Improving Sparse Representation-Based Classification Using Local Principal Component Analysis

Sparse representation-based classification (SRC), proposed by Wright et al., seeks the sparsest decomposition of a test sample over the dictionary of training samples, with classification to the most-contributing class. Because it assumes test samples can be written as linear combinations of their same-class training samples, the success of SRC depends on the size and representativeness of the training set. Our proposed classification algorithm enlarges the training set by using local principal component analysis to approximate the basis vectors of the tangent hyperplane of the class manifold at each training sample. The dictionary in SRC is replaced by a local dictionary that adapts to the test sample and includes training samples and their corresponding tangent basis vectors. We use a synthetic data set and three face databases to demonstrate that this method can achieve higher classification accuracy than SRC in cases of sparse sampling, nonlinear class manifolds, and stringent dimension reduction.Comment: Published in "Computational Intelligence for Pattern Recognition," editors Shyi-Ming Chen and Witold Pedrycz. The original publication is available at http://www.springerlink.co

A window into fungal endophytism in Salicornia europaea: deciphering fungal characteristics as plant growth promoting agents

Aim Plant-endophytic associations exist only when equilibrium is maintained between both partners. This study analyses the properties of endophytic fungi inhabiting a halophyte growing in high soil salinity and tests whether these fungi are beneficial or detrimental when non-host plants are inoculated. Method Fungi were isolated from Salicornia europaea collected from two sites differing in salinization history (anthropogenic and naturally saline) and analyzed for plant growth promoting abilities and non-host plant interactions. Results Most isolated fungi belonged to Ascomycota (96%) including dematiaceous fungi and commonly known plant pathogens and saprobes. The strains were metabolically active for siderophores, polyamines and indole-3-acetic acid (mainly Aureobasidium sp.) with very low activity for phosphatases. Many showed proteolytic, lipolytic, chitinolytic, cellulolytic and amylolytic activities but low pectolytic activity. Different activities between similar fungal species found in both sites were particularly seen for Epiccocum sp., Arthrinium sp. and Trichoderma sp. Inoculating the non-host Lolium perenne with selected fungi increased plant growth, mainly in the symbiont (Epichloë)-free variety. Arthrinium gamsii CR1-9 and Stereum gausapatum ISK3-11 were most effective for plant growth promotion. Conclusions This research suggests that host lifestyle and soil characteristics have a strong effect on endophytic fungi, and environmental stress could disturb the plant-fungi relations. In favourable conditions, these fungi may be effective in facilitating crop production in non-cultivable saline lands

RARZ: Ring-Zone Based Routing Protocol for Wireless Sensor Networks

Sensor networks are handicapped by limited resources in the form of energy, processing, and memory. This paper proposes a new multi-hop energy efficient protocol, namely a routing algorithm using the ring-zone (RARZ) model. The protocol is lightweight, takes routing decisions based on the remaining energy of nodes, and performs location-based routing without the need for the nodes to know their respective positions. The protocol partitions the network into concentric rings around the base station. Each node assigns itself to a particular ring, known by a ringID. Multi-hop routing is performed and nodes within inner rings carry data for the outer rings towards the base station. Simulation results show that RARZ outperforms the address-light integrated MAC routing protocol (AIMRP), ad hoc on-demand distance vector (AODV) and Flooding in terms of end-to-end delay, average hop count, and energy consumption

EEHRT: Energy Efficient Technique for Handling Redundant Traffic in Zone-Based Routing for Wireless Sensor Networks

This paper presents an energy-efficient technique to handle redundant traffic (EEHRT) in the zone-based routing for wireless sensor networks. In this technique, multihop routing is performed based on the remaining energy of the nodes. Afterwards, it performs position-based routing without the need for the nodes to know their respective position. The main objective of this paper is to handle the redundant packets generated in zone-based routing using short beacon messages. Nodes of lower zones route the data of the higher zone to base station (BS) with a minimum number of hops and utilize only those nodes on the path which are energy efficient and located closer to BS. Moreover, the source node is acknowledged by the relaying node using a wireless broadcast advantage (WBA) without sending any special ACK packet to the sender, which reduces the control overhead in the routing process. The EEHRT technique improves the routing against RARZ by ensuring only one copy of the packet is propagated at each hop along the routing path to BS. Simulation results show that EEHRT achieved 28% improvement in energy efficiency, 10% and 25% improvements in data throughput against total and distinct packet reception at BS respectively, 35% increase in overall network lifetime, and 100% reduction in redundant packets generation and propagation in the network against RARZ routing

Towards Automatic Detection of Social Anxiety Disorder via Gaze Interaction

Social anxiety disorder (SAD) is an extreme fear of underperformance in various social situations. It is necessary to detect people with or without SAD for counseling and treatment. A few manual techniques in the existing literature show the possibility of SAD detection from gaze interaction. However, an automated prediction of SAD is scarce. In this research, an automatic technique to predict SAD using gaze interaction/avoidance is proposed, where a custom application was developed that used the Haar Cascade classifier to predict gaze interaction/avoidance. The experiments were conducted on 50 participants in a live environment using the developed application. SAD classes were predicted by using decision tree classifiers from the created gaze dataset. The results proved that SAD could be predicated with an overall accuracy of 80%. Furthermore, four classes of SAD (Mark, Moderate, Severe, Very Severe along with ‘No SAD’) could be predicted with an accuracy of 80%, 70%, 90%, 80%, and 80%, respectively. The research proved the possibility to predict SAD using computer-based methods without human intervention. Furthermore, it created the possibility of aiding a subjective Liebowitz Social Anxiety Scale (LSAS) with an objective technique described in this research

A Reliable Scheme for Synchronizing Multimedia Data Streams under Multicasting Environment

An emerging requirement in multimedia applications over the Internet is the provisioning of synchronized play out of multimedia streams on all the ultimate receivers. Most multimedia applications use real-time transport protocol/real-time control protocol (RTP/RTCP) to transport multimedia data over the internet. Internet Protocol (IP) network incurs a loss and/or delay of media packets resulting in distortions at receivers that can be perceived by the user. These distortions need to be removed before data is presented to the end user. To handle such issues inter-stream and intra-stream synchronization algorithms were developed by the researcher using RTP/RTCP protocols. These schemes could not work under multicasting environment properly. In this paper, we have presented an algorithm based on RTP/RTCP protocol that achieved synchronized playout of multimedia data under multicasting environment. The proposed scheme offers a modification in RTCP and usage of the Network Time Protocol (NTP) as a source of the common clock to achieve synchronized playout of multimedia data on multiple devices at the same time. We have implemented and tested our algorithm in Ericson Research Corporate Unit, Lulea, Sweden. Implementation results show that the proposed algorithm delivered accurately synchronized playout of multimedia data under all the possible scenarios defined in the experimental setup

S2 Data -

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It’s worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.</div

Scenario document.

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It’s worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.</div

Questionnaire and modified SUS Questionnaire.

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It’s worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.</div