a research paper on unity

Mobile Game Development Using Unity Engine

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• First Online: 29 August 2023
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• Fatima Sapundzhi   ORCID: orcid.org/0000-0002-5533-322X 15 ,
• Anton Kitanov 15 ,
• Meglena Lazarova 16 &
• Slavi Georgiev   ORCID: orcid.org/0000-0001-9826-9603 17 , 18  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 769))

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Unity is a popular game development platform. Various industries are inspired by it and this can be a positive impact on the learning motivation, career growth and job opportunities. The aim of this paper is to develop and implement a 3D game application for education promoting through innovation and digital skills. The game consists of two parts. The first part of the developed application is a maze that the player must overcome. In this labyrinth the player has to collect a certain number of specific bags that contain pieces of the needed puzzle. The second part is a puzzle that the player begins to arrange. If the puzzle is arranged correctly, then the player can read an interesting fact about what is seen on the picture. The theme given on the picture is an educational theme and it main aim is to develop the educational and mental abilities of the playersp who may also be students. The game is suitable for a wide range of potential players as it can be interesting and educational for children, teenagers and even adults.

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Acknowledgement

This publication is developed with the support of Project BG05M2OP001-1.001-0004 UNITe, funded by the Operational Programme “Science and Education for Smart Growth”, co-funded by the European Union trough the European Structural and Investment Funds and Bulgarian National Science Fund under Project KP-06-M62/1 “Numerical deterministic, stochastic, machine and deep learning methods with applications in computational, quantitative, algorithmic finance, biomathematics, ecology and algebra” from 2022.

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Department of Communication and Computer Engineering, Faculty of Engineering, South-West University “Neofit Rilski”, 66 Ivan Mihailov Street, 2700, Blagoevgrad, Bulgaria

Fatima Sapundzhi & Anton Kitanov

Faculty of Applied Mathematics and Informatics, Technical University of Sofia, 8 Kliment Ohridski Blvd., 1000, Sofia, Bulgaria

Meglena Lazarova

Institute of Mathematics and Infromatics, Bulgarian Academy of Sciences, 8 Acad. Georgi Bonchev Street, 1113, Sofia, Bulgaria

Slavi Georgiev

Department of Applied Mathematics and Statistics, University of Ruse “Angel Kanchev”, 8 Studentska Street, 7004, Ruse, Bulgaria

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Correspondence to Meglena Lazarova .

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Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia

Zuzana Kubincová

University of L'Aquila, L'Aquila, Italy

Federica Caruso

Universitetet i Tromsø (UiT) – Norges arktiske universitet, Tromsø, Norway

Tae-eun Kim

Technical University of Sofia , Sofia, Bulgaria

Malinka Ivanova

Department of Life, Health and Environmental Sciences, University of L'Aquila, Coppito, Italy

Loreto Lancia

Department of Computer Science, University of Salerno, FISCIANO, Salerno, Italy

Maria Angela Pellegrino

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Sapundzhi, F., Kitanov, A., Lazarova, M., Georgiev, S. (2023). Mobile Game Development Using Unity Engine. In: Kubincová, Z., Caruso, F., Kim, Te., Ivanova, M., Lancia, L., Pellegrino, M.A. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning, Workshops - 13th International Conference. MIS4TEL 2023. Lecture Notes in Networks and Systems, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-031-42134-1_13

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Researchers Unpack Sign Language’s Visual Advantage

Photo credit: Dzmitry Dzemidovich/Getty Images

Linguists have long known that sign languages are as grammatically and logically sophisticated as spoken languages—and also make greater use of “iconicity,” the property by which some words refer to things by resembling them. For instance, the sound of English bang iconically resembles a sharp noise and meow resembles the crying sound of a cat.

Notably, in American Sign Language (ASL) and in numerous other sign languages, there are often two ways to say roughly the same thing—one using standard words (signs) and the other using highly iconic expressions, called “classifiers,” which serve to create visual animations.

But how normal signs and pictorial-like representations are integrated to create meaning is not well understood.

Philippe Schlenker, a researcher at France’s National Center for Scientific Research (CNRS) and New York University, and Jonathan Lamberton, a Deaf native signer of ASL, an independent researcher and a former interpreter for the New York City mayor’s office, propose an answer in a pair of studies in the journal Linguistics & Philosophy , the first of which was co-authored with Marion Bonnet, Jason Lamberton, Emmanuel Chemla, Mirko Santoro, and Carlo Geraci. 

They conclude that ASL can supplement its usual grammar (often with the word order Subject-Verb-Object) with a distinct pictorial grammar in which iconic representations appear in the order they would on a comic book’s illustrated panels—not because ASL borrows techniques from comics, but because the same cognitive mechanism, pictorial representation, is involved in classifiers and comics. Furthermore, just as is the case in comic-book drawings, viewpoint choice is crucial in how classifiers are represented. Spoken language must resort to different modalities (speech and gestures) to create a comparable synthesis of grammar and pictorial representations.

