Real Time Detection, Tracking and Recognition of Medication Intake

In this paper, the detection and tracking of face, mouth, hands and medication bottles in the context of medication intake monitoring with a camera is presented. This is aimed at recognizing medication intake for elderly in their home setting to avoid an inappropriate use. Background subtraction is used to isolate moving objects, and then, skin and bottle segmentations are done in the RGB normalized color space. We use a minimum displacement distance criterion to track skin color regions and the R/G ratio to detect the mouth. The color-labeled medication bottles are simply tracked based on the color space distance to their mean color vector. For the recognition of medication intake, we propose a three-level hierarchal approach, which uses activity-patterns to recognize the normal medication intake activity. The proposed method was tested with three persons, with different medication intake scenarios, and gave an overall precision of over 98%.

Coordination for Synchronous Cooperative Systems Based on Fuzzy Causal Relations

Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.

Radio over Fiber as a Cost Effective Technology for Transmission of WiMAX Signals

In this paper, an overview of the radio over fiber (RoF) technology is provided. Obstacles for reducing the capital and operational expenses in the existing systems are discussed in various perspectives. Some possible RoF deployment scenarios for WiMAX data transmission are proposed as a means for capital and operational expenses reduction. IEEE 802.16a standard based end-to-end physical layer model is simulated including intensity modulated direct detection RoF technology. Finally the feasibility of RoF technology to carry WiMAX signals between the base station and the remote antenna units is demonstrated using the simulation results.

Land Reclamation Using Waste as Fill Material: A Case Study in Jakarta

To coop with urbanization issues and the economic need for expansion, the city of Jakarta is planning to reclaim more land in the Jakarta Bay. However, the reclamation activities of some islands have barely started and already the developers are facing difficulties in finding sufficient quantities of sand as fill material. When addressing the problem of sand scarcity in the case of Jakarta where, an excess of waste production, an inadequate solid waste management system and a lack of dumping ground pose a major problem, it is hard not to think of the use of waste as alternative fill material. This paper analyses the possibilities of using waste in the land reclamation projects, considering the governmental, social, environmental and economic context of the city. The results identify types of waste that could be used, ways of using those types of waste and implementation conditions for the city of Jakarta.

Autonomous Control of a Mobile Manipulator

This paper considers the design of a motion planner that will simultaneously accomplish control and motion planning of a n-link nonholonomic mobile manipulator, wherein, a n-link holonomic manipulator is coupled with a nonholonomic mobile platform, within an obstacle-ridden environment. This planner, derived from the Lyapunov-based control scheme, generates collision-free trajectories from an initial configuration to a final configuration in a constrained environment cluttered with stationary solid objects of different shapes and sizes. We demonstrate the efficiency of the control scheme and the resulting acceleration controllers of the mobile manipulator with results through computer simulations of an interesting scenario.

Simulating and Forecasting Qualitative Marcoeconomic Models Using Rule-Based Fuzzy Cognitive Maps

Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed

Distributed Load Flow Analysis using Graph Theory

In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.

Wireless Distributed Load-Shedding Management System for Non-Emergency Cases

In this paper, we present a cost-effective wireless distributed load shedding system for non-emergency scenarios. In power transformer locations where SCADA system cannot be used, the proposed solution provides a reasonable alternative that combines the use of microcontrollers and existing GSM infrastructure to send early warning SMS messages to users advising them to proactively reduce their power consumption before system capacity is reached and systematic power shutdown takes place. A novel communication protocol and message set have been devised to handle the messaging between the transformer sites, where the microcontrollers are located and where the measurements take place, and the central processing site where the database server is hosted. Moreover, the system sends warning messages to the endusers mobile devices that are used as communication terminals. The system has been implemented and tested via different experimental results.

Transmitter Macrodiversity in Multihopping- SFN Based Algorithm for Improved Node Reachability and Robust Routing

A novel idea presented in this paper is to combine multihop routing with single-frequency networks (SFNs) for a broadcasting scenario. An SFN is a set of multiple nodes that transmit the same data simultaneously, resulting in transmitter macrodiversity. Two of the most important performance factors of multihop networks, node reachability and routing robustness, are analyzed. Simulation results show that our proposed SFN-D routing algorithm improves the node reachability by 37 percentage points as compared to non-SFN multihop routing. It shows a diversity gain of 3.7 dB, meaning that 3.7 dB lower transmission powers are required for the same reachability. Even better results are possible for larger networks. If an important node becomes inactive, this algorithm can find new routes that a non-SFN scheme would not be able to find. Thus, two of the major problems in multihopping are addressed; achieving robust routing as well as improving node reachability or reducing transmission power.

Design and Implementation of Rule-based Expert System for Fault Management

It has been defined that the “network is the system". This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus. In this paper we are addressing a framework to effectively deal with this issue. It consists of components and interactions between them which are required to perform the service fault management. A real-world scenario is used to derive the requirements which have been applied to the component identification. An analysis of existing frameworks and approaches with respect to their applicability to the framework is also carried out.

Early Registration : Criterion to Improve Communication-Inter Agents in Mobile-IP Protocol

In IETF RFC 2002, Mobile-IP was developed to enable Laptobs to maintain Internet connectivity while moving between subnets. However, the packet loss that comes from switching subnets arises because network connectivity is lost while the mobile host registers with the foreign agent and this encounters large end-to-end packet delays. The criterion to initiate a simple and fast full-duplex connection between the home agent and foreign agent, to reduce the roaming duration, is a very important issue to be considered by a work in this paper. State-transition Petri-Nets of the modeling scenario-based CIA: communication inter-agents procedure as an extension to the basic Mobile-IP registration process was designed and manipulated to describe the system in discrete events. The heuristic of configuration file during practical Setup session for registration parameters, on Cisco platform Router-1760 using IOS 12.3 (15)T and TFTP server S/W is created. Finally, stand-alone performance simulations from Simulink Matlab, within each subnet and also between subnets, are illustrated for reporting better end-toend packet delays. Results verified the effectiveness of our Mathcad analytical manipulation and experimental implementation. It showed lower values of end-to-end packet delay for Mobile-IP using CIA procedure-based early registration. Furthermore, it reported packets flow between subnets to improve losses between subnets.

