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Browse all published issues of International Journal of Technical Innovation in Modern Engineering & Science. Click any issue card to view its papers inline.

Volume 12 2026
3 issues  ·  5 papers

Issue 1

(January - March) 2026

2 papers →

Issue 2

(April - June) 2026

2 papers →

Issue 3

(July - September) 2026

1 paper →
Volume 11 2025
4 issues  ·  11 papers

Issue 1

(January - March) 2025

3 papers →

Issue 2

(April - June) 2025

3 papers →

Issue 3

(July - September) 2025

2 papers →

Issue 4

(October - December) 2025

3 papers →
Volume 10 2024
5 issues  ·  13 papers

Issue 1

(January - March) 2024

2 papers →

Issue 2

(April - June) 2024

4 papers →

Issue 3

(July - September) 2024

1 paper →

Issue 4

(October - December) 2024

3 papers →

Issue 10

Issue 10 2024

3 papers →
Volume 9 2023
4 issues  ·  12 papers

Issue 1

(January - March) 2023

3 papers →

Issue 2

(April - June) 2023

2 papers →

Issue 3

(July - September) 2023

2 papers →

Issue 4

(October - December) 2023

5 papers →
Vol.9, Issue 3 — (July - September) 2023 2 papers
01

Vol.9, Issue 3 · (July - September) 2023 · ID: IJT-2023-39256

A Collaborative Wearable and Smartphone-Based Indoor Lifelogging Framework

Khanh Nguyen-Huu , Chang Geun Song, Seon-Woo Lee · Department of Electronic Engineering, Hallym University, Chuncheon, Republic of Korea, Korea

🕔 Received 27 March 2023; received in revised form 19 July 2023; accepted 30 July 2023

Research Article Computer Science Wearable Computing & Activity Recognition Pg. 79-92
Abstract In this study, a lifelogging system is proposed for logging the daily activities of a user using a smartphone and a smartwatch cooperatively in indoor environments. The proposed system attempts to recognize a user’s activities of daily living, including sleeping behavior and various physical activities, and to estimate the user’s daily total energy expenditure (TEE) based on the recognized lifelogs. The TEE has the potential to be useful in personal healthcare management. The system includes both mobile and server systems. The mobile system consists of both a smartwatch and a smartphone used to classify ten activities, including sleeping activities, using sensors on both devices. The server system includes a database server and a set of programs to handle the collected lifelogs for users. An Android app is also developed to display the collected lifelogs and the estimated daily TEE on smartphones to assist in managing users’ health. The experimental results show that the overall average recognition rate of seven activities is 97.5% with four subjects, and the total average error for the three states of sleeping behaviors is 6.64%.

Keywords: lifelogging system, smartphone, smartwatch, activity recognition

02

Vol.9, Issue 3 · (July - September) 2023 · ID: IJT-2023-28289

Intelligent Positioning of AUV Docking Stations Using Optical Sensing and Neural Network Techniques

Thieu Quang Minh Nhat , Hyeung-Sik Choi, Mai The Vu, Joono Sur, Jin-Il Kang, Hyun-Joong Son · Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea, Korea

🕔 Received 26 April 2023; received in revised form 01 July 2023; accepted 31 August 2023

Research Article Robotics & Automation Robotics & Navigation Systems Pg. 93-103
Abstract Detecting the relative position of the docking station is a very important issue for the homing of AUVs (Autonomous Unmanned Vehicles). To detect the position of the light source, a pinhole camera model structure was proposed like the camera model. However, due to the sensor resolution and the distortion errors of the pinhole camera system, the application of the camera of docking the under turbid sea environments is almost impossible.
In this paper, a new method detecting the position of the docking station using a light source is presented. Also, a newly developed optical sensor which makes it much easier to sense the light source than the camera system for homing of the AUV under the water is performed. In addition, to improve the system, a neural network (NN) algorithm constructing a model relating the light inputs and optical sensor which are developed in this study is proposed.
To evaluate the performance of the NN algorithm, the experiments were performed in the air beforehand. The result shows that the NN algorithm with AUV docking system using the NN model is better than the pinhole camera model.

