, Benha University, Benha, Egypt, Ibrahem Heba Talla Adel , Hassan Ashraf Yehya , zekry Abdelhalim
Published: October 2022

This paper introduces QR-SIC detector to minimize the probability of error comparing to SDM system. Spatial-division-multiplexing (SDM) system is a multiple-inputs-multiple-outputs (MIMO) system used to increase data transmission rate in modern communication systems. The major disadvantage of SDM system is the interference between the received symbols. In this paper, a new trans-receiver architecture for SDM system is introduced. This receiver uses a Successive-Interference-Cancellation (SIC) detector based on QR-decomposition of the channel matrix and a Forward-Error- Correction (FEC) channel code. The proposed architecture merges the interference cancellation process in QR-SIC detector and the forward error correction process in the channel decoder. The feedback symbols in the QR-SIC detector are the output symbols from the channel decoder after they are re-encoded and re-modulated and more robust. The new architecture minimizes the probability of error in the demodulated symbols more than the conventional SDM receiver. If the conventional SDM receiver needs 100 MWATT transmitted power the proposed system needs only 64 MWATT transmitted power. So The new architecture of the SDM receiver can save up to 36% of the transmitted signal power used with the conventional SDM receiver. At BER of 10-4, the convolution codes of code rates 3/4, 1/2, and 1/4 achieve coding gains of 15 dB, 24 dB, and 30 dB with respect to the uncoded 4-antennas SDM receiver. the proposed SDM receiver at BER of 10-4 is 2dB, 1.5 dB, and 0.9 dB better than the BER performance of the conventional coded SDM receiver at the same code rates and the same number of antenna. The enhancement in the BER performance of the proposed SDM receiver increases as the code gain of the used code. This increase in the power efficiency and bandwidth comes at the expense of an increase in the receiver complexity and latency
UPISmartHome V.2.0 – A Consumer Product of Smart Home System with an ESP8266 as the Basis
Authors:   Program Studi Sistem Telekomunikasi, Universitas Pendidikan Indonesia, Bandung, Indonesia, Fuada Syifaul , Hendriyana Hendriyana
Published: October 2022

An ESP-Mesh-based smart home system was developed in the previous research using the ESP8266 feature with 3 different nodes, such as mechanical (door lock), electrical (fan, generic power switch, or power plug), and temperature & humidity sensors. This research focused more on the addition of nodes into the IoT-based smart home infrastructure. The purpose is to design, implement, and test hardware and software intended to be incorporated into the ESP8266-based system for normal functionality. These nodes include 1) RGB lamp that is controlled by colour lightning, 2) horizontal and 3) vertical curtain 4) PIR sensor for detecting the presence of humans (suspicious people) around the house, 5) liquefied petroleum gas (LPG) sensor for examining leakage of gas cylinders within the house, 6) smoke sensor for fire detection, and 7) an electric fan using the soft-control (PWM-based) method. The fan is observed to increase in functionality from the previous research, which is regulated by a switch only (hard-control). Meanwhile, the new android application monitors the seven nodes defined without limitations. The method used by the application includes the determination of system specifications, hardware and software design (ESP8266 and android programming), implementation, and verification. The system evaluation procedure used in the previous research comprised 1) RSSI measurement, 2) power consumption, 3) Mesh connection, 4) functionality test of UPISmartHome Apps V.2.0, and 5) the overall system (hardware & software integration). The test results by observing the RSSI parameters reveal that all nodes can be managed (control & monitor) remotely via the android application with an average distance of about 70 meters without an internet connection. Furthermore, all nodes are successfully connected to the ESP-Mesh network with effective self-routing capabilities between 40 – 50 meters because the distance between nodes above 70m cannot do self-configuration; this is the ability of ESP8266. The power consumed by each node both in idle and active conditions is not more than 2 Watts.
A Proposed Method for Synthesizing the Radiation Pattern of Linear Antenna Arrays
Authors:   Australian College of Kuwait, Kuwait, Ka’bi Amin Al
Published: October 2022

The design of antenna arrays is one of the most challenging optimization problems in recent research interests. In this research work a new method of optimization is proposed. This method called "Characteristics Evolution Optimization" is based on parallel processing of streams of binary digits, and hence it can perform well in parallel processing digital systems. In this article, a 16 - element linear antenna array has been taken into consideration, and the performance of the proposed technique for synthesizing the radiation pattern of the array has been investigated and compared with other existing techniques, such as DE (Differential Evolution), IWO (Invasive Weed Optimization), and PSO (Particle Swarm Optimization). Various variants of Invasive Weed Optimization have been investigated as well. It has been observed that the proposed method (Characteristics Evolution optimization) outperforms the other optimization techniques significantly in different aspects.
New Efficient Authentication Model for Vehicular Ad Hoc Networks
Authors:   Hassan First University of Settat , Faculté des Sciences et Technique, Laboratoire d'Ingénierie, de Management Industriel et d'Innovation (LIMII), Morocco, ihyaoui Abdelilah El , Youssefi My Abdelkader , Mouhsen Ahmed , ELfarnane Abdelhafid , Dakir Rachid
Published: October 2022