“These studies highlight the importance of visual animations in language, with consequences for grammar and meaning alike,” explains Schlenker. “The traditional view of language as a discrete system is thus incomplete: within language, discrete words can be complemented with gradient visual animations, in one and the same modality in sign language and in two modalities—speech versus gestures—in spoken language.”

The Role of Classifiers

The simultaneous presence of normal signs and highly iconic classifiers in sign language has long been known. For instance, if an instructor wants to say, “Yesterday, during the break, a student left,” there are two ways to express the action in ASL. As with the English word leave , the signer may use a normal verb that renders unspecified the manner of movement. But the signer may also use an upright index finger—a classifier—to create a simplified animation of an upright person moving out of the room—e.g., fast or slow, towards the right or towards the left, directly or with a detour.     

“In spoken language, words can't create visual animations, but gestures can. This work on sign language classifiers offers a new perspective on gestures in spoken language," says Philippe Schlenker, a researcher at New York University and France’s National Center for Scientific Research.

“The classifier functions as a kind of animated puppet inserted in the middle of a sentence,” explains Jonathan Lamberton. “This gives rise to an extraordinary mix of normal signs and pictorial-like representations.”

The Role of Pictorial-Like Representations

But how are these two components integrated? Schlenker and Jonathan Lamberton, together with Bonnet, Jason Lamberton, Chemla, Santoro, and Geraci, started with word order. In ASL, the basic word order is SVO—Subject-Verb-Object—as in English. But it has been observed that classifiers often prefer for their objects to come  before  the verb—e.g., Subject- Object-Verb (SOV).  The researchers propose that classifiers override the basic word order of ASL because they create visual animations. But they start with an observation that initially deepens the mystery. If a classifier is used to represent a crocodile eating up a ball, both the subject and the object preferably appear before the verb—e.g. SOV. But if the classifier represents a crocodile spitting out a ball it had previously ingested, SVO order is regained.     

Here’s how this can be explained by analyzing classifiers as pictorial-like representations, the authors say. Owing to their pictorial-like nature, classifiers preferably go with the order that would be found in a comic—if you were to view it left to right. For the crocodile eating up a ball, one would typically see the crocodile and the ball before the eating, which is why the subject and object come before the verb (e.g. SOV). By contrast, for the crocodile spitting out a ball, one sees the crocodile (the subject) and the spitting first, and only then the ball (the object) coming out of the crocodile—which is why SVO order is regained.

“In spoken language, words can't create visual animations, but gestures can,” notes Schlenker. “This work on sign language classifiers offers a new perspective on gestures in spoken language.”

It is an old observation that in sequences of silent gestures (pantomimes), speakers of diverse languages preferably use SOV, even if this goes against the order of their native language, as is the case in English (which is SVO). But the authors show that this SOV preference only holds for “eat-up-type” gestures. When “spit-out-type” gestures are considered, SVO order is regained, just as with ASL classifiers. And here too, the explanation is that gestures appear in the order that would be found in a comic.        

While speech alone can’t match the rich iconic component of sign language, speech with gestures sometimes can, the authors of a pair of new studies conclude.

In their second study, Schlenker and Lamberton ask how the meanings of standard signs and classifiers are integrated. Since the 1960's, the meaning of sentences has been analyzed      with logical methods, the researchers explain. Some have recently posited that there can be a logic of pictorial representations. Schlenker and Lamberton propose that the rich meaning components of sign language are integrated by  combining the logic of words and the logic of pictorial-like representations. More specifically, the “glue” between them is the notion of a viewpoint, corresponding to the position of a video camera: the camera position for the animation representing the student leaving will likely correspond to the instructor's viewpoint.

However, there is considerable flexibility in the manipulation of viewpoints. Sometimes two classifiers that occur in the same sentence are evaluated with respect to distinct viewpoints, as happens if an instructor teaches linguistics in one classroom and philosophy in another classroom and wants to represent one student leaving the philosophy classroom fast and another student leaving the linguistics classroom slowly: each animation can come with its own camera position or viewpoint.

“This is but the tip of the iceberg, as viewpoint manipulation can get even more sophisticated,” notes Schlenker.

Here too, sign language classifiers offer a new perspective on gestures in spoken language. While spoken words can't create visual animations, gestures can. And the viewpoint-dependency of sign language classifiers can be found in gestures as well, down to the details. 

This dovetails with an old idea, the authors conclude: While speech alone can’t match the rich iconic component of sign language, speech with gestures sometimes can.

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