Desain dan Manufaktur Tabung Gas Komposit Karbon dengan Metode Wet Bladder Compression Moulding

Penggunaan material komposit semakin beragam seiring dengan kemajuan teknologi di berbagai bidang. Serat karbon merupakan material komposit yang banyak digunakan karena memiliki sifat mekanik yang baik, tahan korosi, memiliki rasio kekuatan terhadap berat jenis yang tinggi. Salah satu aplikasi penggunaan material komposit serat karbon yang sangat terbuka peluang pengembangannya adalah untuk tabung gas. Penelitian ini akan menyajikan desain, proses manufaktur, dan pengujian tabung gas komposit. Proses desain meliputi desain tabung gas komposit, desain cetakan, dan desain bladder. Tabung gas komposit terbuat dari serat karbon dan matriks resin epoxy sebanyak 6 lapis pada dinding tabung. Proses manufaktur dilakukan dengan metode wet bladder compression moulding yaitu dengan menggunakan dua buah mould dari material fiberglass bagian atas dan bawah, dan dengan menggunakan bladder atau kantung bertekanan dari latex untuk menekan material komposit. Uji hidrostatis dilakukan menggunakan manual test pump untuk menguji kekuatan tabung. Hasil pengujian menunjukkan tabung gas komposit serat karbon dapat menahan tekanan hidrostatis hingga 18 bar.

New Training Approach for Improving the Spatial Perception and Orientation Ability of Dentistry Students

Introduction: During a basic prosthetics course, dental students train on plastic teeth for fixed partial dentures (FPD). The complexity of manual skill acquisition and the need for extra training led us to develop a portable tool for home training (PhantHome). The aim of the current study was to assess whether training using the portable tool improves students fine motor skill, spatial perception, and orientation and may predict success in preclinical prosthetics courses. Material and Methods: A total of 42 third year dental students were included in this study. A valid dexterity test (Grooved Pegboard test) and a manual test using the portable tool (PhantHome) were conducted in direct and indirect visions using a mirror at two time points: T0: beginning of study, and T1: after training for one month with the portable tool at home. The students’ manual grades in the portable tool, Grooved test, and final prosthetics course grades were compared. Results: The results showed that indirect tasks were significantly more difficult to perform than direct tasks for PhantHome and Grooved tests at T0 and T1 (p < 0.0005). After practicing with the portable PhantHome tool (T1), the students’ scores of in PhantHome and Grooved tests improved significantly (p < 0.04). A regression analysis showed that students’ motor tasks scored at T0 predicted phantom course success in 86.8% of cases (p = 0.005). Conclusion: There was a positive transfer in learning: PhantHome training led to improved performance on the Grooved tests without further training on these tests. Therefore, training in the PhantHome tool can significantly improve performance in the prosthodontics phantom course. The prediction model predicted success in a prosthodontics course with 86% accuracy.

Automation of online particle measurement during the simulated use of catheters and stent systems

The assessment of the coating integrity of cardiovascular implants such as catheters and stent systems is of crucial importance for device approval. Released particles may represent a potential health risk for the patients. Thus, an analysis of the particles released at simulated in-vivo conditions depending on their size and number is required by international standards (ISO, ASTM) as well as national authorities. In this study, an automated test bench for online particle measurement is presented. For software controlled automation, sensor data transmission and solenoid valves were implemented. A user interface was created for setting test parameters and data recording. The setup was validated by investigating standard particles as well as those released during the simulated application of non-industrial coated balloons. The measurement data were compared with results generated using the previous manual test routine. The results show an improvement in the reproducibility of the measurements, which can be attributed to the simplified handling for the user.

