DSpace collection: 期刊論文

A collaborative filtering recommendation system with dynamic time decay

title: A collaborative filtering recommendation system with dynamic time decay abstract: The collaborative filtering (CF) technique has been widely utilized in recommendation systems due to the precise prediction of users' interests. Most prior CF methods adapted overall ratings to make predictions by collecting preference information from other users. However, in real applications, people’s preferences usually vary with time; the traditional CF could not properly reveal the change in users’ interests. In this paper, we propose a novel CF-based recommendation, dynamic decay collaborative filtering (DDCF), which captures the preference variations of users and includes the concept of dynamic time decay. We extend the idea of human brain memory to specify the level of a user’s interests (i.e., instantaneous, short-term, or long-term). According to different interest levels, DDCF dynamically tunes the decay function based on users’ behaviors. The experimental results show that DDCF with the integration of the dynamic decay concept performs better than traditional CF. In addition, we conduct experiments on real-world datasets to demonstrate the practicability of the proposed DDCF.

Simulation analysis of the wild animal observation system

title: Simulation analysis of the wild animal observation system abstract: The Chinese white dolphin, along the west coast of Taiwan, is claimed as on the brink of distinction species. A top priority before entering the policy process of conservation is to have a well plan of accurate observation. Objective of this paper is to evaluate a proposed novel alternative, which applies the internet of thing (IoT) concept, in the observation of wild animal instead of the conventional way which is manpower intensive. The IoT observation System is consisted of the hydrophone laid on the sea floor, camera/IR sensor carried by Quadcopter, and land control center. Monte Carlo simulation was developed for getting insight of theinteraction between dolphin and IoT observation System. The result showed IoT observation System has a significant effect. The contribution this paper made is to prove that the IoT observation system is far more cost effectively than the manpower intensive boat watching method.

Effectiveness evaluation of Internet of Things-aided firefighting by simulation

title: Effectiveness evaluation of Internet of Things-aided firefighting by simulation abstract: With the emerging Internet of Things technology, the world is facing rapid changes in all areas; firefighting is no exception. Conventional firefighting is a dangerous occupation which involves saving lives and property from fires. The skills of firefighting have not changed greatly over the years; hence, using the IoT to aid firefighters is a way to improve their performance. Due to the lack of research on implementing the IoT in the firefighting domain, the objective of this study was to use the quantitative method to gain insights into the usefulness of using the IoT as an aid to firefighting. A Monte Carlo simulation was developed for processing the detailed firefighting interactions in situations of uncertainty. After the verification of the simulation model, the results showed that the search time ratios of unmanned aerial vehicle (UAV) to conventional firefighting for various levels of severity of fire were 30.09, 26.69, and 22.24%. The search and rescue time ratios of UAV to conventional firefighting were 48.27, 35.95, and 31.87%. The most important of these statistics is that at least 50% of the time spent by firefighters on the scene of the fire can be reduced by using the Internet of Things. All of the above data were analyzed usingt test, which showed significant improvement when the Internet of Things was implemented in firefighting. The contribution of this study is to present quantitative results for proving the value of integrating the Internet of Things into firefighting.

Effectiveness analysis of an IoT mechanism in support of monitoring Chinese white dolphins by simulation model

title: Effectiveness analysis of an IoT mechanism in support of monitoring Chinese white dolphins by simulation model abstract: The population of the Chinese white dolphin is claimed to be critically endangered and is on the International Union for Conservation of Nature (IUCN) Red list. It is estimated that there are fewer than 100 individuals in the East Taiwan Strait, and the number is falling. The dolphin’s habitat has been seriously impacted by man-made pollution, such as industry contamination, fishing, and noise. To prevent extinction of the species, conservative action is vital. Prior to any such action, data on the dolphin are essential for decision makers. The current method of observing dolphins is the man-on-boat-watch approach, which is heavily dependent on manpower. Its performance is seriously affected by the weather, fatigue of those on board, and it is also risky and costly. An Internet of things (IoT) data collection mechanism concept is proposed for the purpose of observing dolphins with close watch. It consists of off-the-shelf products such as hydrophones, unmanned aerial vehicles (UAVs) and a specific command and control in search/detection for carrying out the observation task. A Monte Carlo simulation model was developed to analyze the effectiveness of the feasible alternatives, in which some factors are considered and analyzed for their significance. The simulation result showed that the IoT mechanism has an 8.5 times greater chance of availability in operation and at least 2 times more contact than the man-on-boat-watch method. The significant factor affecting the IoT mechanism’s effectiveness is the number of hydrophones and UAVs in the scenario. The great contribution made by this study is that it is the first analytical paper to reveal the effectiveness of an IoT mechanism in benefitting the observation of Chinese white dolphin. The limitation is that it uses off-the shelf products for the IoT mechanism instead of high-end products which could be more effective.

