Browsing by Author "Lin, Chih-Yu"

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A Folksonomy-based Guidance Mechanism for Context-aware Ubiquitous Learning: A Case Study of Chinese Scenic Poetry Appreciation Activities
(2012-01-01)
Shih, Wen-Chung
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Tseng, Shian-Shyong
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Yang, Che-Ching
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Lin, Chih-Yu
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Liang, Tyne
In this work ubiquitous learning technologies are applied to Chinese scenic poetry appreciation. A folksonomy-based approach is proposed to accumulate knowledge about poems and their corresponding scenic spots. A user can use a "Tagging" operation by a smart phone to associate a concept (a word, a phrase or a sentence) with a scenic spot. These associations will be recorded in a folksonomy, which is then transformed into a Learning Guidance Tree to support personalized guidance in u-learning environments. The purpose of this work is to propose a folksonomy-based guidance mechanism. Also, we attempt to find students' and teachers' attitudes towards the innovative application through a case study. To show the effectiveness of the innovative approach, a ubiquitous learning system was developed to conduct Chinese scenic poetry appreciation activities for a fifth-grade Chinese course in Taiwan, in which forty-eight students participated. The survey results show that the system had a positive impact on students' learning, especially on the affective domain including participation, motivation and interaction.
A Velocity-Preserving Trajectory Simplification Approach
(2016-01-01)
Lin, Chih-Yu
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Hung, Chih-Chieh
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Lei, Po-Ruey
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交大名義發表
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National Chiao Tung University
By the rise of mobile devices, trajectory data could be easily collected and used in several applications, like destination prediction, public transportation optimization, and travel route recommendation. However, due to the spatio-temporal nature, raw trajectory data usually contain redundant movement information. This observation motivates the trajectory simplification approaches which discard some points with preserving some specific features, such as position features, direction features, and so on. Most of existing simplifications ignore the importance of velocity features. This paper proposes an adaptive trajectory approaches while taking the velocity feature into account. Specifically, the Adaptive Trajectory Simplification (ATS) algorithm is proposed, which not only preserves the position feature, but the velocity feature from the given trajectories. ATS algorithm groups the velocity values into several intervals, which are used to partition trajectories into velocity-preserving segments. The simplified trajectory could be derived by applying the position-preserving simplification approach on each segment, where the threshold in a position-preserving approach could be determined without manual setting. Extensive experiments are conducted by using a real trajectory dataset in Porto. The experimental results show ATS algorithm could simplify trajectories effectively while preserving the velocity feature and the position feature at the same time.
Augmenting Car Surrounding Information by Inter-Vehicle Data Fusion
(2019-01-01)
Lee, Tzu-Kuang
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Kuo, Yu-Chiao
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Huang, Shih-Hsuan
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Wang, Guan-Sheng
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Lin, Chih-Yu
Collecting vehicle surrounding information is a key issue for accident prevention and autonomous driving applications. Although GPS and 4G/LTE are widely accepted. it is still a challenge for a vehicle to get complete information of its surrounding vehicles. In this work, we consider the integration of multi-sensory data through V2V communications to help a vehicle to understand its complex surroundings. We propose a fusion algorithm that can integrate four types of sensory inputs: V2V communications, GPS, camera, and inertial data. We show that through such fusion, it is possible for a vehicle to visually see the driving states of its surrounding vehicles.
Distributed Clustering and Spectrum-Based Proximity Device Discovery in a Wireless Network
(2016)
Chang, Tofar C. -Y.
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Wei, Chun-Yi
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Hsu, Min-Chien
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Lin, Chih-Yu
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Su, Yu T.
Direct short-range device-to-device (D2D) conununication enjoys many advantages, such as high transmission rates, low propagation delays, low transmit power and interference. In order to realize the advantages, a device or user equipment participating in the D2D communications have to determine that the devices discovered are in a proximity area and are suitable to establish links with them. Hence, an accurate and efficient clustering scheme, which can organize the devices nearby into multiple D2D communication groups is necessary. Against this background, in this paper we propose a self-clustering scheme which requires no assistance from Cellular Network. The philosophy of our design is to group the devices with similar sensed spectrum profiles. In order to facilitate this self-clustering scheme, we adopt Reed-Solomon (RS) code into our proposed design. More specifically, in our design, a D2D communication group is formed by the D2D devices whose sensed spectrum vectors are mapping to the same valid RS codeword which is broadcast by the form of frequency-hopping (141) pattern. Additionally, the collision event could happen when multiple D2D devices transmit signals to discovery their group members. Hence, we design the FH probing sequence based on a randomly cyclic-shifted non-binary RS codeword to eliminate the possible collision events and interference exited in clustering procedure. In this paper, we provide our detail sequence design and the self-clustering procedure. In the simulation results, we show that the proposed self-clustering is efficient and effective.
