Mobile cloud game in high performance computing environment

Kristiadi, Dedy Prasetya; Sudarto, Ferry; Rahardja, Evan Fabian; Hafizh, Naufal Rayfi; Samuel, Christopher J.; Warnars, Harco Leslie Hendric Spits

doi:10.12928/telkomnika.v18i4.14896

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…Subindex Red (0,0), (0,1), (0,2), (0,3), (0,4), (0,5), (0,6), (1,0), (2,0), (3,0), (4,0), (5,0) Blue (5,1), (5,2), (5,3), (5,4), (5,5), (5,6), (5,7), (0,7), (1,7), (2,7), (3,7), (4,7) Starting from the scenario shown in figure 11, the next step is the simulation of the constraint moves set out in the playing rules (see Figure 11). To transfer the game interface to a graphical user interface (GUI) environment using the libraries provided by the programming language, 'x' and 'y' are represented by red and blue pieces, respectively.…”

Section: Token Colourmentioning

confidence: 99%

“…Therefore, it is necessary to know the rules of the game to subsequently apply the Minimax algorithm. Its application involves managing complete information of the player states to select the best move for each one, assuming that the opponent will choose the worst one [6]. In other words, it seeks to determine and observe the optimal moves in each of the games using a programming language for graphical user interface.…”

Section: Introductionmentioning

confidence: 99%

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Linja: A Mobile Application Based on Minimax Strategy and Game Theory

et al. 2022

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This article presents an application of Minimax strategy and game theory to implement the Linja mobile game. This game theory strategy applies collaborative learning to determine the winner of a game between two opponents, thus determining the optimal move in complex environments. In the development of the collaborative game, different game learning scenarios are proposed where competition between a player and the machine, and competitions against other players, intervene. In the learning process, moves are proposed that allow the maximum gain and the minimum loss among the competitors. In this case, the methodological approach was carried out towards the move that allows maximizing the profit and minimizing the loss, based on the application of the Mini/Max algorithm in search of determining the optimal solution of the game. The process is obtained from the adaptation of mathematical models for the development of games, using specialized tools that support a multi-paradigm programming language working together with the tools that the same language provides and that potentially serve as a contribution to the development of the game. In the search for an intelligent and autonomous system. The intelligent system correctly finds the winner of a game, showing the course of the game move by move. The results show that the game developed with the Minimax strategy allows automatic learning in multiuser environments, correctly identifying the winner of a game, generating the most optimal route of the game from move to move.

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Section: Token Colourmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Linja: A Mobile Application Based on Minimax Strategy and Game Theory

et al. 2022

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“…The memory block eventually got the forget gate [24], [25]. Adaptively forgetting or resetting the cell's memory, the forget gate scales the internal state of the cell before adding it as input through the cell's self-recurrent link [26]- [29].…”

Section: Introductionmentioning

confidence: 99%

A quality control system for logistic ports goods movable harbor cranes based on internet of things and deep learning

Hatem Awad,

Sabry Saraya,

Shrief Mostafa Elksasy

et al. 2024

IJEECS

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The growth of commercial activity and the transportation of goods around the world has increased the challenges of stevedoring within ports. In case of loading and unloading ships safely, quickly, and efficiently, goods movable harbor cranes play an important role. This work aims to propose an industrial internet of things (IIoT)-based quality control system for logistic services ports goods movable harbor crane (QC-GMHC). The GMHC system based on using programmable logic controller (PLC), along with a multi-sensor data collecting system. Several operations have been done to establish the QC-GMHC system as: GMHC sensors real-time data storage, and data sharing; monitoring the GMHC status (remote-local); and the efficiency reporting. In order to validate the proposed system’s hardware, it was used in an already operational GMHC for six months, during which data were collected and analyzed. The results revealed that the proposed hardware system worked efficiently for 24 hours. To forecast the efficiency of the GMHC, a deep learning (DL) conventional long short-term memory (LSTM) and neural network model was trained and validated using synthetic data generated from acquired real data. The results showed that QC-GMHC can calculate efficiency with an accuracy of 80%, which is sufficient for our application.

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“…In the 21st century, communication system applications are utilized in the day-to-day activities of human lives, these include telecommunication, terrestrial television, transportation (maritime & air), military and security. Communication system engineering applications have evolved from the era of line telegraphy, radio telephony to real-time communication through the use of sophisticated smartphones that can perform various tasks including online shopping, cloud gaming, financial processes, controller, measurements and mapping etc [1][2][3][4]. Contemporary smartphones are versatile portable computers-on-chip that exploit the flexibility conferred on them by the existence of operating systems in this case Android that manages and controls operations of the smartphones depending on the architecture.…”

Section: Introductionmentioning

confidence: 99%

Validation of android-based mobile application for retrieving network signal level

Adeniji

Surajudeen-Bakinde

Omitola

et al. 2021

IJEECS

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In recent years, the evolvement of mobile devices which perform sophisticated functions have been on the rise. Mobile applications which solved engineering challenges are now available due to the high computational capabilities, large random access memory and storage location of the mobile devices. An Android application called signal detect, which measures network signal strength value from 2G-4G received on an android mobile device has been developed using android app development environment called Android studio. Validation becomes necessary because different readings were obtained on smartphones with different specifications. Two validation techniques were used to validate the data obtained. To know the efficiency of the application; a field strength meter was used to compare the readings received on the mobile device with the meter. It was observed that there is a time lag on the received values of the mobile device to the field strength meter. Therefore, a moving average technique was used to correlate the two data which increased the correlation coefficient to about 0.85.

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Mobile cloud game in high performance computing environment

Cited by 5 publications

References 23 publications

Linja: A Mobile Application Based on Minimax Strategy and Game Theory

Linja: A Mobile Application Based on Minimax Strategy and Game Theory

A quality control system for logistic ports goods movable harbor cranes based on internet of things and deep learning

Validation of android-based mobile application for retrieving network signal level

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