Wireless networks take advantage of various technologies that wired networks do not use , such as authentication and ad hoc networks . Although it is important to verify such wireless network technologies , it is expensive or technologically difficult to repeatedly reproduce the wireless environments required for verification . Ad-hoc networks have become a hot topic in the research world . Routing in ad-hoc networks has faced so many problems due to the peculiar nature of ad hoc environments . As nodes are connected by wireless links , its becomes easier for attacker to disrupt in the ad hoc networks . Therefore security is the major issue in ad hoc networks as compared to wired network . In this paper , we are discussing the various attacks which are possible in MANET due to fabrication and worm hole attack in AODV and how to secure AODV against wormhole attack using token based approach . Pisa , Italy e-mail : theofanis.raptis@iit.cnr.it © Springer International Publishing AG 2016 S. Nikoletseas et al. ( eds . ) , Wireless Power Transfer Algorithms , Technologies and Applications in Ad Hoc Communication Networks , DOI 10.1007/978 - 3 - 319 - 46810 - 5_18 465 466 C.M. Angelopoulos et al. 18 . Directional Antennas can be used instead of Omni-directional Antennas to reduce the collisions during data transmission , and thereby improve the network throughput . In this paper , we propose a PLBU Routing Protocol for Ad Hoc Communication Networks . Directional MAC Protocol has been used instead of 802.11 MAC , along with Power and Rate Control Mechanisms to help deal with the collision and interference problems among signals and simultaneously improve the Throughput by adapting to the channel behavior . We elaborate on two fundamental models for the emerging technology of Wireless Power Transfer in ad hoc communication networks . The first model is scalar , basically assuming that the received power by multiple transmitters is additive . Thispaperpresents anovel multiple access scheme called peripheral state sensemultiple access withinterference control forad-hoc networks . Theschemesetssomepredefined rules toallowseveral terminals totransmit simultaneously , andsoattains multiple-input multiple-output channel capacity . It explores the challenges on mobile computing and resource management paradigms , including research efforts and approaches recently carried out in response to them to address future open-ended issues . The book includes 26 rigorously refereed chapters written by leading international researchers , providing the readers with technical and scientific information about various aspects of mobile computing , from basic concepts to advanced findings , reporting the state-of-the-art on resource management in such environments . It is mainly intended as a reference guide for researchers and practitioners involved in the design , development and applications of mobile computing systems , seeking solutions to related issues . However , most of the research challenges have focused on typical scenarios existing in the developed economies . In this paper , we present research challenges and novelties in mobile computing domain that take account for differences between developing in particular India and developed economies . Our research is based on commonly available mobile platforms , communication cost , differences in user behavior and acceptable societal norms , among others . As industry and academia try to come up with viable approaches for exascale systems , attention turns to energy efficiency as the primary design consideration . At the same time , energy efficiency has always been the main concern in the mobile computing area . Additionally , mobile and consumer electronic devices are becoming ever more powerful as the use cases ( e.g. , Web 2.0 applications , video encoding , virtual and augmented reality ) become more computationally demanding . In this paper we will discuss one of these mobile devices which is Amazon kindle Fire . Being a new player in the mobile computing sector there have n't been enough studies of it in the field of digital forensics regarding it . In this paper we will discuss an imaging process to acquire the data from the device then we will provide an analysis of these data and their possible sources of evidence . Efficient channel allocation to mobile hosts aims to minimize the number of blocked hosts and is of utmost importance in a mobile computing network . Also , to achieve highly reliable data transmission , wireless mobile networks require efficient and reliable link connectivity regardless of terminal mobility , and thus reliable traffic performance . Upon reviewing the architecture for the network management system in a mobile computing network system and defining a protocol named SRRP , the scheme which can manage the mobile computing network system is presented to design the management system . Then , the software that follows the scheme is developed . The performance of a mobile computing network is depends on employed routing technique by the network and it also plays a significant role to improve the performance in Mobile computing network . In mobile computing network multiple data route exists for data transmission and data distributes on processing units through the most feasible route in order to achieve minimum transmission cost , time and maximum reliability . This research paper demonstrates a routing technique with the help of clusters to distribute data packets among the devices within the mobile computing network . In this paper , we present a set of strategies for reducing energy consumption in a multi-bank memory architecture using energy-conscious dynamic memory allocation/deallocation . Applications that make dynamic memory allocations are used very frequently in mobile computing/networking area . Our strategies focus on such applications and try to cluster dynamically created data with temporal affinity in the physical address space such that the data occupy a small number of memory banks . With the advancement in mobile computing technology , the capture devices and storage for video content become more and more mature and convenient . Live video identification and transmission are two prevalent and fashionable topics in mobile multimedia computing area . The growth of online video content raises new opportunities for the processing and delivery of the contents . The first part is developed the long-term planning method to tackle the challenge of load demand uncertainty in urban area ; the novel algorithm was developed to search for the optimal architecture of minimizing the capital expenditure ( CAPEX ) and the operation expenditure ( OPEX ) which respects to the set of topology and electrical ( current and voltage ) thank to mixed integer quadratically constrained programming ( MIQCP ) , shortest-path , first-fit bin-packing , and Monte-Carlo method . The second part is dealt with the extension of electricity coverage area with two possible solutions which are grid reinforcement and integration of PV-BES for rural village ; the Genetic algorithm ( GA ) and iterative technique were coded to search for location and sizing . The last part is concentrated on the planning of residential low-voltage distribution system in both rural and urban for non-electrified area thanks to the optimal architecture and PV-BES integration over the planning horizon . Subjects were instructed to locate routing signs in the scenes . Performance on the location task was used as a measure of the routing sign conspicuity . The results show that inserting an advertisement lessens the conspicuity of the routing information . We further develop Lagrangian relaxation methods and generate strengthening cuts by exploiting the structural properties of the problem to enhance computational efficiency for large-scale problems . Our numerical studies demonstrate that the proposed integrated model , which jointly optimizes location , allocation , and resource provisioning , can significantly