Reviewerly/exHarmony huggingface dataset:
Personality Prediction from Handwriting using Fine-tuned Transfer Learning Models

Experts in computational linguistics have done a number of research to identify and categorize personality characteristics at various aspects, including terms, sentences, paragraphs, and recommendations. In this research work five stages model was proposed and the experimental result was evaluated on handwriting images.This paper presents a comparative analysis of fine-tuning transfer learning convolutional neural network models such as VGG16, ResNet50 and GoogleNet for personality detection. The results of fine-tuned models are assessed using the accuracy, precision, recall and f1_score measure. From the results it was observed that ResNet50 have achieved best accuracy as compared to GoogleNet and VGG16
The impact of economic education on economic literacy: A prospective study of a sample of respondents

Conventional finance uses models that assume that all participants are rational, that is, they process appropriate information in an efficient and unbiased manner, as their decisions are consistent with maximizing benefit. Conventional economic theories assume that investors make rational decisions, based on the idea that people act rationally and pay attention to all the information available in the decision-making process. In principle, economic literacy is a tool to achieve these goals, as it facilitates rational decision-making and provides more accurate economic decisions that lead to increased economic efficiency and the well-being of both individuals and society. Accordingly, the study aimed to reveal the existence of a statistically significant relationship between economic education and economic literacy, which could lead to an increase in economic efficiency. To reach this goal, a questionnaire was conducted on 100 people in Karbala governorate. And by using the experimental approach and with the help of many financial and statistical methods and through the use of the SPSS18.00 program, the study reached several conclusions and recommendations, the most important of which are: The absence of a positive relationship with statistical significance between economic education and the level of economic literacy, whether at the micro or total level, and the study recommends the need to raise awareness about basic and advanced economic concepts among respondents in our dear country, Iraq in general, and Karbala governorate in particular, and the need to raise their awareness about the necessity of being familiar with those concepts that leave Positive effects on their overall economic activity.
AN ASSESSMENT ON COHERENCE AND GRAMMATICAL STRUCTURE OF STUDENTS’ WRITING SKILLS

This study is aiming at assessing students’ competency in writing skill at First Semester Public Health Students of Diponegoro University. The target population were 25 Public Health students taking English class. A writing test was conducted to asses the students coherence, grammar, and sentence structure. This descriptive qualitative study is to discover (1) students’ awareness of applying transition signals devices to connect ideas (conjunction words, substitution, reference and ellipsis to create coherence. (2) students’ awareness in grammar and sentence structure. The result revealed that students found no problems using connective devices in their sentences. However, concerning grammar and sentence structure students faced difficulties in 1) Subject - Verb Agreement in which students often ignored plural forms, missed verbs, missed subjects in a sentence or they sometimes put two verbs in one sentence. 2) They were also still confused dealing with pronoun references. 3) Students also tend to write too long sentences without any punctuations.
ANALISIS KESIAPAN SISWA FILIAL DAMBUNG RAYA DALAM MENGIKUTI ANALISIS NASIONAL BERBASIS KOMPUTER DI SMAN 1 BINTANG ARA KABUPATEN TABALONG

The problem behind this research is the emergence of various perceptions regarding the readiness of filial students to receive education in the middle of the forest without electricity and internet connection in attending ANBK at SMAN 1 Bintang Ara, Tabalong Regency. The results showed that the readiness of Dambung Raya filial students in participating in the computer based national analysis at SMAN 1 Bintang Ara, Tabalong Regency belonged to the category of quite ready. This is supported by: the mental and physical readiness of the Dambung Raya filial students to take the computer based national exam at SMAN 1 Bintang Ara, Tabalong Regency, the unskilled students in operating computers, and the students mastery of the subject matter included in the ANBK, especially materials that have been completed discussed at school.
Game-Theoretic Strategies for Quantum-Conventional Network Infrastructures

Fundamentally and practically, quantum networks and conventional networks are inextricably tied, since the basic quantum protocols such as teleportation require both networks and the conventional network fiber is also used for the quantum network. A Recursive System of Systems (RSOS) model is developed for quantum-conventional (QC) networks by modeling the correlations at various levels based on the failure and attack modes of quantum, conventional and hybrid components and the propagative effects across QC boundaries. A game-theoretic formulation is developed to capture the cost-benefit trade-offs of the provider in defending against component attacks, using sum-form utility functions. By applying the Nash Equilibrium results, the conditions and sensitivity functions of the survival probabilities of a QC network at different levels are derived using the strong dependencies between quantum and conventional infrastructures. The results provide insights into the dependencies between conventional and quantum networks, including cross QC boundary effects in terms of disruption impact of conventional networks on quantum networks, and vice versa.
DSP-Net: Diverse Structure Prior Network for Image Inpainting

