Reviewerly/exHarmony huggingface dataset:
PICT-CLRL at WASSA 2023 Empathy, Emotion and Personality Shared Task: Empathy and Distress Detection using Ensembles of Transformer Models

This paper presents our approach for the WASSA 2023 Empathy, Emotion and Personality Shared Task.Empathy and distress are human feelings that are implicitly expressed in natural discourses.Empathy and distress detection are crucial challenges in Natural Language Processing that can aid our understanding of conversations.The provided dataset consists of several long-text examples in the English language, with each example associated with a numeric score for empathy and distress.We experiment with several BERT-based models as a part of our approach.We also try various ensemble methods.Our final submission has a Pearson's r score of 0.346, placing us third in the empathy and distress detection subtask.
Design of intelligent wheelchair control system based on speed planning

In order to optimize the movement performance of intelligent wheelchair through narrow environment and turning obstacle avoidance, and realize the speed change of wheelchair more smooth and stable, based on the principle of speed planning, this paper designs and develops a new intelligent wheelchair movement control system, and uses STM32 control chip for hardware circuit design and main software programming. The motion control driver is applied to the power system of the wheelchair, which drives two 24V DC motors to work together. Good results are obtained through experiments, and better driving control for the intelligent wheelchair is realized.
Track association based on the empirical mode decomposition in passive localization

In distributed passive localization and tracking system, the track observed by the subsystem seems like Brownian motion track, because the tracked target is non-cooperative target and its maneuver is often complex, and the localization accuracy is poor. These track characteristics will seriously disturb track association between different subsystems. In order to solve this problem, the track to track association algorithm based on empirical mode decomposition (EMD) is proposed in this article. To lessen the impact of target placement and maneuvering mistakes, components that do not follow the track trend are removed from each dimension of the track recorded by each sub-system. The track motion trend vector is formed using the remaining low-frequency components as track characteristics, and the relevant correlation criteria are created. The track association between sub-systems is ultimately finished since the correlation threshold is self-adaptive and does not require the creation of a motion model. Results from simulations indicate that the suggested method is capable of successfully completing the track connection in passive systems
The design and development of the MetAR framework for designing an augmented reality application based on experts' consensus

This study aims to design and develop a framework for designing a metacognitive-supported augmented reality application for teaching and learning basic pneumatic systems. This multi-method study with the fuzzy delphi method (FDM) and interpretive structural modelling (ISM) approach involved 12 experts in multidisciplinary fields. The data was collected using seven Likert-type scale questionnaires. The design phase of the framework using the FDM found that the expert consensus for all principal components and the elements is greater than 75% with the threshold value, d ≤ 0.2. In contrast, the development phase of the framework was performed based on experts' voting using the ISM approach. The Concept Star software was used to develop the sequence of the elements based on their priority from every principal component to produce the MetAR design framework.
Research on mass data storage and retrieval method of relational database based on KID cognitive model

In order to solve the problems of high space occupation rate and low retrieval security existing in traditional methods, this paper designs a massive data storage and retrieval method based on KID cognitive model of relational database. First, the singular value of the information flow of the data with similar attributes in the database is decomposed, and the data with similar attributes is removed, and then the mass data is stored according to the mapping relationship between the data. Then, the KID cognitive model is used to transform the data mode, and the safe retrieval coefficient is obtained by determining the threshold value of the core point of the data to realise the safe retrieval of the data. Experimental results show that the space occupancy rate of this method is always less than 10%, and the safety factor of data retrieval is the highest about 0.95.
JPBlock: augmenting security of current journal and paper publication processes using blockchain and smart contract

Scholarly journals (SJ) play an indispensable role in the scrutiny and dissemination of research. However, the current SJ and academic paper publishing infrastructure is fragmented and dependent on centralised servers compelling researchers to hop from one journal platform to another for familiarity, account registration and subsequent usage. In this work, we advance a secure blockchain-based multi-tenant decentralised framework dubbed JPBlock to facilitate paper submission through publication and discoverability. Leveraging fundamental attributes of blockchain, smart contract and decentralised storage technology, we advance novel capabilities including paper tracking, proof of authorship and voting on reputation of journals while enforcing core security principles on-chain and off-chain. Open access papers are made available on a global scale while non-open access papers are securely encrypted supporting the subscription-like model. Results from our proof-of-concept implementation reveal that the framework is feasible and satisfies fundamental security requirements with journals and authors incurring overall costs of $46.66 and $25.61 respectively.
Access control system of face recognition for smart campus based on cloud-side collaborative priority verification strategy

