Reviewerly/exHarmony huggingface dataset:
A Novel Approach to Optimize Memory Reconstruction Using Joint Multimodal Networks

Memories play a crucial role in the human life experience. Whether they are used to make decisions or understand current situations, memories influence the past, present, and future. However, some memories are unreliable; in the court of law, the false memories of victims can cause inaccurate verdicts. To reconstruct human memories directly from the brain, recent studies have used electroencephalographic (EEG) brain signals in machine learning frameworks like generative adversarial networks (GANs), which generates new data from old ones. However, traditional GANs tend to produce the same images, an issue called mode collapse. Therefore, a conditional variational autoencoder-generative adversarial network (CVAE-GAN), which had not been used before in memory reconstruction, was developed to address GAN failures by jointly-training (1) an encoder and (2) GAN. CVAE-GAN correlated the MindBigData dataset’s EEG brain signals with the corresponding ImageNet dataset images and produced new memories of participants, such as pandas, humans, and fish. CVAE-GAN’s Inception Score, which marked how diverse and distinct its generated images were, was 1.00 on average. The number of floating operations, or FLOPS, was 102 Gigaflops, which was less than the traditional GAN’s 198 Gigaflops. While limitations with time, computational memory, and mode collapse prevented the CVAE-GAN from recreating accurate memories, it still generated distinct image colors and general features. Future studies can build on existing network architectures and include more homogeneity in datasets. Ultimately, CVAE-GAN has the potential to advance new understandings of the brain and could elevate the memory reconstruction field.
The Impact Of Work Communication And Discipline On Employee Performance

The objective of this study is to determine and analyze the effects of the work environment, communication, and discipline on employee performance. The background of this study is the phenomenon of inadequate company facilities, budget constraints, poor communication with colleagues, where employees tend to form separate groups, and the low level of discipline and self-awareness of employees and superiors regarding compliance with regulations. The study is quantitative, and the data was analyzed using multiple linear regression. A sample of 41 employees was taken with the saturated sampling approach. The results showed that work facilities had a good and statistically significant effect on staff performance at PT. Prosperous Administration Development, as well as on work communication and work discipline. Furthermore, the impact of work facilities, communication, and discipline on the performance of PT. Bina Administration Sejahtera staff was also significant.&#x0D; &#x0D;
Pelatihan desain grafis dan seminar kewirausahaan bagi umkm sebagai upaya peningkatan kualitas promosi dan pemasaran produk pada masa covid-19

The COVID-19 pandemic has hurt the economy in Indonesia, one of which is the impact on MSMEs. The impact of this pandemic requires MSME players to develop marketing strategies and creativity. MSME players must be more creative and innovative in developing marketing strategies. Therefore, KKN IAIN Salatiga 2022 is carrying out graphic design training and entrepreneurship seminars for MSME players with the aim of MSME players having the skills to create attractive and creative promotions in various e-commerce so that MSME products can be promoted with a broader reach and can attract buyers. The methods used are counseling, graphic design training, and holding entrepreneurship seminars, which are carried out in several stages: preparation, implementation, and evaluation. The results of this Community Service Activity are (1) MSMEs can master material regarding the importance of graphic design, (2) MSMEs are starting to create their product catalogs, and (3) MSMEs are innovating with their brands and product packaging.
The Use of Deixis in Online Classroom Interaction Among the University Students

Pragmatics is the study related to linguistics used by a person. It is the study of language and its content. Therefore, it becomes the basis for knowing the meaning of a language. Pragmatics is focused on the investigation of importance as conveyed by the speaker (or author) and deciphered by the audience (or reader). This research aimed to find the use of deixis in online class interaction among the third-semester students of the graduate school Universitas Negeri Semarang 2020/2021, the data of this study were the students' interactions in the WhatsApp application during the class of the graduate school Universitas Negeri Semarang. This research was a form of qualitative research proposed by Creswell (2009). We were required to be able to classify, collect, analyze, and draw conclusions through the phenomena that have been analyzed without making a generalization. The findings showed that from 26 students' discussion results, 1.156 deixes were found in the students’ discussions. Then, the deixis were categorized into five categories based on Levinson’s theory. There were 529 personal deixes that equal to 45.76%, 55 temporal deixes that equal with 4.75%, there are 108 in spatial deixis that equal to 9.34%, 329 in social deixis that equal with 28.46%, and 135 in discoursal deixis that equal to 11.67%. This study in like manner expected to give inspiration for the readers who are intrigued on the deixis study and it will be an additional reference for readers who are intrigued on examining this examination
The Degree of Assertiveness in Speeches Delivered by Debaters on NSDC 2020 Final Round

