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This paper proposes an automatic flow to repair IR-drop violations by Engineering Change Order (ECO). Our ECO technique provides cell move and downsize solutions. We use machine learning to predict IR-drop so that we can prevent over-fixing. We use a commercial tool to predict timing so that this is a timing-aware ECO. With the above two predictions, we propose a novel multi-round bipartite matching to optimize the ECO resource utilization. Experimental results show that for a 5M gate real design, our proposed method repairs 2,504 (22%) violation cells out of the original 11,555 violation cells and repairs 36,272mV (37%) total excessive IR out of the original 98,674mV total excessive IR. We are able to perform ECO on seven thousand cells within 13 hours, so our ECO flow is practical and can be applied to large industrial designs.

A new scheme of ultra-fast mode-locked laser (MLL) employing broadband single mode Cr-doped fiber (SMCDF) and multilayer graphene is experimentally investigated. This is the first time report of broadband SMCDF and stacked graphene used in the MLLs. The advantage and performance of ultra-fast MLLs will be reported.

Launching a new store is one of the most important decisions a proprietor must make, with the placement of the store making the difference between financial success and financial ruin. However, since such decisions are based on data sampling and payroll records, a fully realistic analysis is often not feasible. Under such circumstances, a faulty analysis may lead to faulty decision-making, which in turn affects the business. In recent years, gradually maturing technology and its various applications have allowed researchers to use data about people flow to model real customer behavior. This paper discusses the analysis of this data as it pertains to the execution of a store launch. To test the efficacy of our methods, we will use the data from Feng Chia University as the basis for our analysis and discuss how to use it to determine a suitable location for the school cafeteria.

Global Positioning System (GPS) is widely used as the outdoor position system because of it provides the satisfactory results especially for outdoor navigation. However, it is not suitable for the circumstances of non-line of sight (NLoS) and complex indoor environments. To fill the gap, Wi-Fi signal has grasped the great attention being purposed as the solution for Indoor Positioning System (IPS). Existing enormous efforts have been exerted to focus on the Wi-Fi fingerprinting to achieve high accuracy. Through deep learning and machine learning, the current Wi-Fi fingerprinting can localize the object with the accuracy better than GPS. Nonetheless, it involves huge labor-cost calibration and high training complexity for intensive site survey and requires recalibration for a different environment. Due to these limitations, the current approach using Wi-Fi fingerprinting is impractical as the indoor localization solution to present-day scientific and enterprise interest. In this paper, we proposed an adaptive Wi-Fi trilateration-based indoor localization system which involves minimum labor-cost calibration to achieve a good accuracy, as a prominent research solution to location-based services (LBS).

The optimization of stacking graphene layers as saturable absorber in mode-locked lasers is demonstrated. The lower stacking layer is preferable to provide broader tunable range, whereas the higher one generates shorter pulsewidth.

Phenotyping definitions are widely used in observational studies that utilize population data from Electronic Health Records (EHRs). Biomedical text mining supports biomedical knowledge discovery. Therefore, we believe that mining phenotyping definitions from the literature can support EHR-based clinical research. However, information about these definitions presented in the literature is inconsistent, diverse, and unknown, especially for text mining usage. Therefore, we aim to analyze patterns of phenotyping definitions as a first step toward developing a text mining application to improve phenotype definition. A set random of observational studies was used for this analysis. Term frequency-inverse document frequency (TF-IDF) and Term Frequency (TF) were used to rank the terms in the 3958 sentences. Finally, we present preliminary results analyzing phenotyping definitions patterns.

This paper proposes an automatic method to diagnose risky cells that are responsible for PSN (Power Supply Noise) violations. We can also find ECO (Engineering Change Order) method (resize or move) to perform on risky cells to repair PSN violations. We apply superposition principle to model the diagnosis and repair as a linear programming problem. We consider not only PSN constraints but also timing constraints to make sure that we can repair all PSN violations without causing new timing violations. With our diagnosis result, designers can perform ECO with very little effort. The experimental results show that we can repair all PSN violations with only less than 2% of all candidate cells.

Interactions between drugs (also known as drug-drug interactions or DDIs), which may cause adverse affects, are of much concern; predicting, anticipating and avoiding them is key for improving patient safety and treatment outcome. Knowledge of DDIs is important for physicians to avoid adverse effects when prescribing two drugs simultaneously. DDIs are often published in the biomedical literature; however, gathering information about DDIs is time consuming given the shear volume of publications. Automatic text classification can speed up access to documents related to DDIs. However, the biomedical literature contains a relatively small number of publications relevant to DDIs, compared to the vast amount of irrelevant publications. This imbalance can lead to incorrect classification. While methods addressing class imbalance have been introduced to correctly identify items in the minority (relevant) class to improve recall, they often misclassify items in the majority (irrelevant) class, which leads to low precision. To reduce the number of irrelevant documents misclassified as relevant (false positive), we develop a two-stage cascade classifier. In each step, we separate publication abstracts that are DDI-relevant from those that are either drug-irrelevant or drug-relevant but DDI-irrelevant. We compare our classifier with other popular learning methods that aim to handle imbalance, applying the methods to a well-curated corpus consisting of DDI-relevant and DDI-irrelevant PubMed abstracts. Our method achieves higher precision and F1 measure than other methods while maintaining similar recall.