In this article, we present a security model architecture for communications, it offers a lightweight authentication in real-time, decentralized, efficient, that can be applicated in real mode, the proposed model respects the security requirements authenticity, anonymity, integrity, and non-repudiation. In our scheme, we firstly initialize the authentication between vehicle and RSU, the vehicle has an Access Token and key to join the group, then we use a hash message authentication code (HMAC) to avoid time consuming CRL checking. Finally, the vehicle can be using the generated Access Token for communication. The performances show that our model is more efficient in terms of authentication speed and consuming resources, it results a real time authentication.
Route Discovery Using Hybrid Approach for Disaster Management in MANET
Authors:   Department of Computer Science, Fakulti Sains Komputer Dan Teknologi Maklumat (FSKTM), University Tun Hussein Onn Malaysia (UTHM), Malaysia, Soomro Abdul Majid , Fudzee Mohd Farhan Md. , Saim Hafiz Muhamad , Zaman Gohar
Published: October 2022

A disaster situation is an event that alters in the normal execution of activities. A mobile ad-hoc network (MANET) is a self-controlled, autonomous wireless network used in an uncertain environment with decentralized control. In disaster, when communication between nodes is not performed properly, MANET can impart an important role of communication between nodes in uncertain situations. In MANET, routing is considered one of the most salient aspects of data transfer in a disaster situation. Proactive and reactive protocols are used as standard in various applications of MANET owing to the simplicity in their design and performance. Combining three routing protocols makes a hybrid approach to get better performance inefficient route discovery and maintenance. This is because reactive routing protocols, sometimes, do not provide better performance in heavy traffic and load, especially in a disaster. This is because the hybrid approach is very useful for fast convergence with low memory and power management. This paper introduces an improved hybrid routing protocol (IHRP) approach that combines two reactive and one proactive routing protocol to provide efficient route discovery and maintenance mechanisms. The simulation environment is used for the proposed approach. Results after simulation illustrate that it provides better performance in data packet delivery, routing load, throughput, and end-to-end delay data packet delivery, routing load, throughput, and end-to-end delay than the Ad-hoc On-demand Distance Vector (AODV) and Zone-based Routing Protocol (ZRP). The contrasting results between the IHRP and existing protocol indicate that the IHRP outperforms and increases the performance from 9% to 12%.
Comparison of Automatic Modulation Classification Techniques
Authors:   Sudan University of Science and Technology, College of Engineering, Dept of Electronics, Sudan, Jassim Salah Ayad , Khider Ibrahim
Published: October 2022

The advancement of digital communication and technology triggered new challenges related to the channel and radio spectrum utilization. From the other hand, real-time communications are keen of time where requests need to be processed in very short time. Automatic modulation is one of promising approaches that relies on pretrained classifiers in order to recognize the type of modulation techniques used by the transmitter. Considering that noise is dominating between the transmitter and receiver, the task of automatic modulation classification is become harder. Noise is destroying the obvious features of the signals and degrade the classification accuracy. The modulation identification technique is made to recognize the type of modulation using the deep learning technology. This paper is listing the common stat of the arts used in automatic modulation classification along with their performance measures. It was realized that deep learning classifier manifested in Conventional Neural Network (CNN) is outperformed in AMC scoring of 85.41 % of recognition accuracy.
Implementation of Satellite Road Image Denoising using Iterative Domain Guided Image Filtering with Gray World Optimization
Authors:   GITAM (Deemed to be University), Visakapatnam, India, Subhashini D. , Dutt V. B. S. Srilatha Indira
Published: October 2022

Generally, Satellite road images are in noisy conditions such as noise, snow, thin cloud, dust, etc., which results in contrast degradations in the image. Denoising is defined as the technique for removing noise or atmospheric impurities from an image to increase the quality of an image. But most of the state of art approaches failed to remove the atmospheric effects and noise from the road image perfectly. To solve this problem, this paper majorly focuses on developing a Gray World Optimization (GWO) algorithm for the perfect estimation of atmospheric road light. The work also develops the novel method for dark channel prior-based transmission map estimation and refinement in pixel-wise and patch-wise manner. Thus, the atmospheric road effects are resolved in each pixel-based patch. Finally, a fast iterative domain guided image filtering (ID-GIF) approach was developed to obtain smoothen output with Denoising properties. The simulation results show that the proposed work provides better quantitative and qualitative results than state-of-the-art approaches.
A Throughput Fairness Control Method for Concurrent Communications in Wireless Local-Area Network with Multiple Access-Points
Authors:   Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan, Rahman Md. Mahbubur , Funabiki Nobuo , Munene Kwenga Ismael , Roy Sujan Chandra , Kuribayashi Minoru , Kao Wen-Chung
Published: October 2022

