• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.221-225
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• 2014

Low power RF devices, such as RFID and Zigbee, are important for ubiquitous sensing. These devices, however, are powered by portable energy sources, such as batteries, which limits their use. To mitigate this problem, this study developed RF energy harvesting with W-CDMA for a low power RF device. Diodes are required with a low turn on voltage because the diode threshold is larger than the received peak voltage of the rectifying antenna (rectenna). Therefore, a Schottky diode HSMS-286 was used. A prototype of RF energy harvesting device showed the maximum gain of 5.8dBi for the W-CDMA signal. The 16 patch antennas were manufactured with a 10 dielectric constant PTFT board. In low power RF devices, the transmitter requires a step-up voltage of 2.5~5V with up to 35 mA. To meet this requirement, the Texas Instruments TPS61220 was used as a low input voltage step-up converter. From the evaluated result, the achievable incident power of the rectenna at 926mV to operate Zigbee can be obtained within a distance of 12m.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.473-482
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• 2017

Hand gesture recognition is regarded as new Human Computer Interaction (HCI) technologies for the next generation of mobile devices. Previous hand gesture implementation requires a large memory and computation power for hand segmentation, which fails to give real-time interaction with mobile devices to users. Therefore, in this paper, we presents a low latency and memory-efficient hand segmentation architecture for natural hand gesture recognition. To obtain both high memory-efficiency and low latency, we propose a streaming hand contour tracing unit and a fast contour filling unit. As a result, it achieves 7.14 ms latency with only 34.8 KB on-chip memory, which are 1.65 times less latency and 1.68 times less on-chip memory, respectively, compare to the best-in-class.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.4
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• pp.569-577
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• 2009

Mobile information retrieval is an evolving branch of information retrieval that is centered on mobile and ubiquitous environments. In general, mobile devices are characterized by lightweight, low power, small memory, small display, limited input/output, low bandwidth, and so on. Some of these characteristics make it impossible to apply general information retrieval to mobile environments without any modification. In order to relieve this problem, we design and implement an information retrieval system for mobile devices like wireless phones, PDA and handheld devices. We use document summarization techniques to alleviate the limitation of small display and user profiles to retrieve the most proper documents for each individual user for personalized search. Futhermore we use meta-search to lighten some burdens visiting several portal sites. In this paper, we have implemented and demonstrated the proposed mobile information retrieval system on the domain of travel and received good evaluation from users subjectively.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.676-678
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• 2002

In this work, we present the novel scheduling algorithm of the multimedia data retrieval for the mobile disk drive. Our algorithm is focused on minimizing the power consumption involved in data retrieval from the local disk drive. The prime commodity in mobile devices is the electricity. Strict restriction on power consumption requirement of the mobile device put unique demand in designing of its hardware and software components. State of the art disk based storage subsystem becomes small enough to be embedded in handhold devices. It delivers abundant storage capacity and portability. However, it is never be trivial to integrate small hard disk or optical disk drive in handhold devices due to its excessive power consumption. Our algorithm ARM in this article generates the optimal schedule of retrieving data blocks from the mobile disk drive while guaranteeing continuous playback of multimedia data.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.133-144
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• 2019

Although deep learning-based visual image recognition technology has evolved rapidly, most of the commonly used methods focus solely on recognition accuracy. However, the demand for low latency and low power consuming image recognition with an acceptable accuracy is rising for practical applications in edge devices. For example, most Internet of Things (IoT) devices have a low computing power requiring more pragmatic use of these technologies; in addition, drones or smartphones have limited battery capacity again requiring practical applications that take this into consideration. Furthermore, some people do not prefer that central servers process their private images, as is required by high performance serverbased recognition technologies. To address these demands, the object and scene recognition technologies for mobile/embedded devices that enable optimized neural networks to operate in mobile and embedded environments are gaining attention. In this report, we briefly summarize the recent trends and issues of object and scene recognition technologies for mobile and embedded devices.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.157-168
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• 2005

