Recent advances of data compression in wireless sensor network

Wireless Sensor Networks (WSNs) have emerged as one of the most promising wireless communication systems supporting wide variety of applications ranging from military tasks, healthcare, disaster prediction and indoor positioning. The low complexity and cost of the nodes result in constraints such as computational power, communication bandwidth and battery power. Energy consumption is one of the most critical to WSN. In WSN communication, data transmission is considered the largest contributor to total energy exhaustion and apparently, it is influenced by the size of the data. Favorably, data compression can be used to reduce the amount of data that requires to be transmitted and hence prolongs sensor's lifetime. In this study, we survey various approaches, issues and challenges to WSN efficiency related to data compression discuss the effect of the data size on the sensor efficiency and how data compression algorithms can be used to address small size data transmission. Finally, recent approaches are reviewed with highlighting of advantages and disadvantages of each solution

Thermal analysis of both ventilated and full disc brake rotors with frictional heat generation

In automotive engineering, the safety aspect has been considered as a number one priority in development of a new vehicle. Each single system has been studied and developed in order to meet safety requirements. Instead of having air bags, good suspension systems, good handling and safe cornering, one of the most critical systems in a vehicle is the brake system. The objective of this work is to investigate and analyze the temperature distribution of rotor disc during braking operation using ANSYS Multiphysics. The work uses the finite element analysis techniques to predict the temperature distribution on the full and ventilated brake discs and to identify the critical temperature of the rotor. The analysis also gives us the heat flux distribution for the two discs

Distribution power loss minimization via distributed generation, capacitor and network reconfiguration

This paper presents a solution to solve the network reconfiguration, DG coordination (location and size) and capacitor coordination (location and size), simultaneously. The proposed solution will be determined by using Artificial Bee Colony (ABC). Various case studies are presented to see the impact on the test system, in term of power loss reduction and also voltage profiles. The proposed approach is applied to a 33-bus test system and simulate by using MATLAB programming. The simulation results show that combination of DG, capacitor and network reconfiguration gives a positive impact on total power losses minimization as well as voltage profile improvement compared to other case studies

Passively mode-locked ultrashort pulse fiber laser incorporating multi-layered graphene nanoplatelets saturable absorber

In this paper, a passive mode-locked erbium-doped fiber laser (EDFL) incorporating graphene nanoplatelet (GNP) powder-based saturable absorber (SA) with short pulse duration in femtosecond range is demonstrated. A good synthesis of GNP can be simply produced via a combination of thermal, chemical, and mechanical exfoliation of expandable graphite. The GNP-SA is fabricated by mechanically imprinting the powder onto the tip of a single mode fiber ferrule. The characterization of SA is done via focus ion beam scanning electron microscope, energy dispersive X-ray spectroscopy, as well as Raman spectroscopy. The fabricated GNP-SA has 1.8 % modulation depth and C-band transmission loss of less than 1.8 dB. The ring-configuration EDFL integrated with GNP-SA yields a mode-locking threshold of 22.6 mW pump power. Net anomalous dispersion of the laser cavity is validated by the observation of Kelly’s sideband in the optical spectrum. At maximum pump power of 115.8 mW, the mode-locked EDFL has a pulse repetition rate of 13.11 MHz, sech2 profile fitted pulse duration of 694 fs, peak-to-pedestal extinction ratio of 58.2 dB, average output power of 6.7 mW, and pulse energy of 507.2 pJ. Our proposed GNP-SA is feasible as a mode-locker for ultrashort pulsed fiber laser with advantage in terms of simple synthesis and fabrication technique

Split-Half Analysis : Measurement of Validity and Reliability of the Career Counselling Self-Efficacy Scale (CCSES) in Malaysian Public Universities

Self-efficacy is an important aspect in measuring counsellor’s abilities to conduct counselling processes. This study aims to assess the validity and reliability of self-efficacy using the Split-half technique. The Career Counselling Self-Efficacy Scale (SSES) aims to measure the level of counsellor’s readiness to provide career counselling services to clients that covers aspects of knowledge and skills. A quantitative approach was used and data analysed by using the SPSS. The instrument has been translated into Malay and involved a 25 items instrument consisting of five sub-scales related to the counsellor’s efficacy. The analysis using the Split-half approach reported the reliability value for the entire item of Part 1 (0.96) and Part 2 (0.97). The study has inferred that the instrument has a satisfactory level of reliability and can be used in the Malaysian context. The new version of instruments has an impact to the counsellor competency in practice. The counsellor will have a view in terms of their ability to handle career counselling. Aside from curriculum development, career counselling can be improved in line with current need. There are a limited numbers of inventories translated into Malay. The new version of CCSES can minimise the cultural issues faced by counsellors in their practice

Sensitive and specific protein sensing using single-mode tapered fiber immobilized with biorecognition molecules

We examine and demonstrate a biosensor using single-mode tapered fiber that has been immobilized with biorecognition molecules to sense targeted proteins. Interaction of evanescent waves with the external medium surrounding the tapered region produces an interferometric-patterned spectrum, which shifts correspondingly to any changes of refractive index (RI) in the external medium. The proposed setup managed to obtain an RI sensitivity and concentration sensitivity of 2526.8 nm/RIU and 20.368 nm/μM, respectively, which, to our knowledge, is highly sensitive when compared with previous studies. The dynamic performance, good specificity, and high sensitivity of the proposed method highlight an immensely beneficial choice for immunological diagnostics

Trends of reactive hyperaemia responses to repetitive loading on skin tissue of rats – Implications for pressure ulcer prevention

Tissue recovery is important in preventing tissue deterioration, which is induced by pressure and may lead to pressure ulcers (PU). Reactive hyperaemia (RH) is an indicator used to identify people at risk of PU. In this study, the effect of different recovery times on RH trend is investigated during repetitive loading. Twenty-one male Sprague-Dawley rats (seven per group), with body weight of 385–485 g, were categorised into three groups and subjected to different recovery times with three repetitive loading cycles. The first, second, and third groups were subjected to short (3 min), moderate (10 min), and prolonged (40 min) recovery, respectively, while fixed loading time and pressure (10 min and 50 mmHg, respectively). Peak hyperaemia was measured in the three cycles to determine trends associated with different recovery times. Three RH trends (increasing, decreasing, and inconsistent) were observed. As the recovery time is increased (3 min vs. 10 min vs. 40 min), the number of samples with increasing RH trend decreases (57% vs. 29% vs. 14%) and the number of samples with inconsistent RH trend increases (29% vs. 57% vs. 72%). All groups consists of one sample with decreasing RH trend (14%). Results confirm that different recovery times affect the RH trend during repetitive loading. The RH trend may be used to determine the sufficient recovery time of an individual to avoid PU development

Unmanned aerial vehicle (UAV) gps jamming test by using software defined radio (SDR) platform

Overhang property issue has sustained over the past ten years in Malaysia. Major overhang property issue was contributed from the unsold residential property. Though the government announced to build a data system and provide the housing data to prevent a mismatch of supply-demand in the property market, there are still not many relevant studies or research on predicting residential property prices. Hence, it is essential to understand the factors that influence the price of residential properties. The study aims to predict the price of a residential property by using a machine learning algorithm. Three algorithms were selected, namely Decision Tree, Linear Regression, and Random Forest, tested against the training and testing datasets obtained from the Malaysian Valuation and Property Services Department. Results show that the Random Forest model produced high accuracy with lower r_squared (R2), RMSE, and MAE values. Significantly, the study has contributed a new insight into essential property features that primarily influence the property price, which will be useful for property developers and buyers who wish to invest in the property market