Enhanced Appearance-based Finger Detection and Tracking Using Finite State Machine Control

title: Enhanced Appearance-based Finger Detection and Tracking Using Finite State Machine Control abstract: Real-time finger detection and tracking systems have been growing rapidly in the past decade. Among those methods, Appearance-based and Model-based methods have produced excellent results. However, the occlusion issue is one of the main challenges in this field. In this study, we address this issue by considering the repeating-finite gestures of a guitar-strumming or a hand puppet and, represent using a Finite State Machine model. Also we proposed a novel finger pose tracking system using FSM Model combining with the appearance-based method.. The proposed system consists of two parts: FSM-FT builder creates the FSM hand, and the FSM-FT runner controls the FSM-FT system. Empirically, we conducted an experimental study involving one sample repeating hand gesture and our approach achieved a significance recognition rate of 82% in the testing phase.

Error resilience for block compressed sensing with multiple-channel transmission

title: Error resilience for block compressed sensing with multiple-channel transmission abstract: Compressed sensing is well known for its superior compression performance, in existing schemes, in lossy compression. Conventional research aims to reach a larger compression ratio at the encoder, with acceptable quality reconstructed images at the decoder. This implies looking for compression performance with error-free transmission between the encoder and the decoder. Besides looking at compression performance, we applied block compressed sensing to digital images for robust transmission. For transmission over lossy channels, error propagation or data loss can be expected, and protection mechanisms for compressed sensing signals are required for guaranteed quality of the reconstructed images. We propose transmitting compressed sensing signals over multiple independent channels for robust transmission. By introducing correlations with multiple-description coding, which is an effective means for error resilient coding, errors induced in the lossy channels can effectively be alleviated. Simulation results presented the applicability and superiority of performance, depicting the effectiveness of protection of compressed sensing signals.

3D finger tracking and recognition image processing for real-time music playing with depth sensors

title: 3D finger tracking and recognition image processing for real-time music playing with depth sensors abstract: In this research, we propose a state-of-the-art 3D finger gesture tracking and recognition method. We use the depth sensors for both hands in real time music playing. In line with the development of 3D depth cameras, we implemented a set of 3D gesture-based instruments, such as Virtual Cello and Virtual Piano, which need precise finger tracking in 3D space. For hands tracking, model-based tracking for left hand and appearance-based tracking for right hand techniques are proposed. To detect finger gestures, our approaches consist number of systematic steps as reducing noise in depth map and geometrical processing for Virtual Cello. For Virtual Piano, we introduce the Neural Network (NN) method to detect special hand gestures. It has Multilayer Perceptron (MLP) structure with back propagation training. Literature has few examples using touch screen as medium, with fixed-coordinates, and 2D–gestures to control MIDI input. The end users should no longer carry anything on their hands. We use Senz3D and Leap Motion due to a few technical benefits. Senz3D and Leap Motion use a closer distance to hands, thus detailed finger gestures can be precisely identified. In the past years, we announced a set of virtual musical instruments and the MINE Virtual Band. Our research work is tested on lab environment and professional theatrical stage. More information and demonstrations of the proposed method can be accessed at: http://video.minelab.tw/DETS/VMIB/.

Balanced Error Distribution for Internet Video Retargeting

title: Balanced Error Distribution for Internet Video Retargeting abstract: With the progress of network technology, online video is widely used by users and popular. Image and video retargeting techniques have been proposed in the recent past by researchers around the world, low-complexity algorithms allow video to be transmitted more quickly. Our Balanced Error Distribution (BED) retargeting method follows the same concept like uniform scaling, but only removes unimportant regions, balancing main objects’ error distribution. Priority map is proposed in this paper to maintain the structure of straight lines and irregular shape of objects without deforming complex image contents, which may be altered in traditional seam carving for complex image or video. In addition, the proposed mechanism adopts the general temporal coherence algorithm with strict condition (two continuous seams must be close as possible) to maintain visual continuity, such that the resulting video will not look shaky due to sudden changes in the background. The proposed method not only resizes the video with the retention of important information but also maintains the structural properties of objects in different kinds of videos.

Applying sentiment analysis in social web for smart decision support marketing.

title: Applying sentiment analysis in social web for smart decision support marketing. abstract: Because of the rapid development of communication and service in Taiwan, competition among telecommunication companies has become ever fiercer. Differences in marketing strategy usually become the key factor in keeping existing customers while attracting new ones. Although electronic word-of-mouth (e-WOM) is one of the most important pieces of information to a consumer making a purchase decision, very few articles on opinion mining have discussed and compared the relationship between multifaceted word-of-mouth (WOM) and marketing strategy. In this paper, we use our Chinese opinion-mining system (Wu et al. in J Supercomput 73:2987–3001, 2017) not only to retrieve articles related to 4G and conduct reputation analysis but also to discuss the relation between WOM and marketing strategy. The results show that (1) e-WOM can immediately and directly reflect the results of marketing strategy, and (2) although users are primarily concerned with aspects of price, online speed, and signal quality, for most Taiwanese customers, price is the key in choosing a telecommunication company. Moreover, although this paper used 4G-related articles from June 2014 to June 2015 for analysis, the results are consistent with the Taiwanese telecommunication companies’ current marketing strategy of attracting customers through low pricing

Direct mail promotion mechanisms and their application in supermarkets.

title: Direct mail promotion mechanisms and their application in supermarkets. abstract: In this study, we consider the problem of selecting supermarket loyalty program members to receive physical direct mail and promotional electronic direct mail (i.e., direct email). To help marketers choose the target members for physical direct mails, we modify the customer’s preference index of our original model to predict members’ repurchase rates for a physical supermarket’s members. Based on members’ predicted repurchase rates, marketers can design proper marketing strategies for different types of supermarket member to improve marketing effectiveness. In addition, because members can only spend a short amount of time reading direct emails before choosing the products that they like, a recommender system based on a simple combination method is introduced. The system determines the most suitable combination of commodity types under the condition that a customized direct email can include only a small, fixed number of such types. In this study, member transaction records from a well-known Taiwanese supermarket were used as the test data. This supermarket’s marketing department reviewed all the experimental results and confirmed that our approach is not only superior to the current approach employed by the supermarket but also useful in designing appropriate direct-mail marketing strategies for selected supermarket members. Our approach is also suitable for direct email sent by the supermarket.