Campus access management is an essential component of school security. As the notion of intelligent campuses progressively evolves, there is an increasing appreciation of the significance of the campus access control system. Currently, there are two face recognition-based access control schemes available. On the one hand, the cloud server employs online authorization delegation to grant access, while on the other hand, the edge device utilizes local authorization to regulate access control. However, due to many school staff and access control terminals, the current method still needs to improve authorization delays and parallel server pressure. Therefore, this paper proposes an online verification priority strategy based on cloud-edge collaboration, which fully utilizes the characteristics of cloud servers and edge devices to solve the above-mentioned problems.
Fuzzy C-mean clustering algorithm based on genetic simulated annealing algorithm battlefield site selection

In this paper, for a battlefield material point siting problem, we do not adopt the traditional ideas, but treat it as a classification and solution module model, and choose to bring in a nested algorithm model to fuzzy cluster the points on the battlefield in order to divide them into multiple independent siting problems, and change the aggregation path of each node according to a heuristic algorithm to traverse all reach possibilities as much as possible. Dividing the battlefield area into n regions for clustering optimization: the fuzzy C-mean clustering algorithm using genetic simulated annealing algorithm for fuzzy clustering within the battlefield area, and then the immune algorithm to make a selection of all possibilities, can guarantee the accuracy rate while greatly reducing the model running time and achieving higher efficiency. (1) regional selection stage, based on the difficulty of attacking each point of the battlefield to establish an evaluation index system, the use of cluster analysis methods[1] to divide the battlefield area into n categories to achieve for different looking for the corresponding command center, material center target group; (2) Immune algorithm optimization, based on the immune algorithm to construct the corresponding model and design a modified genetic algorithm to optimize the optimal addressing[2]. After using the genetic algorithm with adaptive parameters, a more stable centroid is obtained in 500 iterations. Based on the above two-stage planning method, the empirical study results show that it can provide scientific personalized optimal addressing points for addressing class problems.
A fast route planning algorithm for civil aircraft test flight

In the process of civil aircraft test flight, different test flight subjects need to be carried out in different natural environments, so it is necessary to conduct frequent transfer flights; In addition, there are functional and reliability test flights, route demonstration flights and other route flight tasks during the process of civil aircraft test flight. As the test flight aircraft has not obtained the type certificate, there are many special restrictions on airworthiness conditions. So it is necessary to make special route for test flight aircraft. In this paper, we present a fast planning algorithm for civil aircraft test flight routes, which takes into account the special requirements of test aircraft for routes, incorporates Dijkstra's algorithm, and can quickly construct routes suitable for test aircraft by combining existing route resources, and gives an implementation example of the algorithm. The results show that the route planned by this method is effective and reliable.
Prediction and Prevention of Theft in Jewellery Shop

The internet of Things (IoT)-based total security is the most broadly used protection framework introduced by the technological developments. Sensors and cameras play a vital role in detecting movement and alerting the humans in lots of security applications. As these security gadgets are always accompanied with alarm systems, it is more popularly used for preventing the theft in public places like shopping malls and shops. In such areas, conventional CCTV cameras are usually used as it helps in non-stop human tracking, and detections of crimes. The proposed system is also on such intelligent security system capable of identifying mis-happenings in the public places. With real-time image feedback, the proposed device provides the owner with assurance even when they are not around. These studies examine the possibility of implementing automation technologies in the near future to provide complete protective control. The research suggests a fully automated security system that uses alarm messages and the internet of things (IoT) to predict and prevent unwanted activities in the jewellery shop.
Double strategy fusion improved sparrow search algorithm

Aiming at the shortcomings of sparrow search algorithm, such as dependence on initial solution, sudden drop of population diversity in the late iteration period, and easy to fall into local optimal value, a multi-strategy algorithm was proposed to improve sparrow search algorithm. In the initialization stage of the algorithm, the standard Brownian motion is introduced to enhance the global search ability of the algorithm and improve the population diversity. In the later stage of the algorithm iteration, the improved artificial bee colony search strategy is introduced to accelerate the convergence of the algorithm, and the influence of local extreme points on SSA can be reduced to improve the ability of the algorithm to jump out of the local optimal solution. The experimental results show that the improved sparrow search algorithm has faster global convergence speed, better optimization accuracy and stability in function optimization.
A path planning method for mobile robots incorporating artificial potential field method and ant colony algorithm