Keywords: optical sensor, neural network, pinhole camera, navigation

Volume 8 2022
7 issues  ·  7 papers

Issue 2

(April - June) 2022

1 paper →

Issue 3

(July - September) 2022

1 paper →

Issue 4

(October - December) 2022

1 paper →

Issue 5

Issue 5 2022

1 paper →

Issue 10

Issue 10 2022

1 paper →

Issue 11

Issue 11 2022

1 paper →

Issue 12

Issue 12 2022

1 paper →
Volume 7 2021
10 issues  ·  15 papers

Issue 1

(January - March) 2021

3 papers →

Issue 2

(April - June) 2021

2 papers →

Issue 4

(October - December) 2021

1 paper →

Issue 5

Issue 5 2021

2 papers →

Issue 7

Issue 7 2021

1 paper →

Issue 8

Issue 8 2021

1 paper →

Issue 9

Issue 9 2021

2 papers →

Issue 10

Issue 10 2021

1 paper →

Issue 11

Issue 11 2021

1 paper →

Issue 12

Issue 12 2021

1 paper →
Volume 6 2020
12 issues  ·  80 papers

Issue 1

(January - March) 2020

7 papers →

Issue 2

(April - June) 2020

6 papers →

Issue 3

(July - September) 2020

8 papers →

Issue 4

(October - December) 2020

5 papers →

Issue 5

Issue 5 2020

8 papers →

Issue 6

Issue 6 2020

8 papers →

Issue 7

Issue 7 2020

4 papers →

Issue 8

Issue 8 2020

7 papers →

Issue 9

Issue 9 2020

7 papers →

Issue 10

Issue 10 2020

11 papers →

Issue 11

Issue 11 2020

7 papers →

Issue 12

Issue 12 2020

2 papers →
Volume 5 2019
19 issues  ·  1424 papers

Issue 1

(January - March) 2019

68 papers →

Issue 2

(April - June) 2019

59 papers →

Issue 3

(July - September) 2019

202 papers →

Issue 4

(October - December) 2019

202 papers →

Issue 5

Issue 5 2019

194 papers →

Issue 6

Issue 6 2019

111 papers →

Issue 7

Issue 7 2019

61 papers →

Issue 8

Issue 8 2019

39 papers →

Issue 9

Issue 9 2019

14 papers →

Issue 10

Issue 10 2019

4 papers →

Issue 11

Issue 11 2019

9 papers →

Issue 12

Issue 12 2019

6 papers →

Issue 13

Issue 13 2019

162 papers →

Issue 14

Issue 14 2019

56 papers →

Issue 15

Issue 15 2019

18 papers →

Issue 16

Issue 16 2019

46 papers →

Issue 17

Issue 17 2019

12 papers →

Issue 18

Issue 18 2019

142 papers →

Issue 19

Issue 19 2019

19 papers →
Volume 4 2018
13 issues  ·  1461 papers

Issue 1

(January - March) 2018

44 papers →

Issue 2

(April - June) 2018

22 papers →

Issue 3

(July - September) 2018

22 papers →

Issue 4

(October - December) 2018

64 papers →

Issue 5

Issue 5 2018

240 papers →

Issue 6

Issue 6 2018

251 papers →

Issue 7

Issue 7 2018

201 papers →

Issue 8

Issue 8 2018

157 papers →

Issue 9

Issue 9 2018

120 papers →

Issue 10

Issue 10 2018

92 papers →

Issue 11

Issue 11 2018

104 papers →

Issue 12

Issue 12 2018

114 papers →

Issue 13

Issue 13 2018

30 papers →
Volume 3 2017
12 issues  ·  216 papers

Issue 1

(January - March) 2017

1 paper →

Issue 2

(April - June) 2017

3 papers →

Issue 3

(July - September) 2017

20 papers →

Issue 4

(October - December) 2017

37 papers →

Issue 5

Issue 5 2017

22 papers →

Issue 6

Issue 6 2017

15 papers →

Issue 7

Issue 7 2017

12 papers →

Issue 8

Issue 8 2017

4 papers →

Issue 9

Issue 9 2017

9 papers →

Issue 10

Issue 10 2017

26 papers →

Issue 11

Issue 11 2017

32 papers →

Issue 12

Issue 12 2017

35 papers →
Volume 2 2016
9 issues  ·  32 papers

Issue 1

(January - March) 2016

1 paper →

Issue 4

(October - December) 2016

7 papers →

Issue 5

Issue 5 2016

7 papers →

Issue 6

Issue 6 2016

1 paper →

Issue 8

Issue 8 2016

1 paper →

Issue 9

Issue 9 2016

3 papers →

Issue 10

Issue 10 2016

5 papers →

Issue 11

Issue 11 2016

4 papers →

Issue 12

Issue 12 2016

3 papers →

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