Exploiting spatial correlation at the link layer for event-driven sensor networks
(2012)
Lin, Chih-Yu
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Tseng, Yu-Chee
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Lai, Ten H.
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資訊工程學系
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Department of Computer Science
Wireless Sensor Networks (WSNs) can generally be classified into two categories: time-driven and event-driven. In an event-driven WSN, sensors report their readings only when they detect events. In such behaviour, sensors in the event area may suffer from higher contention. In this paper, we solve this problem by jointly considering two sub-issues. One is exploiting the spatial correlation of sensor data and the other is designing a specific MAC protocol. We propose a novel hybrid TDMA/CSMA protocol with the following interesting features that differentiate itself from traditional TDMA-based protocols: (1) the TDMA part is based on very loose time synchronisation and is triggered by the appearance of events; (2) the slot assignment strategy associated with the TDMA part takes the spatial correlation of sensor data into consideration and thus allows less strict slot allocation than conventional TDMA schemes. Simulation results show the efficiency of the proposed protocol.
Imprecision-Tolerant Location Management for Object-Tracking Wireless Sensor Network
(2010-03-01)
Lin, Chih-Yu
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Tseng, Yu-Chee
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Liu, Yung-Chih
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資訊工程學系
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Department of Computer Science
An important issue of wireless sensor networks is object tracking, where the key steps include event detection, target classification, location estimation and location management. The main theme of this paper is location management. Because imprecision is an inherent property in object-tracking sensor networks, this paper focuses on the scenarios where users can tolerate a certain degree of imprecision in their query results. We intend to develop a location management scheme that can achieve two goals. First, multiple precision levels are provided. Second, the query cost is proportional to the precision level. To achieve these two goals, we propose a tree-based imprecision-tolerant location management scheme that includes three major components: (1) update and query mechanisms that can support imprecision-tolerant queries, (2) the approach to taking the statistics of imprecision-tolerant queries and (3) a tree construction algorithm that can reduce the query cost and minimize the increment of update cost. Performance evaluations are conducted through simulations to verify the proposed scheme.
Message-efficient in-network location management in a multi-sink wireless sensor network
(2006)
Lin, Chih-Yu
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Tseng, Yu-Chee
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Lai, Ten H.
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資訊工程學系
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Department of Computer Science
A wireless sensor network consists of many tiny sensor nodes. The distributed memory spaces of sensors can be considered as a large distributed database, in which one can conduct in-network data processing. This paper considers a sensor network used for object tracking where distributed location updates and queries are performed inside the network. Although this issue has been intensively studied for cellular networks, the same problem in sensor networks has very different characteristics. In this paper, we propose an efficient location management scheme for object tracking in a multi-sink sensor network where users can inquire the locations of objects via any sink in the network. A message-efficient algorithm that describes how to perform location updates and queries is proposed. Furthermore, two distributed virtual tree construction algorithms are also presented. The goal is to reduce the overall update and query cost. The efficiency of the proposed algorithms is evaluated and verified by simulations.
On Local Cache Management Strategies for Mobile Augmented Reality
(2014-01-01)
Wu, Chien-Cheng
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Tung, Li-Ping
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Lin, Chih-Yu
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Lin, Bao-Shuh P.
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Tseng, Yu-Chee
Mobile Augmented Reality (MAR) is generally defined as the service that is capable of enhancing the real-world camera views of a smartphone with extra information on top of the screen. Thus, MAR has triggered strong interests in mobile e-commerce, location-based service, etc. However, MAR is usually constrained by the local storage and computing power of the device as well as the latency and bandwidth of the underlying wireless channel. The computation demand is high because a targeted object needs to be compared to lots of images in the database. The communication demand is high because potential objects need to be continuously transmitted to the server and the augmented information needs to be downloaded from the server. This paper investigates the Local Cache Management (LCM) problem to manage the computation and communication work of a mobile device and harmonize the local and remote workloads. We present strategies to pre-fetch higher-priority objects from the server and replace lower-priority objects in the local cache based on temporal and spatial access locality. We verify the effectiveness of our strategies in term of cache hit ratio, response latency, and remote requests via simulations.
SensingGO - Toward Mobile/Cellular Data Measurement with Social and Rewarding Activities
(2018-01-01)
Lin, Yi-Hao
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Chen, Jyh-Cheng
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Lin, Chih-Yu
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Su, Bo-Yue
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Lee, Pei-Yu
Mobile Crowd Sensing (MCS) is a promising paradigm to collect large-scale network data globally. However, how to motivate people to collect and share data is a challenge. We believe the major reason why many MCS systems are not pervasive is because there are no incentives for people to use them. In this paper, we present SensingGO, a system which encourages people to keep sensing data by integrating incentive mechanisms. The sensed data are then transmitted to our backend server. The data we collected and the source code of SensingGO are open to anyone freely. We also demonstrate the analysis of real mobile data collected from SensingGO.