For the problems of long planning paths and slow convergence speed of the ant colony optimization (ACO) in mobile robot path planning, this paper improves the ant colony optimization and introduces the artificial potential field method (APF). Firstly, the initial pheromone concentration is differentiated to make the ants more directional at the early stage of the algorithm. Second, the heuristic factor in the heuristic function is dynamically adjusted to optimize the pheromone update strategy so that the algorithm can effectively distinguish the high-quality paths from the common ones. Finally, the distance parameter is added to the repulsion function of APF, the improved ant colony algorithm is fused with APF, and a fusion algorithm based on the improved ant colony algorithm-artificial potential field method (IACO-APF) is proposed. In the simulation experiments, the trajectories are optimized by the B-spline curve method, and the experiments show that the IACO-APF algorithm can obtain better solutions in a shorter time compared with the traditional ant colony algorithm and other algorithms mentioned in the literature.
Fish swarmed Fuzzy Time Series for Photovoltaic’s Forecasting in Microgrid

Forecasting irradiation and temperature is important for designing photovoltaic systems because these two factors have a significant impact on system performance. Irradiation refers to the amount of solar radiation that reaches the earth's surface, and directly affects the amount of energy that can be generated by a photovoltaic system. Therefore, accurate irradiation forecasting is essential for estimating the amount of energy a photovoltaic system can produce, and can assist in determining the appropriate system size, configuration, and orientation to maximize energy output. Temperature also plays an important role in the performance of a photovoltaic system. With increasing temperature, the efficiency of the solar cell decreases, which means that the energy output of the system also decreases. Therefore, accurate temperature forecasts are essential for estimating system energy output, selecting suitable materials, and designing effective cooling systems to prevent overheating. In summary, forecasting irradiation and temperature is important for designing photovoltaic systems as it helps in determining suitable system size, configuration, orientation, material selection, and cooling system, which ultimately results in higher energy output and better system performance. In recent decades, many forecasting models have been built on the idea of fuzzy time series. There are several forecasting models proposed by integrating fuzzy time series with heuristic or evolutionary algorithms such as genetic algorithms, but the results are not satisfactory. To improve forecasting accuracy, a new hybrid forecasting model combines fish swarm optimization algorithm with fuzzy time series. The results of irradiance prediction / forecasting with the smallest error are using the type of Fuzzy Time Series prediction model optimized with FSOA with RMSE is 0.83832.
A hybrid framework to enhance cloud security for storing and retrieving confidential data in clouds

&lt;p&gt;The building pieces for creating a secure cloud framework for data exchange with authenticated and authorized users are ECC and ABAC. So, the goal of this study is to improve access control and encryption-related methods in order to increase security. The elliptic curve is a key component of the comparative study of cloud encryption and access control techniques. This research project’s main goal is to provide a security architecture that combines authenticated access with attribute-based access control and better elliptic curve encryption. The second goal is to provide a better mapping strategy with reduced time and space complexity for elliptic curve encoding from plain text. To boost the performance of the standard ECC, a thorough algorithm focusing on designing an improved mapping mechanism for encoding plain text to elliptic curve points with excellent security has been included. The strength of the security should not be sacrificed in order to reduce security measures’ overhead costs. ABE is regarded as an effective way for protecting cloud data, according to study results. Because to the use of complex pairing processes, the same is difficult to use. As a result, a hybrid approach using ECC and ABAC performs better to handle the increasing processing capacity.&lt;/p&gt;
Specifications, Procedures, and Fittings for Tapping and Plugging to Achieve Effective Pipeline Modification and Repair

Although some civil engineers may be aware of the general concept of tapping into and plugging a pipeline in order to accomplish repair or reconfiguration of piping systems while maintaining service, there are others that are unfamiliar with the process. This is because the information in public references and standards commonly used by civil engineers is usually limited to taps for small diameter service lines. More detailed information for larger diameter pipes relative to this procedure is confidential and particular to the relatively few industrial organizations that offer the fittings and tapping and plugging services. As a result, it is not uncommon for engineers to simply indicate a tap and plugging procedure in documents, or develop an incomplete or erroneous specification that could be detrimental to an efficient and economical execution of a project. This paper discusses tapping and plugging specifications; selection and design of appropriate fittings and their respective configurations for different pipe materials and pipeline product; fitting installation and testing; tapping and plugging procedures; options for addressing loads and thrusts developed during operations; plugging sequencing; withdrawal of equipment and closure of fittings in order to improve project effectivity.
THE CHALLENGES AND BENEFITS OF KNOWLEDGE MANAGEMENT SYSTEM TO LIBRARIAN COMPETENCIES AND SKILLS: A SYSTEMATIC LITERATURE REVIEW