reduce cost and improve quality-of-service when compared with a hierarchical approach that optimizes these decisions sequentially . Moreover , our proposed solution methods outperform state-of-the-art commercial software in computational performance . With the proliferation of wireless devices , it is important to understand how radio frequency interference ( RFI ) can impact on pervasive computing applications . In this article , we investigate the impact of RFI on device-free CSI-based location-oriented activity recognition . We present data to show that RFI can have a significant impact on the CSI vectors . In this paper , we present a new approach to derive groupings of mobile users based on their movement data . We assume that the user movement data are collected by logging location data emitted from mobile devices tracking users . We formally define group pattern as a group of users that are within a distance threshold from one another for at least a minimum duration . The project is mainly focused on both hardware and software . The project implements power theft detection and other management services such as voice announcement facility to the concerned department , finding the location of power theft , plotting GPS points in google maps , auto police complaint to the nearest police station , power theft location sharing to police and finally capturing photos remotely for proof of theft . Our project consists of SMS enabled application and voice-based application . This experiment using Hierarchical Finite State Machine to design the behavior of agents and refers to the scheme of supply chain management so that the behavior approach to the real world . Placement agent location coordinates using a scheme of supply chain approach to gravity location coordinates of the model in order to produce an optimal position so that the time and costs in the food distribution can be minimized . The results show the average percentage cost and time savings for 52.97 % and 48.47 % . In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems ( ITSs ) . ITSs are transport systems that utilise information and communication technologies to increase their level of automation , in this way levering the performance of such a system beyond the capabilities of the human driver . Therefore , conventional machine learning models may not perform well . In this paper , we propose an ensemble-based machine learning model , together with novel feature engineering techniques , for location tracking of passive RFID , which can work seamlessly with any supervised learning methods . The reader-based sub-models training method used in our model significantly reduces the training time by splitting our model into smaller sub-models and training them in parallel , which is desirable in real-world application . An approach to robust feature location in images that treats the feature sought as a collection of micro-features is discussed . The spatial responses of multilayer perceptrons trained on micro-features are interpreted as probability distributions conditional on the image data . The paper deals with the problem of time series classification for the feeding state of calves by means of features evaluated for acceleration real-time data sets . The eartags equipped with an active sensor were developed for location and animal activity identification . Video records synchronized with a sensor data were collected from three calves . A Scalable Infrastructure for Scoped Service Location in Ubiquitous Computing . Until recently , most efforts in service location have focused on finding local services . Location refinement . In order to improve location precision we follow : we add a location refinement FC layer after the FC7 and use the relative offsets from a scoremap location to the ground truth as targets . Regression to other parts . Inspired by the observation that a human glances at an image and instantly knows how many and where the objects are in the image , we formulate instance - aware clustering by parallelly inferring the instance number and pixel - wise instance location , discarding the requirement of time - consuming region proposal generation . We modify a same backbone architecture to incorporate two sibling branches as the generator of NAN for location - sensitive learning , where denotes the network parameters for the generator and denotes the pre - defined instance location coordinate number . As multi - scale features integrating both global and local contextual information are crucial for increasing location prediction accuracy , we further augment the pixel - wise instance location prediction branch with a M ulti - S cale F usion subsubsection : Implementation Details Throughout the experiments , the sizes of the RGB image , the semantic saliency prediction , inputs to the discriminator and inputs to the generator are fixed as ; the sizes of the instance - agnostic parsing prediction , instance - aware clustering prediction , inputs to the discriminator , inputs to the generator , inputs to the discriminator and instance location map are fixed as ; the channel number of the pixel - wise instance location map is fixed as , incorporating two corner points of the associated bounding box ; the constraint factors are empirically fixed as and , respectively ; the generator is initialized with FCN - 8s by replacing the last layer with a new convolutional layer with kernel size , pretrained on PASCAL - VOC - 2011 and finetuned on the target dataset ; the generator is initialized with WS - ResNet by eliminating the spatial pooling layers , increasing the strides of the first convolutional layers up to 2 in B , eliminating the top - most global pooling layer and the linear classifier , and adding two new convolutional layers with kernel sizes and , pretrained on ImageNet and PASCAL - VOC - 2012 , and finetuned on the target dataset ; the generator is initialized with the same backbone architecture and pre - trained weights with ( which are learned separately ) , by further augmenting it with two sibling branches for pixel - wise instance location map prediction and instance number prediction , where the first branch utilizes a MSFU ( three convolutional layers with kernal sizes for specific scale adaption ) ended with a convolutional layer with kernel size for multi - scale feature aggregation and a final convolutional layer with kernel size for location regression and the second branch utilizes the feature maps downsampled by 8 concatenated with the feature maps from the first branch ended with a global pooling layer , a hidden 512 - way fully - connected layer and a final 1 - way fully - connected layer for instance number regression ; the three discriminators ( which are learned separately ) are all initialized with a VGG - 16 by adding a new convolutional layer at the very begining with kernel size for input adaption , and replacing the last layer with a new 1 - way fully - connected layer activated by sigmoid , pre - trained on ImageNet and finetuned on the target dataset ; the newly added layers are randomly initialized by drawing weights from a zero - mean Gaussian distribution with standard deviation ; we employ an off - the - shelf clustering method to obtain the instance - aware clustering map ; the dropout ratio is empirically fixed as ; the weight decay and batch size are fixed as and , respectively ; We use an initial learning rate of for pre - trained layers , and for newly added layers in all our experiments ; we decrease the learning rate to of the previous one after 20 epochs and train the network for roughly 60 epochs one after the other ; the proposed network is implemented based on the publicly available TensorFlow platform , which is trained using Adam ( ) on four NVIDIA GeForce GTX TITAN X GPUs with 12 G memory ; the same training setting is utilized for all our compared network variants ; we evaluate the testing time by averaging the running time for images on the target set on NVIDIA GeForce GTX TITAN X GPU and Intel