The IEEE 802.11n wireless local-area network (WLAN) has been widely deployed at every place around the world for the Internet access services. In WLAN, the throughput unfairness problem appears among concurrently communicating hosts due to their signal strength differences when the distances to access-points (APs) are different. Previously, to achieve fair network services among users, we have studied the method of controlling the packet transmission delay at one AP using PI controller. However, it cannot be applied to multiple APs that are common in WLAN. In this paper, we propose a throughput fairness control method of applying traffic shaping at the APs to provide the fair throughput among concurrently communicating hosts with multiple APs. For evaluations, we implement the testbed system using Raspberry Pi for APs and conduct extensive experiments in six topologies with up to four APs. The results show that the throughput of every host is similar to each other in any topology, which confirms the effectiveness of the proposal.
Design of DCO-OFDM System for VLC on Chip at the Register-Transfer Level
Authors:   Program Studi Sistem Telekomunikasi, Universitas Pendidikan Indonesia, Bandung, Indonesia, Fuada Syifaul , Putra Angga Pratama , Adiono Trio
Published: October 2022

This paper reports a System-on-Chip (SoC) architecture design for the DC-biased optical OFDM (DCO-OFDM) Visible Light Communication (VLC) transceiver. The proposed SoC comprises several Digital Signal Processing (DSP) blocks, i.e., Fast Fourier Transform (FFT), Convolutional Encoder (CE), Viterbi Decoder, Quadrature Phase-Shift Keying (QPSK) Modulator/Demodulator, Interleaver/Deinterleaver, and Synchronizer. System was designed through the combination of two Intellectual Property (IP) types: designing IP from the scratch (custom-based IP) and employing available core accelerator IP served by the third party, which is Xilinx library (reuse-based IP). All DSP blocks were targeted for the FPGA development board (Xilinx Zynq SoC 7000), then combined with the ARM microprocessor. In this study, ARM microprocessors were used for various tasks, i.e., scheduling process, on-chip memory as a temporary data storage function, Analog-to-Digital Converter (A/D), Digital-to-Analog Converter (D/A), and Ethernet module as communication medium between SoCs and personal computer (PC). Testing was carried out on the Register Transfer Level (RTL) for hardware (H/W) and software (S/W) models implemented on ARM microprocessors. The system performances were measured through the point-to-point data communication scenarios between a PC transmitter and PC receiver. A 77 kbps of data communication speed and 2.9 ms of data processing latency were obtained using 100 MHz clock speed. The VLC on-chip was successfully demonstrated in RTL phase. This system is suitable for a low-rate communication system application, generally for joint VLC and Internet-things (IoT) technology, (then called as VLC/IoT).
ON THE APPLICATION OF VARIATIONAL AUTO ENCODERS (VAE) FOR DAMAGE DETECTION IN ROLLING ELEMENT BEARINGS
Authors: LINDLEY C. A. , ROGERS T. , DWYER-JOYCE R. , DERVILIS N. , WORDEN K.
Published: October 2022

In structural health monitoring (SHM) and condition monitoring (CM) applications, the expense of testing programmes may be too high to obtain adequate datasets. When limited by the number of available data samples, one may rely on dimensional reduction methods to proceed with a meaningful statistical and probabilistic analysis. In this work, some state-of-the-art dimensionality-reduction techniques were investigated as part of a simple ball-bearing damage detection problem. A variational auto-encoder (VAE) was compared to other methods, based on their capability to generate low-dimensional representations of the data. Unlike other common alternatives, such as principal component analysis (PCA) or auto-encoding (AE) networks, the VAE introduces a probabilistic framework via the latent embeddings. A well-defined distribution is thereby constructed on the latent variables, making the transformed dataset an optimal one for subsequent pattern recognition analysis. The results demonstrated an increase in classification performance given the low-dimensional representation generated by the VAE.
APPLICATIONS OF SURROGATE FINITE ELEMENT MACHINE LEARNING APPROACH FOR STRUCTURAL MONITORING
Authors: CHOPPALA SAM , VURTURBADARINATH POOJHITA , CHIERICHETTI MARIA , KHAKI FATEMEH DAVOUDI
Published: October 2022