Solution-Processable Quinoidal Dithioalkylterthiophene-Based Small Molecules Pseudo-Pentathienoacenes via an Intramolecular S center dot center dot center dot S Lock for High-Performance n-Type Organic Field-Effect Transistors
(2020-06-03)
Vegiraju, Sureshraju
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Torimtubun, Alfonsina Abat Amelenan
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Lin, Po-Shen
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Tsai, Hsin-Chia
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Lien, Wei-Chieh
A new organic small-molecule family comprising tetracyanoquinodimethane-substituted quinoidal dithioalky(SR)terthiophenes (DSTQs) (DSTQ-6 (1); SR = SC6H13, DSTQ : 10 (2); SR = SC10H21, DSTQ14 (3); SR = SC10H21) was synthesized and contrasted with a nonthioalkylated analogue (DRTQ14 (4); R = C14H29). The physical, electrochemical, and electrical properties of these new compounds are thoroughly investigated. Optimized geometries obtained from density functional theory calculations and single-crystal X-ray diffraction reveal the planarity of the SR-containing DSTQ core. DSTQs pack in a slipped pi-pi stacked two-dimensional arrangement, with a short intermolecular stacking distance of 3.55 A and short intermolecular S center dot center dot center dot N contacts of 3.56 angstrom. Thin-film morphological analysis by grazing incident X-ray diffraction reveals that all DSTQ molecules are packed in an edge-on fashion on the substrate. The favorable molecular packing, the high core planarity, and very low lowest unoccupied molecular orbital (LUMO) energy level (-4.2 eV) suggest that DSTQs could be electron-transporting semiconductors. Organic field-effect transistors based on solution-sheared DSTQ : 14 exhibit the highest electron mobility of 0.77 cm(2) V-1 s(-1) with good ambient stability, which is the highest value reported to date for such a solution process terthiophene-based small molecular semiconductor. These results demonstrate that the device performance of solution-sheared DSTQs can be improved by side chain engineering.
Solution-Processed High-Performance Tetrathienothiophene-Based Small Molecular Blends for Ambipolar Charge Transport
(2018-07-11)
Vegiraju, Sureshraju
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Lin, Chih-Yu
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Priyanka, Pragya
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Huang, Deng-Yi
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Luo, Xian-Lun
Four soluble dialkylated tetrathienoacene (TTAR)-based small molecular semiconductors featuring the combination of a TTAR central core, pi-conjugated spacers comprising bithiophene (bT) or thiophene (T), and with/without cyanoacrylate (CA) end-capping moieties are synthesized and characterized. The molecule DbT-TTAR exhibits a promising hole mobility up to 0.36 cm(2) V-1 s(-1) due to the enhanced crystallinity of the microribbon-like films. Binary blends of the p-type DbT-TTAR and the n-type dicyanomethylene substituted dithienothiophene-quinoid (DTTQ-11) are investigated in terms of film morphology, microstructure, and organic field-effect transistor (OFET) performance. The data indicate that as the DbT-TTAR content in the blend film increases, the charge transport characteristics vary from unipolar (electron-only) to ambipolar and then back to unipolar (hole-only). With a 1:1 weight ratio of DbT-TTAR DTTQ-11 in the blend, well-defined pathways for both charge carriers are achieved and resulted in ambipolar transport with high hole and electron mobilities of 0.83 and 0.37 cm(2) V-1 s(-1), respectively. This study provides a viable way for tuning microstructure and charge carrier transport in small molecules and their blends to achieve high-performance solution-processable OFETs.
Transportation Type Identification by using Machine Learning Algorithms with Cellular Information
(2019-01-01)
Lin, Yi-Hao
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Chen, Jyh-Cheng
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Lin, Chih-Yu
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Su, Bo-Yue
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Lee, Pei-Yu
It is crucial for future 5G networks to intelligently understand how users move so that the networks can allocate different resources efficiently. In this paper, we try to find practical features to identify four common types of motorized transportations, including High-Speed Rail (HSR), subway, railway, and highway. We propose a system architecture that can provide accurate, real-time, and adaptive solution by using cellular information only. Because we do not use GPS as that in most of the prior studies, we can reduce energy consumption, size of log data, and computational time. Around 500-hour data are collected for performance evaluation. Experimental results confirm the effectiveness of the proposed algorithm, which can improve well-known machine learning algorithms to approximately 98% classification accuracy. The results also show that battery consumption can be reduced about 37%.