Generative regular-freeform surface recognition for generating material removal volume from stock model

The present paper illustrates the development of generative surface recognition for regular and freeform. To obtain the final form of product, material removal volume generation from a stock model is also discussed. Only a few studies integrated the regular and freeform surfaces to provide a comprehensive definition of surface recognition as well as for the volumetric estimation of removal material in finishing and roughing operations. The current research deploys a comprehensive surface recognition approach that can recognise both regular and freeform surfaces based on the geometry as well as loop entity of a face. In contrast to the regular surface that can be categorised into a particular group of geometrical shape, such as cylindrical shape, the proposed approach enables the recognition of a freeform surface that cannot be defined as a generic geometrical shape. In addition, the new method also simplifies the existing surface recognition for regular surfaces. The material removal volumes created consist of machining volumes for finishing and roughing operations needed to be machined to obtain the final form of the product. The present research provides a unique user customisation feature that enables user to specify the volumetric thickness for material removal volume in the finishing operation as well as the size for the stock model. These estimated volumes are prepared for subsequent manufacturing applications, such as sequencing of machining operation.     

Silver (Ag) as a novel masking material in glass etching for microfluidics applications

In this paper, we report the use of a single masking film for deep glass etching in hydrofluoric acid (HF). Thin film silver (Ag) is the key masking material in this work enabling a simple and low cost fabrication of microfluidic structures. The Ag film was deposited by evaporation and etched in a diluted nitric acid and de-ionized water solution at a ratio of 1:3. Surface morphology for different thicknesses of Ag film and its correlation to the maximum achievable etch depth is analyzed. AFM results shows low roughness values (<5 nm), indicating the Ag films are of smooth surface. With a 100 nm Ag film, a 220 μm etch depth in borosilicate glass substrates were produced and by further thickening the Ag to 300 nm, etch depths exceeding 300 μm were successfully achieved. SEM images show that thinner Ag films are of finer grains, potentially a source for pinholes formation where rapid penetration of HF along the grain boundaries peels off the Ag film from the glass surface. However, the Ag film was found not to react with HF. The process was demonstrated in the fabrication of cavities for integration with other microfluidic devices.     

Generation and Separation of Closely Separated Dual Baseband Channels for Provisioning of Independent Services in WDM-PON

This letter presents a novel technique that enables simple provisioning of independent services in wavelength-division-multiplexed passive optical networks. The technique uses a single laser and modulator for generation and a periodic passive filter for separation of two closely separated baseband channels. We present experimental results of the bit-error-rate performance for the two 1.5-Gb/s independent service channels at a frequency separation of only 6 GHz.     

Variations in white blood count, thromboxane B2 levels and hematocrit in chronic venous hypertension

OBJECTIVE: To analyze variations in leukocyte count and thromboxane B2 production in the femoral vein of patients with chronic venous hypertension (CVH). DESIGN: Prospective clinical study, controlled, non randomized and open. LOCATION: Hospital das Clínicas, Faculdade de Medicina da Universidade de S?o Paulo, referral center, university hospital. PARTICIPANTS: 15 patients with recurring stasis ulcer were analyzed, selected randomly from the venous diseases outpatient center, and 4 without lower limb venous alterations were also analyzed. INTERVENTION: Blood samples from the femoral and brachial veins were drawn following supine and 45 degrees reverse Trendelenburg. MAIN OUTCOMES MEASURES: Direct leukocyte count and analysis of the thromboxane B2 with enzyme linked immunosorbent assay test. RESULTS: After 30 minutes in reverse Trendelenburg, patients with CVH showed a leukocyte count reduced by +/- 27% (p = 0.02) and thromboxane B2 levels increased by +/- 158% (p = 0.02). CONCLUSIONS: We suggest that future studies of medications for stasis ulcers include their effects on leukocyte entrapment and thromboxane B2 production in the lower limb venous system.     

A semantic-aware log generation method for network activities

International Journal of Information Security - Context-aware network logging is becoming more prevalent for enterprise networks, data centers, and forensics. Monitoring agents are strategically...     

DDoS Detection in SDN using Machine Learning Techniques

Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and network operation over a network infrastructure. The SDN controller is considered as the operating system of the SDN based network infrastructure, and it is responsible for executing the different network applications and maintaining the network services and functionalities. Despite all its tremendous capabilities, the SDN face many security issues due to the complexity of the SDN architecture. Distributed denial of services (DDoS) is a common attack on SDN due to its centralized architecture, especially at the control layer of the SDN that has a network-wide impact. Machine learning is now widely used for fast detection of these attacks. In this paper, some important feature selection methods for machine learning on DDoS detection are evaluated. The selection of optimal features reflects the classification accuracy of the machine learning techniques and the performance of the SDN controller. A comparative analysis of feature selection and machine learning classifiers is also derived to detect SDN attacks. The experimental results show that the Random forest (RF) classifier trains the more accurate model with 99.97% accuracy using features subset by the Recursive feature elimination (RFE) method.     