Core i7 - 4930 K CPU@3.40GHZ ; our NAN can rapidly process one image in about 1 second , which compares much favorably to other state - of - the - art approaches , as the current state - of - the - art methods rely on region proposal preprocessing and complex processing steps . subsubsection : Evaluation Metrics Objects in these categories are smaller and have fewer lidar points , so they benefit the most from high - resolution camera data . Although sparse lidar points often suffice in determining the spatial location of an object , image appearance features are still helpful in estimating the object dimensions and orientation . This effect is analyzed qualitatively below . Reading text in natural images is a challenging task under active research . It is driven by many real - world applications , such as Photo OCR , geo - location , and image retrieval . In a text reading system , text detection , i.e. localizing text with bounding boxes of words or text lines , is usually the first step of great significance . – ( [ reference ] ) , where and are vectors , and are matrices . We extend this content - based attention mechanism of the original model to be location - aware by making it take into account the alignment produced at the previous step . First , we extract vectors for every position of the previous alignment by convolving it with a matrix : These additional vectors are then used by the scoring mechanism : recalls . introduces Average Segmentation Accuracy ( ASA ) for joint detection and segmentation , and Average Location Precision ( ALP ) for joint detection and 3D location similar to AOS . We also use these metrics here . [ reference ][ reference ][ reference ] . Single - stage approaches : CascadeCNN [ reference ] proposes a strategy to detect face coarse to fine . A mutli - task learning method [ reference ] named MTCNN is present to predict face and landmark location simultaneously . Dense - Box [ reference ] employs a fully deep convolutional neural network to directly predict face confidence and corresponding bounding box . Recently , proposes a 2D - driven 3D object detection method that is similar to ours in spirit . However , they use hand - crafted features ( based on histogram of point coordinates ) with simple fully connected networks to regress 3D box location and pose , which is sub - optimal in both speed and performance . In contrast , we propose a more flexible and effective solution with deep 3D feature learning ( PointNets ) . Recognizing objects and estimating their poses in 3D has a wide range of applications in robotic tasks . For instance , recognizing the 3D location and orientation of objects is important for robot manipulation . It is also useful in human - robot interaction tasks such as learning from demonstration . Speed is main factor which affect the communication . This paper presents the critical analysis of various methods of location management based on various methodologies for mobile devices . It describes various techniques for location prediction and management . It reduces DAD dependency , scope for DoS attack and temporary address dependency . It reduces cost increases reliability , robustness and location management becomes easier . QoS improvement and recycling of address pool are also aimed at here . Massive increase in the mobile data traffic volume has recently resulted in a big interest towards the distributed mobility management solutions that aim to address the limitations and drawbacks of centralized mobility management . Location management is an important requirement in a distributed mobility management environment . To provide seamless Internet data services to a mobile node , the location of a mobile node is stored and periodically updated on a location server through a location update message that is sent by the mobile node . This work describes the neural network technique to solve location management problem . A multilayer neural model is designed to predict the future prediction of the subscriber based on the past predicted information of the subscriber . The basic service it provides is acknowledged exchange of short messages among subscribers or network-based servers . Like cellular/PCS systems , wireless two-way messaging systems are cellular in structure , and thus share the location management problem . We study the problem of location management for wireless two-way messaging . In this paper , we quantitatively analyze a hybrid replication with forwarding scheme that can be uniformly applied to all users . The most striking feature of the hybrid scheme is that it can determine and apply the optimal number of replicas and forwarding chain length on a per-user basis to minimize the communication cost due to location management operations while still being able to use the same data structure and algorithm to execute location management operations in a uniform way for all users . We develop a stochastic Petri net model to help gather this information and show how the information obtained statically can be used efficiently by the system at runtime to determine the optimal number of replicas and forwarding chain length when given a use user 's profile . Each one of those schemes has its own advantages and drawbacks . The route optimization solves the triangular route problem and the corresponding larger delay associated with the Base Mobile-IP with the expense of larger overhead for location management purposes . The Local Registration Mobile-IP scheme was introduced to enhance the performance by processing the MN 's registration requests at a local agent . To cope with an increasing number of subscribers , modern cellular telecommunication networks have been employing smaller , lower-power cells . The smaller diameter and larger number of these cells , however , result.in increased signaling requirements for location management purposes . Several location management schemes have been proposed to improve the performance of such networks , but a fair assessment and comparison of their performance is difftcult without a realistic mobility model , since the performance of location management schemes depends considerably on subscriber mobility patterns . In future cellular networks , tracking areas ( TAs ) that are defined for location management purposes will be frequently updated to cope with changes in user trends . In this paper , an automatic method for defining when and how to change an existing TA plan to minimize network signaling is presented . Since the LU cost is much higher than the cost of paging , this paper focuses on location management using LU only . A thorough study of different existing LU procedures of location management process in Personal Communication Service ( PCS ) network and its related research work are presented in this paper . The meaning of “ quality of flow ” in this context is not defined . This debate raises important epistemological questions for those working in lean construction and location-based management . While the concept of “ production flow quality ” is important , the Sacks et al. methodology does not address the detailed planning of individual crews . The growth of cellular subscribers and the increasing communication activities have generated a lot of signaling transactions in PCS network . In location management perspective , the effect of user mobility will affect signaling transactions in location update and paging operations . In this paper , we evaluate the impact of mobility activity and analyze the signaling activities in registration system : visitor location register and home location register . Thus , this mechanism that allows the sharing of functionality among different devices in same environment change the way of user communication for searching fast query time in mobile computing environment . The aim of this research is to make innovation in query optimization technique in mobile computing environment . This research focuses on improvement of various query optimization techniques for highly effective