Motion tracking by sensors for real-time human skeleton animation.

title: Motion tracking by sensors for real-time human skeleton animation. abstract: Research on Human Computer Interaction has emerged in the early 1980s with the advent of computer technology. Human Motion Capture is the process of recording the movement of people. Among many kinds of human motion capture devises, Microsoft Kinect sensor and inertial sensors are most popular nowadays. In this paper we propose an efficient motion tacking mechanism to construct real time human skeleton animation using inertial sensors. We compare the results of our proposed method with the Microsoft Kinect sensor over the complicated motion tracking and joint position. During the experiment we observed that our results are much steady than Microsoft Kinect results. Some motions like hand cross over or leg cross over, our method showed better results than Kinect because the Kinect may lose skeleton of the blocked parts. On the other hand, since we use radio frequency inertial sensors, our method has a larger working area than Kinect.

The Cloud-Based Virtual Electronic Fences Proactive Tracking System

title: The Cloud-Based Virtual Electronic Fences Proactive Tracking System abstract: Because early symptoms of dementia are often ignored, the most worrying part is elders easily get lost due to their wandering behavior. Most of related devices only periodically update locations through the system server. When a relative or friend sends a tracking request, the system will only reply with updates on the position of the time of the last tracked end. We use GPS, 3G positioning signals, and base station information to calculate the position of elders. On the other hand, we use the virtual electronic fences technology to sure the elders leave the safe range or not. When elders at the time point of departure abnormal set range, the system will initiatively notify the family. We implement a cloud platform-based active notification tracking system to reduce the risk of elderly getting lost. Index Terms—Dementia Care, Proactive Notification, Tracking System, Virtual Electronic Fences, Cloud-Based.

A Real-time Fire Evacuation System with Cloud Computing

title: A Real-time Fire Evacuation System with Cloud Computing abstract: An effective evacuation system can help people escape from building fire. Most evacuation systems consist of an indoor positioning system, a back-end database, and a display device with calculation and display software. However, very few of them can smartly determine which evacuation route is the best decision. If all the locations of the evacuating people can be simultaneously determined, the best evacuation routes can be decided to avoid congestion, and survival rate can increase. The previous radio frequency identification (RFID) based evacuation system focused on detecting the RFID tags using a mobile phone in order to determine the location of the mobile phone user so that an evacuation route can be displayed. However, the system is available for one person regardless of the number of evacuating people or exits. This study is based on the previous RFID based evacuation system investigating the best evacuation routes. The system introduces cloud computing that calculates for positioning the evacuating people and determining the optimum evacuation routes for each of them. The system will be implemented at Tamkang University on Lanyang campus.

Smart environment effectiveness analysis of a pursuit and evasion scenario.

title: Smart environment effectiveness analysis of a pursuit and evasion scenario. abstract: The internet of things (IoT) has become a trend in interactive environments for providing information to decision-makers. Anti-submarine warfare (ASW) is a typical pursuit and evasion (PE) game that is a very complicated process. The ASW helicopter is assigned to execute the final phase of hunting the submarine with a torpedo attack. In most cases, a single helicopter is assigned to detect the submarine by dipping sonar, and then drops a torpedo. Once the dipping sonar goes off, uncertainty takes over, with the possible result of losing track of the submarine. To prevent this problem, using the IoT concept to create a wireless sensor network (WSN) in the area of interest for keeping ears on the evading submarine is a potential solution. The objective of this paper is to gain insights into this PE scenario so as to quantify the interaction result in order to demonstrate the effectiveness of the helicopter in terms of hunting the submarine. Monte Carlo simulation has been developed as the analytical tool, and ANOVA was used to verify the significance of the output measure of effectiveness (MOE) before analysis. The results show that a slow, unalerted submarine has a very low chance of survival. An alerted submarine has very high chance of survival, but when the proposed sonobuoy WSN is in place, this situation benefitting the submarine will be reversed. The WSN has been proved to be effective in a single helicopter carrying out its ASW task.

Simulation analysis of the search effectiveness on information-based firefighting

title: Simulation analysis of the search effectiveness on information-based firefighting abstract: Nowadays, fire accident is still a thorny problem due to the current firefighting still heavily relies on the experience instead of information. Saving lives from fireground is the primary task in firefighting, in which the speed of effective search largely relies on the sufficient and instant information. When insufficient information situation follows firefighter tightly, the firefighter's life can be jeopardised. Equipped firefighter with the advancing information technology, such as IR, laser range-finder, camera, augmented reality and an unmanned aerial vehicle for acquiring more fireground information may be useful for firefighting task. This study focuses on using Monte Carlo simulation model to quantify the feasible alternatives and finds out the significant effect by t-test. The result showed the time in search of victim is significantly reduced as using new way of firefighting. The contribution of this paper is to disclose the value of the proposed information-based technology in support of firefighting.