A novel multi-band broadband antenna for mobile handsets application is proposed in this article. An asymmetric T-type monopole antenna with a shorting-line is designed to be operated in long term evolution (LTE, 698MHz-960MHz, 1710MHz-2170MHz, 2500MHz-2690MHz) and wireless local area network (WLAN, IEEE 802.11ac, 5150MHz-5850MHz) bands. A prototype of the proposed antenna with 50 mm in length and 8 mm in width is fabricated and investigated experimentally. The experimental results indicate that the bandwidths for VSWR of 3:1 achieved were 37.75%, 24.63%, 11.46% and 21.76% at 800MHz, 1900MHz, 2600MHz and 5500MHz, respectively. The specific absorption rate (SAR) for an input power of 24dBm in LTE band, and an input power of 13dBm in IEEE 802.11ac band meet the SAR limit of 1.6 mW/g.

Many neurological or orthopedic disorders may cause motor impairments of shoulder. Patients require intensive training in order to recover from those impairments. However, the intensive training will lead to growing demand for strenuous work. Robot-aided therapy is able to alleviate the therapist's laborious burden and to provide more information about patient's condition during the therapy. Generally, the requirement of active therapy arises during the later stage of recovery. To realize the active therapy, a useful active control of the robot and effective recovery assessment for the active robot-aided therapy are essential. In this paper, a new active control method and an active therapy protocol with assessment indexes are designed. In this pilot research, several experiments on healthy subjects are designed to verify the proposed method with its active control performance and the effectiveness of the assessment indexes.

The application of liquid level sensing based on optical chaos is proposed and experimentally demonstrated. The liquid level sensor is a segment of no-core fiber (NCF) with a faraday reflection mirror (FRM) attached next to it, and with the filtering of a fiber Bragg grating (FBG), the intensity of the reflection light from the sensor is modulated by the liquid level. By monitoring the position and amplitude of the peak in the correlation curve, the measurement of liquid level and the locating of sensing point can be simultaneously achieved. Experimental result shows a linear range of 3.8 cm. This demodulation method also shows the ability of precise fault locating with the accuracy of several centimeters, making it easy for network maintenance.

The key function of recommendation systems is to analyze social network data and identify similar users. In recent years, multi-criteria algorithms called skyline queries have been used in conjunction with neural networks to search for similar users. However, many skyline query methods are slow and cumbersome, and generate user groups that are not similar enough to the target user. To solve these problems, we built an approximate skyline region using a neuro-fuzzy network. Simulation results demonstrated the effectiveness and efficiency of our approach.

This paper presents an inertial-sensor-based portable instrument and its associated swing motion detection algorithm to detect the following several major stages of a full golf swing motion: address, back swing, top of swing, down swing, impact, follow through, and finish. The portable instrument consisting of a microcontroller, a triaxial accelerometer, a triaxial gyroscope, and a Bluetooth wireless transmission module can be mounted on the golf club to measure swing motion signals. A swing motion detection algorithm composed of the procedures of signal collection, signal preprocessing, and swing motion segmentation has been developed for recognizing golf swing motion stages. Experimental results show that the portable instrument with its swing motion detection algorithm is a promising tool for serving as a training assistant tool for golfers.

Patients with upper limb disabilities caused by neurologic or orthopedic disorder required rehabilitation for the motor function recovery. In this research, based on a novel physical therapy, "bilateral arm training", the bilateral control interface connecting an IMU system and the exoskeleton robot NTUH-II is developed for patients to conduct passive or active-assistive rehabilitation. As for the active-assisting strategy, it is to generate the virtual guidance torque as a sufficient aid to the impaired side if needed with reference to the motion of the healthy side. Various experiments have been conducted to verify the tracking performance and assisting effect of proposed bilateral control. From these results, the utility of the developed bilateral control method has been confirmed.

A novel combo antenna for mobile handset applications is proposed in this article. An asymmetric T-type monopole antenna with a shorted-line is designed to be operated in LTE and WLAN (698MHz∼960MHz, 1710MHz∼2170MHz, 2400MHz∼2690MHz and 5150MHz∼5850MHz) bands. A prototype of the proposed antenna with 50 mm in length and 8 mm in width is fabricated and experimentally investigated. The specific absorption rate (SAR) for an input power of 24dBm in LTE bands are all meet the SAR limit of 1.6 mW/g. Experimental results are shown to verify the validity of theoretical work.

Search algorithms designed to seek out similar users in social networking sites are a significant function of recommendation systems. Conventionally, such sub-algorithms consider all the dimensions of user data as a whole. However, as the information in various dimensions is generally independent, the conventional approaches may not be the best way to find similar users. This paper solves this problem by proposing an approach based on depth-k skyline queries that searches for similar users with multiple conditions. This paper also presented an algorithm to accelerate this process, the effectiveness of which was demonstrated in a simulation.