and trustworthy query optimization methods . This paper proposes " MobileSocket " which realizes session layer communication continuity support for Java Applications towards the continuous operations for mobile applications . In the mobile computing environment where mobile hosts move around the network even during communications with the remote , maintenance of the communication continuity between the applications is significant . Not only mobility support but virtual circuit continuity support is required for communication continuity . Data broadcast is an advanced technique to realize large scalability and bandwidth utilization in a mobile computing environment . In this environment , the channel bandwidth of each channel is variant with time in real cases . This success originates in the simplicity exhibited by programming along the client-server paradigm . Unfortunately , connectivity and bandwidth restrictions defy the unchanged porting of this well known mechanisms to the mobile computing field . In this paper we present an approach that allows to develop applications which are tailored for the specific requirement of mobile computing , while retaining the simple and well understood remote execution paradigm . Vehicular Ad hoc Network ( VANET ) is one of the emerging research areas in the mobile computing field which is considered as future technology and promising topic in computer science and computer networks . Which provides road safety , updated traffic information , and infotainment . Relational database can be replicated and distributed in the mobile computing scenario . To protect the ownership of the data and to trace the trail of data distribution , we devise a complex database watermark scheme . The framework assembles these units with a set of well-identified architectural design patterns . A mobile computing scenario illustrates the framework 's benefits . Context : Quality of Experience ( QoE ) enables the description of user perceptions about the performance of a particular application or service . In the mobile computing context , it is an important measure for service providers and users , since QoE makes it possible to improve it and make it more competitive to achieve user fidelity . In turn , the importance of QoE in mobile technologies increases due to the various factors that affect the applications that run on mobile devices . The realization of high-end mobile applications , such as virtual organization ( VO ) , are becoming reality due to the enhanced wireless communication bandwidth , reliability and services offered by WWW . However , the general-purpose operating systems are not completely capable to handle the challenges of mobile computing paradigm . The novel concept of mobile distributed virtual memory ( MDVM ) extends the server CPU and memory resources to the mobile clients over the mobile communication interface in the VO framework . We analyze the structure of the general algorithm of data mining , and classify the data mining technology in details , including more than 10 techniques of decision tree technology , neural network technology , rough set and fuzzy set . Finally , the research directions of data mining in artificial intelligence , e-commerce applications and mobile communication computing are discussed . 11n Integrated Heterogeneous Network and Performance Analysis of the Network . Advent of portable low cost smart & user friendly devices make the era of 21 century , the era of mobile communication & computing . So providing indoor , outdoor mobile facility has become a primary feature or condition [ 1 ] . With the popularity of wireless devices and the increase of computing and storage resources , there are increasing interests in supporting mobile computing techniques . Particularly , ad hoc networks can potentially connect different wireless devices to enable more powerful wireless applications and mobile computing capabilities . To meet the ever increasing communication need , it is important to improve the network throughput while guaranteeing transmission reliability . With the popularity of wireless devices and the increase of computing and storage resources , there are increasing interests in supporting mobile computing techniques . Particularly , ad hoc networks can potentially connect different wireless devices to enable more powerful wireless applications and mobile computing capabilities . To meet the ever increasing communication need , it is important to improve the network throughput while guaranteeing transmission reliability . To benefit from these physiological advantages , you must be pointing at the target directly with the finger itself , not using one or more fingers indirectly to control a cursor through a device such as a mouse or trackball . DESIGN FOR MOBILE COMPUTING Mobile computing introduces constraints on input devices that are not present in a workstation environment . Input devices can not be too large or expensive and they must be contained within the mobile unit ( e.g. laptop ) or easily attached to it .
Wireless networks take advantage of various technologies that wired networks do not use , such as authentication and ad hoc networks . Although it is important to verify such wireless network technologies , it is expensive or technologically difficult to repeatedly reproduce the wireless environments required for verification .
Ad-hoc networks have become a hot topic in the research world . Routing in ad-hoc networks has faced so many problems due to the peculiar nature of ad hoc environments .
As nodes are connected by wireless links , its becomes easier for attacker to disrupt in the ad hoc networks . Therefore security is the major issue in ad hoc networks as compared to wired network . In this paper , we are discussing the various attacks which are possible in MANET due to fabrication and worm hole attack in AODV and how to secure AODV against wormhole attack using token based approach .
Pisa , Italy e-mail : theofanis.raptis@iit.cnr.it © Springer International Publishing AG 2016 S. Nikoletseas et al. ( eds . ) , Wireless Power Transfer Algorithms , Technologies and Applications in Ad Hoc Communication Networks , DOI 10.1007/978 - 3 - 319 - 46810 - 5_18 465 466 C.M. Angelopoulos et al. 18 .
Directional Antennas can be used instead of Omni-directional Antennas to reduce the collisions during data transmission , and thereby improve the network throughput . In this paper , we propose a PLBU Routing Protocol for Ad Hoc Communication Networks . Directional MAC Protocol has been used instead of 802.11 MAC , along with Power and Rate Control Mechanisms to help deal with the collision and interference problems among signals and simultaneously improve the Throughput by adapting to the channel behavior .
We elaborate on two fundamental models for the emerging technology of Wireless Power Transfer in ad hoc communication networks . The first model is scalar , basically assuming that the received power by multiple transmitters is additive .
Thispaperpresents anovel multiple access scheme called peripheral state sensemultiple access withinterference control forad-hoc networks . Theschemesetssomepredefined rules toallowseveral terminals totransmit simultaneously , andsoattains multiple-input multiple-output channel capacity .
It explores the challenges on mobile computing and resource management paradigms , including research efforts and approaches recently carried out in response to them to address future open-ended issues . The book includes 26 rigorously refereed chapters written by leading international researchers , providing the readers with technical and scientific information about various aspects of mobile computing , from basic concepts to advanced findings , reporting the state-of-the-art on resource management in such environments . It is mainly intended as a reference guide for researchers and practitioners involved in the design , development and applications of mobile computing systems , seeking solutions to related issues .