Illustrating the Impact of Uneven Saline Distribution on Thermal Lesion during Radiofrequency Ablation Using Computer Simulation for Smarter Healthcare Treatment Planning

title: Illustrating the Impact of Uneven Saline Distribution on Thermal Lesion during Radiofrequency Ablation Using Computer Simulation for Smarter Healthcare Treatment Planning abstract: Radiofrequency ablation (RFA) is a technique by which deposition of electromagnetic energy is used to thermally heat tissues. In addition, incomplete treatment with heat-based therapy alone may sometimes occur. It has been used widely in Taiwan for all variety of clinical treating modalities. To improve the efficacy of thermal therapies, many attempts have been used by modifying the tumor’s underlying physiologic characteristics. The objective of this study is to determine whether fluid saline injection during radiofrequency ablation (RFA) can increase the coagulation area and how parameters of both electrical conductivity and blood perfusion rate would impact on thermal lesion formation. Although the heat generated by this high-frequency current arises in all the conducting tissue pathways, high temperature only develops in tissues near the electrode, where the current density is high. Barely any heat arises in tissues further from the electrode because of the fall in current density and the cooling (or radiator) effect of blood flow. Continuous saline infusion is assumed at several locations to investigate the current density and temperature reaction. A simple two dimension (2D) geometry was used to illustrate electrical current pathways and temperature field. Finite-element numerical simulations are performed to solve the Laplace equation of the electric field calculation and Pennes bio-heat transfer equation of calculation temperature field. Results showed that injected saline regions could raise higher temperatures due to increasing electrical conductivity and thus extend the thermal lesion margins. Reversely, the blood perfusion rate which acted as heat sink effect could reduce the maximum temperature at squares.

Evaluation of life extension by migrating the legacy TTS to be under HLA architecture

title: Evaluation of life extension by migrating the legacy TTS to be under HLA architecture

Apply HIP to Handover Procedures in Hybrid Access Mode LTE Femtocells

title: Apply HIP to Handover Procedures in Hybrid Access Mode LTE Femtocells abstract: Femtocell networks that use Home evolved NodeB (HeNB) and existing networks for backhaul connectivity can fulfill the upcoming demand for high data rates in wireless communication systems as well as extend the coverage area. In this paper we seem handover between femtocell and macrocell as a heterogeneous handover and apply the Host Identity Protocol (HIP) with Media Independent Handover (MIH) to achieve handover execution. It considers handover parameters for, including interference, velocity, RSS and quality of service (QoS) level. We propose a new handover strategy based on HIP between the femtocell and the macrocell for LTE (Long Term Evolution) -based networks in hybrid access mode. This strategy can avoid unnecessary handovers and can reduce handover failure.

Distributed Fault-Tolerant Embedding of Multiple Networks in Incrementally Extensible Hypercube Graphs

title: Distributed Fault-Tolerant Embedding of Multiple Networks in Incrementally Extensible Hypercube Graphs abstract: The performance of parallel and distributed computer systems depends on the effectiveness of the underlying interconnection network. Embedding is ofgreat importance in the applications ofparallel and distributed computer systems. This paper presents embedding multiple networks into a faulty Incrementally Extensible Hypercube, including linear array, ring, mesh, torus, and double-rooted complete binary tree. To obtain the replaceable node ofthe faulty node, 2-expansion is permitted such that up to (n+ 1) faults can be tolerated with dilation 3, congestion I and load 1. It is demonstrated that O(n) faults can be tolerated. Furthermore, the presented embedding methods are optimized mainly for balancing the processor loads, while minimizing load as far as possible. Based on these results, this methodology of embedding enables extremely high-speed parallel and distributed computation. Moreover, the technology can be applied in grid computing and cloud computing.

Time Stamp Data-flow Broadcasting Mechanism with Mobile Sinks in Wireless Sensor Networks

title: Time Stamp Data-flow Broadcasting Mechanism with Mobile Sinks in Wireless Sensor Networks abstract: Sensor nodes will transmit the sensed data to sink by multi-hop strategy in wireless sensor networks. However, this will cause the hotspot problem and also decrease the effectiveness ofthe sensed data in larger networks environment. We proposed data transmission mechanism with mobile sinks using timestamp in wireless sensor networks to solve the above problems. We assume that all mobile sinks are synchronized and equipped with the timer. Mobile sinks will periodically update the timestamp of sensor nodes. After that. sensor nodes will decide to broadcast the sensed data or not by comparing the timestamp when event occurred

Mining unexpected patterns using decision trees and interestingness measures: a case study of endometriosis

title: Mining unexpected patterns using decision trees and interestingness measures: a case study of endometriosis abstract: Because clinical research is carried out in complex environments, prior domain knowledge, constraints, and expert knowledge can enhance the capabilities and performance of data mining. In this paper we propose an unexpected pattern mining model that uses decision trees to compare recovery rates of two different treatments, and to find patterns that contrast with the prior knowledge of domain users. In the proposed model we define interestingness measures to determine whether the patterns found are interesting to the domain. By applying the concept of domain-driven data mining, we repeatedly utilize decision trees and interestingness measures in a closed-loop, in-depth mining process to find unexpected and interesting patterns. We use retrospective data from transvaginal ultrasound-guided aspirations to show that the proposed model can successfully compare different treatments using a decision tree, which is a new usage of that tool. We believe that unexpected, interesting patterns may provide clinical researchers with different perspectives for future research.