Current maintenance intervals of mechanical systems are scheduled a priori based on the life of the system, resulting in expensive maintenance scheduling, and often undermining the safety of passengers. This problem is particularly relevant in the development of autonomous vehicles, especially in the concept of urban air mobility. The actual usage of the vehicle will be used to predict stresses in the structure and therefore to define maintenance scheduling. Supervised regression machine learning algorithms are used to map a reduced set of data coming from real-time measurements of a structure into a detailed/high-fidelity finite element analysis (FEA) model of the same system, therefore creating a surrogate of the finite element model. The paper will present applications of the approach to a one-dimensional beam structure, modeled with finite element methods. Based on the response of the beam measured at a few reference locations, the surrogate finite element approach determines the entire response of the beam at all spatial locations (displacements, velocities, accelerations, stresses, strains) using neural networks. The FEA-based machine learning approach estimates the stress distribution over the entire system during operations, thus improving the ability to define ad-hoc, safe and efficient maintenance procedures. The effect of type of input features and output and their relationship on the performance of the neural network is discussed, as well as the effect of the beam boundary conditions on network performance.
ON AN APPLICATION OF GENERATIVE ADVERSARIAL NETWORKS ON REMAINING LIFETIME ESTIMATION
Authors: TSIALIAMANIS G. , WAGG D. , DERVILIS N. , WORDEN K.
Published: October 2022

A major problem of structural health monitoring (SHM) has been the prognosis of damage and the prediction of the remaining useful life of a structure. Both tasks depend on multiple parameters, many of which are often uncertain. A wide range of models have been developed for the aforementioned tasks, but they have been either deterministic or stochastic with the ability to take into account only a restricted set of past states of the structure. In the current work, a generative model is proposed in order to make predictions about the damage evolution of structures. The model is able to perform in a population-based SHM (PBSHM) framework, to take into account many past states of the damaged structure, to incorporate uncertainties in the modelling process and to generate potential damage evolution outcomes according to data acquired from a structure. The algorithm is tested on a simulated damage evolution example and the results reveal that it is able to provide quite confident predictions about the remaining useful life of structures within a population.
COMPARISON OF ERROR MEASURES AND MACHINE LEARNING METHODS FOR STRAIN-BASED STRUCTURAL HEALTH MONITORING
Authors: PFINGSTL SIMON , TUSCH OLAF , ZIMMERMANN MARKUS
Published: October 2022

The development of aircraft structures requires many fatigue tests. These tests are usually carried out to validate the corresponding finite element and damage models and to prove the expected damage-tolerant behavior. Monitoring aircraft structures requires experienced staff and is very time-consuming and expensive as the recurring inspection of the structure is a tedious task. We propose a machine learning-based approach that exploits continuous load and strain measurement data to support structural health monitoring and to shift the inspection program towards predictive maintenance. The machine learning model is used for mapping loads onto local strains. With the trained model, different error measures between current measurements and the predicted values are determined. When a specific threshold value based on an error confidence level is exceeded, an alarm is set off, and appropriate actions can be taken. The approach is applied to several fatigue tests with two different types of structures and damage mechanisms. Various error measures and models are compared. The paper shows that, first, simple error measures, such as the root mean squared error, are sufficient and even outperform more sophisticated error distances for detecting cracks with continuous strain measurements. Second, the standard deviation of strain or rather the load-strain slope is a key feature to detect cracks. And third, machine learning models enable structural health monitoring with sensors that even have only small strain values.
RAIL NEUTRAL TEMPERATURE ESTIMATION USING ZERO GROUP VELOCITY MODES AND MACHINE LEARNING
Authors: WU YUNING , HUANG CHI-LUEN , LEE SANGMIN , ZHANG KEPING , POPOVICS JOHN , DERSCH MARCUS , ZHU XUAN
Published: October 2022

With increasingly frequent extreme heat events over the past half century, thermal stress measurement and management of continuous welded rail (CWR) have become more important for railroad maintenance. Methods, including visual inspections and rail lifting, are routinely performed in railroad networks of the U.S. to prevent rail thermal buckling. When intervention becomes necessary, a rail distressing process, involving rail cutting and welding, will be performed to re-establish the zero-stress state at a desirable temperature. And the temperature at which the rail is stress-free is defined as rail neutral temperature (RNT). In this work, an RNT predictive tool that exploits zero group velocity (ZGV) modes and machine learning is proposed. First, the existence of ZGV modes in CWR is investigated through numerical simulation, using both semianalytical finite element analysis (SAFE) and finite element (FE) models. Further, parametric studies are performed to quantify the effect of axial loads and rail temperature on ZGV modes. Additionally, the team established an instrumented field test site at a revenue-service line and performed multi-day data collection to cover a wide range of temperature and thermal stress levels. FE models were calibrated based on the field-collected vibrational data via a linear program optimization approach and an excellent agreement between model and experimental results was obtained. Finally, a supervised learning framework was developed to estimate the RNT using rail temperature and resonance frequencies as the inputs. The results show that the proposed framework can provide RNT estimation with reasonable accuracy (±5 ºF) when measurement noise is low.
Moral Intelligence and its Relationship to Academic Entitlement and Academic Performance of Secondary School Students
Authors: Abdellatif Mohamed Sayed
Published: October 2022