However , most of the research challenges have focused on typical scenarios existing in the developed economies . In this paper , we present research challenges and novelties in mobile computing domain that take account for differences between developing in particular India and developed economies . Our research is based on commonly available mobile platforms , communication cost , differences in user behavior and acceptable societal norms , among others .
As industry and academia try to come up with viable approaches for exascale systems , attention turns to energy efficiency as the primary design consideration . At the same time , energy efficiency has always been the main concern in the mobile computing area . Additionally , mobile and consumer electronic devices are becoming ever more powerful as the use cases ( e.g. , Web 2.0 applications , video encoding , virtual and augmented reality ) become more computationally demanding .
In this paper we will discuss one of these mobile devices which is Amazon kindle Fire . Being a new player in the mobile computing sector there have n't been enough studies of it in the field of digital forensics regarding it . In this paper we will discuss an imaging process to acquire the data from the device then we will provide an analysis of these data and their possible sources of evidence .
Efficient channel allocation to mobile hosts aims to minimize the number of blocked hosts and is of utmost importance in a mobile computing network . Also , to achieve highly reliable data transmission , wireless mobile networks require efficient and reliable link connectivity regardless of terminal mobility , and thus reliable traffic performance .
Upon reviewing the architecture for the network management system in a mobile computing network system and defining a protocol named SRRP , the scheme which can manage the mobile computing network system is presented to design the management system . Then , the software that follows the scheme is developed .
The performance of a mobile computing network is depends on employed routing technique by the network and it also plays a significant role to improve the performance in Mobile computing network . In mobile computing network multiple data route exists for data transmission and data distributes on processing units through the most feasible route in order to achieve minimum transmission cost , time and maximum reliability . This research paper demonstrates a routing technique with the help of clusters to distribute data packets among the devices within the mobile computing network .
In this paper , we present a set of strategies for reducing energy consumption in a multi-bank memory architecture using energy-conscious dynamic memory allocation/deallocation . Applications that make dynamic memory allocations are used very frequently in mobile computing/networking area . Our strategies focus on such applications and try to cluster dynamically created data with temporal affinity in the physical address space such that the data occupy a small number of memory banks .
With the advancement in mobile computing technology , the capture devices and storage for video content become more and more mature and convenient . Live video identification and transmission are two prevalent and fashionable topics in mobile multimedia computing area . The growth of online video content raises new opportunities for the processing and delivery of the contents .
The first part is developed the long-term planning method to tackle the challenge of load demand uncertainty in urban area ; the novel algorithm was developed to search for the optimal architecture of minimizing the capital expenditure ( CAPEX ) and the operation expenditure ( OPEX ) which respects to the set of topology and electrical ( current and voltage ) thank to mixed integer quadratically constrained programming ( MIQCP ) , shortest-path , first-fit bin-packing , and Monte-Carlo method . The second part is dealt with the extension of electricity coverage area with two possible solutions which are grid reinforcement and integration of PV-BES for rural village ; the Genetic algorithm ( GA ) and iterative technique were coded to search for location and sizing . The last part is concentrated on the planning of residential low-voltage distribution system in both rural and urban for non-electrified area thanks to the optimal architecture and PV-BES integration over the planning horizon .
Subjects were instructed to locate routing signs in the scenes . Performance on the location task was used as a measure of the routing sign conspicuity . The results show that inserting an advertisement lessens the conspicuity of the routing information .
We further develop Lagrangian relaxation methods and generate strengthening cuts by exploiting the structural properties of the problem to enhance computational efficiency for large-scale problems . Our numerical studies demonstrate that the proposed integrated model , which jointly optimizes location , allocation , and resource provisioning , can significantly reduce cost and improve quality-of-service when compared with a hierarchical approach that optimizes these decisions sequentially . Moreover , our proposed solution methods outperform state-of-the-art commercial software in computational performance .
With the proliferation of wireless devices , it is important to understand how radio frequency interference ( RFI ) can impact on pervasive computing applications . In this article , we investigate the impact of RFI on device-free CSI-based location-oriented activity recognition . We present data to show that RFI can have a significant impact on the CSI vectors .
In this paper , we present a new approach to derive groupings of mobile users based on their movement data . We assume that the user movement data are collected by logging location data emitted from mobile devices tracking users . We formally define group pattern as a group of users that are within a distance threshold from one another for at least a minimum duration .
The project is mainly focused on both hardware and software . The project implements power theft detection and other management services such as voice announcement facility to the concerned department , finding the location of power theft , plotting GPS points in google maps , auto police complaint to the nearest police station , power theft location sharing to police and finally capturing photos remotely for proof of theft . Our project consists of SMS enabled application and voice-based application .
This experiment using Hierarchical Finite State Machine to design the behavior of agents and refers to the scheme of supply chain management so that the behavior approach to the real world . Placement agent location coordinates using a scheme of supply chain approach to gravity location coordinates of the model in order to produce an optimal position so that the time and costs in the food distribution can be minimized . The results show the average percentage cost and time savings for 52.97 % and 48.47 % .
In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems ( ITSs ) . ITSs are transport systems that utilise information and communication technologies to increase their level of automation , in this way levering the performance of such a system beyond the capabilities of the human driver .
Therefore , conventional machine learning models may not perform well . In this paper , we propose an ensemble-based machine learning model , together with novel feature engineering techniques , for location tracking of passive RFID , which can work seamlessly with any supervised learning methods . The reader-based sub-models training method used in our model significantly reduces the training time by splitting our model into smaller sub-models and training them in parallel , which is desirable in real-world application .
An approach to robust feature location in images that treats the feature sought as a collection of micro-features is discussed . The spatial responses of multilayer perceptrons trained on micro-features are interpreted as probability distributions conditional on the image data .