Considering the crucial roles of interpersonal meaning in argumentative speech, the study evaluated the use of interpersonal meaning using Halliday’s theory (2014) in debate speeches. It aimed to find out the use of mood and modality in the speech of debaters and how mood and modality realize assertiveness. This research used a qualitative research design with the data from spoken language, especially the final round of the National School Debating Championship 2020. The result of the study on 6 high school debaters showed that there are 1061 mood systems found; they are classified as declarative, interrogative, and imperative mood systems. The most occurred mood in the speech was the declarative mood, which is 999 clauses and categorized as a statement that contains information for the debater to present their idea. The presented ideas were used in an attempt to justify the team’s stances. The modality system found that the most common type of modality in speech was the inclination modality, which is 40 clauses. It indicates that the debater wants to show their determination on how the debater deals with the motion. By analyzing the speech using interpersonal meaning, the highest number of declarative mood and inclination modalities indicates the assertiveness in every debater’s speech.
Errors in Discourse Marker Usage in Descriptive Texts by SMA Negeri 12 Semarang Students

This study delves into the analysis of common errors found in descriptive texts authored by a sample of 32 students, randomly selected from SMA Negeri 12 Semarang. Its primary objective is to identify, categorize, and evaluate errors pertaining to adverbial phrases, conjunctions, prepositional phrases, and discourse markers while assessing their impact on the coherence of the text. Employing a rigorous research methodology encompassing both quantitative and qualitative techniques, this study provides a thorough evaluation of the student's writing abilities. Quantitative analysis of the collected data exposes a spectrum of errors, encompassing discourse marker misuses, sentence structure deficiencies, inaccuracies in prepositional phrases, conjunction errors, and problems with adverbial phrases. Notably, discourse marker errors, including the omission of commas and the repetitive use of words, emerged as the most prevalent issues. These errors have the potential to significantly hinder the clarity and overall flow of the text. The motivation for this study arises from the recognition that students often encounter challenges when it comes to effectively utilizing discourse markers and other grammatical elements in their descriptive writing. These difficulties can adversely impact text coherence and, consequently, the overall quality of the students' compositions. In light of the quantitative findings, this research underscores the critical importance of targeted grammar instruction and consistent writing practice to enhance students' writing skills. Addressing these common errors collaboratively, educators and learners can work towards improving the quality of descriptive texts.
Improving Sustainability: A Cryptocurrency-Based Reward Scheme for Reducing Carbon Emissions

The Rewarding System for Carbon Emission Reduction Using Cryptocurrency presents a novel approach to incentivizing sustainable practices and combating climate change. This system leverages blockchain technology and cryptocurrencies to provide economic rewards to individuals, businesses, and organizations for their efforts in reducing carbon emissions. By integrating cryptocurrencies, such as stablecoins, and creating a transparent and secure blockchain platform, the system aims to address key challenges in measuring, verifying, and rewarding carbon reduction activities. The benefits of this rewarding system are significant, including increased adoption of sustainable practices, global collaboration, and amplified impact of carbon reduction efforts. However, challenges such as cryptocurrency volatility, scalability, regulatory compliance, and measurement accuracy need to be addressed for the system's success. Looking ahead, the future prospects of the rewarding system for carbon emission reduction using cryptocurrency are promising, with potential for increased adoption, technological advancements, policy support, and financial innovation. This innovative approach has the potential to drive meaningful change and contribute to a greener and more sustainable future.
Virtual Reality is Revolutionising Healthcare: A Groundbreaking Method for Medical Applications

Virtual reality (VR) has emerged as a transformative technology with immense potential in various fields, including healthcare. Virtual reality medical application systems offer a novel approach to medical training, patient care, and research. By creating immersive and interactive virtual environments, these systems enable healthcare professionals to simulate realistic scenarios, practice complex procedures, and enhance their skills without compromising patient safety. Patients, on the other hand, can benefit from VR experiences that provide a deeper understanding of their medical conditions, facilitate informed decision-making, and improve treatment outcomes. VR also holds promise in areas such as mental health therapy, rehabilitation, and telemedicine, expanding access to healthcare services and improving the overall patient experience. This article explores the key aspects of virtual reality medical application systems, including their components, benefits, future prospects, and the impact they can have on the healthcare industry.
An Embedded Approach to Hypervisor-Oriented Interruption Virtualization Operation