Virtual guitar: using real-time finger tracking for musical instruments

title: Virtual guitar: using real-time finger tracking for musical instruments abstract: Kinect, a 3D sensing device from Microsoft, invokes the human-computer interaction research evolution. Kinect was implemented in many areas including music. One was implemented in a virtual musical instrument (VMI) system, which uses natural gestures to produce synthetic sounds similar to real musical instruments. From related work, it was found that the use of a large joint such as hand, arm and leg is inconvenient and limits the way of playing VMI. Thus, this study proposes a fast and reliable finger tracking algorithm suitable for virtual musical instrument playing. In addition, a virtual guitar system application is developed as an implementation of the proposed algorithm. Experimental results show that the proposed method can be used to play many varieties of songs with an acceptable quality. Furthermore proposed application could be used by a beginner who does not have any experience in music or on playing a real musical instrument.

A Context-Aware, Interactive M-Health System for Diabetics

title: A Context-Aware, Interactive M-Health System for Diabetics abstract: In this paper, context-aware interactive mobile-health (m-health) system (ImHS) provides real-time, two-way communication between diabetes patients and caregivers by utilizing Internet of Things (IoT) technology. When a diabetic patient records abnormal blood sugar values during measurement, the ImHS sends a reminder to the patient and caregivers, motivating behavior change and improving the quality of chronic care. The ImHS features user-friendly interfaces for patients, family, and professional caregivers that lets them rapidly understand the patient's health status. In this study, the authors look at ImHS use in diabetes care. However, the ImHS can be easily adapted for integration into other healthcare systems.

Parametric Analysis of Effective Tissue Thermal Conductivity, Thermal Wave Characteristic, and Pulsatile Blood Flow on Temperature Distribution during Thermal Therapy

title: Parametric Analysis of Effective Tissue Thermal Conductivity, Thermal Wave Characteristic, and Pulsatile Blood Flow on Temperature Distribution during Thermal Therapy abstract: This study examines the coupled effects of pulsatile blood flow in a thermally significant blood vessel, the effective thermal conductivity of tumor tissue, and the thermal relaxation time in solid tissues on the temperature distributions during thermal treatments. Due to the cyclic nature of blood flow as a result of the heartbeat, the blood pressure gradient along a blood vessel was modeled as a sinusoidal change to imitate a pulsatile blood flow. Considering the enhancement in the thermal conductivity of living tissues due to blood perfusion, the effective tissue thermal conductivity was investigated. Based on the finite propagation speed of heat transfer in solid tissues, a modified wave bio-heat transfer transport equation in cylindrical coordinates was used. The numerical results show that a larger relaxation time results in a higher peak temperature. In the rapid heating case I (i.e., heating power density of 100 W cm− 3 and heating duration of 1 s) and a heartbeat frequency of 1 Hz, the maximum temperatures were 62.587 and 63.107 °C for thermal relaxation times of 0.464 and 6.825 s, respectively. In contrast, the same total heated energy density of 100 J cm− 3 in a slow heating case (i.e., heating power density of 5 W cm− 3 and heating duration of 20 s) revealed maximum temperatures of 57.724 and 61.233 °C for thermal relaxation times of 0.464 and 6.825 s, respectively. In rapid heating cases, the occurrence of the peak temperature exhibits a time lag due to the influence of the thermal relaxation time. In contrast, in slow heating cases, the peak temperature may occur prior to the end of the heating period. Moreover, the frequency of the pulsatile blood flow does not appear to affect the maximum temperature in solid tumor tissues.

Influence of blood vessel on the thermal lesion formation during radiofrequency ablation for liver tumors

title: Influence of blood vessel on the thermal lesion formation during radiofrequency ablation for liver tumors abstract: PURPOSE: The major obstacles of radiofrequency ablation (RFA) heat treatments are nonuniform heating in the thermal lesion and heat sinks caused by large blood vessels during treatments which could lead to high tumor recurrence in patients. The objective of this study is to help comprehend RFA heat treatment through thermal lesion formation using computer simulation, and thus to provide helpful assistance in planning RFA. METHODS: RFA heat treatment is a popular "minimally invasive" treatment method for both primary and metastatic liver tumors, and the heat treatment is studied by numerical calculation. A finite difference model is used to solve all partial differential equations for a simple three-dimensional cubic geometry model. Maximum tissue temperature is used as a critical index for reaching thermal lesion during RFA. Cylindrical RF cool-tip electrode is internally cooled at constant water temperature. RFA thermal lesion is studied at various impacts by single and countercurrent blood vessel(s) traversing the thermal lesion. Several factors are considered, such as location, diameter, and orientation of the blood vessel(s) to the electrode. RESULTS: Results show the thermal lesion size decreases as the lesion blood perfusion rate increases. And, single large blood vessel which is orthogonal to RF electrode will cause less undercooled volume in the thermal lesion than one which is parallel to RF electrode. Furthermore, convective energy may easily damage parallel vessel and its surrounding normal tissues during RFA. Small blood vessels (or larger vessels with slow blood flow rate) during RFA could form "tail-like" thermal lesion formation, which could damage vessel downstream spots. CONCLUSIONS: Studies suggested that incomplete RF tumor ablation still exists within 1 cm distance between large blood vessel and RF electrode in a liver. This could have significant impact on local tumor recurrence rates. Second, if thermally significant vessel existed inevitably within the lesion, avoiding the RF cool-tip electrode placement next to the parallel large blood vessel would have a better heat treatment during RF heating. Additionally, reduced blood flow rate could help reduce significant cooling by large blood vessel.