600MHz BiCMOS digitally controlled oscillator for clock recovery and frequency synthesis PLLs

A 16-bit digitally controlled BiCMOS ring oscillator (DCO) is described. This BiCMOS DCO design provides improved frequency stability under thermal fluctuations. Simulations of a 5-stage DCO using 1μm BiCMOS process parameters achieved a controllable frequency range of 90-640MHz with a linear/quasi-linear range of around 300MHz. A tiny test chip was fabricated using MOSIS Orbit 2μm low-cost analogue CMOS process technology that provides a lateral NPN bipolar device option. Monotone frequency gain (frequency vs control-word transfer function) with fine stepping (tuning) over several kHz was verified experimentally, thus auguring the prospect of accurate frequency lock in an all-digital phase-locked loop (ADPLL) application. Worstcase jitter due to digital control transitions at pathological control-word boundaries for the BiCMOS DCO was observed to be less than 50 ps. This BiCMOS design would thus provide performance enhancement in PLL applications such as clock recovery and frequency synthesis.     

Social Engineering Attack Classifications on Social Media Using DeepLearning

In defense-in-depth, humans have always been the weakest link in cybersecurity. However, unlike common threats, social engineering poses vulnerabilities not directly quantifiable in penetration testing. Most skilled social engineers trick users into giving up information voluntarily through attacks like phishing and adware. Social Engineering (SE) in social media is structurally similar to regular posts but contains malicious intrinsic meaning within the sentence semantic. In this paper, a novel SE model is trained using a Recurrent Neural Network Long Short Term Memory (RNN-LSTM) to identify well-disguised SE threats in social media posts. We use a custom dataset crawled from hundreds of corporate and personal Facebook posts. First, the social engineering attack detection pipeline (SEAD) is designed to filter out social posts with malicious intents using domain heuristics. Next, each social media post is tokenized into sentences and then analyzed with a sentiment analyzer before being labelled as an anomaly or normal training data. Then, we train an RNN-LSTM model to detect five types of social engineering attacks that potentially contain signs of information gathering. The experimental result showed that the Social Engineering Attack (SEA) model achieves 0.84 in classification precision and 0.81 in recall compared to the ground truth labeled by network experts. The experimental results showed that the semantics and linguistics similarities are an effective indicator for early detection of SEA.     

Validation of respiratory inductive plethysmography using the Qualitative Diagnostic Calibration method in anaesthetized infants

The aim of this study was to compare tidal volume (VT) derived from the Qualitative Diagnostic Calibration (QDC) method (VT,QDC) with measurements from pneumotachography (VT,PN,T) in anaesthetized infants. Measurements were made during spontaneous (SV) and intermittent positive pressure (IPPV) ventilation, sighs and airway occlusions. The VT,DIF was the difference between VT,QDC and VT,PNT (%VT). The contribution of the ribcage (rc) to VT,QDC (%rc) and the thoracoabdominal phase lag were also derived. Twenty-eight infants, mean (SD) age 14.0 (6.2) months were studied. VT,QDC represented VT,PNT most closely when > or = 20 breaths were analysed. There was close agreement during SV immediately after the calibration period (95% limits of agreement (LA; QDC - PNT) -23, 3.0%). The 95% LA increased to -9.6, 10.2% after 10 min. Accuracy diminished during IPPV (95% LA -38, 31%), and sighs. During airway occlusions, when VT,PNT was zero, the 95% LA were -63, 4.1 mL x kg(-1). Mean phase lag was 36 and 2%, respectively, during SV and IPPV (p<0.05). The %rc appeared to be overestimated, being in excess of 50% in infants under 12 months. The Qualitative Diagnostic Calibration method used to estimate tidal volume in anaesthetized infants was limited by the need to analyse > or = 20 breaths and by a loss of within-subject accuracy if measurement conditions or pattern of breathing changed.     

The Hering-Breuer reflex in anesthetized infants: end-inspiratory vs. end-expiratory occlusion technique

Both end-inspiratory (EIO) and end-expiratory (EEO) occlusions have been used to measure the strength of the Hering-Breuer inflation reflex (HBIR) in infants. The purpose of this study was to compare both techniques in anesthetized infants. In each infant, HBIR activity was calculated as the relative prolongation of expiratory and inspiratory time during EIO and EEO, respectively. Respiratory drive was assessed from the change in airway pressure during inspiratory effort against the occlusion, both at a fixed time interval of 100 ms (P0.1) and a fixed proportion (10%) of the occluded inspiratory time (P10%). Twenty-two infants [age 14.3 +/- 6. 4 (SD) mo] were studied. No HBIR activity was present during EIO [-11.8 +/- 15.9 (SD) %]. By contrast, there was significant, albeit weak, reflex activity during EEO [HBIR: 27.2 +/- 17.4%]. A strong HBIR (up to 310%) was elicited in six of seven infants in whom EIO was repeated after lung inflation. P0.1 was similar during both types of occlusions, whereas mean +/- SD P10% was lower during EEO than during EIO: 0.198 +/- 0.09 vs. 0.367 +/- 0.15 kPa, respectively (P < 0.01). These data suggest a difference in the central integration of stretch receptor activity in infants during anesthesia compared with during sleep.