Reviewerly/exHarmony huggingface dataset:
A Comparative Study of Metaheuristic Optimization Algorithms for Solving Engineering Design Problems

Metaheuristic optimization algorithms (Nature-Inspired Optimization Algorithms) are a class of algorithms that mimic the behavior of natural systems such as evolution process, swarm intelligence, human activity and physical phenomena to find the optimal solution. Since the introduction of meta-heuristic optimization algorithms, they have shown their profound impact in solving the high-scale and non-differentiable engineering problems. This paper presents a comparative study of the most widely used nature-inspired optimization algorithms for solving engineering classical design problems, which are considered challenging. The teen metaheuristic algorithms employed in this study are, namely, Artificial Bee Colony (ABC), Ant Colony Optimization (ACO), Biogeography Based Optimization Algorithm (BBO), Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES), Cuckoo Search algorithm (CS), Differential Evolution (DE), Genetic Algorithm (GA), Grey Wolf Optimizer (GWO), Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO). The efficiency of these algorithms is evaluated on teen popular engineering classical design problems using the solution quality and convergence analysis, which verify the applicability of these algorithms to engineering classical constrained design problems. The experimental results demonstrated that all the algorithms provide a competitive solution.
No-Reference Point Cloud Quality Assessment via Contextual Point-Wise Deep Learning Network

For the processing of point clouds, an accurate assessment of the quality is essential. However, point cloud quality assessment has proven to be a difficult issue, especially when the pristine point clouds are unavailable. Most existing no-reference point cloud quality assessment methods adopt projection-based routes, which inevitably suffer from occlusion and misalignment, resulting in loss of information. Alternatively, this paper proposes a novel no-reference point cloud quality assessment method via a contextual point-wise deep learning network (CPW-Net). Compared with projection-based methods, it reduces information loss by learning features directly from point coordinates and attributes. In particular, CPW-Net utilizes an Offset Attention Feature Encoder (OAFE) module to extract local and contextual features. Experiment results demonstrate that the proposed method overwhelms most publicly available no-reference metrics on SJTU dataset and gains compatible performance in comparison with most full-reference methods.
DANAA: Towards Transferable Attacks with Double Adversarial Neuron Attribution

While deep neural networks have excellent results in many fields, they are susceptible to interference from attacking samples resulting in erroneous judgments. Feature-level attacks are one of the effective attack types, which target the learned features in the hidden layers to improve their transferability across different models. Yet it is observed that the transferability has been largely impacted by the neuron importance estimation results. In this paper, a double adversarial neuron attribution attack method, termed ‘DANAA’, is proposed to obtain more accurate feature importance estimation. In our method, the model outputs are attributed to the middle layer based on an adversarial non-linear path. The goal is to measure the weight of individual neurons and retain the features that are more important toward transferability. We have conducted extensive experiments on the benchmark datasets to demonstrate the state-of-the-art performance of our method. Our code is available at: https://github.com/Davidjinzb/DANAA .
3D Path Planning and Tracking of Quadrotors Based on Improved Whale Optimization Algorithm

Aiming at the shortcomings of standard whale optimization algorithm (WOA) in three-dimensional (3D) path planning of quadrotors, such as long path length, high time-consumption and path roughness, an improved whale optimization algorithm called SAMWOA is proposed in this paper. Firstly, Singer chaotic mapping strategy is introduced to enrich the diversity of whale population and improve the quality of initial solution of the algorithm. Secondly, an adaptive cognitive factor is proposed to improve the position updating method of the whale leader and balance the exploration and development ability. Then, the wavelet mutation mechanism is used to disturb the current optimal solution position of the whale population, so that the algorithm can jump out of the local optimum. Moreover, the cubic spline interpolation method is utilized to smooth the path planned by the proposed SAMWOA. Finally, the proposed SAMWOA is applied to the 3D path planning and tracking of the quadrotor. The simulation results show that, compared with the WOA, the path length, steering cost and time-consuming planned by the proposed SAMWOA is reduced by 25.78%, 37.5% and 42.21%, respectively. The proposed SAMWOA not only solves the issues of the WOA, but also can plan and track the 3D path and avoid obstacles in real time, which is advanced and robust.
Banking sector's financial performance: Bibliometric data analysis and its visualization