A Robust Al-Hawalees Gaming Automation using Minimax and BPNN Decision

Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.

The MUST ADS Concept

The presented work is motivated by a French law regarding nuclear waste management. A new conceptual Accelerator Driven System (ADS) designed for the Minor Actinides (MA) transmutation has been assessed by numerical simulation. The MUltiple Spallation Target (MUST) ADS combines high thermal power (up to 1.4 GWth) and high specific power. A 30 mA and 1 GeV proton beam is divided into three secondary beams transmitted on three liquid lead-bismuth spallation targets. Neutron and thermalhydraulic simulations have been performed with the code MURE, based on the Monte-Carlo transport code MCNPX. A methodology has been developed to define characteristic of the MUST ADS concept according to a specific transmutation scenario. The reference scenario is based on a MA flux (neptunium, americium and curium) providing from European Fast Reactor (EPR) and a plutonium multireprocessing strategy is accounted for. The MUST ADS reference concept is a sodium cooled fast reactor. The MA fuel at equilibrium is mixed with MgO inert matrix to limit the core reactivity and improve the fuel thermal conductivity. The fuel is irradiated over five years. Five years of cooling and two years for the fuel fabrication are taken into account. The MUST ADS reference concept burns about 50% of the initial MA inventory during a complete cycle. In term of mass, up to 570 kg/year are transmuted in one concept. The methodology to design the MUST ADS and to calculate fuel composition at equilibrium is precisely described in the paper. A detailed fuel evolution analysis is performed and the reference scenario is compared to a scenario where only americium transmutation is performed.

Comparison of Different Types of Sources of Traffic Using SFQ Scheduling Discipline

In this paper, SFQ (Start Time Fair Queuing) algorithm is analyzed when this is applied in computer networks to know what kind of behavior the traffic in the net has when different data sources are managed by the scheduler. Using the NS2 software the computer networks were simulated to be able to get the graphs showing the performance of the scheduler. Different traffic sources were introduced in the scripts, trying to establish the real scenario. Finally the results were that depending on the data source, the traffic can be affected in different levels, when Constant Bite Rate is applied, the scheduler ensures a constant level of data sent and received, but the truth is that in the real life it is impossible to ensure a level that resists the changes in work load.

Cumulative Learning based on Dynamic Clustering of Hierarchical Production Rules(HPRs)

An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.

Reduction of Overheads with Dynamic Caching in Fixed AODV based MANETs

In this paper we show that adjusting ART in accordance with static network scenario can substantially improve the performance of AODV by reducing control overheads. We explain the relationship of control overheads with network size and request patterns of the users. Through simulation we show that making ART proportionate to network static time reduces the amount of control overheads independent of network size and user request patterns.

A Comparative Study on Available IPv6 Platforms for Wireless Sensor Network

The low power wireless sensor devices which usually uses the low power wireless private area network (IEEE 802.15.4) standard are being widely deployed for various purposes and in different scenarios. IPv6 low power wireless private area network (6LoWPAN) was adopted as part of the IETF standard for the wireless sensor devices so that it will become an open standard compares to other dominated proprietary standards available in the market. 6LoWPAN also allows the integration and communication of sensor nodes with the Internet more viable. This paper presents a comparative study on different available IPv6 platforms for wireless sensor networks including open and close sources. It also discusses about the platforms used by these stacks. Finally it evaluates and provides appropriate suggestions which can be use for selection of required IPv6 stack for low power devices.

A Novel Neighborhood Defined Feature Selection on Phase Congruency Images for Recognition of Faces with Extreme Variations

A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.

Survival of Neutrino Mass Models in Nonthermal Leptogenesis

The Constraints imposed by non-thermal leptogenesis on the survival of the neutrino mass models describing the presently available neutrino mass patterns, are studied numerically. We consider the Majorana CP violating phases coming from right-handed Majorana mass matrices to estimate the baryon asymmetry of the universe, for different neutrino mass models namely quasi-degenerate, inverted hierarchical and normal hierarchical models, with tribimaximal mixings. Considering two possible diagonal forms of Dirac neutrino mass matrix as either charged lepton or up-quark mass matrix, the heavy right-handed mass matrices are constructed from the light neutrino mass matrix. Only the normal hierarchical model leads to the best predictions of baryon asymmetry of the universe, consistent with observations in non-thermal leptogenesis scenario.

On the Analysis of Bandwidth Management for Hybrid Load Balancing Scheme in WLANs

In wireless networks, bandwidth is scare resource and it is essential to utilize it effectively. This paper analyses effects of using different bandwidth management techniques on the network performances of the Wireless Local Area Networks (WLANs) that use hybrid load balancing scheme. In particular, we study three bandwidth management schemes, namely Complete Sharing (CS), Complete Partitioning (CP), and Partial Sharing (PS). Performances of these schemes are evaluated by simulation experiments in term of percentage of network association blocking. Our results show that the CS scheme can provide relatively low blocking percentage in various network traffic scenarios whereas the PS scheme can enhance quality of services of the multimedia traffic with rather small expenses on the blocking percentage of the best effort traffic.