The paper deals with the problem of time series classification for the feeding state of calves by means of features evaluated for acceleration real-time data sets . The eartags equipped with an active sensor were developed for location and animal activity identification . Video records synchronized with a sensor data were collected from three calves .
A Scalable Infrastructure for Scoped Service Location in Ubiquitous Computing . Until recently , most efforts in service location have focused on finding local services .
Location refinement . In order to improve location precision we follow : we add a location refinement FC layer after the FC7 and use the relative offsets from a scoremap location to the ground truth as targets . Regression to other parts .
Inspired by the observation that a human glances at an image and instantly knows how many and where the objects are in the image , we formulate instance - aware clustering by parallelly inferring the instance number and pixel - wise instance location , discarding the requirement of time - consuming region proposal generation . We modify a same backbone architecture to incorporate two sibling branches as the generator of NAN for location - sensitive learning , where denotes the network parameters for the generator and denotes the pre - defined instance location coordinate number . As multi - scale features integrating both global and local contextual information are crucial for increasing location prediction accuracy , we further augment the pixel - wise instance location prediction branch with a M ulti - S cale F usion
subsubsection : Implementation Details Throughout the experiments , the sizes of the RGB image , the semantic saliency prediction , inputs to the discriminator and inputs to the generator are fixed as ; the sizes of the instance - agnostic parsing prediction , instance - aware clustering prediction , inputs to the discriminator , inputs to the generator , inputs to the discriminator and instance location map are fixed as ; the channel number of the pixel - wise instance location map is fixed as , incorporating two corner points of the associated bounding box ; the constraint factors are empirically fixed as and , respectively ; the generator is initialized with FCN - 8s by replacing the last layer with a new convolutional layer with kernel size , pretrained on PASCAL - VOC - 2011 and finetuned on the target dataset ; the generator is initialized with WS - ResNet by eliminating the spatial pooling layers , increasing the strides of the first convolutional layers up to 2 in B , eliminating the top - most global pooling layer and the linear classifier , and adding two new convolutional layers with kernel sizes and , pretrained on ImageNet and PASCAL - VOC - 2012 , and finetuned on the target dataset ; the generator is initialized with the same backbone architecture and pre - trained weights with ( which are learned separately ) , by further augmenting it with two sibling branches for pixel - wise instance location map prediction and instance number prediction , where the first branch utilizes a MSFU ( three convolutional layers with kernal sizes for specific scale adaption ) ended with a convolutional layer with kernel size for multi - scale feature aggregation and a final convolutional layer with kernel size for location regression and the second branch utilizes the feature maps downsampled by 8 concatenated with the feature maps from the first branch ended with a global pooling layer , a hidden 512 - way fully - connected layer and a final 1 - way fully - connected layer for instance number regression ; the three discriminators ( which are learned separately ) are all initialized with a VGG - 16 by adding a new convolutional layer at the very begining with kernel size for input adaption , and replacing the last layer with a new 1 - way fully - connected layer activated by sigmoid , pre - trained on ImageNet and finetuned on the target dataset ; the newly added layers are randomly initialized by drawing weights from a zero - mean Gaussian distribution with standard deviation ; we employ an off - the - shelf clustering method to obtain the instance - aware clustering map ; the dropout ratio is empirically fixed as ; the weight decay and batch size are fixed as and , respectively ; We use an initial learning rate of for pre - trained layers , and for newly added layers in all our experiments ; we decrease the learning rate to of the previous one after 20 epochs and train the network for roughly 60 epochs one after the other ; the proposed network is implemented based on the publicly available TensorFlow platform , which is trained using Adam ( ) on four NVIDIA GeForce GTX TITAN X GPUs with 12 G memory ; the same training setting is utilized for all our compared network variants ; we evaluate the testing time by averaging the running time for images on the target set on NVIDIA GeForce GTX TITAN X GPU and Intel Core i7 - 4930 K CPU@3.40GHZ ; our NAN can rapidly process one image in about 1 second , which compares much favorably to other state - of - the - art approaches , as the current state - of - the - art methods rely on region proposal preprocessing and complex processing steps . subsubsection : Evaluation Metrics
Objects in these categories are smaller and have fewer lidar points , so they benefit the most from high - resolution camera data . Although sparse lidar points often suffice in determining the spatial location of an object , image appearance features are still helpful in estimating the object dimensions and orientation . This effect is analyzed qualitatively below .
Reading text in natural images is a challenging task under active research . It is driven by many real - world applications , such as Photo OCR , geo - location , and image retrieval . In a text reading system , text detection , i.e. localizing text with bounding boxes of words or text lines , is usually the first step of great significance .
– ( [ reference ] ) , where and are vectors , and are matrices . We extend this content - based attention mechanism of the original model to be location - aware by making it take into account the alignment produced at the previous step . First , we extract vectors for every position of the previous alignment by convolving it with a matrix : These additional vectors are then used by the scoring mechanism :
recalls . introduces Average Segmentation Accuracy ( ASA ) for joint detection and segmentation , and Average Location Precision ( ALP ) for joint detection and 3D location similar to AOS . We also use these metrics here .
[ reference ][ reference ][ reference ] . Single - stage approaches : CascadeCNN [ reference ] proposes a strategy to detect face coarse to fine . A mutli - task learning method [ reference ] named MTCNN is present to predict face and landmark location simultaneously . Dense - Box [ reference ] employs a fully deep convolutional neural network to directly predict face confidence and corresponding bounding box .
Recently , proposes a 2D - driven 3D object detection method that is similar to ours in spirit . However , they use hand - crafted features ( based on histogram of point coordinates ) with simple fully connected networks to regress 3D box location and pose , which is sub - optimal in both speed and performance . In contrast , we propose a more flexible and effective solution with deep 3D feature learning ( PointNets ) .
Recognizing objects and estimating their poses in 3D has a wide range of applications in robotic tasks . For instance , recognizing the 3D location and orientation of objects is important for robot manipulation . It is also useful in human - robot interaction tasks such as learning from demonstration .