One important factor in determining economic expansion is the efficiency of the banking sector. Banks borrow funds from investors who promote general growth in the economy and invest it as deposits. Directly channelling funds and taking part in economic activity is a recent phenomenon in the banking sector. As a result, scholars and researchers are becoming increasingly concerned about bank profitability and how it affects economic growth. To better understand various research communities who published this particular academic research, this article will look at them. This study used the VOSviewer application to conduct bank financial performance and science mapping analysis by extracting the data from the Scopus online database. We examined and visualized bibliometric data from 1057 banking publications published over 38 years (1971-2021). We present the top journals, authors, coauthors by country, keyword occurrence, cocitation analysis, and annual trend of published financial performance publications in banking. The results of this study may help bank managers and shareholders better understand the performance of their institutions. In the meantime, academic scholars and students can discover conclusions and recommendations to study the banking sector.
Differentiated Instruction as Strategy in Improving Reading Comprehension

Reading and understanding what was read are integral parts in the life of every individual and are indispensable in the circle of educational system. However, this vital skill is what most students lack interest of. As a result, it affects their understanding in the other areas of their education endeavor. To address the problem, Robert Glaser proposed a strategy, the so called Individually Prescribed Instruction [IPI], which later on was known as Differentiated Instruction. It showcases a variety of classroom practices that accommodate differences in students’ learning styles, interests, prior knowledge, socialization needs, and comfort zones. This study, therefore, aims to determine the effectiveness of differentiated instruction strategy in improving reading comprehension among students in Sta. Rosa National High School Junior High School. The study utilized a quasi-experimental method which the 50 Grade 7 English research subjects of the study were divided into two groups, namely control and experimental. Strategies employed in these groups were different. The traditional method was practiced in the control group, while the differentiated instruction strategy was implemented in the experimental group. For data gathering, a Phil-IRI adapted test questionnaire was used as the main instrument. Another test questionnaire from Phil-IRI was used as a springboard in the implementation of strategies for both groups. Statistical treatments used for data analysis were frequency count, percentages, t-Test for Correlational Samples for Means, and t-Test for Two Independent Samples. Findings revealed that in measuring subjects’ reading comprehension skills, there was a significant difference between the posttest performances of the groups. The research subjects under experimental group performed higher than the control group. Based on the findings, the study concludes that Differentiated Instruction is an effective strategy in improving reading comprehension skills.
POLICY ENVIRONMENT AND GROWTH OF (WO)-MEN OWNED MSEs IN KENYA

There is a growing discourse about a powerful untapped economic force in Kenya, the (wo)-men. The debate has triggered political pronouncements and the formulation of female-specific empowerment policies through entrepreneurship, which was the basis of this study. The study analyzed the influence of resource support on their MSEs’ growth. The study design was a Cross-sectional Survey, anchored on Resource-based Theory. It based on a Positivist Paradigm and applied a Quantitative Multi-method approach. Using multi-stage sampling, 375 adult female entrepreneurs participated in the study. Data was analyzed through inferential methods; correlation coefficient and coefficient of determination. The results revealed there being strong relationship. For example, first step results showed significant indirect relationship of entrepreneur’s traits on growth through resource support, b= .0199, BCa CI (.0110, .0304) and R2 (R-sq med .1391). Also, considering the Preacher and Kelley Kappa-squared, k2=.1755, 95% BCa CI (.1130, .2341), there is a significant indirect relationship between entrepreneur’s traits and performance through resource support, meaning that there are other mediators other than entrepreneurs’ profile. This was further supported by the normal theory tests for indirect effect where b=.0199, z=4.4065 and p=&lt;.001.&#x0D; Keywords: Venture Growth, Resource Support Programs, (Wo)Men-Owned Mse Growth, Cross-Sectional Survey.
PENINGKATAN SKILL MENULIS ABSTRAK BAHASA INGGRIS MELALUI PEMBELAJARAN REVIEW BUKU BAGI SANTRI FLASHROOM

Writing requires language structure, graphology, and vocabulary skills. Improving students' writing skills requires a creative approach and continuous practice. One type of writing skill that students need to master is abstract writing. Writing abstracts through book reviews is a fun alternative learning approach for students. This approach is very helpful for the students of Pesantren Ngalah about how to write abstracts easily. This research uses classroom action research method. With this method, it is possible to know in detail the problems in the classroom, and how to solve them. This study aims to provide recommendations to teachers as learning evaluation materials. Thus, it is hoped that the quality of learning will be better. Based on the results of the study that students were able to write abstracts properly and correctly with the percentage level of the high category interval 60%, the medium category 26.67%, and the low category 13.33%.&#x0D; &#x0D;
Detecting demands of public library users: The growth points and perception stereotypes

