Graph-based High Level Motion Segmentation using Normalized Cuts

Motion capture devices have been utilized in producing several contents, such as movies and video games. However, since motion capture devices are expensive and inconvenient to use, motions segmented from captured data was recycled and synthesized to utilize it in another contents, but the motions were generally segmented by contents producers in manual. Therefore, automatic motion segmentation is recently getting a lot of attentions. Previous approaches are divided into on-line and off-line, where on-line approaches segment motions based on similarities between neighboring frames and off-line approaches segment motions by capturing the global characteristics in feature space. In this paper, we propose a graph-based high-level motion segmentation method. Since high-level motions consist of several repeated frames within temporal distances, we consider all similarities among all frames within the temporal distance. This is achieved by constructing a graph, where each vertex represents a frame and the edges between the frames are weighted by their similarity. Then, normalized cuts algorithm is used to partition the constructed graph into several sub-graphs by globally finding minimum cuts. In the experiments, the results using the proposed method showed better performance than PCA-based method in on-line and GMM-based method in off-line, as the proposed method globally segment motions from the graph constructed based similarities between neighboring frames as well as similarities among all frames within temporal distances.

Energy Efficient Clustering Algorithm with Global and Local Re-clustering for Wireless Sensor Networks

Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering  algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.

A New Technique for Multi Resolution Characterization of Epileptic Spikes in EEG

A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

High Speed Video Transmission for Telemedicine using ATM Technology

In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Faculty Stress at Higher Education: A Study on the Business Schools of Pakistan

Job stress is one of the most important concepts for the today-s corporate as well as institutional world. The current study is conducted to identify the causes of faculty stress at Higher Education in Pakistan. For the purpose, Public & Private Business Schools of Punjab is selected as representative of Pakistan. A sample of 300 faculty members (214 males, 86 females) responded to the survey. Regression analysis shows that the Workload, Student Related issues and Role Conflicts are the major sources contributing significantly towards producing stress. The study also revealed that Private sector faculty members experienced more stress as compared to faculty in Public sector Business Schools. Moreover, females, younger ages, lower designation & low qualification faculty members experience more stress as compared to males, older ages, higher designation and high qualification. The study yield many significant results for the policy makers of Business Institutions.

Broadband PowerLine Communications: Performance Analysis

Power line channel is proposed as an alternative for broadband data transmission especially in developing countries like Tanzania [1]. However the channel is affected by stochastic attenuation and deep notches which can lead to the limitation of channel capacity and achievable data rate. Various studies have characterized the channel without giving exactly the maximum performance and limitation in data transfer rate may be this is due to complexity of channel modeling being used. In this paper the channel performance of medium voltage, low voltage and indoor power line channel is presented. In the investigations orthogonal frequency division multiplexing (OFDM) with phase shift keying (PSK) as carrier modulation schemes is considered, for indoor, medium and low voltage channels with typical ten branches and also Golay coding is applied for medium voltage channel. From channels, frequency response deep notches are observed in various frequencies which can lead to reduce the achievable data rate. However, is observed that data rate up to 240Mbps is realized for a signal to noise ratio of about 50dB for indoor and low voltage channels, however for medium voltage a typical link with ten branches is affected by strong multipath and coding is required for feasible broadband data transfer.

Heavy Metals Transport in the Soil Profiles under the Application of Sludge and Wastewater

Heavy metal transfer in soil profiles is a major environmental concern because even slow transport through the soil may eventually lead to deterioration of groundwater quality. The use of sewage sludge and effluents from wastewater treatment plants for irrigation of agricultural lands is on the rise particularly in peri-urban area of developing countries. In this study soil samples under sludge application and wastewater irrigation were studied and soil samples were collected in the soil profiles from the surface to 100 cm in depth. For this purpose, three plots were made in a treatment plant in south of Tehran-Iran. First plot was irrigated just with effluent from wastewater treatment plant, second plot with simulated heavy metals concentration equal 50 years irrigation and in third plot sewage sludge and effluent was used. Trace metals concentration (Cd, Cu) were determined for soil samples. The results indicate movement of metals was observed, but the most concentration of metals was found in topsoil samples. The most of Cadmium concentration was measured in the topsoil of plot 3, 4.5mg/kg and Maximum cadmium movement was observed in 0-20 cm. The most concentration of copper was 27.76mg/kg, and maximum percolation in 0-20 cm. Metals (Cd, Cu) were measured in leached water. Preferential flow and metal complexation with soluble organic apparently allow leaching of heavy metals.

Hardware Centric Machine Vision for High Precision Center of Gravity Calculation

We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.

Latent Semantic Inference for Agriculture FAQ Retrieval

FAQ system can make user find answer to the problem that puzzles them. But now the research on Chinese FAQ system is still on the theoretical stage. This paper presents an approach to semantic inference for FAQ mining. To enhance the efficiency, a small pool of the candidate question-answering pairs retrieved from the system for the follow-up work according to the concept of the agriculture domain extracted from user input .Input queries or questions are converted into four parts, the question word segment (QWS), the verb segment (VS), the concept of agricultural areas segment (CS), the auxiliary segment (AS). A semantic matching method is presented to estimate the similarity between the semantic segments of the query and the questions in the pool of the candidate. A thesaurus constructed from the HowNet, a Chinese knowledge base, is adopted for word similarity measure in the matcher. The questions are classified into eleven intension categories using predefined question stemming keywords. For FAQ mining, given a query, the question part and answer part in an FAQ question-answer pair is matched with the input query, respectively. Finally, the probabilities estimated from these two parts are integrated and used to choose the most likely answer for the input query. These approaches are experimented on an agriculture FAQ system. Experimental results indicate that the proposed approach outperformed the FAQ-Finder system in agriculture FAQ retrieval.

Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Fuzzy EOQ Models for Deteriorating Items with Stock Dependent Demand and Non-Linear Holding Costs

This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with  stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number  (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0

Comparative Analysis of the Software Effort Estimation Models

Accurate software cost estimates are critical to both developers and customers. They can be used for generating request for proposals, contract negotiations, scheduling, monitoring and control. The exact relationship between the attributes of the effort estimation is difficult to establish. A neural network is good at discovering relationships and pattern in the data. So, in this paper a comparative analysis among existing Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model and Neural Network Based Model is performed. Neural Network has outperformed the other considered models. Hence, we proposed Neural Network system as a soft computing approach to model the effort estimation of the software systems.

Subpixel Detection of Circular Objects Using Geometric Property

In this paper, we propose a method for detecting circular shapes with subpixel accuracy. First, the geometric properties of circles have been used to find the diameters as well as the circumference pixels. The center and radius are then estimated by the circumference pixels. Both synthetic and real images have been tested by the proposed method. The experimental results show that the new method is efficient.

Prerequisites to Increase the Purchase Intent fora Socially Responsible Company –Development of a Scale

Increasing attention has been given in academia to the concept of corporate social responsibility. Also, the number of companies that undertake social responsibility initiatives has been boosting day by day since behaving in a socially responsible manner brings a lot to the companies. Literature provides various benefits of social responsibility and under which situations these benefits could be realized. However, most of these studies focus on one aspect of the consequences of behaving in a socially responsible manner and there is no study that unifies the conditions that a company should fulfill to make customers prefer its brand. This study aims to fill this gap. More specifically, the purpose of this study is to identify the conditions that a socially responsible company should fulfill in order to attract customers. To this end, a scale is developed and its reliability and validity is assessed through the method of Multitrait- Multimethod Matrix.

Designing of Multi-Agent Rescue Robot: Development and Basic Experiments of Master-Slave Type Rescue Robots

A multi-agent type robot for disaster response in calamity scene is proposed in this paper. The proposed grouped rescue robots can perform cooperative reconnaissance and surveillance to achieve a given rescue mission. The multi-agent rescue of dual set robot consists of one master set and three slave units. The research for this rescue robot system is going to detect at harmful environment where human is unreachable, such as the building is infected with virus or the factory has hazardous liquid in effluent. As a dual set robot, with Bluetooth and communication network, the master set can connect with slave units and send information back to computer by wireless and monitor. Therefore, rescuer can be informed the real-time information in a calamity area. Furthermore, each slave robot is able to obstacle avoidance by ultrasonic sensors, and encodes distance and location by compass. The master robot can integrate every devices information to increase the efficiency of prospected and research unknown area.

A Study of Relationship between Mountaineering Participation Motivation and Risk Perception

The main purpose of this study is to analyze climbers involved in motivation and risk perception and analysis of the predictive ability of the risk perception "mountaineering" involved in motivation. This study used questionnaires, to have to climb the 3000m high mountain in Taiwan climbers object to carry out an investigation in order to non-random sampling, a total of 231 valid questionnaires were. After statistical analysis, the study found that: 1. Climbers the highest climbers involved in motivation "to enjoy the natural beauty of the fun. 2 climbers for climbers "risk perception" the highest: the natural environment of risk. 3. Climbers “seeking adventure stimulate", “competence achievement" motivation highly predictive of risk perception. Based on these findings, this study not only practices the recommendations of the outdoor leisure industry, and also related research proposals for future researchers.

Evaluation of Energy-Aware QoS Routing Protocol for Ad Hoc Wireless Sensor Networks

Many advanced Routing protocols for wireless sensor networks have been implemented for the effective routing of data. Energy awareness is an essential design issue and almost all of these routing protocols are considered as energy efficient and its ultimate objective is to maximize the whole network lifetime. However, the introductions of video and imaging sensors have posed additional challenges. Transmission of video and imaging data requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. In this paper, the performance of the energy-aware QoS routing Protocol are analyzed in different performance metrics like average lifetime of a node, average delay per packet and network throughput. The parameters considered in this study are end-to-end delay, real time data generation/capture rates, packet drop probability and buffer size. The network throughput for realtime and non-realtime data was also has been analyzed. The simulation has been done in NS2 simulation environment and the simulation results were analyzed with respect to different metrics.

Layout Based Spam Filtering

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.

Walking Hexapod Robot in Disaster Recovery: Developing Algorithm for Terrain Negotiation and Navigation

In modern day disaster recovery mission has become one of the top priorities in any natural disaster management regime. Smart autonomous robots may play a significant role in such missions, including search for life under earth quake hit rubbles, Tsunami hit islands, de-mining in war affected areas and many other such situations. In this paper current state of many walking robots are compared and advantages of hexapod systems against wheeled robots are described. In our research we have selected a hexapod spider robot; we are developing focusing mainly on efficient navigation method in different terrain using apposite gait of locomotion, which will make it faster and at the same time energy efficient to navigate and negotiate difficult terrain. This paper describes the method of terrain negotiation navigation in a hazardous field.

Achieving High Availability by Implementing Beowulf Cluster

A computer cluster is a group of tightly coupled computers that work together closely so that in many respects they can be viewed as though they are a single computer. The components of a cluster are commonly, but not always, connected to each other through fast local area networks. Clusters are usually deployed to improve performance and/or availability over that provided by a single computer, while typically being much more cost-effective than single computers of comparable speed or availability. This paper proposed the way to implement the Beowulf Cluster in order to achieve high performance as well as high availability.