Reviewerly/exHarmony huggingface dataset:
Implementasi Metode Taboo Code Untuk Kompresi File Video

Video is a technology for capturing, recording, processing, and rearranging images usually using electronic signals, or digital media. For example, a video file that is large in size causes the sending process to take longer, and uses a large amount of memory space in its storage. Problems that arise due to the large file size include the wasteful storage media used, as well as more time in terms of data exchange, data transfer via the internet is a big problem in Indonesia because download and upload speeds are very low. To overcome this problem, data compression techniques are needed. The concept of compression was born as a real solution to the problem of the amount of space needed to store various digital files, including video files. Compression technique is a technique that compresses files so that their size becomes smaller while maintaining the quality of the representation of the filet.
Improve the efficiency of deep reinforcement learning through semantic exploration guided by natural language

Reinforcement learning is a powerful technique for learning from trial and error, but it often requires a large number of interactions to achieve good performance. In some domains, such as sparse-reward tasks, an oracle that can provide useful feedback or guidance to the agent during the learning process is really of great importance. However, querying the oracle too frequently may be costly or impractical, and the oracle may not always have a clear answer for every situation. Therefore, we propose a novel method for interacting with the oracle in a selective and efficient way, using a retrieval-based approach. Since the interaction can be modeled as a sequence of templated questions and answers, and that there is a large corpus of previous interactions available. We use a neural network to encode the current state of the agent and the oracle, and retrieve the most relevant question from the corpus to ask the oracle. The agent's policy and value function was updated by the oracle's answer. We evaluate our method on an object manipulation task. Our method can significantly improve the efficiency of RL by reducing the number of interactions needed to reach a certain level of performance, compared to baselines that do not use the oracle or use it in a naive way.
Implementasi Fungsi Hash Dengan Algoritma Sha-256 Pada Aplikasi Duplicate Image Scanner

Nowadays we are in the era of the digital world, there are lots of equipment that has a tool for recording photos in the form of a camera on a smartphone. The weakness of smartphones is the small storage space, so users must be good at managing files stored on the smartphone. There are so many applications in smartphones that provide facilities for sharing images. This of course will greatly burden the storage space of the smartphone because it stores image files which are generally large in size, especially if the image files are the same or duplicate, of course it is very burdensome for storage space. It will be very difficult to distinguish an image file without looking at the contents of the image file. So if you want to distinguish one image file from another, the user must see the contents of the image file and this will certainly be very difficult. For that we need a method that can be used to identify the same image file or duplicate image files so that a decision can be made to delete the duplicate document files so as to save storage space. In cryptography there is a hash function which is a one-way function that can generate the identity of a file, where if the image file contains the same content, it will produce the same hash value. It can be used to identify the same or duplicate image files. In the hash function there is the SHA-256 method or the Secure Hash Algorithm 256 which is one of the hashing algorithms that is often used to encrypt data with a length of 256 bits. By applying this algorithm to the file scanner application, the results of the image file search are grouped based on the same hash value and users can make it easier and faster for users to delete duplicate image files without having to open and view the contents of the file.
Sistem Pakar Diagnosa Penyakit Skizofrenia Dengan Menerapkan Kombinasi Metode Constraint Satisfaction Problem (CSP) Dan Metode Certainty Factor

Psychiatric illness is a change in mental function that causes disturbances in ways of thinking, will, emotions, actions and social relations that can cause obstacles in carrying out social roles. One type of psychiatric disorder that is very often known by the public is schizophrenia. If schizophrenia is not followed up, it will have a lot of impact on Indonesian society. For this reason, we need a system that is designed to mimic the expertise of an expert in answering questions and solving a problem in accordance with the knowledge of an expert that is entered into a computer system. The development of artificial intelligence technology that has occurred has enabled expert systems to be applied in detecting diseases using programming languages. One of them is in providing information about various problems, especially psychiatric disorders or often called schizophrenia. The expert system method used is a combination of the Constraint Satisfaction Problem (CSP) and Certainty Factor (CF) methods, which is one of the solutions that can display the final results of several diagnoses of schizophrenia. With the facilities provided to users, it is possible to use this system according to their individual needs. Users are given the convenience of finding information about the symptoms of Schizophrenia and its prevention. This expert system was created using the Microsoft Visual Basic 2010 application.
Research on cross-regional path planning algorithm for aircraft unmanned tractor based on improved A* algorithm