The authors investigate into inconsistency between the purpose of the library as a social institution and stereotypical perception of libraries by involved and uninvolved audiences. The libraries modernizing and transforming themselves into digital ecosystems along with accomplishing their traditional mission of information archive, are becoming the centers of cultural life, interactive spaces offering users wide variety of information services and resources, and multimedia areas for co-working, communication, and learning. At the same time, the fixed stereotypical perception of the library as a book depository becomes a barrier to the expansion of the user audience. The purpose of the study is to diagnose the demands of actual and potential users of libraries and to assess the change in purpose and role of libraries as a social institution under conditions of expanding access to information services. The methodology of the study was determined by the works documenting the relevance of the search for fundamentally new approaches in the interaction of the libraries with their target audiences in the context of media communications to increase the attractiveness of libraries. Sociological methods were used to identify stereotypical ideas about libraries: the survey of two groups of respondents, i. e. engaged and unengaged users (adults and students). Methods of statistical analysis of empirical information were used for data analysis. The main findings are: the study captures the needs in positioning library services within the wider communicative space. The access is needed to special market segments with building multi-subject user chains and new ways of informing young actual and potential users about the array of services. The relatively inefficient building of awareness of new services may indicate the prevalence of traditional positioning in the nearest target market and, so far, rather low penetration into other segments. The novelty of the study is expanding knowledge of the library potential target audience, which would make the foundation for developing communication tools and attracting primarily the young audience. The flexibility of communication methods, formats, and channels is essential for interaction with the young users.
DEVELOPMENT OF E-LEARNING-BASED EDUCATION IN THE PAI STUDY PROGRAM, TARBIYAH DEPARTMENT, STAI AL-QODIRI JEMBER

This study aims to produce an e-learning product in PAI Study Program, Tarbiyah Department, STAI Al-Qodiri Jember. The research method used in this research is using the R&amp;D method. The R&amp;D model in this study uses the Alessi &amp; Trollip model. In the model, there are three phases of the development procedure, namely planning, design and development. The results showed that educational psychology E-learning was developed using Moodle LMS. The development stage includes making modules, presentation materials and quizzes, hosting, installing Moodle, determining the chosen theme, compiling, uploading and managing e-learning materials or content into Moodle and product revisions (results from alpha test, beta test).&#x0D; &#x0D;
3D path planning problem for fighter aircraft with multiple constraints

Abstract Path planning is a crucial component for ensuring the safety and efficiency of flight missions, especially for fighter aircraft. To enhance the combat effectiveness of fighter aircraft, it is important to consider how to avoid danger sources an terrain obstacles, reduce fuel consumption, and utilize the aircraft's own performance to accomplish the mission objectives. In the modern battlefield environment, the shortest path is not the only criterion for planning, but also other factors such as the threat level to the aircraft, fuel consumption, mission completion time, and minimum turning radius. In this paper, the authors propose a multi‐constraint path planning method for fighter aircraft that incorporates these factors into an improved particle swarm algorithm. The authors transform the constraints of three‐dimensional terrain, threat source, fuel consumption, and mission time into an aggregated fitness function. The authors construct a limit curvature matrix to evaluate the feasibility of the generated path. The authors also introduce an adaptive adjustment strategy based on the activation function for the parameters in the particle swarm algorithm. The weights of each constraint are determined according to the actual demand. The experiment results show that the authors’ method can efficiently plan the optimal path that satisfies the requirements. Compared with other improved particle swarm algorithms, the authors’ method has higher optimal search efficiency and better convergence effect. The authors also provide optimal values for important parameters such as mission energy consumption, mission time, flight speed and others to support the overall mission planning. The authors’ method has a certain practical application value.
The effectiveness of a proposed training program in developing digital learning skills among practical education students at Al-Balqa applied university in Jordan

This study aimed to investigate the effectiveness of a proposed training program based on associative communication theory in developing digital learning skills among practical education students at Al-Balqa Applied University in Jordan. It utilized a descriptive and experimental approach with a semiexperimental design on a sample consisting of 100 practical education students at Al-Huson College at Al-Balqa University. They were randomly divided into a control group consisting of 50 students and an experimental group consisting of 50 students. The researchers prepared a proposed training program to develop the digital learning skills of the experimental group, which consisted of 12 training sessions. The digital learning skills test was applied, which consists of 28 questions distributed evenly on four main axes of digital learning, namely, basic skills for digital learning, managing digital learning, using digital learning applications, and applying digital learning in the educational process. The results showed that there were statistically significant differences between the mean scores of the experimental group (18.60) and the control group (10.81) in the post application of the digital learning skills test. The findings were in favor of the experimental group that was trained in the program, which confirms the effectiveness of the training program. Finally, the study recommended the development of training programs to provide practical education students with digital learning skills and to enhance their ability to use and employ modern learning technologies.
Perbedaan Individual dan Konsekuensinya Bagi Pembelajaran Bahasa Indonesia