This paper presents an easy-to-use simulation tool named VSAT for voltage stability analysis in smart grids. The proposed VSAT, which is a graphical user interface (GUI) software package, is develop by means of the visualization capabilities of Matlab for both research and educational applications. A series of case studies conducted on the IEEE 14-bus and IEEE 39-bus systems is used to demonstrate the effectiveness and flexibility of the proposed tool.

This paper proposes an integrated battery-charger for an electric-propulsion system. The system includes a rectifying diode bridge, an inverter, a motor, a digital signal processor, a battery set, and three relays. By suitably controlling the three relays and the switching states of the inverter, the proposed system can be operated either an electric propulsion system or a charger. Moreover, the charger can be operated as a boost converter or a buck converter. The input power factor is higher than 0.9, which can meet the IEC 1000-3-2 standard. Only three additional relays are required and the windings of the motor are connected. A digital signal processor, TMS-320-F-2808, is used to execute all of the control algorithms. As a result, the hardware circuit is quite simple. The volume and cost of the proposed system can be reduced when compared the traditional charger with a traditional propulsion system. Experimental results can validate the theoretical analysis and show the correctness and feasibility of the proposed method.

Under the efficient and compact coupling from optical waveguide, the field highly enhanced and concentrated around gap of gold bowtie structure can trap nano-particle precisely with very strong optical forces compared with most nanophotonic tweezers.

This paper presents a synchrophasor-based approach with cubic spline extrapolation technique for real-time voltage stability margin estimation which can increase voltage stability monitoring situational awareness. The proposed algorithm takes system load trends into account for practical applications. The benefit of the proposed measurement-based approach is that it does not require detailed power system model; that is, the performance of the proposed method is influenced very little by the uncertainty of modelling process. Moreover, the proposed method has low computational burden such that it is suitable for real-time use. Extensive simulations of Taiwan Power Company (Taipower) system are presented to validate the proposed algorithm.

In this paper we propose a scheme for reach ability testing to obtain statement coverage in the dynamic testing of concurrent programs. The proposed scheme derives inputs from SYN-sequences obtained in reach ability testing and uses these inputs to perform reach ability testing multiple times in order to achieve statement-coverage testing for a concurrent program.

Cloud computing is gaining tremendous momentum in both academia and industry, with more and more people and enterprises migrating their data and applications into the cloud. Cloud computing provides a new computing model with elastic scaling, a resource pool of unprecedented size, and the on-demand resource provisioning mechanism, which bring numerous challenges in implementing workflow management systems (WfMSs) in the cloud. Establishing scalable and cross-enterprise WfMSs in the cloud requires the adaptation and extension of existing concepts for process management. This paper presents a framework for how cross-enterprise processes can be implemented, secured, controlled, and scaled. We also explain why existing engine-based centralized and distributed WfMSs cannot guarantee the no repudiation requirement. The proposed framework is a document-routing system that implements major required security features such as authentication, confidentiality, data integrity, and nonrepudiation in the cloud computing environment. Its security framework is built by applying element-wise encryption and a cascade-based method of embedding digital signatures. The implementation and experimental results demonstrate the feasibility of the proposed framework.

Estrogens control multiple functions of hormone-responsive breast cancer (BC) cells [1]. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer [2]. However, ERα requires distinct co-regulator complex or modulators for efficient transcriptional regulation. To have insight into the regulatory network of ERα and discover the novel modulators of ERα which acted by distinct mechanisms, we proposed an analytical method based on a linear regression model to identify translational modulators and the relationship between genes for network. To comprehend the network associated with ERα, a dynamic gene expression profile and ChIP-Seq data shown to characterize the breast cancer cell response to estrogens are utilized. The role of modulators within molecular mechanism can be learned from the exploration of these two data sets. Based on the active or repressive function of the ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on the ERα, the ERα/modulator/target relationships were categorized into 27 classes.

Recently medical cosmetology has attracted significant business opportunity. Micro cosmetic surgery usually involves the minimally invasive cosmetic procedures such as non-ablative laser procedure for skin rejuvenation. However, an appropriate treatment selection for skin relies on accurate preoperative evaluation. In this paper, an automatic facial skin defects detection and recognition system is proposed. The system automatic locates the facial region and extracts region of interest. A support-vector-machine-based classifier is then used to classify the potential defects into spot, acne and normal skin. Experimental results demonstrate effectiveness of the proposed approach.

This paper presents an analytical model to address the scenarios of positioning errors for both Hall sensors and phase windings. This model is capable of demonstrating the qualitative features of torque ripples due to the indicated positioning defects. Moreover, it can be employed to investigate and predict various quantitative aspects such as fundamental frequency and corresponding harmonics, effects on average torque, etc. Incorporating this model into a conventional PWM PMBDCM model and conduct a realistic simulation further justify the capability and effectiveness of the proposed analytical model.