Future Classroom with the Internet of things A Service-Oriented Framework

title: Future Classroom with the Internet of things A Service-Oriented Framework abstract: The future classroom emerges as an approach to enhance pedagogy. Classroom participants can become more involved in their learning by interaction and collaboration. This becomes practical due to the extensive availability of modern electronic devices and networks. To implement an environment that supports the future classroom, an integration mechanism for various types of devices is required. In this paper, a framework design is proposed using the concept of the Internet of Things (IoT). The IoT aims to model an application domain as a set of things that are associated with the Internet. By analyzing the project requirements of future classroom applications, the Extensible Messaging and Presence Protocol (XMPP) is selected as the communication method for the things. Two examples are also provided to demonstrate the effectiveness of the design.

Effective heating for tumors with thermally significant blood vessels during hyperthermia treatment

title: Effective heating for tumors with thermally significant blood vessels during hyperthermia treatment abstract: Significant cooling effect by blood vessels, particularly in treated tumor region, during hyperthermia treatment has been recognized by researchers. The present study investigated a heating strategy, using a preheating zone and adaptive optimization, to effectively reduce the cooling effect as thermally significant blood vessels flowed through treated region during hyperthermia treatment. The preheating zone is located in a vessel's entrance region adjacent to treated tumor and the heating strategy attempted to elevate blood temperature before blood flowing into the treated region. We numerically calculated blood and tissue temperatures using 3-D models and the goal of treatment was to reach a uniform therapeutic temperature in the tumor region using the proposed heating strategy. Results showed first, for large blood vessels, the heating strategy effectively elevated blood temperature at the entrance of treated tumor and reduced total tumor power deposition. Consequently, it helped to reach the ideal treated temperature on tumor more effectively, and avoided extreme power deposition due to the cooling effect of blood vessels entering the treated region. For small blood vessels, the preheating zone could further improve the treatment result. Secondly, heating flowing blood with adaptive optimization results in a unique phenomenon along blood flow paths. That is a strong convective nature of blood flow, which creates high thermal gradients in the treated region. Thus, it plays a different and significant role in adaptive optimization process as compared to thermal diffusion of solid tissues.

Development of a Chinese opinion-mining system for application to Internet online forums

title: Development of a Chinese opinion-mining system for application to Internet online forums abstract: Articles posted on a forum often contain new Internet words related to opinion elements (feature words and opinion words). Consequently, existing Chinese opinion-mining systems may exhibit low recall and precision because they cannot recognize these new Internet words. Therefore, we propose a simple algorithm to elaborate on the opinion elements of such articles by extracting the opinion elements. Moreover, when an opinion word is combined with a specific word or concatenated with another opinion word, it may cause a change in the polarity or meaning of the opinion. This fact is prone to cause difficulties by changing the polarity or meaning of certain opinion elements, leading to errors in the analysis results of the Chinese system. We designed three algorithms with context dependency to address this problem. In this paper, we develop a semi-automatic Chinese opinion-mining system with these algorithms to extract these new opinion elements. Then, we determine whether the new word identified through manual judgment is a useful opinion element for a specific domain and add it to the thesaurus. In comparison with semi-automatic annotation methods, our approach can save considerable labor. After a 20-month follow-up analysis, the experimental data indicated that the precision, recall, and F1 of the system reached 84.0, 89.4 %, and 0.865, respectively.

Brokering knowledge in networks: institutional intermediaries in the Taiwanese biopharmaceutical innovation system

title: Brokering knowledge in networks: institutional intermediaries in the Taiwanese biopharmaceutical innovation system abstract: The literature maintains that in the development models of the Asian tigers in the 1980s, policy-induced intermediaries played the key mediating roles in acquiring technology from abroad to enhance local capabilities. In this paper, we examined how the intermediaries fare in terms of their expected brokerage roles in the context of the Taiwanese biopharmaceutical sector. By applying social network methods to data on this specific sub-sector, we demonstrate that the intermediary organisations under-performed in terms of brokering the transfer and diffusion of foreign technologies. Two factors underlie this result: intermediaries need to possess sufficient capabilities to be able to drive the strategy of stimulating a science-intensive sector through foreign technology, and intermediaries alone are not sufficient for the success of this strategy. We conclude that, instead of heavily relying on intermediaries to act as brokers, enabling research organisations and firms to play more effective brokerage roles may be a more successful strategy to develop a science-intensive sector such as biopharmaceuticals.