The purpose of the current research is to identify the correlations between moral intelligence and both academic entitlement and academic performance; in addition to identify the mediating role of academic entitlement between moral intelligence and academic performance. Four hundred and forty-four students from (Yemen, Egypt, Saudi Arabia, Iraq, and Jordan) participated in the research. The moral intelligence scale and the academic entitlement scale were applied to the participants and data were analyzed using Pearson's correlation coefficient and path analysis. The results revealed that there was a statistically significant negative correlation between moral intelligence and academic entitlement and a significant positive correlation between moral intelligence and academic performance. Besides, results demonstrated the mediating role of academic entitlement between moral intelligence and academic performance. The results of this research can be employed in building programs and setting plans for developing moral intelligence and eliminating academic entitlement behaviors and beliefs to encounter the problems of secondary school students.
Soft Skills Through the Prism of Primary School Teachers
Authors: Ouchen Laila , Tifroute Lahcen , El-Hariri Khadija
Published: October 2022

COVID-19 and the expansion of distance learning pose new challenges to the educational system. Soft skills are imperative in this context, for children's effective and adaptive learning. The following study aims to discover teachers' representations by identifying their common conceptual framework of soft skills in primary school. Semi-structured interviews were conducted with teachers. The teachers' comments helped identify and define a framework of soft skills that would help children learn effectively. The results illustrate that the lack of practice of soft skills activities depends on the teachers' perceptions of the importance of their role in transmitting disciplinary knowledge. The study concluded that the lack of a clear and shared vision of soft skills influences the representations and practice of teachers.
Stuck in a Lockdown: Filipino Students' Odyssey of Resilience
Authors: Gaylo Derren N. , Aňar Lora E. , Improgo Cecille Marie T. , Alugar Ritchelee B.
Published: October 2022

The COVID-19 outbreak in the Philippines forced schools to close. Many Filipino students were stranded in their dormitories and boarding houses due to government-imposed lockdowns. As the study's impetus, the researchers explored the phenomenon of stranded students during a pandemic. A transcendental phenomenological inquiry was conducted in Northern Mindanao, Philippines, to disclose the experiences of six stranded students. Stranded students' lifeworld throughout the lockdown was documented through phenomenological interviews. The phenomenological reduction technique was used to transcribe and analyze the data. Provisional codes were used to classify critical statements into themes for the initial analysis of the interview data. The research revealed the themes of (a) groping in the dark, (b) journeying towards the light, and (c) welcoming the breaking dawn. The various stages of reality in the life of the stranded students are shown in these topics. They relate the story of how their confinement experience taught them to be resilient, which covers resilience as a process. The paper discusses numerous pedagogical implications of the phenomenon.
Challenges of Online Education for Teachers and Parents in the Emirati School System
Authors: Khaled Ahmed , Hazaymeh Wafa’ A. , Montierre Maude Evelyn
Published: October 2022

This study examined the challenges and issues faced by teachers and parents related to the transition from face-to-face instruction to online instruction. During the COVID-19 pandemic, ten teachers and ten parents from the United Arab Emirates (UAE) school system were interviewed to reveal their challenges in managing online teaching and learning. According to the findings, both teachers and parents encountered several problems. Teachers faced challenges such as the need to adapt their teaching strategies and techniques to the new situation, the need for technical support to facilitate the teaching-learning process, the lack of students’ in-class participation and genuine motivation, and the nature and format of the teaching platform, and the fact that they need to have a high level of experience in using technology to serve their students well and engage them in interactive classroom activities. Parents reported several challenges, including lack of experience with the online learning platform, unwillingness to work with teachers to use the online learning platform effectively, lack of experience in properly preparing their children to participate in active online instruction, and multiple children attending different classes at the same time. These challenges place a great burden on parents who must support their children in the younger grades.
Environmental Literacy and Teaching Activities of Preschool Teachers in Vietnam
Authors: Tran Ho Uyen , LePage Ben A. , Fang Wei-Ta
Published: October 2022

In this study we modeled the environmental literacy of Vietnamese preschool teachers. 324 in-service preschool teachers from Ha Noi, Da Nang, and Ho Chi Minh, Vietnam contributed to the study via an online survey. Structural Equation Modeling (SEM) was used to test the hypotheses of the relationships between environmental knowledge (KN), environmental awareness (AS), decision attitude (DA), personal behavior (PB) and environmental teaching activities (ACT) of these teachers. The results showed that the level of environmental literacy of preschool teachers in Vietnam was moderate with mean score for AS, DA, PB, and ACT ranged from 3.18 to 4.32 on a 5-point Likert-type scale. The results also indicate that the preschool teacher’s KN had a positive impact on AS and DA; PB was influenced by AS, but not by KN or DA. In addition, a correlation analysis showed AS and PB had a positive impact on ACT, while DA had a negative influence on ACT. These findings imply that preschool teachers with certain desirable environmental literacy had more tendencies to implement ACT. Based on the findings, recommendations and implications are provided for policy makers, preschool teachers, and researchers in Vietnam and other countries.
Early Literacy Assessment among Kindergarten Teachers in Indonesia: A Phenomenological Study
Authors: Christianti Martha , Retnowati Trie Hartiti , Wening Sri , Hasan Aminuddin , Ratnawati Heri
Published: October 2022