The latest deep learning-based approaches have advanced diverse image inpainting task. However, existing methods limit to be aware of the structure information well, which constricts the performance of diverse generations. The intuitive representation of diversity generation is the structure change since the structure is the basis of the image. In this paper, we make full use of the structure information and propose the diverse structure prior network (DSP-Net). Specifically, there are two stages in DSP-Net to generate the diverse structure first and refine the texture next. For the diverse structure generation, we prompt the structural distribution to be similar to the Gaussian distribution to sample the diverse structural prior. With these priors, we refine the texture with a proposed propagation attention module. Meanwhile, we propose a structure diversity loss to enhance the ability of diverse structure generation further. Experiments on benchmark datasets including CelebA-HQ and Places2 indicate that DSP-Net is effective for diverse and visually realistic image restoration.
Functional-Penetrated Interactive System Towards Virtual-Real Fusion Environments

Current mixed reality technology cannot completely map the information in the physical world to the virtual environment, and the user must take off the head-mounted display to deal with the affairs in the real environment when using the mixed reality system. This greatly reduces the immersion created by the virtual reality system, and also reduces work efficiency. In order to realize the user's direct interaction with the physical world in the virtual environment without destroying the immersion of the virtual reality system, this paper proposes a functional-penetrated interactive system towards the virtual-real fusion environment, which extracts the visual information of objects from the real scene captured by the RGB camera through deep neural networks, completes virtual-real registration and presents it in real time in the virtual environment, and finally enables the user to complete the manipulation of the physical objects in the virtual environment. In addition, the system also allows the user to dynamically adjust the virtual-real fusion ratio according to the user's needs, which achieves a balance between the immersion of the virtual-real fusion environment and the interaction efficiency of the system. Experimental results show that the system can provide users with more realistic physical feedback, with higher interaction freedom and universality.
Path Planning of Unmanned Underwater Vehicles Based on Deep Reinforcement Learning Algorithm

This paper implemented path planning for unmanned underwater vehicle (UUV) using deep reinforcement learning (DRL)algorithms with the UUV Simulator. We used three different algorithms, including twin delayed deep deterministic policy gradient (TD3), Soft Actor-Critic (SAC), and Proximal Policy Optimization (PPO). By conducting multiple experiments in a simulation environment and evaluating their results, we found that all three algorithms have good performance and robustness, and each has its own advantages in different test cases. The research results of this paper can provide some reference and guidance for UUV path planning.
A Three-Stage Low-Illumination Image Enhancement Method Based on Feature Refining and Its Application in Inspection Robot for High-Voltage Substation Room

To address color deviation and noise problem in some Retinex theory based image enhancement methods, this paper proposes a three-stage low-illumination image enhancement method based on feature refining. Additionally, a vision subsystem for an electric inspection robot is introduced based on this network to mitigate the impact of low illumination environments on vision detection tasks in high-voltage substation rooms. In the first stage, the proposed network decomposes the image using Retinex theory and leverages the Swin Transformer to perceive global information. In the second stage, the image undergoes preliminary enhancement. In the third stage, the feature refining network is introduced. Initially, a U-shaped network is employed to extract image features. Subsequently, a convolutional neural network and attention mechanism are applied to screen the extracted information, completing the feature refinement and improving the quality of the result. Through illumination assessment and algorithm selection, the proposed vision subsystem for the robot effectively addresses the challenges of low illumination enhancement and object detection in complex lighting conditions in high-voltage transformer rooms. Experimental results demonstrate that the proposed network outperforms some state-of-the-art methods in terms of peak signal-to-noise ratio and structural similarity index. Moreover, the vision subsystem presented in this paper significantly enhances the robot's detection capabilities, reducing the omission ratio and fallout ratio, thus validating the effectiveness of the proposed method.
Federating Hashing Networks Adaptively for Privacy-Preserving Retrieval

With the rise of neural networks, many deep hashing networks have been successfully trained on the basis of large-scale data. However, the conventional learning process has received increasing challenges from the data privacy concerns and the decentralized storage status, especially in sensitive scenarios like surveillance retrieval. Further considering the probable different distributions of the decentralized data, in this paper, we present a collaborative hashing paradigm FedA-Hash (Federating Adapted Hashing nets) to produce personalized hashing models for the clients without exchanging their local data. To this end, the bilateral knowledge is blended gradually during the learning process between the aggregated global model and the local hashing model, instead of replacing the local model with the global model directly. Extensive experiments are conducted on representative hashing networks, involving tasks as image retrieval and person re-identification. The results show that FedA-Hash significantly enables the collaborated performance among different clients.
Expression-Guided Attention GAN for Fine-Grained Facial Expression Editing