Speed is main factor which affect the communication . This paper presents the critical analysis of various methods of location management based on various methodologies for mobile devices . It describes various techniques for location prediction and management .
It reduces DAD dependency , scope for DoS attack and temporary address dependency . It reduces cost increases reliability , robustness and location management becomes easier . QoS improvement and recycling of address pool are also aimed at here .
Massive increase in the mobile data traffic volume has recently resulted in a big interest towards the distributed mobility management solutions that aim to address the limitations and drawbacks of centralized mobility management . Location management is an important requirement in a distributed mobility management environment . To provide seamless Internet data services to a mobile node , the location of a mobile node is stored and periodically updated on a location server through a location update message that is sent by the mobile node .
This work describes the neural network technique to solve location management problem . A multilayer neural model is designed to predict the future prediction of the subscriber based on the past predicted information of the subscriber .
The basic service it provides is acknowledged exchange of short messages among subscribers or network-based servers . Like cellular/PCS systems , wireless two-way messaging systems are cellular in structure , and thus share the location management problem . We study the problem of location management for wireless two-way messaging .
In this paper , we quantitatively analyze a hybrid replication with forwarding scheme that can be uniformly applied to all users . The most striking feature of the hybrid scheme is that it can determine and apply the optimal number of replicas and forwarding chain length on a per-user basis to minimize the communication cost due to location management operations while still being able to use the same data structure and algorithm to execute location management operations in a uniform way for all users . We develop a stochastic Petri net model to help gather this information and show how the information obtained statically can be used efficiently by the system at runtime to determine the optimal number of replicas and forwarding chain length when given a use user 's profile .
Each one of those schemes has its own advantages and drawbacks . The route optimization solves the triangular route problem and the corresponding larger delay associated with the Base Mobile-IP with the expense of larger overhead for location management purposes . The Local Registration Mobile-IP scheme was introduced to enhance the performance by processing the MN 's registration requests at a local agent .
To cope with an increasing number of subscribers , modern cellular telecommunication networks have been employing smaller , lower-power cells . The smaller diameter and larger number of these cells , however , result.in increased signaling requirements for location management purposes . Several location management schemes have been proposed to improve the performance of such networks , but a fair assessment and comparison of their performance is difftcult without a realistic mobility model , since the performance of location management schemes depends considerably on subscriber mobility patterns .
In future cellular networks , tracking areas ( TAs ) that are defined for location management purposes will be frequently updated to cope with changes in user trends . In this paper , an automatic method for defining when and how to change an existing TA plan to minimize network signaling is presented .
Since the LU cost is much higher than the cost of paging , this paper focuses on location management using LU only . A thorough study of different existing LU procedures of location management process in Personal Communication Service ( PCS ) network and its related research work are presented in this paper .
The meaning of “ quality of flow ” in this context is not defined . This debate raises important epistemological questions for those working in lean construction and location-based management . While the concept of “ production flow quality ” is important , the Sacks et al. methodology does not address the detailed planning of individual crews .
The growth of cellular subscribers and the increasing communication activities have generated a lot of signaling transactions in PCS network . In location management perspective , the effect of user mobility will affect signaling transactions in location update and paging operations . In this paper , we evaluate the impact of mobility activity and analyze the signaling activities in registration system : visitor location register and home location register .
Thus , this mechanism that allows the sharing of functionality among different devices in same environment change the way of user communication for searching fast query time in mobile computing environment . The aim of this research is to make innovation in query optimization technique in mobile computing environment . This research focuses on improvement of various query optimization techniques for highly effective and trustworthy query optimization methods .
This paper proposes " MobileSocket " which realizes session layer communication continuity support for Java Applications towards the continuous operations for mobile applications . In the mobile computing environment where mobile hosts move around the network even during communications with the remote , maintenance of the communication continuity between the applications is significant . Not only mobility support but virtual circuit continuity support is required for communication continuity .
Data broadcast is an advanced technique to realize large scalability and bandwidth utilization in a mobile computing environment . In this environment , the channel bandwidth of each channel is variant with time in real cases .
This success originates in the simplicity exhibited by programming along the client-server paradigm . Unfortunately , connectivity and bandwidth restrictions defy the unchanged porting of this well known mechanisms to the mobile computing field . In this paper we present an approach that allows to develop applications which are tailored for the specific requirement of mobile computing , while retaining the simple and well understood remote execution paradigm .
Vehicular Ad hoc Network ( VANET ) is one of the emerging research areas in the mobile computing field which is considered as future technology and promising topic in computer science and computer networks . Which provides road safety , updated traffic information , and infotainment .
Relational database can be replicated and distributed in the mobile computing scenario . To protect the ownership of the data and to trace the trail of data distribution , we devise a complex database watermark scheme .
The framework assembles these units with a set of well-identified architectural design patterns . A mobile computing scenario illustrates the framework 's benefits .
Context : Quality of Experience ( QoE ) enables the description of user perceptions about the performance of a particular application or service . In the mobile computing context , it is an important measure for service providers and users , since QoE makes it possible to improve it and make it more competitive to achieve user fidelity . In turn , the importance of QoE in mobile technologies increases due to the various factors that affect the applications that run on mobile devices .
The realization of high-end mobile applications , such as virtual organization ( VO ) , are becoming reality due to the enhanced wireless communication bandwidth , reliability and services offered by WWW . However , the general-purpose operating systems are not completely capable to handle the challenges of mobile computing paradigm . The novel concept of mobile distributed virtual memory ( MDVM ) extends the server CPU and memory resources to the mobile clients over the mobile communication interface in the VO framework .
We analyze the structure of the general algorithm of data mining , and classify the data mining technology in details , including more than 10 techniques of decision tree technology , neural network technology , rough set and fuzzy set . Finally , the research directions of data mining in artificial intelligence , e-commerce applications and mobile communication computing are discussed .