HUBUNGAN PENGUASAAN KOSAKATA SISWA DENGAN KEMAMPUAN BERBICARA SISWA KELAS XI SMA NEGERI 1 LEDO TAHUN AJARAN 2016/2017

Penelitian ini bertujuan untuk mengetahui hubungan penguasaan kosakata siswa dengan keterampilan berbicara mereka. Penelitian ini dilakukan melalui desain korelasional. Sampel penelitian ini adalah siswa kelas XI SMAN 1 Ledo tahun pelajaran 2016-2017. Penelitian ini merupakan penelitian korelasi dengan Teknik pengumpulan data kuantitatif deskriptif statistic dan inferensial statistik. alat yang digunakan dalam penelitian ini adalah rubrik score speaking performance untuk mengukur keterampilan berbicara siswa, sedangkan untuk mengukur penguasaan kosakata siswa (vocabulary mastery) menggunakan Multiple choice test (tes pilihan ganda) dimana secara manual (test Item validity and reliability) telah dilakukan validitas dan relibilitas terhadap kedua alat test tersebut. Untuk menganalisis data didalam penelitian ini penulis menggunakan descriptive statistic (nilai individu atau individual score, nilai rata rata atau mean score) dan inferential statistic (pearson product momen correlation) untuk menghitung variable penguasaan kosakata (vocabulary mastery) dan keterampilan berbicara (speaking skill). Hasil penelitian ini menunjukkan bahwa untuk tingkat Kosa Kata dan Prestasi Berbicara Siswa pada kelas XI SMAN 1 Ledo berada pada tingkat yang baik. Peneliti juga menemukan bahwa terdapat korelasi positif antara penguasaan kosakata dengan keterampilan berbicara siswa kelas XI SMAN 1 Ledo tahun pelajaran 2016-2017 dengan signifikansi korelasi sebesar 0,943. Korelasi tersebut tergolong korelasi erat artinya kedua variabel memiliki korelasi yang kuat. Berdasarkan hasil penelitian dapat disimpulkan penguasaan kosakata dan keterampilan berbicara siswa berkorelasi positif, artinya tingkat penguasaan kosakata tertinggi maka tingkat keterampilan berbicara juga tinggi. Oleh karena itu, guru yang berperan dalam mengontrol siswa dalam proses belajar mengajar juga penting untuk mengetahui peningkatan kosa kata dan keterampilan berbicara.

The Impact of NLP on Software Testing

The number of applications being built and deployed everyday are increasing by leaps and bounds. To ensure the best user/client experience, the application needs to be free of bugs and other service issues. This marks the importance of testing phase in application development and deployment phase. Basically, testing is dissected into couple of parts being Manual Testing and Automation Testing. Manual testing, which is usually, an individual tester is given software guidance to execute. The tester would post the findings as “passed” or “failed” as per the guidance. But this kind of testing is very costly and time taking process. To eliminate these short comings, automation testing was introduced but it had very little scope and applications are limited. Now, that Artificial Intelligence has been foraying into many domains and has been showing significant impact over those domains. The core principles of Natural Language Processing that can be used in Software Testing are discussed in this paper. It also provides a glimpse at how Natural Language Processing and Software Testing will evolve in the future. Here we focus mainly on test case prioritization, predicting manual test case failure and generation of test cases from requirements utilizing NLP. The research indicates that NLP will improve software testing outcomes, and NLP-based testing will usher in a coming age of software testers work in the not-too-distant times.

Automated Driving License Evaluation

The paper is regarding the automating of driver’s license testing system and updating the results to the person through website and conjointly through registered email. Usually, while driving test the person who requested for license have to be compelled to show his driving skills ahead of the authorities. The person need to operate the vehicle according to several rules. If he fails, he/she are knocked out and have to appear for the driving test next time. The Officials observe mistakes of the applicant physically. The proposed solution for the automation of existing manual test method permits the elimination of intervention of humans and improves the accuracy of driving test thereby going paperless, with Driving Skill Evaluation System. In the proposed system, we have a tendency of taking data from sensor as inputs from hardware simulator and stores into the database. In this system, the person participating in the test are obsereved by sensors. Therefore weather the person is qualified or not is informed to the applicant as well as the authorities. Gradual increase in number of road hazards are due to less practice in driving and illegal driving license given to the unskilled drivers by taking bribe. To beat this drawback, automated driving license test will be advantageous. This solution is introduced for ensuring the quality in approving in license to enhance safety.

The TOAST (Traction on Ankle Stress Test): A Supplemental Clinical and Dynamic Ultrasound Examination Approach for Focal Assessment of Axial Ankle Joint Instability.

Ankle drawer and varus-valgus stress tests have evolved to examine for excessive joint displacement in the sagittal and coronal planes which may correlate to ligament instability. However, there appear to be no formal manual test(s) assessing for axial plane (longitudinal) instability of the mortise joint. In keeping with Cartesian and Cyriax principles, The TOAST (Traction On Ankle Stress Test) was developed to dynamically assess for 3rd vector axial strain pain generation and long-axis mortise joint gapping. The test is easy to learn as longitudinal manual traction of the mortise joint and applied counterforce hand positions are similar to emergent ankle fracture dislocation reduction technique. The TOAST may also be performed under dynamic ultrasound control.

Reliable Automated Software Testing Through Hybrid Optimization Algorithm

Software testing is an important process in product development of software companies to ensure the product quality. The developed application must satisfy the customer needs and meets the industrial standards without any compromise. Thus, verification of products through manual test engineer and validate the product once it meets all the necessary requirements. The issues in manual testing is its high computation and analysis time, accuracy and reliability. In order to reduce the issues in manual testing automatic testing is introduced. Though it is also an application which requires parameters to test the given product. Efficient tuning of the product could be achieved through automatic testing. This proposed research work provides an optimized automatic software testing model through differential evolution and ant colony optimization as a hybrid model to achieve improved accuracy and reliability in software testing. Conventional models like artificial neural network and particle swarm optimization are compared with proposed model to validate the reliability of proposed model.