Facial expression editing aims at manipulating the expression of a face image with fine-grained conditions, while keeping the irrelevant regions unchanged. Previous methods have certain limitations in the quality of generated images and usually suffer from changing condition-irrelevant regions, such as background and facial details. In this paper, we propose an expression-guided attention GAN (EGA-GAN) to achieve fine-grained facial expression editing. We take the relative Facial Action Units (AUs) as the condition for target expression. The conditions are used to control two modules called latent space manipulation and multi-scale feature manipulation. The former is designed to edit expression and generate realistic and natural expression changes, and the latter is designed to preserve the unrelated region. To take advantages of both modules, we generate an attention mask from the expression condition and the input image to fuse the features of the two modules in a fine-grained manner. Through experiments, we show that our method achieves state-of-the-art performance on the accuracy of expression editing and can better disentangle the change of expression from irrelevant regions.
Tracing the Future

The chapter presents a comprehensive evaluation of the transformative role of blockchain and internet of things (IoT) in augmenting food supply chain transparency, primarily focusing on inventory management and food safety tracking. The global food supply chain, fraught with myriad challenges such as economic adulteration, microbial pathogens, and non-permitted additives, necessitates the integration of cutting-edge technology to ensure safety and sustainability. Blockchain and IoT, with their inherent qualities of traceability and transparency, can revolutionize the food industry by enabling real-time tracking, fostering responsible sourcing, minimizing waste, and bolstering consumer satisfaction. The chapter underscores these advantages while highlighting some existing challenges within the food supply chain and how these technologies can address them.
Underdevelopment in Nigerian and Other Developing Countries: Imperialism Versus Corruption

The conception that Africa is underdeveloped because of the incursion of Europeans vis-à-vis slave trade, imperialism and colonialism is so overwhelming that it beclouds contemporary reality of the fundamental causes of underdevelopment in Nigeria and other developing countries. Very recently, precisely January 22, 2016, John Kerry (US Secretary of States) declared that corruption is killing Nigeria and 5 other states. Alhaji Lai Mohammed (Nigerian Minister of Information and Culture) had earlier stated that about 55 people stole a total of 1.34 trillion Naira between 2006 and 2013. This arousesconsciousness on corruption and brings to question the Afrocentric theories of underdevelopment. The study appraises the basic assumptions of dependency / imperialism conceptions and juxtaposes it with cases of corruption in Nigeria. The study concludes that Nigeria and other developing countries should stop brooding over slavery, imperialism and colonialism that ended several decades ago and face present realities because almost all the countries of the world were at one time or the other brutalized, subjugated and exploited. The reality is that corruption is the root cause of contemporary underdevelopment in Nigeria and other developing countries. The study recommends among other things that anti-corruption agencies in Nigeria should be strengthened and granted more coercive and enforcement powers. There should be no sacred cows or caveats in the fight against corruption. Stiffer penalties and punishment should be meted out on corruption cases and immunities of politicians should be conditional waived in glaring cases of corruption.
Analisis Kesalahan Berbahasa Tataran Fonologi dan Morfologi pada Teks Sinopsis Cerita Karya Siswa Kelas V SD Negeri Menuran 03 Sukoharjo

Language occupies a very crucial role for humans in this life, especially in terms of communication with other humans. One of the language skills used to communicate indirectly is writing skill. In the world of writing, writing mistakes have become a natural thing. Therefore, this study aims to improve and describe various errors in the Indonesian language at the phonological and morphological levels in the story synopsis text by students of class V SD Negeri Menuran 03. The method used in this study is a qualitative descriptive method. The data source in this study came from written data in the form of story synopsis text results, while the data collection technique used was reading and note-taking techniques. The results of this study indicated that there were 45 language errors at the phonological and morphological levels. At the phonological level (adding phonemes, changing phonemes, and removing phonemes) there were 30 errors or 66.7%, while at the morphological level (affixation and reduplication) there were 15 errors or 33.3%.
Tantangan dalam Pembelajaran Berhitung di Kelas Awal dan Cara Mengatasinya