11n Integrated Heterogeneous Network and Performance Analysis of the Network . Advent of portable low cost smart & user friendly devices make the era of 21 century , the era of mobile communication & computing . So providing indoor , outdoor mobile facility has become a primary feature or condition [ 1 ] .
With the popularity of wireless devices and the increase of computing and storage resources , there are increasing interests in supporting mobile computing techniques . Particularly , ad hoc networks can potentially connect different wireless devices to enable more powerful wireless applications and mobile computing capabilities . To meet the ever increasing communication need , it is important to improve the network throughput while guaranteeing transmission reliability .
With the popularity of wireless devices and the increase of computing and storage resources , there are increasing interests in supporting mobile computing techniques . Particularly , ad hoc networks can potentially connect different wireless devices to enable more powerful wireless applications and mobile computing capabilities . To meet the ever increasing communication need , it is important to improve the network throughput while guaranteeing transmission reliability .
To benefit from these physiological advantages , you must be pointing at the target directly with the finger itself , not using one or more fingers indirectly to control a cursor through a device such as a mouse or trackball . DESIGN FOR MOBILE COMPUTING Mobile computing introduces constraints on input devices that are not present in a workstation environment . Input devices can not be too large or expensive and they must be contained within the mobile unit ( e.g. laptop ) or easily attached to it .
NETorium: high-fidelity scalable wireless network emulator Zone-based Proactive Source Routing Protocol for Ad-hoc Networks Securing AODV against Wormhole Attack using Token based Approach Wireless Power Transfer in Sensor Networks with Adaptive, Limited Knowledge Protocols Design of Plbu Routing Protocol Using Directional Antennas for Emergency Ad Hoc Networks Towards more Realistic Models for Wireless Power Transfer Algorithm Design Peripheral-state SenseMultiple Access Interference Control (PSMAIIC) forDistributed Radio ResourceManagement Resource Management in Mobile Computing Environments Challenges and novelties while using mobile phones as ICT devices for Indian masses: short paper Towards Energy Efficient Parallel Computing on Consumer Electronic Devices Amazon Kindle Fire from a Digital Forensics Perspective Multi-objective optimization for channel allocation in mobile computing using NSGA-II Network management system based on SNMP in the mobile computing network CLUSTER BASED ROUTING MECHANISM FOR OPTIMIZED DATA DISTRIBUTION IN MOBILE COMPUTING Energy-Conscious Memory Allocation and Deallocation for Pointer-Intensive Applications Live video identification and transmission over wireless network Planification du réseau de distribution basse tension avec intégration de sources photovoltaïques et stockage : cas du réseau du Cambodge The influence of advertisements on the conspicuity of routing information. Data Center Network Design for Internet-Related Services and Cloud Computing From Real to Complex: Enhancing Radio-based Activity Recognition Using Complex-Valued CSI Efficient mining of group patterns from user movement data Smart grid and smart transformer powered by IoT Supply chain management untuk agen game RTS menggunakan HFSM Location-based forwarding in vehicular networks Ensemble-Based Location Tracking Using Passive RFID Facial feature location using multilayer perceptrons and micro-features Automated Classification of a Calf’s Feeding State Based on Data Collected by Active Sensors with 3D-Accelerometer Regions: A Scalable Infrastructure for Scoped Service Location in Ubiquitous Computing DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation Detecting Oriented Text in Natural Images by Linking Segments Attention-Based Models for Speech Recognition Subcategory-Aware Convolutional Neural Networks for Object Proposals and Detection Face Detection Using Improved Faster RCNN Frustum PointNets for 3D Object Detection from RGB-D Data PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes Critical Analysis of Recent Location Management Methods in Mobile Computing Environment Mobile-autoconf: Mobility management with autoconfiguration in mobile ad-hoc networks Intelligent Reduction in Signaling Load of Location Management in Mobile Data Networks Location Prediction of Mobility Management Using Soft Computing Techniques in Cellular Network Update and search algorithms for wireless two-way messaging: design and performance Quantitative Analysis of a Hybrid Replication with Forwarding Strategy for Efficient and Uniform Location Management in Mobile Wireless Networks Supporting reduced location management overhead and fault tolerance in Mobile-IP systems An activity-based mobility model and location management simulation framework Automatic Replanning of Tracking Areas in Cellular Networks Overview on Location Management in PCS Network: A Survey CME Forum: a response to “Construction flow index: a metric of production flow quality in construction” Evaluation of distance-based location update and sequential paging in PCS registration system Advanced query processing and its optimization for mobile computing environment MobileSocket: toward continuous operation for Java applications A General Framework of Time-Variant Bandwidth Allocation in the Data Broadcasting Environment Delegating Remote Operation Execution in a Mobile Computing Environment An Improved CF-MAC Protocol for VANET Tracing Mobile Database with Complex Watermark Software Architecture Patterns for a Context-Processing Middleware Framework Quality of Experience in Mobile Applications: A Systematic Mapping of Metrics and Tools Design Architecture and Model of MDVM System Intelligent computing system based on pattern recognition and data mining algorithms Design of IEEE 802. 16m and IEEE 802. 11n Integrated Heterogeneous Network and Performance Analysis of the Network Exploiting Cooperative Relay for High Performance Communications in MIMO Ad Hoc Networks Adaptive exploitation of cooperative relay for high performance communications in MIMO ad hoc networks A finger-mounted, direct pointing device for mobile computing
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AINTEC Wireless Power Transfer Algorithms, Technologies and Applications in Ad Hoc Communication Networks DCOSS Resource Management in Mobile Computing Environments NSDR ICT-GLOW CyberC EMSOFT DSAA 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ArXiv 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) NIPS 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) ArXiv 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Robotics: Science and Systems INFOCOM ISCC ICCCN INTELLCOMM MASS ACM Symposium on User Interface Software and Technology
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