Smart Mobile Phone Usage Restriction by Extending Phone Circuitry — An Alternative to Jamming

Background: Mobile phones have become an indispensable part of modern human life. With the ever-increasing utilization of smart phones, several psychological & behavioural problems have emerged. Excessive use of smart phones has also led to poor academic performance among students. Keeping all these points in mind, a study was conducted in professional colleges to obtain base line data. Objectives: To assess the usage pattern of smart mobile phone among students of professional colleges and to evaluate the mobile phone dependence in students of professional colleges. Materials and methods: In Visakhapatnam, a cross-sectional study was conducted among 100 Medical & 100 Engineering students selected by random sampling technique. Data were collected using a pre-designed& pre-tested questionnaire from October 2018 to November 2018. SAS-SV Scale was used to assess the mobile phone dependence. Collation of data was done using inferential statistical methods. Results: The study population of Medical group consisted of 32% males & 68% females; of these 45% were Day scholars & 55% were residents of hostels. The study population of Engineering group consisted of 63% males& 37% females; of these 76% were Day scholars & 24% were residents of hostels. The majority of students in both the professional groups were of the age group of 19 years. While assessing mobile phone usage pattern, it was found that age of initiation of mobile phone use was above15 years in 88.5 % in both the groups. 75%. of students in both the groups were using mobile phone between 1-6 hours a day. 45% of students were using mobile phone at home while 55%were using while on move. While 32% students had Addiction scale more than SAS-SV: cut off 31; factors like daily life Disturbance, withdrawal, cyber space-orientation relationship, overuse etc. 33% students were in the range of being at risk group (SAS-SV: 20 to 30). Out of 19 % Medical & 32% Engineering students who attended calls while driving, 26% & 25% continued conversation while still driving in both the groups respectively.131students often woke up from their sleep to check whether they had a Notification or a Missed call or SMS (P=<0.01). False perception of mobile phone ringing was present among 12% of Medical and 14% of engineering students. Conclusion: The study showed an increased dependence of mobile phone use among Medical & Engineering students, which imparts a negative effect on physical and mental health & also poor academic performance.

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The association of smart mobile phone usage with cognitive function impairment in Saudi adult population

Pakistan Journal of Medical Sciences ◽

10.12669/pjms.36.7.2826 ◽

2020 ◽

Vol 36 (7) ◽

Author(s):

Thamir M. Al-Khlaiwi ◽

Syed Shahid Habib ◽

Sultan Ayoub Meo ◽

Mohammed Saeed Alqhtani ◽

Abeer A. Ogailan

Keyword(s):

Cognitive Function ◽

Mobile Phone ◽

Mobile Phones ◽

Adult Population ◽

Cross Sectional ◽

Function Impairment ◽

Mobile Phone Usage ◽

Smart Mobile Phone ◽

Smart Mobile ◽

Moca Score

Background & Objectives: Excessive use of mobile phones has raised a great concern about adverse health effects on human health. The present study’s aim was to investigate the association of the usage of smartphones with cognitive function impairment in the Saudi adult population. Methods: The present cross-sectional study was conducted in the Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia during September 2019 to January 2020. A total of 251 Saudi adults who were using mobile phones were recruited, and knowledge, attitude and practices were assessed by interview using a predesigned proforma. The Montreal Cognitive Assessment (MOCA) tool was employed to assess the cognitive functions, comparison was made between daily mobile phone usage group and their correlated Montreal Cognitive Score (MOCA). Results: The mean age for 251 Saudi adult participants was 32.43±12.8 years. More than 80% of the participants used their mobile phone for more than two hours daily. About 61% of the participants were not aware of the side effect of the radiation generated from mobile phone. The participants showed a decrease in MOCA score with increased daily mobile phone usage (MOCA=26.8 for <1 hour daily usage, 26.1 for 1-2 hours, and 24.6 for >2 hours with P< 0.05). In addition, participants showed decreased MOCA score by keeping their mobile phone near their pillow while sleeping; MOCA=24.35 for near pillow groups and >25.5 for the groups that placed their mobile phone away from the pillow. Conclusions: Excessive use of mobile phones can cause cognitive function impairment. Strict policies must be implemented to control the use of smartphones in order to minimize the effects on mobile phone radiation on cognition. The media has to be on the forefront in educating the public about the proper usage of mobile phones. doi: https://doi.org/10.12669/pjms.36.7.2826 How to cite this:Al-khlaiwi TM, Habib SS, Meo SA, Alqhtani MS, Ogailan AA. The association of smart mobile phone usage with cognitive function impairment in Saudi adult population. Pak J Med Sci. 2020;36(7):---------. doi: https://doi.org/10.12669/pjms.36.7.2826 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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AUTHENTICATION OF FINGERPRINT BIOMETRICS ACQUIRED USING A CELLPHONE CAMERA: A REVIEW

International Journal of Wavelets Multiresolution and Information Processing ◽

10.1142/s0219691313500331 ◽

2013 ◽

Vol 11 (05) ◽

pp. 1350033 ◽

Cited By ~ 4

Author(s):

MOHAMMED S. KHALIL ◽

FAJRI KURNIAWAN ◽

KASHIF SALEEM

Keyword(s):

Mobile Phone ◽

Mobile Phones ◽

High Performance ◽

Personal Information ◽

Current Trend ◽

Recognition System ◽

Fingerprint Recognition ◽

Fingerprint Biometrics ◽

Smart Mobile Phone ◽

Smart Mobile

Over the past decade, there have been dramatic increases in the usage of mobile phones in the world. Currently available smart mobile phones are capable of storing enormous amounts of personal information/data. The smart mobile phone is also capable of connecting to other devices, with the help of different applications. Consequently, with these connections comes the requirement of security to protect personal information. Nowadays, in many applications, a biometric fingerprint recognition system has been embedded as a primary security measure. To enable a biometric fingerprint recognition system in smart mobile phones, without any additional costs, a built-in high performance camera can be utilized. The camera can capture the fingerprint image and generate biometric traits that qualify the biometric fingerprint authentication approach. However, the images acquired by a mobile phone are entirely different from the images obtained by dedicated fingerprint sensors. In this paper, we present the current trend in biometric fingerprint authentication techniques using mobile phones and explore some of the future possibilities in this field.

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Study and Analysis a Powerful Debug Method for Smart Mobile Systems

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.130-134.4270 ◽

2011 ◽

Vol 130-134 ◽

pp. 4270-4273

Author(s):

Jian Guo Yuan ◽

Sheng Gu

Keyword(s):

Complex Systems ◽

Mobile Phone ◽

Software Package ◽

Random Access ◽

Random Access Memory ◽

Exception Handling ◽

Mobile Systems ◽

Access Memory ◽

Smart Mobile Phone ◽

Smart Mobile

When dealing with such complex systems such as the software package of a smart mobile phone, it is necessary to apply powerful methods to detect and report errors when they occur. This paper probes and analyzes a powerful debug method called trap and exception handling, which is supported by the ARM platforms. The method can easily capture some valuable debug information. When a fatal error occurs during runtime or system detects an abnormal, a trap or an exception shall be logged and stored in the non-volatile random access memory (NVRAM). The information must be enough and easy for engineer to analyze the software error.

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