Pengembangan Lembar Kerja Siswa Berstruktur Metode Penemuan Terbimbing untuk Meningkatkan Kemampuan Komunikasi Matematis Siswa

: This study aims to produce LKS structured method of guided discovery material and area of ​​a circle whose circumference is valid, practical, and effective. The method used in this research is the research and development (research and development) which adapts the model of development of Borg and Gall. The research subject is class VIII SMP Negeri 2 Sebangki of 20 people limited trial and 56 trials spacious. The results of data analysis 1) is valid based on ratings validator with an average score of 90%, as the average score of the validation of more than 80%, the LKS is categorized as very valid, meaning LKS could be tested, 2) practical based on the responses of students with an average score of 88% and enforceability of Lesson Plan with an average score of 98% in both catagories is very good, that is practical worksheets used in the learning process, 3) the effectiveness seen from the mathematical ability of written and oral communication students. Result written communications skills mathematical average of 76% and the average verbal score of students by 78%, as written and oral communication skills are both good students category, then LKS meets aspects of effective, meaning that students can express ideas or idea in the form of pictures, making working steps, and solving mathematical problems in writing, or orally

Experimental analysis of tribological performance of modified jatropha oil enriched with nanoparticle additives for machining application

The intensified developments of the vegetable-based metalworking fluids have been growing rapidly due to the environmental and health issue of the utilization of the mineral based oil. The vegetable oils are a great potential substitution of the mineral based oil which has been explored in recent years due to their high biodegradability, renewability and low toxicity in comparable with mineral oil. Non-edible vegetable oil had attracted an attention of the researches in contrast with edible oil which significantly compete with the human food supply. The main focus of this study was to evaluate a new formulation of vegetable-based nanofluid from chemically modified jatropha oil (MJO) blended with hexagonal boron nitride (hBN), graphene and copper oxide (CuO) nanoparticles at 0.05 wt.% concentration. The physicochemical testing was carried out in term of kinematic viscosity, viscosity index and flash point and was compare with commercial synthetic ester (SE). The analysis of MJO mixed with nanoparticles in the perspective of it tribological has been performed through a four ball tribo testing to determine the coefficient of friction, mean wear scar diameter, friction torque, surface roughness and volume wear rate. The results showed that the tribological performance the MJO+0.05wt.% CuO exhibit lowest value in of coefficient of friction and friction torque followed by MJO+0.05wt.% graphene, MJO+0.05wt.% hBN and SE. Nevertheless, the MJO+0.05wt.% graphene and MJO+0.05wt.% hBN provided the significant improvement by providing the lowest value of the mean wear scar diameter and surface roughness respectively. It concluded that the modified jatropha oil enriched with nanoparticles had a great improvement on their tribological performance, hence it’s a highly potential substitution of the SE for machining process

Upgrading n-Heptane via Catalytic Hydroisomerisation

An atmospheric pressure upgrading of n-heptane was carried out in a temperature range of 300 to 450oC over an in situ developed molybdenum carbide phase supported over sulphated zirconia. Although a decreased in surface area with increased in pore volume were observed after carburization, the physicochemical data showed no noticeable alteration to the zirconia structure or the sulphate species. The catalyst formed a good system with high selectivity to iso-heptanes under either low temperature or high space velocity. It therefore has promising features that could offer mitigation to some of the challenges faced by the petroleum refineries with noble metals promoted zeolites. Keywords: n-heptane, hydroisomerisation, carbide catalyst, stability, sulphated zirconia

High-Pressure Phase Diagram in the Manganites: a Two-site Model Study

The pressure dependence of the Curie temperature $T_C$ in manganites, recently studied over a wide pressure range, is not quantitatively accounted for by the quenching of Jahn-Teller distortions, and suggests the occurrence of a new pressure-activated localizing processes. We present a theoretical calculation of $T_C$ based on a two-site double-exchange model with electron-phonon coupling interaction and direct superexchange between the $t_{2g}$ core spins. We calculate the pressure dependence of $T_C$ and compare it with the experimental phase diagram. Our results describe the experimental behavior quite well if a pressure-activated enhancement of the antiferromagnetic superexchange interaction is assumed

The HH34 outflow as seen in [FeII]1.64um by LBT-LUCI

Dense atomic jets from young stars copiously emit in [FeII] IR lines, which can, therefore, be used to trace the immediate environments of embedded protostars. We want to investigate the morphology of the bright [FeII] 1.64um line in the jet of the source HH34 IRS and compare it with the most commonly used optical tracer [SII]. We analyse a 1.64um narrow-band filter image obtained with the Large Binocular Telescope (LBT) LUCI instrument, which covers the HH34 jet and counterjet. A Point Spread Function (PSF) deconvolution algorithm was applied to enhance spatial resolution and make the IR image directly comparable to a [SII] HST image of the same source. The [FeII] emission is detected from both the jet, the (weak) counter-jet, and from the HH34-S and HH34-N bow shocks. The deconvolved image allows us to resolve jet knots close to about 1\arcsec from the central source. The morphology of the [FeII] emission is remarkably similar to that of the [SII] emission, and the relative positions of [FeII] and [SII] peaks are shifted according to proper motion measurements, which were previously derived from HST images. An analysis of the [FeII]/[SII] emission ratio shows that Fe gas abundance is much lower than the solar value with up to 90% of Fe depletion in the inner jet knots. This confirms previous findings on dusty jets, where shocks are not efficient enough to remove refractory species from grains.Comment: 5 pages, 4 figures, note accepted by A&