This paper presents a method for virtualizing interruptions in an embedded hypervisor environment. The method involves the hypervisor taking control of hardware interruptions, providing them to a guest operating system (OS) for virtualization, and simulating interruption events through service threads running on the hypervisor. The guest OS executes a virtualization interruption service program using interruption injection operations provided by the hypervisor, bypassing the need to respond to hardware interruptions. This approach allows interruption service programs to be executed in a conventional stack environment, eliminating the need for copying and preserving the execution context. A comparative analysis with the virtualization scheme in Xen reveals that the proposed method reduces the overhead associated with field preservation, thereby enabling more efficient interruption response.
An Aerial Robotics Investigation into the Stability, Coordination, and Movement of Strategies for Directing Swarm and Formation of Autonomous MAVs and Diverse Groups of Driverless Vehicles (UGVs)

This study will discuss the matter of movement communication and preparation of tight configurations of land &amp; flying robots. Remotely Operated Cars (UGVs) and Unmanned Aerial Vehicles (UAVs), in specific Micro Aerial Vehicles (MAVs), would be used to fix circumstances where a creation of UGVs and UAVs, in specific Micro Aerial Vehicles (MAVs), should counteract their velocity and direction to finish a mission of traffic sequence to a targeted area. The motion planning and stabilisation strategy given here is a useful tool for deploying closely collaborating robot teams including both outdoor and indoor settings. The installation of large groups of Micro Aerial Vehicles (MAVs) in a legitimate (indoor and outdoor) environment without the use of auxiliary positioning applications (such as Vicon or GPS) is indeed a natural development in the area of autonomously flying systems. Stability, control, and trajectory planning techniques for guiding swarm or configurations of unmanned MAVs, as well as diverse groups with Unmanned Ground Vehicles (UGVs) operating alongside MAVs, will be discussed in greater detail. These approaches discussed all are designed for the use of inter squads in true complex scenarios even without necessity for worldwide translation or motion capture systems, as they are predicated on board optical comparative localisation of single MAVs. This multi - objective optimisation being an enabler for the introduction of swarming of tiny autonomous drones beyond the labs with equipment for precise robot positioning. Model Predictive Control (MPC) is being used to address a formations to goal territory issue, and the form drive idea is based on a simulated approach. The Particle swarm optimization approach is utilised for digital leader trajectories planning, as well as control and stabilisation of follows (MAVs and UGVs). The proposed technique could be tested in the future using a range of simulation and practical tests.
Using Attack Path Formalisation Analysis in Software Design Stage Threat Modelling Method

This research proposes a comprehensive method for threat modeling in the software design stage, incorporating attack path formalization analysis. The approach involves extracting software defect information through UML active graph decomposition of the application or system and performing threat modeling. The method comprises several steps, including creating and modeling use cases, generating an application/system silhouette, decomposing the application/system using the active graph, constructing a threat tree with key asset information as the threat object, classifying and evaluating the threat object, and calculating the attack path of the threat tree. By comparing it with existing approaches, this invention aims to enhance software product safety, improve software quality, broaden the application range of threat modeling, and achieve automation in threat modeling, resulting in reduced technical threshold, cost, and development time for trusted software development.
Cloud Storage Systems with Secure Attribute-Based Access Control

This research presents a novel approach to safe access procedure in cloud storage structure by addressing the challenges associated with managing and distributing complex secret keys. The proposed procedure utilizes attribute-based access control and incorporates a client process, an authentication terminal process, and a storage terminal process. The client generates a main secret key and public parameters for each user using an attribute password mechanism. The authentication terminal maintains user attribute, file attribute, and attribute secret key databases. Access control is determined by constructing an access control string from the attributes of the user, file, and file operation type, enabling fine-grained access control and accommodating large-scale user dynamic expansion. Consequently, the access control costs of the cloud storage structure are significantly reduced, while offering a flexible, effective, and secure access control mechanism for safe storage structure access.
Building a Platform for Data Mining in a Big Data Environment Combining R-language with Hadoop

With the exponential growth of data in various industries, the need for effective data mining platforms has become crucial. This research focuses on constructing a data mining platform suitable for processing large-scale and diverse data sets. The platform leverages the power of the R language and utilizes the scalability and processing capabilities of Hadoop. The system architecture encompasses a physical layer, virtualization layer, service layer, and application layer. Heterogeneous hardware resources are deployed at the physical layer, while virtual machines are created and managed using CloudStack at the virtualization layer. The service layer integrates the R language, enabling the implementation of various data mining functions. Finally, the application layer provides users with a user-friendly interface to customize flow paths and configure parameters. The proposed method effectively processes big data, facilitates comprehensive data analysis, and achieves high processing efficiency.
Reliable Techniques for Providing Secure Access Control for Cloud Storage on Mobile Devices