The low level of students' understanding in learning mathematics is caused by the assumption held by most students that mathematics is a difficult and boring subject. This diminishes students' motivation to learn, leading to the suggestion that mathematics is a subject to be avoided. This challenge serves as the foundation for the writing of this academic work. Through this research, it is hoped that we can identify the challenges in early math education, particularly in mathematics, and propose efforts to overcome difficulties in learning mathematics, especially in the third grade of Elementary School. This study is conducted using a qualitative method with a descriptive analysis approach. Data collection aims to adjust and obtain information about the factors that make it difficult for students to grasp mathematical concepts. The research results indicate that students' difficulties in learning mathematics consist of three components: difficulty in understanding concepts, difficulty in skills, and difficulty in problem-solving. The factors causing difficulties in learning mathematics originate from both internal and external factors. Based on these factors, efforts that can be made to reduce difficulties in learning mathematics include teaching math in an enjoyable way, using tangible learning media, increasing practice exercises, and establishing cooperation with students' parents.
The State and Development Guidelines for Science Teaching and Learning Management of Primary Schools in Guangdong, China

The purpose of this study is to investigate the current situation of science teaching management in primary schools in Guangdong Province, and to propose development guidelines. The sample group included 226 primary school teachers in Guangdong Province, and five of them were randomly interviewed. Questionnaires and interviews were used to collect data. According to the interview and the current development policy of primary school science teaching management in Guangdong Province, the future development of science discipline should pay attention to the concept of quality education, practical ability and scientific thinking training; Teachers should pay attention to the combination of systematic knowledge and science curriculum practice in teaching; At the same time, science teachers should innovate teaching methods, pay attention to personalized teaching and make full use of teaching resources.
An Analysis of Cyber Threat in the Merger and Acquisition Process and the Role of Cyber-security for a Successful Merger

Businesses are increasingly giving cybersecurity the attention it deserves to facilitate successful mergers and acquisitions. Cyber security due diligence is not only essential for just the acquiring company. Excellent cybersecurity benefits both sides of the M&amp;A process. A clean bill of health concerning cybersecurity can make a target firm more attractive, and cybersecurity best practices on both ends make for a smoother, more secure transition period. This Research paper analysis the major cyber threat possible in Merger and Acquisition cases and provide deep understanding of the cyber risk in merger deals, the role of due diligence in Cyber Security and migration strategies for Cyber Risk in merger. This paper concludes that cybersecurity is a critical consideration in the M&amp;A process, with data breaches and cyber threats posing significant risks to both acquiring and target companies. By adopting a proactive and multi-layered approach to cybersecurity, businesses can mitigate risks, protect sensitive data, and foster a smooth post-merger integration. Prioritizing cybersecurity throughout the M&amp;A lifecycle is essential in today's digital landscape to safeguard against evolving cyber threats.
MEDIA CANVAS SEBAGAI BAHAN AJAR IPA UNTUK MENINGKATKAN KUALITAS HASIL BELAJAR SISWA KELAS IV SEKOLAH DASAR

The era of the 21st century, which is synonymous with the era of the industrial revolution 4.0, is marked by various forms of paradigm change. The development of the modern world provides a new touch in the world of education that needs to be adjusted by educators and educated alike. Therefore, the aim of this research is to provide assistance to elementary science teachers in understanding the applications they want to apply in this study. One application that is often used is Canvas. This application is often used to design information using images, very unique icons that are able to convey information to readers in a simple and easily understood manner. Science material is one of the lessons that contains environmental pictures and calculations. Therefore, to improve the quality of learning for Grade IV elementary school students, Canvas media will be assisted as an interesting teaching material that is liked by elementary school students. Based on the results of research conducted using the interview method at 3 elementary schools, namely SDI Besterin, SDK Manumuti and SDK Betun I, namely before being given treatment the absorption and completeness values ​​were below the standard of 65% and 80% due to the lack of understanding of teachers in utilizing technology in the current era. After being given treatment using teaching materials designed with canvas the quality of learning is quite improved with absorption and completeness values ​​above average. This is because researchers provide special assistance to science teachers in operating canvas applications so that in applying them to students the teacher has total control.
Survey on Ordering and Eating Food Using Online Food Delivery Applications

The convenience of online food ordering has rapidly grown in popularity in recent years, as technology has made it easier for people to access and purchase food from their favourite restaurants without leaving their homes. This analysis of the survey responses from a sample of consumers indicates the trend and preferences of online food ordering after the COVID-19 pandemic, particularly by younger generations. The survey aimed to collect data on the frequency of online food ordering, the type of food ordered, the level of due diligence conducted by the respondents while ordering food, the impact of online food ordering on overall food consumption, and the perceived advantages and disadvantages of ordering food online. By gathering insights into these areas, the survey aimed to provide a comprehensive overview of the trend of online food ordering and its impact on individual consumers, online food delivery and food industry.