• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.738-754
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• 2024

Side-channel analysis (SCA) is a cryptanalytic technique that exploits physical leakages, such as power consumption or electromagnetic emanations, from cryptographic devices to extract secret keys used in cryptographic algorithms. Recent studies have shown that training SCA models with semi-supervised learning can effectively overcome the problem of few labeled power traces. However, the process of training SCA models using semi-supervised learning generates many pseudo-labels. The performance of the SCA model can be reduced by some of these pseudo-labels. To solve this issue, we propose the HWFilter method to improve semi-supervised SCA. This method uses a Hamming Weight Pseudo-label Filter (HWPF) to filter the pseudo-labels generated by the semi-supervised SCA model, which enhances the model's performance. Furthermore, we introduce a normal distribution method for constructing the HWPF. In the normal distribution method, the Hamming weights (HWs) of power traces can be obtained from the normal distribution of power points. These HWs are filtered and combined into a HWPF. The HWFilter was tested using the ASCADv1 database and the AES_HD dataset. The experimental results demonstrate that the HWFilter method can significantly enhance the performance of semi-supervised SCA models. In the ASCADv1 database, the model with HWFilter requires only 33 power traces to recover the key. In the AES_HD dataset, the model with HWFilter outperforms the current best semi-supervised SCA model by 12%.

• Environmental Engineering Research
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• v.21 no.4
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• pp.355-364
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• 2016

Beijing, as a cradle of modern industry and the third largest metropolitan area in China, faces more responsibilities to adjust industrial structure and mitigate carbon emissions. The purpose of this study is aimed at predicting and comparing industrial carbon emissions of Beijing in ten scenarios under different policy focus, and then providing emission-cutting recommendations. In views of various scenarios issues, system dynamics has been applied to predict and simulate. To begin with, the model has been established following the step of causal loop diagram and stock flow diagram. This paper decomposes scenarios factors into energy structure, high energy consumption enterprises and growth rate of industrial output. The prediction and scenario simulation results shows that energy structure, carbon intensity and heavy energy consumption enterprises are key factors, and multiple factors has more significant impact on industrial carbon emissions. Hence, some recommendations about low-carbon mode of Beijing industrial carbon emission have been proposed according to simulation results.

• ETRI Journal
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• v.43 no.4
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• pp.717-727
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• 2021

In this study, new multiplier and adder method designs with multiplexers are proposed. The designs are based on quaternary logic and a carbon nanotube field-effect transistor (CNTFET). The design utilizes 4 × 4 multiplier blocks. Applying specific rotational functions and unary operators to the quaternary logic reduced the power delay produced (PDP) circuit by 54% and 17.5% in the CNTFETs used in the adder block and by 98.4% and 43.62% in the transistors in the multiplier block, respectively. The proposed 4 × 4 multiplier also reduced the occupied area by 66.05% and increased the speed circuit by 55.59%. The proposed designs are simulated using HSPICE software and 32 nm technology in the Stanford Compact SPICE model for CNTFETs. The simulated results display a significant improvement in the fabrication, average power consumption, speed, and PDP compared to the current bestperforming techniques in the literature. The proposed operators and circuits are evaluated under various operating conditions, and the results demonstrate the stability of the proposed circuits.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• KIEAE Journal
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• v.8 no.4
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• pp.19-27
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• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.

• Journal of ILASS-Korea
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• v.29 no.1
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• pp.1-6
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• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.527-536
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• 2020

It has been found that an attacker can extract the secret key embedded in a security device and recover the operation instruction using power consumption traces which are some kind of side channel information. Many profiling-based side channel attacks based on a deep learning model such as MLP(Multi-Layer Perceptron) method are recently researched. In this paper, we implemented a disassembler for operation instruction set used in the micro-controller AVR XMEGA128-D4. After measuring the template traces on each instruction, we automatically made the pre-processing process and classified the operation instruction set using a deep learning model CNN. As an experimental result, we showed that all instructions are classified with 87.5% accuracy and some core instructions used frequently in device operation are with 99.6% respectively.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.69-76
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• 2012

This paper proposes an efficient power consumption scheme using sleep mode in home gateway. The scheme by this paper classifies incoming real time packet and non-real time packet in home gateway and delay non-real time packet. Therefore, the home gateway can have longer sleep time because non-real time packet can get additional delay time by proposing mechanism using timer. We use non-preemptive two priority queueing model for performance analysis. As a results, we verify that power consumption of proposed scheme is reduced more than existing scheme by delay of non-real time traffic.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.12
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• pp.1730-1738
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• 2001

This paper presents an overview of testing and analyzing field performance of a centrifugal chiller which has a rated capacity of 200 RT(703 kW). Field data of a chiller installed in the cleanroom research building of KIST has been collected far performance analysis. The operating data included start-up, shut-down, and quasi-static state where cooling capacity and compressor power consumption varied cyclically. It was found that the steady-state thermodynamic model could be applied to relate the cooling capacity and COP under quasi-static conditions. The results led to finding the required cooling load pattern and a possible energy saving method. This study provides a method of evaluating performance of a large capacity centrifugal chiller in which field test is necessary.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.12
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• pp.73-81
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• 2019

Titanium alloys have been spotlighted in numerous industries owing to their superior mechanical properties, such as high specific strength. However, the high heat and wear resistance of titanium alloys also lower their machinability and limit the wider application of the material. Many researchers have investigated the processing of titanium alloys, and it is required to evaluate the effectiveness and efficiency of developed technologies. From this perspective, this research studied sustainability in titanium alloy machining. The power consumption of the machine was measured during the process and analyzed in terms of process parameters and individual machine components. Here, an end mill specially designed for titanium was also investigated and compared with a general-purpose cutting tool. Based on the experimental results, a model was constructed to predict the power consumption of the overall process. It is expected that this study will contribute to the more effective and efficient processing of titanium alloys.