Monkey and cell-phone-user mobilities scale similarly

2010 ◽  
Vol 6 (12) ◽  
pp. 929-930 ◽  
Author(s):  
Peter D. Walsh ◽  
Denis Boyer ◽  
Margaret C. Crofoot
Keyword(s):  
Cell Phone ◽  
Phone User

scholarly journals Deep Learning applied to the handoff of cellular systems: a survey

2019 ◽  
Author(s):  
Federico Aguirre
Keyword(s):  
Deep Learning ◽  
Cell Phone ◽  
State Of The Art ◽  
Base Station ◽  
Cellular Systems ◽  
Coverage Area ◽  
Learning Techniques ◽  
A Cell ◽  
Spatio Temporal ◽  
Phone User

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Times New Roman'; min-height: 15.0px} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px 'Times New Roman'} span.s1 {font: 12.0px 'Times New Roman'} <p><br></p> <p> <b>Mobility is a key aspect in current cellular networks, allowing users to access the provided services almost anywhere. When a user transitions from a base station’s coverage area to another cell being serviced by another station, a handoff process takes place, where resources are released in the first base station, and allocated in the second for the purpose of servicing the user. Predicting the future location of a cell phone user allows the handoff process to be optimized. This optimization allows for a better utilization of the available resources, regarding bot the transmitted power and the frequency allocation, resulting in less amount of wasted power in unwanted directions and the possibility of reusing frequencies in a single base station. To achieve this goal, Deep Learning techniques are proposed, which have proven to be efficient tools for predicting and detecting patterns. The purpose of this paper is to give an overview of the state of the art in Deep Learning techniques for making spatio-temporal predictions, which could be used to optimize the handoff process in cellular systems. </b></p>

scholarly journals Use of Cell Phone in Receiving Agricultural Information by the Farmers

2019 ◽  
Vol 3 (1) ◽  
pp. 19
Author(s):  
Sk. Md. Nur-E-Alam ◽  
Md. Sekender Ali ◽  
M. Zahidul Haque
Keyword(s):  
Cell Phone ◽  
Positive Relationship ◽  
Family Income ◽  
Negative Relationship ◽  
Farm Size ◽  
Face To Face ◽  
Organizational Participation ◽  
Significant Negative Relationship ◽  
Phone User ◽  
The Relationship

Cell phone is an easy, fast and convenient device for communication. The main purpose of the study was to determine the extent of use of Cell Phone in receiving agricultural information and to explore the relationship between the selected characteristics of the farmers in using Cell Phone for receiving agricultural information. Data were obtained from 97 Cell Phone user farmers in selected village named Chorjamalpur of Boyra union under Singair upazila of Manikganj through face-to-face interview. Appropriate scales were developed in order to measure the concerned variables. Pearson Product Moment Correlation test was used to ascertain the relationship between each of the selected characteristics of the farmers with their use of Cell Phone for receiving agricultural information. The finding shows that 89.7 percent of the respondents had no use to low use of Cell Phone for receiving agricultural information and 10.3 percent of the respondents had medium use to high use of Cell Phone for receiving agricultural information. The finding clearly indicates the ignorance of the respondents about the use of Cell Phone for receiving agricultural information. Among 11 selected characteristics of the farmers, eight characteristics namely, education, land possession, effective farm size, annual family income, agricultural training exposure, organizational participation, innovativeness, cosmopoliteness showed significant and positive relationship with their use of Cell Phone. Problem confrontation of the farmers in using Cell Phone showed significant negative relationship with their use of Cell Phone for receiving agricultural information. But age of the farmers and farming experience of the farmers showed non significant relationship with the use of Cell Phone by the farmers.

scholarly journals The influence of cell phone users' relationship intentions on expectations and perceptions of service recovery

2015 ◽  
Vol 46 (1) ◽  
pp. 57-69 ◽  
Author(s):  
L. Kruger ◽  
P. G. Mostert
Keyword(s):  
South African ◽  
Cell Phone ◽  
Service Failure ◽  
Service Recovery ◽  
Service Failures ◽  
Service Failure And Recovery ◽  
Phone User ◽  
First Time ◽  
Moderate Relationship

With the first-time cell phone user market quickly shrinking, it is becoming increasingly important for South African cell phone network providers to retain customers by building long-term relationships with them and consistently offering quality service. Despite cell phone network providers' best intentions, service failures do occur. Not all customers want to build relationships with cell phone network providers, and therefore it is important to consider the influence of customers' relationship intentions within a service failure and recovery setting. The purpose of the study was to determine the influence of relationship intention on expectations and perceptions of two service recovery scenarios within the cell phone industry. Non-probability convenience sampling was used to collect data from 605 cell phone users residing in Gauteng. Results indicate that as respondents' relationship intentions increase, so do their expectations that their cell phone network providers should take service recovery action. It was also found that respondents with high and moderate relationship intentions perceived service recovery strategies of their cell phone network providers including an acknowledgement, apology, explanation and rectification of the problem more favourable, compared to a service recovery strategy only rectifying the problem, than those respondents with low relationship intentions.

scholarly journals Deep Learning applied to the handoff of cellular systems: a survey

2019 ◽  
Author(s):  
Federico Aguirre
Keyword(s):  
Deep Learning ◽  
Cell Phone ◽  
State Of The Art ◽  
Base Station ◽  
Cellular Systems ◽  
Coverage Area ◽  
Learning Techniques ◽  
A Cell ◽  
Spatio Temporal ◽  
Phone User

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Times New Roman'; min-height: 15.0px} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px 'Times New Roman'} span.s1 {font: 12.0px 'Times New Roman'} <p><br></p> <p> <b>Mobility is a key aspect in current cellular networks, allowing users to access the provided services almost anywhere. When a user transitions from a base station’s coverage area to another cell being serviced by another station, a handoff process takes place, where resources are released in the first base station, and allocated in the second for the purpose of servicing the user. Predicting the future location of a cell phone user allows the handoff process to be optimized. This optimization allows for a better utilization of the available resources, regarding bot the transmitted power and the frequency allocation, resulting in less amount of wasted power in unwanted directions and the possibility of reusing frequencies in a single base station. To achieve this goal, Deep Learning techniques are proposed, which have proven to be efficient tools for predicting and detecting patterns. The purpose of this paper is to give an overview of the state of the art in Deep Learning techniques for making spatio-temporal predictions, which could be used to optimize the handoff process in cellular systems. </b></p>

Systematic evaluation methodology for cell phone user interfaces

2006 ◽  
Vol 18 (2) ◽  
pp. 304-325 ◽  
Author(s):  
Young Seok Lee ◽  
Sang W. Hong ◽  
Tonya L. Smith-Jackson ◽  
Maury A. Nussbaum ◽  
Kei Tomioka
Keyword(s):  
User Interfaces ◽  
Cell Phone ◽  
Evaluation Methodology ◽  
Systematic Evaluation ◽  
Phone User
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