The study aims to identify how kindergarten teachers perform early literacy assessments in the classroom and the challenges these teachers have in performing such assessments. During the study, the data were gathered through an in-depth interview in the form of a forum group discussion (FGD). Then, the phenomenological data were attained from 30 public and private Kindergarten teachers. The researchers could illustrate how these kindergarten teachers assessed their children's early literacy through these data. Furthermore, the study results show that the teachers' literacy knowledge has been sufficient and that the literacy programs for the children have been variously designed in each school. The teachers' techniques in performing the early literacy assessment are observation and documentation (portfolio), and the measurement of literacy skills itself refers to the scope of literacy. Concerning the findings, numerous obstacles and expectations that kindergarten teachers have are also discussed within the study.
Group inverses of matrices of directed trees
Authors: Nandi R. , Sivakumar K. C.
Published: October 2022

A new class of directed trees is introduced. A formula for the group inverse of the matrices associated with any tree belonging to this class is obtained. This answers affirmatively, a conjecture of Catral et al., for this new class.
‘Already doing the work’: social work, abolition and building the future from the present
Authors: Hunter Dom , Wroe Lauren Elizabeth
Published: October 2022

Social work internationally is currently subject to debate. Some call for the abolition of social work, detailing legacies of harm, inadequate practices and theoretical limitations. Central to abolitionist thought is the tradition of community work to build alternative futures in the present, an area currently receiving less attention. This article adopts an auto-ethnographic method, drawing on the authors’ experiences of social work in the UK – in childhood and as a professional career, respectively – to consider the limitations of social work responses to childhood harm, alongside existing community harm-reduction practices. Four themes are identified that capture the limitations of social work intervention, as well as acts of community care and resistance. These are: the extent of engagement with context and community knowledge; resources for caring; legacies of harm; and the role of social work in relation to community harm-reduction work. Implications for research methods and social work practice are discussed.
Sustainable consumption and the power of economic growth: exploring alternatives to the growth-dependency narrative
Authors: Gumbert Tobias , Mamut Pia , Fuchs Doris , Welck Tobias
Published: October 2022

Increasing shares of the sustainable consumption literature postulate the need for a focus on limits to consumption as a basis for achieving absolute reductions in resource use. After all, improvements in the sustainability of consumption expected from technological innovation and efficiency gains have been eaten up by rebound effects, to date. The decoupling that proponents of green growth were hoping for is nowhere in sight. However, discussions about limits to consumption immediately meet opposition from political representatives, powerful associations and industry lobby groups alike. Specifically, opponents claim that we simply cannot afford a scaling back of consumption and the economic growth it is supposed to drive due to the growth-dependent nature of our welfare systems. Such claims have become very dominant narratives that influence what societies deem ‘realistic’ and ‘possible’ regarding the politics of sustainable consumption, cementing the current status quo. It also shows that research on strong sustainable consumption governance, that is, governance pursuing a reduction in consumption levels and fundamental shift in consumption patterns (especially in the Global North), needs to target such claims head on, if existing paradigmatic barriers to a sustainability transition are to be overcome. But what counter-narrative(s) can scholars offer? To identify potential elements of such counter-narrative(s) for consumption scholars to draw on, the present article investigates what answers critical sustainability research, in particular the degrowth literature, has in stock regarding the affordability of reductions in consumption-driven growth from the perspective of democratic welfare states.
Impacts of Covid-19 Pandemic and Adaptive Strategies to Build Resilience in the Kenyan Aquaculture Sector
Authors: Munguti Jonathan , Iteba Jacob , Outa Nicholas , Kirimi James , Mungai Daniel , Kyule Domitila , Obiero Kevin , Ogello Erick
Published: October 2022

This study examines the impacts of the Covid-19 pandemic and adaptive strategies to build resilience among stakeholders and actors in the aquaculture value chain in Kenya. Prior to the pandemic, Kenya's aquaculture sector had progressed from a minor player to a key component of the country's fish food system. Fish and fishery products have become the most heavily traded food commodity in the Kenyan markets. The results indicate the pandemic had significant impacts on the access to aquaculture inputs, fish trade, and socio-economic livelihoods of the aquaculture value chain stakeholders and actors during the two whole years. Thus, initial and longer-term adaptive measures, in particular by private sector players and government agencies, can contribute to building resilience to multiple shocks and stressors among stakeholders and actors in the aquaculture sector. Some measures include a government incentive package to overcome the damage to the fisheries and aquaculture sector, improve farming operations and win the market trust and adopt new methods such as intelligent sensors, camera systems and automated or remotely controlled monitoring/feeding strategies to reduce labour intensity. Such measures and policies can cushion the sector against future shocks occasioned by such pandemics.
Data Analytics and Techniques
Authors: Abdul-Jabbar Safa S. , K. Farhan Alaa
Published: October 2022