A survey on intelligent sensor network and its applications

title: A survey on intelligent sensor network and its applications abstract: With advances in technology, small form-factor sensors are feasible for various kinds of applications. The improvements on communication technology further make it practical to construct a wireless sensor network (WSN). In this paper, we review the works that are related to intelligent sensor network. Because there are no precise definitions of intelligent sensor network, we group them into two categories. One is to solve WSN issues with intelligent algorithms. The other is to design an intelligent application that incorporates sensor networks as the data sources. According to the categorization, the description of WSN issues, intelligent algorithms, and intelligent application technology are also provided in this article.

A Novel Algorithm for Mining Closed Temporal Patterns from Interval-Based Data

title: A Novel Algorithm for Mining Closed Temporal Patterns from Interval-Based Data abstract: Closed sequential patterns have attracted researchers’ attention due to their capability of using compact results to preserve the same expressive power as conventional sequential patterns. However, studies to date have mainly focused on mining conventional patterns from time interval-based data, where each datum persists for a period of time. Few research efforts have elaborated on discovering closed interval-based sequential patterns (also referred to as closed temporal patterns). Mining closed temporal patterns are an arduous problem since the pairwise relationships between two interval-based events are intrinsically complex. In this paper, we develop an efficient algorithm, CCMiner, which stands for Closed Coincidence Miner to discover frequent closed patterns from interval-based data. The algorithm also employs some optimization techniques to effectively reduce the search space. The experimental results on both synthetic and real datasets indicate that CCMiner not only significantly outperforms the prior interval-based mining algorithms in execution time but also possesses graceful scalability. Furthermore, we also apply CCMiner to a real dataset to show the practicability of time interval-based closed pattern mining.

A novel algorithm for mining closed temporal patterns from interval-based data

title: A novel algorithm for mining closed temporal patterns from interval-based data

Torpedo performance Markov model

title: Torpedo performance Markov model abstract: The improved evasive capability of the modern deiseal submarine can downgrade the performance of a torpedo seriously. However, a few studies have concerned the sophisticate diesel submarine as a main factor for the influence of a torpedo's attack. This paper presents a torpedo performance Markov model for making quick analyses on a torpedo performance in pursuit of a diesel submarine under various conditions. This model takes into account the effectiveness of submarine's counter measures and maneuvering behaviors of both sides. The Markov process is used and six states are sorted out for representing the dynamic behaviors for both of submarine and torpedo systematically. Through cases analyses, we prove that the torpedo performance is deteriorating exponentially as the number of counter measure is increasing. This analytical result may refine the anti-submarine warfare decision to avoid the possible misleading by solely relying on the deterministic torpedo probability of kill in the engagement. It also identifies that two pairs of jammer coupling with two decoys can be the best combination to saturate torpedo attack that can direct provide the decision makers a basic doctrine for controlling their engagement behaviors.

Incremental mining of temporal patterns in interval-based database

title: Incremental mining of temporal patterns in interval-based database abstract: In several real-life applications, sequence databases, in general, are updated incrementally with time. Some discovered sequential patterns may be invalidated and some new ones may be introduced by the evolution of the database. When a small set of sequences grow, or when some new sequences are added into the database, re-mining sequential patterns from scratch each time is usually inefficient and thus not feasible. Although there have been several recent studies on the maintenance of sequential patterns in an incremental manner, these works only consider the patterns extracted from time point-based data. Few research efforts have been elaborated on maintaining time interval-based sequential patterns, also called temporal patterns, where each datum persists for a period of time. In this paper, an efficient algorithm, Inc_TPMiner (Incremental Temporal Pattern Miner) is developed to incrementally discover temporal patterns from interval-based data. Moreover, the algorithm employs some optimization techniques to reduce the search space effectively. The experimental results on both synthetic and real datasets indicate that Inc_TPMiner significantly outperforms re-mining with static algorithms in execution time and possesses graceful scalability. Furthermore, we also apply Inc_TPMiner on a real dataset to show the practicability of incremental mining of temporal patterns.

Survey of Bio-inspired Computing for Information Hiding

title: Survey of Bio-inspired Computing for Information Hiding abstract: In this paper, we performed surveys of bio-inspired techniques for information hiding. The applications of bio-inspired optimization for information hiding or watermarking have emerged in early 2000's. Due to the exibility of algorithm designs, parameter selections, and performance metrics, the uses of bio-inspired ptimization techniques provide effective solutions for information hiding. Relating schemes from different papers in literature are extensively surveyed and are briefly discussed. This survey aims at providing the background knowledge for further researches in this field.