Unmanned tractors can replace experienced drivers in driving and warehousing aircraft on the ground. When the airport and hangar environment is more complex, higher requirements are also put forward for the path planning algorithm. The A* algorithm is a heuristic search algorithm widely used in path planning. Improved based on the classic A* algorithm, it can avoid obstacles across regions while improving efficiency and reducing path cost consumption. First, a region segmentation method was designed, and then the evaluation function was redesigned to avoid falling into local optimality. At the same time, it was improved to delete child nodes that have passed the obstacle vertex when selecting child nodes to avoid collisions. Finally, the optimisation path was improved, redundant nodes were deleted, and secondary optimisation was performed to reduce the number of turns and the total number of turns. Simulation experiments were conducted through Matlab, and the data showed that the improved A* algorithm has high smoothness, avoided collisions, reduced crossing areas, and saved movement time.
Review on Research of Automated Machine Learning

Automated Machine Learning (AutoML) can automatically discover high-performance models to build deep learning systems without human assistance, with the ultimate goal of reducing the complexity and entry barriers of building deep learning systems. Although AutoML has achieved a certain degree of automation through four important steps: data preparation, feature engineering, model generation, and model evaluation, there is still a significant gap compared to the ultimate ideal of achieving truly intelligent lifelong learning. Therefore, a deep understanding of AutoML can help drive the development of artificial intelligence. Firstly, we comprehensively reviewed the latest technologies and achievements involved in these four steps, then we introduced their shortcomings and challenges. Secnodly, a detailed introduction was given to the existing AutoML libraries and the theoretical and practical applications of AutoML. Finally, we summarized AutoML models and Proposed an outlook.
Towards Discrete Object Representations in Vision Transformers with Tensor Products

In this work, we explore the use of Tensor Product Representations (TPRs) in a Vision Transformer model to form image representations that can later be used for symbolic manipulation in a neurosymbolic model. We propose the Tensor Product Vision Transformer (TP-ViT), an enhancement of a Vision Transformer that incorporates TPRs, an object representation methodology that utilizes filler and role vectors to represent objects. TP-ViT is the first application of TPRs on visual input, and we report qualitative and quantitative results which show that the use of TPRs allows for the formation of more targeted and diverse object representations when compared to a standard Vision Transformer.
Modular Multi-Face Tracking Geared Toward Face Recognition in Surveillance Videos

Face recognition has achieved great accuracy when used in controlled conditions, however, these results aren’t usually carried over to video surveillance scenarios. To facilitate the use of face recognition for video surveillance, face selection can be employed as an intermediate step. This dissertation presents a study of face selection where we rework a multi-face tracking pipeline and with few changes manage to increase tracking and reconnection capabilities. Through experimentation with different face detection models, random parameter search and a simpler face quality measure, we achieved an increase of 10.1% in Multiple Object Tracking Precision (MOTP) and 9% more in the IDF1 metric. All experiments were conducted on a public multi-face tracking dataset, which we also expanded through manual video annotations.
Sistem Pendukung Keputusan Pemilihan Virtual Private Server (VPS) Menggunakan Metode MOORA

Virtual Private Server (VPS) is a hosting solution where one physical server is divided into several isolated virtual servers. Each virtual server operates independently with the resources assigned to it. VPS uses virtualization technology that allows multiple virtual servers to run on one physical server. The main advantage of VPS is the ability to have complete control over the server without the need to manage complex physical infrastructure. In addition, VPS also offers a higher level of privacy and security compared to share hosting. However, in choosing a VPS, several problems can arise. Too few resources can hurt website or application performance, while too many resources can result in waste and unnecessary costs. Also, issues such as downtime, poor connection speed, or server constraints can cause disruption to the hosted website or application. To choose a VPS that suits user needs, the MOORA method is used as a decision support system. In this case, 9 VPS providers were selected which would be evaluated based on the criteria of CPU, RAM, Storage, Bandwidth and Cost. After applying the MOORA method, alternative A4 with a Yi value of 1,590 was declared the best alternative, and the Exabytes provider was considered the best VPS service provider.
Implementasi Algoritma MD4 Pada Aplikasi Duplicate Audio Scanner

Nowadays there are many applications that help the process of duplicating audio, of course this takes up more storage space. For that we need a method that can be used to identify the same or duplicate audio files. The solution that can be done to handle duplication of audio files or duplicates is to apply hash type cryptography techniques where the process of identifying the hash value of the audio file is carried out so that the resulting value is different from the original file. The hash type cryptographic algorithm used is the MD4 algorithm. The results obtained from the process of applying the MD4 algorithm are grouping audio files based on the same hash value, making it easier and faster for users to delete duplicate audio files
Counter-Improvised Explosive Devices (C-IED) mission support capabilities