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide improvements for many applications. In addition, critical challenges and research issues were provided based on published paper limitations to help researchers distinguish between various analytics techniques to develop highly consistent, logical, and information-rich analyses based on valuable features. Furthermore, the findings of this paper may be used to identify the best methods in each sector used in these publications, assist future researchers in their studies for more systematic and comprehensive analysis and identify areas for developing a unique or hybrid technique for data analysis.
Effect of nitrogen fertilizers on agronomic, essential and enzymatic properties of marigold (Calendula officinalis L.) under normal and drought conditions
Authors: Afsaneh Pirmani , Touraj Mir Mahmoudi , Saman Yazdan seta , Soran Sharafi
Published: October 2022

To investigate the effect of mineral and organic nitrogen fertilizers on some of the quantitative and qualitative reactions of marigold under normal and drought stress, a study was conducted in a split-plot factorial and based on a completely randomized block design with three replications. The first factor included irrigation (normal and water deficit) in the main plot and sub-factor included foliar application of nitrogen fertilizer (control, nitrogen (N), nano-chelate nitrogen (NC) and nitrogen fertilizer+ nano-nitrogen fertilizer (N+NC)) and biofertilizer (control, Azotobacter and Azospirillum) as factorial was placed in sub-plots. Although water deficit stress reduced plant height, flower dry weight, number of seeds per head, 1000-grain weight, biological yield, grain yield and essential oil yield, N + NC foliar application could moderate the adverse effect of water stress on the grain yield, biological yield and essential oil yield. In addition, inoculation of seeds with Azospirillum under water stress conditions could increase the number of seeds per head, 1000-grain weight and essential oil yield compared to the control treatment. NC foliar application and Azotobacter inoculation showed a synergistic effect on the content of proline enzymes and antioxidant activity. Also, simultaneous application of nitrogen + nano-chelate nitrogen foliar application along with seed inoculation with Azospirillum could have a positive effect on increasing flower dry weight, the number of seeds per head, 1000-seed weight, biological yield, grain yield, essential oil yield and proline content.
A History of Corporate Social Responsibility in Ghana
Authors: AMO-MENSAH MAVIS
Published: October 2022

There have been several contributions and research perspectives on Corporate Social Responsibility (CSR), however, research suggests that there is paucity of literature on historical accounts on the concept.  There is also considerable evidence that the few CSR histories that have been documented have mostly focused on US-based literature. This paper attempts to detail the history of CSR in the Ghanaian context. The paper is a culmination of archival data and academic reviews on the history of CSR as well as interviews conducted with purposely selected informants. An analysis of the historical data revealed three key phases of CSR development in Ghana: the Pre-CSR phase, the Early CSR beginnings phase and the CSR Professionalisation phase. Significantly, this paper contributes to the prevailing CSR management literature, especially on national CSR histories. A thorough review of the literature suggests that there is no documented history on CSR in Ghana. This paper therefore addresses this gap. It contributes to a more distinctive historical understanding of how CSR has evolved from its early days to its current state in Ghana. It further provides useful background context to inform future research, analysis and interpretation.
A Preliminary Brief Report on the Therapeutic Orientation Questionnaire (TOQ): What Does a Discrepancy Between a Student’s Preferences for Theoretical Orientation Mean?
Authors: Nakao Gen
Published: October 2022

Therapists each hold a therapeutic orientation, and therapists are sometimes also patients. Anecdotal evidence suggests that therapists may have discrepant theoretical orientations qua therapist versus qua patient. In this current preliminary study, the author developed the Therapeutic Orientation Questionnaire (TOQ) to investigate the phenomenon of this discrepancy. Based on the qualitative analysis, several themes related to self-referential statement emerged. Future directions and practical implications were also discussed.
Qualidade fisiológica e tolerância de sementes de Genipa americana L. à secagem
Authors: Nascimento Cardoso Milena , Ribeiro Soares Adrielle Naiana , Albuquerque Resende Oliveira Leila , Andrade Nascimento Lucas Henrique , Silva Ledo Ana , Silva Ana Veruska Cruz
Published: October 2022