Every learner has a different way of adapting and understanding instructions, especially in language learning. Cognitive abilities possessed by each individual are intelligence, language learning talent, or memory capacity or speed. In addition, affective abilities such as fear, motivation, and emotions of an individual. Research on individual differences can be seen from the interaction or relationship of the two aspects in humans and also to the context of learning, individual understanding naturally of an instruction can be identified properly. Every learner has a different way of adapting and understanding instructions, especially in language learning. First, individual differences consist of two factors, namely personal factors and general factors. Personal factors include (1) group dynamics, (2) attitudes towards teachers and teaching materials, and (3) individual learning techniques, while general factors include (1) age, (2) intelligence and dexterity, (4) cognitive-style, (5) attitude and (6) motivation, and (7) personality. Second, the consequences of individual differences for learning Indonesian in this discussion relate to the way educators teach. Third, related to learning components (learning resources, teaching materials, learning strategies, and assessments).&#x0D; &#x0D; &#x0D;
A Prompt Tuning Method for Chinese Medical Text Classification

The field of clinical medicine involves complex data analysis and mining, and text classification task in natural language processing can assist in case screening, etiology analysis, disease prediction, and other aspects in the medical field, thereby improving research efficiency and accuracy. However, obtaining supervised data is difficult due to the fact that medical texts such as cases often contain sensitive patient information. This difficulty partially explains why existing text classification methods do not perform well in medical tasks. Although the prompt tuning performs better than traditional neural networks and fine tuning methods in few-shot learning and interpretability. Chinese requires at least two characters to express complex semantics, which makes it challenging to apply the prompt tuning method that is primarily designed for English in Chinese text classification tasks. To address this issue, we propose Knowledge Enhanced Multi-Token Prompt Tuning (KMPT). KMPT first uses multiple tokens as label words to have complete Chinese semantics, and then uses external knowledge to expand the label words set, improving coverage and reducing bias. The experimental results on the Chinese medical dataset CHIP-CTC show that KMPT outperforms baseline methods in Chinese medical text classification tasks and has better interpretability and convergence speed than fine tuning.
Robust dense‐field based copy‐move forgery localization using generic radial harmonic Fourier moment invariants

As the importance of reliable multimedia content increases in today's society, image forensics is a growing field of research. The act of copying and pasting specific parts of an image, known as copy-move forgery, may be utilized for illegal or unethical purposes. Just as with other vision-related technologies, the accuracy of forensic analysis depends on having an appropriate image representation. Most existing feature extraction techniques do not accurately reflect the underlying image content leading to reduced performance. In this article, to detect the copy-move forgery attack, the Generic Radial Harmonic Fourier Moment (GRHFM) is proposed for reliable and distinctive image representation. The algorithm has the ability to effectively manipulate the distribution of zeros to emphasize certain image regions. Additionally, the relationships between complex exponentials and trigonometric functions are exploited to efficiently compute and easily implement the transform kernels. The efficacy of the algorithm is illustrated through experiments on dense-domain-based matching patterns. Experimental results on five benchmarking databases prove the effectiveness of the proposed approach compared with the state-of-the-art methods. According to the average scores, the proposed method demonstrates superior accuracy in overall localization performance. The F1 score, precision, and recall percentage values obtained are 92.5, 95.44, and 91.96, respectively. Robustness experiments on more challenging attacks are also conducted on FAU dataset. Results show that the proposed framework satisfies invariance to the various image variations, and thus an enhanced robustness compared to the previous methods. Moreover, the advantage of reasonable computational cost implies its potential use in real-world forensic applications.
The social, economic and environmental impacts of a 4-day workweek in an organization.

Purpose: This research project examines the socio, environmental, and economic impact of a 4 Day work week on an organization’s outcomes. Methodology: Interviews were conducted with both the managers and employees of the organization to gather primary data. Implications: The recommendations are proposed to solve the issues observed with implementing the new 4- day workweek system. Findings: We found that the social impact was positive, but the economic impact of the change was negative. The lack of consensus in employees’ views showed that productivity is a subjective topic in the organization. Moreover, the environmental impact was found to be unclear and difficult to measure. Originality: This research applies the three pillars of sustainability to ascertain the impact of move to shorter workweek by an organization based in the Emirate of Sharjah, UAE. To our knowledge this is the first study in the region that has examined this issue to ascertain the effectiveness of this approach.