Actions and activities taken against the IED threat comprise complex tasks. In thebeginning, the focus was on the deactivation and destruction of IEDs, as the only wayto fight against them. As time has passed, more existing capabilities were included inthe field of C-IED, which were able to contribute to the mitigation of the effectivenessof an IED attack.Due to the fact that the first type of response to IED-threat was tasked to combatengineers, particularly to EOD personnel, that was rather obvious that C-IED missionsand responsibilities fell to combat engineers. Nowadays, however, capabilities andcapacities in the C-IED can be identified that exceed the competence of engineer unitsand commanders. The C-IED requires a comprehensive approach. In a staff andheadquarters lots of capabilities and capacities should be involved in C-IED activities,which requires coordination and cooperation. The involvement of those capabilitiesdepends on the type of mission, its phases, and the nature of IED threat. Thus amission commander needs to understand which are the C-IED enablers that cancontribute to C-IED tasks, when and how they influence or mitigate IED threats.
Scaling Machine Learning with a Ring-based Distributed Framework

In centralized distributed machine learning systems, communication overhead between servers and computing nodes has always been an important issue affecting the training efficiency. Although existing research has proposed various measures to reduce communication overhead between nodes in parameter server frameworks, the communication pressure and overhead inherited from centralized architectures are still significant. To address the above issue, this paper proposes a ring-based parameter server framework that is distinct from node division and model training mechanism in the standard p/s framework. The ring-based architecture cancels the global model stored on the server side, and each computing node stores a local copy of the model. During model training, computing nodes can asynchronously train local models based on local or remote training data. After all nodes finish learning, the ensemble learning method can predict test data based on all local models. To avoid the negative impact of remote data reading on model training efficiency, a producer-consumer data reading strategy is proposed. This strategy can reduce data reading overhead in a pipeline manner. To make rational use of the input and output bandwidths of all nodes, a circular data scheduling mechanism is proposed. At any given time, this mechanism ensures each node has at most one input stream and one output stream, thereby dispersing communication pressure. The experimental results show that the proposed distributed architecture achieves significantly better performance (1.7%-2.1% RMSE) than the state-of-the-art baselines and also achieves a 2.2x-3.4x speedup when reaching a comparable RMSE performance.
Modifikasi Pembentukan Algoritma Rc4 Cipher Dengan Metode Acak Mid-Square Technique Untuk Pengamanan Voice Chat

Technological developments and human lifestyles allow access to information systems in new ways, for example using online conversations (chat) via an internet connection, which is often in the form of text communication (text chat) or voice (voice chat). Instant messaging only became popular when the internet began to be widely used in the mid-1990s. Along with the human need for easy and fast communication, the application that can be used is Voice Chat which allows users to carry out voice communication. But the voice chat application is less secure because it is easily intercepted by other parties. Eavesdroppers can easily find out the contents of conversations in instant messaging and the lack of privacy for chat users. The RC4 algorithm has a weakness in its use to encrypt a message. The downside is that Vigenere can only perform encryption and decryption processes for short messages. One way that can be used is to make security for the voice chat application using the Mid-Square Technique algorithm
Penerapan Algoritma K-Medoids untuk Klustering Bakery dan Cake yang Laris

The culinary business has been a promising business from the past until now, there are many kinds of businesses that are in demand, namely heavy food to light food. One of the promising businesses currently is the bakery and cake shop business. The large amount of sales competition makes the owner enthusiastic about competing to create delicious flavors and have characteristics that are different from other businesses. Mawar Bakery and Cake shop is a culinary business shop made from flour and has many branches in North Sumatra. The many delicious products created can attract the attention of customers, but every month the management must record the products that are sold a lot and the lack of interest. This is done to anticipate losses that occur every month. Therefore, the author created clustering data mining to group bakery and cake sales that were sold a lot and those that were not. The K-Medoids method is able to become an algorithm that is able to carry out the process of collecting data on Mawar bakery and cake sales because the algorithm is practical and efficient in grouping data. The results of data from sales that have been grouped can be concluded that cluster 2 is the best-selling because it gets the highest score
Sistem Pendukung Keputusan Pengangkatan Tamping Pada Tanjung Gusta Medan Menerapkan Metode Analytic Process Network (ANP)