Development of Digital Resistivity Meter

A digital resistivity meter was designed and constructed using microcontroller (PIC16F877A) and other carefully selected components. The meter was developed, using the state of the art technology, to measure the earth’s electrical resistivity through application of direct current electrical resistivity method. It was designed as a system with various subunits implemented as modules, to help greatly in trouble shooting the system in case of system failure. This meter injected currents of 0.1mA, 1mA and 10mA and two, 6V batteries connected in series powered it. Its capability of accepting analog input and displaying digital output gives it advantage of minimizing errors associated with output display. Microcontroller operated using a configuration of hardware components and functional software written and burnt into the microcontroller’s memory. The meter was tested with a specially designed test unit and the generated results were compared with the calculated values, the two agreed. Keywords: Electrical resistivity, microcontroller, analog, digita

Personalised meta-learning for human activity recognition with few-data.

State-of-the-art methods of Human Activity Recognition(HAR) rely on a considerable amount of labelled data to train deep architectures. This becomes prohibitive when tasked with creating models that are sensitive to personal nuances in human movement, explicitly present when performing exercises and when it is infeasible to collect training data to cover the whole target population. Accordingly, learning personalised models with few data remains an open challenge in HAR research. We present a meta-learning methodology for learning-to-learn personalised models for HAR; with the expectation that the end-user only need to provide a few labelled data. These personalised HAR models benefit from the rapid adaptation of a generic meta-model using provided few end-user data. We implement the personalised meta-learning methodology with two algorithms, Personalised MAML and Personalised Relation Networks. A comparative study shows significant performance improvements against state-of-the-art deep learning algorithms and other personalisation algorithms in multiple HAR domains. Also, we show how personalisation improved meta-model training, to learn a generic meta-model suited for a wider population while using a shallow parametric model

Effect of Cutting Parameters on Tool Wear when Trochoidal Pocket Milling Ti6Al4V

Despite being an attractive material for aerospace components such as engine parts and airframes, titanium alloy is categorized as a difficult-to-machine material which results in rapid tool wear and tool failure. It was reported that trochoidal machining method is preferred as compared to conventional machining due to its ability to prolong the tool life. This machining technique has the ability to reduce the load and provide enough space for the chips to evacuate and allowing sufficient time for the tool to be cooled. This study was conducted to investigate the effect of cutting parameters on the tool wear of TiAlN/TiN coated carbide tool when trochoidal milling Ti6Al4V under wet condition. Design of experiment based on response surface method (RSM) was adopted with three factors (cutting speed, feed rate and step over), two levels and five centre points with a total of 17 experimental runs. The cutting speed (Vc) was set at 60 to 90 m/min, feed rate (fz) at 0.06 to 0.1 mm/tooth and step over (ae) at 1.5 to 2.5 mm. The experimental results indicated that cutting speed was the dominant factor affecting the tool wear, followed by feed rate and lastly the step over. ANOVA results showed that all three cutting parameters exhibit positive interaction towards wear condition thus implying that higher value of cutting speed, feed rate and step over resulted in rapid tool wear and shorten the tool life

Development of a sparse RFID reader deployment algorithm for effective RFID network planning

A well planned Radio Frequency Identification (RFID) network achieves the following twin objectives, (a) reduces the cost of acquiring the readers to be deployed (b) completes coverage of tags deployed in the network. A reader deployment approach that considered the physical topology of passive tags that were sparsely deployed in a RFID network was developed. In the implemented technique, readers could not be deployed outside the work area which implied that tags located outside the work area could not be detected. Bidirectional communication between the readers and tags could only be established if their receiver sensitivity was less than or equal to the incoming signal. The developed algorithm was optimized by logically integrating some sub-algorithms such as Useless Reader Elimination Algorithm (UREA) and Redundant Reader Elimination Algorithm (RREA). The effectiveness of the developed Sparse Reader Deployment Algorithm (SRDA) was demonstrated through simulation of various scenarios. The implemented approach was compared to the Constrained Reader Deployment Approach (CORDA) and the former outperformed the latter in terms of Optimal Power Dissipated (OPD) which was 255mW. The impact of increasing the number of tags and coverage area on the OPD of SRDA was investigated in a bid to ascertain the robustness of the developed algorithm.Keywords: RFID; CORDA; SRDA; OPD