Knowledge Management is relatively new to libraries, hence it is important to find its impact and implications for libraries and LIS professionals. The objective of this paper is to summarize the existing researches concerning the challenges and benefits as implications of knowledge management system in libraries. Through a systematic literature review method, this paper wants to research knowledge management system related to librarian competencies and skills from challenges and benefits point of view. The results showed that the librarian should prepare to face for the challenges of KM to get benefits by utilized the KMS so that they can increase their competencies and skills in the future.
Regulatory framework of the export potential of the Russian agricultural education system

Introduction. The relevance of the article is due to the problems of competitiveness of domestic education in the world market of educational services, including agricultural education. The article talks about the need to have a sufficient regulatory framework for its implementation and a reliable mechanism for assessing the export potential of the Russian agricultural education system. Purpose setting. The purpose of the study is to identify the regulatory framework of the strategy for the development of the national education system, taking into account the circumstances in which the country's economy found itself, sanctions from Western countries against Russia. Methodology and methods of the study. The study includes a review of bibliographic and regulatory sources on the problem of the formation and functioning of the mechanism for assessing the export potential of the Russian agricultural education system. Results. The results of the work include a description and analysis of the problems associated with the disclosure of the concepts of «educational potential of Russian universities» and «export potential of the Russian agricultural education system»; summarizing information on the regulatory framework of the Russian education system (projects, programs, strategies and initiatives) aimed at attracting foreign students to Russian universities. The idea of raising the share of non-primary exports of the Russian Federation by increasing the attractiveness of Russian education in the international educational market is revealed. The authors propose an algorithm that represents a sequence of steps in the implementation of the migration process for new entrants to Russian universities, the passage of which allows citizens of various countries to become Russian students and receive their chosen education. Conclusion. In the final part of the work, it is said that the problem of research is practice-oriented in nature, allows us to determine the organizational and pedagogical conditions for the qualitative functioning of domestic agricultural education from the perspective of international interaction of universities in the new educational space.
Research on key technologies of attitude adjustment and involution of reconfigurable flexible wing body

The versatility and agility of the assembly system is the key to affect the cost and efficiency. This paper focuses on the application scene of wing-body attitude adjustment, and puts forward a modular reconfigurable layout method and a spatial motion data calculation method based on measured position for tooling equipment; for the control system, a general communication method library based on ModbusTCP protocol is constructed; for process monitoring, a decisionmaking and monitoring model driven by all elements of PPR is established. The data show that the method can reduce the infrastructure construction cost and improve the assembly efficiency.
Dual-vehicle co-working system based on OpenMV

The dual-vehicle system uses TI's 32-bit high performance, low-cost, low-power MSP432P401R as a control kernel to design a car-following system for a given multitasking situation. The vehicles have a controllable speed in this system, follow the track, and are capable of performing multiple tasks in conjunction with each other. The main body of the vehicle includes an encoder to obtain the current wheel speed, a greyscale detector, an OpenMV to obtain the track information, and an ultrasound distance measurement module to control the vehicle distance. In addition, the dual vehicles communicate with each other through Bluetooth modules to ensure that the vehicle tracking system can start and stop nearly simultaneously. During the driving process, both cars can smoothly follow the black track and perform the corresponding tasks of overtaking and parking. This system meets the requirements of design and the operation process shows excellent performance.
An unsupervised anomaly detection approach using spatiotemporal feature in hot strip rolling

In the hot strip rolling process, anomalies can potentially have a considerable impact on the overall production process owing to the interdependent nature of the production module and variables. To address this concern, this paper proposes a data-driven framework that leverages a spatiotemporal feature extraction method based on Symbolic Dynamic Filtering to identify the causal relationships among the variables. These extracted features are then used to learn more representational features via a Restricted Boltzmann Machine, and the monitoring statistics are built on its concept of energy to form an anomaly detection method. The experimental findings demonstrate the efficacy and feasibility of the proposed framework in detecting faults, exhibiting notable accuracy and promptness in real-time scenarios.