This study aims to build a support system in the main decision making for the appointment of Tamping at Tanjung Gusta Medan. Tamping is a prisoner who assists correctional officers in carrying out coaching activities in prisons. The research data used were obtained from Tanjung Gusta Prison. This decision support system was built using vb.net 2008 by implementing the Analytic Network Process (ANP). The Analytic Network Process (ANP) method is a method that is applied to various problems including decision making, prediction or forecasting, evaluation, mapping, resource allocation and so on. The results of the study are useful to help the leadership of the Tanjung Gusta Medan prison choose quality tamping and can provide direction to every convict at the Tanjung Gusta Medan prison
Implementasi Checksum Dengan Menggunakan Algoritma Fletcher Untuk Mendeteksi Keaslian Sertifikat Rumah

In today's era, renewal is continuously carried out in order to achieve better integrity. The issuance of certificates, which are usually printed on paper, is considered to be prone to damage and loss. Along with the times, certificates are now also issued in digital form. So many people switch to using certificates in digital form. So a mechanism is needed to help secure the certificate. Digital certificates can only be issued by authorized parties. Then the competent authority issues a certificate to another person who has the right to the certificate. Of course, the authenticity of the certificate information has been secured first through the checksum function so that the message in it is encrypted. In cryptography there are many methods and algorithms that can be used, one of which is the Fletcher checksum algorithm. The aim of Fletcher is to provide error detection properties that approximate cyclic redundancy checking but with lower computational effort associated with the summation technique. So that digital certificates that have changed will be detected as authentic.
Modifikasi Algoritma El-gamal Dengan Menerapkan Algoritma Kargers Min Cut Untuk Pembangkitan Kunci

El-gamal algorithm has two keys, namely public key and secret key. This algorithm has security that lies in the difficulty in calculating discrete algorithms. Both encryption and decryption keys are integers. El-gamal algorithm type asymmetric cryptography algorithm consists of two keys namely public key to encrypt while private key to decrypt. In El-gamal algorithms, distributed keys are public keys that are not required confidentiality while private keys remain stored or not distributed. Anyone who has a public key can do the encryption process but the result of that encryption can only be read by the person who has the private key. To increase the strength of the algorithm, the key used to perform the encryption and decryption process will be modified first using the randomization algorithm that is Karger Min Cut Algorithm. Karger Min Cut algorithm is a probabilistic random algorithm used to verify matrix multiplication. The purpose of using Kargers Min Cut algorithm is to make the resulting key more difficult to guess, making it difficult to read the message or information
Implementasi Metode Analytical Network Process (ANP) Pada Sistem Pendukung Keputusan Dalam Seleksi Atlet Penyandang Disabilitas Sumatera Utara Untuk Bertanding Di Ajang Pekan Paralimpiade Nasional (PEPARNAS)

National Paralympic Week (Peparnas) is a competition event that resembles the National Sports Week (PON) for athletes with disabilities in Indonesia. At the National Paralympic Week (Peparnas) North Sumatra Province also registered athletes with disabilities to be able to compete to become champions at the event. In order to achieve the main goal of being a champion at the National Paralympic Week (Peparnas) it is necessary to need competent athletes with disabilities. Therefore, an appropriate selection process for athletes with disabilities is carried out by involving several established criteria. In this study the authors conducted research at the Medan City Youth and Sports Office to obtain the data needed for the selection procedure for athletes with disabilities in North Sumatra to compete at the National Paralympic Week (Peparnas). The purpose of this study is to design a decision support system for the selection of athletes with disabilities in North Sumatra using the Analytic Network Process (ANP) method. The system that has been designed can make it easier for the Medan City Youth and Sports Office to conduct the selection process for good and competent athletes with disabilities to be registered at the National Paralympic Week (Perparnas) competition. Where the results of the application of ANP, based on the evaluation results, the alternative that has the highest priority weight is the Foggia i alternative. Therefore, Foggia was chosen as Tamping at Tanjung Gusta Medan. Randi has a priority weight of 1.62
Modelling of Subject Scheduling Systems Using Hybrid Artificial Bee Colony Algorithm

A common schedule problem found in colleges is the positioning of courses in a certain space and time. This placement process often encounters barriers that must be met so that there is no imbalance in the school schedule. One of the problems that often arise is the placement of class capacity that does not match the course requirements. In this study, the researchers used the Artificial Bee Colony Hybrid Algorithm (HABC) to construct course schedules efficiently at the college. The objective of the research was to develop a course scheduling system using the HABC algorithm by combining the Engineering of Artificial Bee Colony (ABC) and genetic algoritms, especially on the crossover process to better address the schedule problems. The research procedure used is to design and implement a course scheduling system using the Hybrid ABC algorithm. The results of the research demonstrate that the Hybrid ABC algorithm is effective in generating optimal course schedule schedules, in line with time limits, room needs, and lecturer requirements and can automate course schedule processes, saving time and resources, while ensuring optimal schedules.&#x0D;