O jenipapeiro (Genipa americana L.) é uma árvore frutífera neotropical que se estende do norte da América do Sul à Argentina. É utilizado na arborização urbana e possui características que auxiliam na restauração de áreas degradadas, enquanto seus frutos são economicamente importantes na fabricação de doces, geleias, vinhos e destilados. A propagação da espécie ocorre por sementes, mas com germinação lenta e desigual. Portanto, compreender os processos de germinação em uma espécie sensível à dessecação é um fator importante na resolução de problemas de armazenamento das sementes. O objetivo do presente estudo foi avaliar a influência da secagem das sementes na emergência e crescimento inicial do jenipapeiro. As sementes foram provenientes do município de Umbaúba, Sergipe, Brasil, e após a limpeza, foram submetidas a diferentes períodos de secagem (0; 24; 48; 72; 96 e 120 horas) à temperatura de 28 ºC ± 2 ºC. A semeadura foi realizada em sacos de polietileno contendo solo + fibra de coco, na proporção 2:1 (v/v). As variáveis analisadas foram: teor de água, porcentagem de emergência, índice de velocidade de emergência, comprimento de plântulas, número de folhas, tamanho de folhas e massa fresca e seca de plântulas. As sementes são classificadas como intermediárias, e perdem sua viabilidade à Medida que o teor de água é reduzido. Houve redução da qualidade fisiológica e crescimento de plântulas das sementes a partir de 48 horas de secagem.
Açaí pulp dehydration by foam-mat drying to produces açaí powder
Authors: Colaço Rafaella , Araújo Éder , Souza Jesus , Almeida Rômulo , Botelho Vanessa , Correa Nádia
Published: October 2022

The foam-mat drying was used as a dehydration method for açaí pulp. The types of foaming agents, the influence of concentration and whipping time were evaluated for foam formation. After choosing the agent/additive a 2² Factorial Experimental Design, with three central points were realized to evaluated the influence of the drying process conditions. The optimized condition was verified by the desirability function and it was compared to the açaí pulp and açaí foam both freeze-dried. Emustab was identify as an appropriate foaming agent for açaí foam. The drying temperature showed significative effects on total anthocyanins and moisture, while the Concentration and the interaction Concentration and Temperature were significants for lightness. The açaí dehydrated by foam-mat was equal to the freeze-dried açaí pulp in terms of moisture and water activity results, as freeze-dried açaí foam showed divergent results for these parameters. All dehydrated products differed in terms of color parameters.
Avaliação da qualidade de produtos magistrais e fitoterápicos à base de Ginkgo biloba, Passiflora incarnata e Matricaria recutita comercializados no mercado brasileiro e argentino
Authors: Aparecido-Gouveia Edson Junio , Mano-Sousa Brayan Jonas , Chequer Farah Maria Drumond , Duarte-Almeida Joaquim Maurício
Published: October 2022

Os produtos naturais, além de refletir nossa cultura e tradição, representam uma grande participação no mercado de medicamentos. Dentre as plantas mais usadas, estão Ginkgo biloba, Matricaria recutita e Passiflora incarnata. O objetivo desse estudo foi avaliar a qualidade das cápsulas e comprimidos contendo estas plantas, produzidas por farmácias magistrais ou por empresas de fitoterápicos do Brasil e da Argentina, avaliando conforme os parâmetros farmacopeicos e/ou normas vigentes brasileiras. As informações descritas nas embalagens, o peso médio e desvio padrão relativo das cápsulas e comprimidos, análises microscópicas e macroscópicas do seu conteúdo, bem como o perfil fitoquímico por Cromatografia em Camada Delgada e os teores de compostos fenólicos e de flavonoides totais foram avaliados. Nesse estudo foram analisados seis produtos fitoterápicos contendo G. biloba (5 brasileiros e 1 argentino), três à base de M. recutita (todos brasileiros) e cinco contendo P. incarnata (4 brasileiros e 1 argentino).   Observou-se que 100% dos produtos não continham o nome do prescritor, em 21,42% faltavam a posologia e 21,46% estavam fora do limite de variação aceitável de peso médio e desvio padrão relativo. Quanto à qualidade, 28,57% deles podem ter sido fraudados por sofisticação e 7,14% das amostras não foram detectados os compostos bioativos. Os resultados mostraram uma negligência ainda existente em relação aos produtos fitoterápicos. Esse estudo mostra uma falha na garantia da qualidade nas matérias-primas e no desenvolvimento do produto fitoterápico. Essa deficiência pode aumentar a taxa de adulteração nesses produtos, comprometendo a eficácia e segurança dos produtos naturais.
New records of Sarcophaga Meigen (Diptera: Sarcophagidae: Sarcophaginae) for the Northeast region of Brazil
Authors: Ramos Ramon Lima , Trindade-Santos Matheus Eduardo , Pamponet Fernanda Maria , Lopes Daniele Santos , De Mello-Patiu Cátia Antunes , De Oliveira Favízia Freitas
Published: October 2022

With the aim of reducing the gap in the knowledge on the Sarcophagidae fauna that occurring in the Northeast region of Brazil, the present work reports the unheard occurrence of two species of the genus Sarcophaga Meigen, 1826 in Bahia. The specimens were sampled in the urban area of the Salvador municipality (Bahia State, Brazil), through two collecting methods: traps using human feces as baits [adapted from the model proposed by Ferreira (1978)], and active sweep with entomological net. The present study brings the first record of Sarcophaga (Bercaea) africa for the Brazilian Northeast region and the first record of Sarcophaga (Liopygia) ruficornis for Bahia State.