This research focuses on the development of a credible access control method for mobile device cloud storage. The proposed method involves a six-step process, including user registration and login, key generation, data encryption and upload, authentication theory between mobile devices, and data download and decryption. The method incorporates the use of mobile TPM (Trusted Platform Module) chips to ensure trust chain transmission during key exchange. Additionally, encryption based on elliptic curve cryptography is employed to reduce the key length and facilitate secure key sharing among multiple mobile devices. The proposed method offers enhanced security and reliability compared to conventional data encryption methods provided by cloud storage service providers, with minimal interaction data and increased confidence level. It holds significant practical value and exhibits a wide range of potential applications in the field of cloud storage security technology.
Komparasi Artikel Ilmiah Tentang Pengembangan Koleksi Perpustakaan

This research is entitled "scientific article collaboration on library collection development". The purpose of this research is to find out how the collection development process is carried out in the library in particular. This study uses a qualitative research design. By collecting primary data, secondary and literature review. Data analysis techniques using data presentation, drawing conclusions. The results of this study. This shows that collection development is an important and vital activity in the library. There is no library without collections, both print, non-print and electronic collections to meet their various information needs. Library collection development is very important for library growth, therefore it needs to be continuously evaluated to assess their strengths and weaknesses. This process will lead to the removal of material that is no longer relevant. Given the shortage of books in libraries and based on the premise that no library is independent, libraries engage in inter-library lending or sharing of resources. Information Communication Technology based on on-line access related to collection development in developed countries.
Unveiling the Geological Divide: Contrasts Between Intraplate and Plate Boundary Earthquakes.

This review compares the distinctions between interplate earthquakes, primarily situated at plate boundaries, and intraplate earthquakes occurring within the interior of tectonic plates. While plate tectonics effectively explains the mechanisms of interplate seismicity, intraplate earthquakes, notably observed in northeast Asia, pose a more intricate puzzle with no overarching model. This study tackles the fundamental question of whether these two seismic categories exhibit similarities, exploring their respective origins and variations. Despite the challenges associated with understanding intraplate earthquakes due to their infrequency compared to plate-boundary seismic events, this comparative analysis seeks to provide insights into the shared and unique aspects of these significant geological occurrences.
Data Persistence Storage in VMs Cloud-Based Software

The virtual machine data persistence storage method in a cloud environment addresses the challenge of persistent storage for user data in cloud computing systems. This paper proposes a system and method that enables the creation and expansion of block devices for virtual machines. The method involves a major node receiving user requests, determining whether it is a block device creation or expansion request, and executing the appropriate steps. The major node interacts with storage nodes to create logical volumes and register them as block device services. By implementing this method, the issue of non-persistent storage for user data after virtual machine shutdown is effectively resolved. This paper presents a detailed description of the method, its background, research objectives, and a conclusion highlighting the significance and benefits of the proposed virtual machine data persistence storage system.
Interative effects of trade openness and foreign direct investment on economic growth in Nigeria

The study examined the interactive effects of trade openness and foreign direct investment on economic growth in Nigeria over the period of 1982 to 2021. Specifically, the study sought to: determine the effects of trade openness on the economic growth in Nigeria and ascertain the effects of foreign direct investment on the economic growth in Nigeria. These variables consist of real gross domestic product (RGDP), Foreign Direct Investment (FDI), trade openness (TRAOPEN), inflation rate (INFLA), exchange rate (EXR) and trade tariff (TRADE). The variables used in the model were foreign direct investment (FDI), trade openness (TRAOPEN), and trade tariff (TRADE). The methods of data analysis was Autoregressive distributive lag Model. The following findings were stipulated; trade openness (TRAOPEN) has positive and significant impact on real gross domestic product (RGDP) its probability value of 0.0001 was less than 0.05 but it was positive and significant impact on real gross domestic product (RGDP) its probability value of 0.0027 was less than 0.05 in long run; foreign direct investment (FDI) has positive and significant impact on real gross domestic product (RGDP) its probability value of 0.0001 was less than 0.05 but it was positive and significant impact on real gross domestic product (RGDP) its probability value of 0.0027 was less than 0.05 in long run. The study recommends that policymakers of Nigeria government should consistently formulate and implement policies that would increase their annual inflows of FDI and their degree of trade openness.