Group key agreement protocols are designed to provide a group of parties securely communicating over a public network with a session key. The mobile computing architecture is asymmetric in the sense of computational capabilities of participants. That is, the protocol participants consist of the stationary server(application servers) with sufficient computational Power and a cluster of mobile devices(clients) with limited computational resources. It is desirable to minimize the amount of computation performed by each group member in a group involving low-power mobile devices such as smart cards or personal digital assistants(PDAs). Furthermore we are required to update the group key with low computational costs when the members need to be excluded from the group or multiple new members need to be brought into an existing group. In this paper, we propose a dynamic group key protocol which offers computational efficiency to the clients with low-power mobile devices. We compare the total communicative and computational costs of our protocol with others and prove its suity against a passive adversary in the random oracle model.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.193-199
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• 2011

In this paper, we proposed battery driven low power algorithm in mobile device. Algorithm the mobile devices in power of the battery for the task to perform power consumption to reduce the frequency alters. Power of the battery perform to a task power consumption of is less than the task perform to frequency the lower. Frequency control the task, depending on in the entire system devices used among the highest frequency with devices first target perform to. Frequency in the decrease the second largest frequency with of the device the frequency in changes the power consumption to calculate. The calculated consumption power the battery of level is greater than level the frequency by adjusting power consumption, lower power of the battery the task perform when you can to the frequency to adjust. Experiment the frequency by adjusting power consumption a method to reduce using [6] and in the same environment power of the battery consider the task to perform frequency were controlled. The results in [6] perform does not battery power on task operates that the result was.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.25-44
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• 2010

With the increasing popularity of mobile devices, it has become necessary to protect private information and content in these devices. Face recognition has been favored over conventional passwords or security keys, because it can be easily implemented using a built-in camera, while providing user convenience. However, because mobile devices can be used both indoors and outdoors, there can be many illumination changes, which can reduce the accuracy of face recognition. Therefore, we propose a new face recognition method on a mobile device robust to illumination variations. This research makes the following four original contributions. First, we compared the performance of face recognition with illumination variations on mobile devices for several illumination normalization procedures suitable for mobile devices with low processing power. These include the Retinex filter, histogram equalization and histogram stretching. Second, we compared the performance for global and local methods of face recognition such as PCA (Principal Component Analysis), LNMF (Local Non-negative Matrix Factorization) and LBP (Local Binary Pattern) using an integer-based kernel suitable for mobile devices having low processing power. Third, the characteristics of each method according to the illumination va iations are analyzed. Fourth, we use two matching scores for several methods of illumination normalization, Retinex and histogram stretching, which show the best and $2^{nd}$ best performances, respectively. These are used as the inputs of an SVM (Support Vector Machine) classifier, which can increase the accuracy of face recognition. Experimental results with two databases (data collected by a mobile device and the AR database) showed that the accuracy of face recognition achieved by the proposed method was superior to that of other methods.

• Journal of electromagnetic engineering and science
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• v.14 no.4
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• pp.353-359
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• 2014

Recently, the use of mobile devices has increased, and mobile traffic is growing rapidly. In order to deal with such massive traffic, cognitive radio (CR) is applied to efficiently use limited-spectrum resources. However, there can be multiple communication systems trying to access the white space (unused spectrum), and inevitable interference may occur to cause mutual performance degradation. Therefore, understanding the effects of interference in CR-based systems is crucial to meaningful operations of these systems. In this paper, we consider a long-term evolution (LTE) system using additional spectra by accessing the TV white space, where low-power devices (LPDs) are licensed primary users, in addition to TV broadcasting service providers. We model such a heterogeneous system to analyze the co-existence problem and evaluate the interference effects of LPDs on LTE user equipment (UE) throughput. We then present methods to mitigate the interference effects of LPDs by 'de-selecting' some of the UEs to effectively increase the overall sector throughput of the CR-based LTE system.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1754-1764
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• 2004

Lately mobile handheld devices such as Personal Digital Assistant (PDA) and cellular phones are getting more popular for personal web surfing. However, today most mobile handheld devices have relatively poor web browsing capability due to their low performance so their users have to suffer longer communication latency than those of desktop Personal Computers (PCs). In this paper, we propose an effective pre-refresh mechanism for embedded web browser of mobile handheld devices to reduce this problem. The proposed mechanism uses the idle time to pre-refresh the expired web objects in an embedded web browser's cache memory. It increases the utilization of Central Processing Unit (CPU) power and network bandwidth during the idle time and consequently reduces the client's latency and web browsing cost. An experiment was done using a simulator designed by us to evaluate the efficacy of the proposed mechanism. The experiment result demonstrates that it has a good performance to make web surfing faster.