Confluent Thermal Lesion Formation in Liver with Radio Frequency Ablation by Using Internally Cooled Multiple-Electrode Technique: Computational Results

title: Confluent Thermal Lesion Formation in Liver with Radio Frequency Ablation by Using Internally Cooled Multiple-Electrode Technique: Computational Results abstract: Radiofrequency ablation (RFA) has been used successfully in the treatment of liver tumors. However, current RFA procedures are less effective against tumors that are large. The purpose of this study was to investigate internally cooled multiple-electrode technique with radio-frequency ablation (RFA) which technique could provide larger thermal lesion by using computer simulation and to determine optimal RF electrode spacing based on coagulation necrosis zone volume. Multiple electrically independent electrodes have been powering up by switching to the next electrode at a predetermined time interval of certain time period. As to computer models, the mathematical equations use Laplace equation of electric field calculation, and Bio-heat transfer equation of calculation temperature field. Numerical methods will consider Gauss-Seidel iteration to obtain 3-D finite difference solutions of a set of partial differential equations for a simple three-dimensional cubic geometry model. Maximum tissue temperature (T_(max)) is used as a critical index for reaching thermal lesion formation during RFA and threshold temperature (T_(thresh)) is used to estimate coagulation zone volume. Cylindrical RF cool-tip electrode is internally cooled at constant water temperature. Results showed several clover-shaped resultant coagulation necrosis and enlarged thermal lesions which were consistent with experimental results.

A robust power deposition scheme for tumors with large counter-current blood vessels during hyperthermia treatment

title: A robust power deposition scheme for tumors with large counter-current blood vessels during hyperthermia treatment abstract: In local hyperthermia, the goal is to raise target tumor temperatures to a uniform therapeutic temperature (i.e. 41–45 °C) with minimal injury to normal tissues. However, existing thermally significant blood vessels within or near a tumor makes hyperthermia treatment difficult as the traditional 1st-order iterative adaptive power scheme is unable to heat the tumor fast enough during treatment [1]. Strong convective heat transfer by large blood vessels is the main reason. The objective of this paper is to investigate a novel fast adaptive power scheme when a pair of counter-current blood vessels (artery-vein) is present in a tumor being treated with hyperthermia. Convergence value (CV) represents normalized root-mean-square deviation (NRMSD) of temperatures (with respect to therapeutic temperature); this value is used in the study to search for optimal power deposition. Higher order power deposition schemes (up to the 7th order), two counter-current blood vessels, and various distances between large artery and vein have been proposed and tested in computer simulations. The results show that the new scheme is robust with more than one large blood vessel under considerations. The scheme is capable of estimating power density deposition with accuracy in a short time, and interestingly reveals “scheme mismatch” which could speed up the convergence process.

Using syntactic rules to combine opinion elements in Chinese opinion mining systems

title: Using syntactic rules to combine opinion elements in Chinese opinion mining systems abstract: Most Chinese opinion mining systems use the specific pattern and nearby approach to combine relevant opinion elements (feature words and opinion words) to express the opinion tendencies of authors. In this paper, we propose a rule-based ad hoc method to study the combination problem of Chinese opinion elements. We extracted the opinion elements of articles based on lexicons and then combined them with the different sentence patterns and grammars to analyze the authors’ opinions. Because the articles on the online communities such as blogs, wikis, online forums, etc. do not have a defined format, there are often opinion comments that do not refer to the topic, resulting in information loss and significantly reduced recall. Therefore, the “default topic” method is proposed to correct this type of problem. Additionally, there might be errors when using the nearby approach to combine opinion elements. Thus, we propose the concept of “clause priority” to increase precision. After 20 months of long-term tracking and analysis, the experimental result indicates that the method proposed in this paper had good precision, recall, and F1 of opinion tendency analysis for review articles.

Blending Methods for Tactical Decision Evaluation of Diesel Submarine in the Engagement Scenarios

title: Blending Methods for Tactical Decision Evaluation of Diesel Submarine in the Engagement Scenarios abstract: 不同於傳統分析性模型之效益指標僅考量戰具、系統之效能，本研究之目的係以人之冒險本性為中心，提出產生最適可行作戰行動方案之決策科學方法，其中包括兩個作業程序：一、運用系統模擬求出潛艦存活率並以任務權重方式計算完成任務之給分。二、建立效用初值，運用效用函式進行最適作戰方案之分析。結果顯示，最適決策方案會依決策者(三類型指揮官) 風險偏好有所不同，本研究中選擇高風險卻能迅速完成任務方案之機率分別為：風險追求者 100%；風險中立者 80%；風險規避者 40%。本研究須獲得更多專家經驗以精準效用函數函式，彌補現況之不足。 Other than the traditional analytical models which heavily emphasize on platforms and systems performance , the objective of this paper is to use human risk-taking centric method for generating and optimizing the Course Of Actions (COAs) that includes two processes: first, use simulation for sub survivability and mission weight for scoring sub mission achievement; second, establish utility value and analyze COAs by utility process. The result shows the chance for three types of commanders (risk seeking, neutral and averse) choosing risky but efficient COA is100%, 80% and 40%. This analysis needs more interviewing samples for being accurate risk-taking utility function in contrast to current limited situation.

A location-based context-aware service discovery approach for cycling experience

title: A location-based context-aware service discovery approach for cycling experience abstract: This study explored the use of context-aware information to facilitate web service discovery in a ubiquitous computing setting. Consumer electronics and internet access enable ubiquitous computing and have played an essential part in our daily lives, including cycling experience. Future applications for cyclists will be required to interact with multiple specialised services. In this study, a service-oriented architecture (SOA)-based service discovery framework that is implemented using the extensible messaging and presence protocol (XMPP) technology is proposed, and the framework design is presented. An example of a restaurant recommendation system for cyclists is highlighted as a proof of concept prototype to demonstrate and investigate the feasibility and effectiveness of the proposed framework.