Authors:Madan Lal, Shadi Khan Baloch, Shoaib Rehman Soomro Pages: 1 - 13 Abstract: We propose an integrated 3D image capture and display system using a transversely moving camera, regular 2D display screen and user tracking that can facilitate the multi-view capture of a real scene or object and display the captured perspective views in 3D. The motion parallax 3D technique is used to capture the depth information of the object and display the corresponding views to the user using head tracking. The system is composed of two parts, the first part consists of a horizontally moving camera interfaced with a customized camera control and capture application. The second part consist of a regular LCD screen combined with web camera and user tracking application. The 3D multi-view images captured through the imaging setup are relayed to the display based on the user location and corresponding view is dynamically displayed on the screen based on the viewing angle of the user with respect to the screen. The developed prototype system provides the multi-view capture of 60 views with the step size of 1 cm and greater than 40˚ field-of-view overlap. The display system relays 60 views providing the viewing angle coverage of ±35˚ where the angular difference between two views is 1.2˚. PubDate: 2022-03-22 DOI: 10.24003/emitter.v10i1.604
Authors:Yunarso Anang, Rahadi Jalu Yoga Utama, Masakazu Takahashi, Yoshimichi Watanabe Pages: 14 - 30 Abstract: Computer-based test or assessment has been used widely, especially in the current COVID-19 pandemic, where many schools are conducting distance learning as well as distance examination. The need for a computer or software system to support education is inevitable. A range of solutions, from the free/open source software systems to the paid/proprietary ones have been publicly available. Still, an organization with limited resources prefers to find free or low-budget, while yet demanding reliable solutions. We have reported the use of the computer-based test in a new student recruitment test which is held country-wide. We developed the system based on TCExam, a free and open source computer-based test software, and successfully fulfilled the requirements, but with some tweaks. We found that the TCExam has a performance degradation when used by a large number of examinees concurrently, especially during specific phases during the test. This paper reports the result of our investigation to address the problem and suggests some modifications to the base codes as well as a recommendation of the hardware configuration. We evaluated the modified system in a simulated environment. We successfully achieved up to 56% performance gain using the modified system. PubDate: 2022-04-07 DOI: 10.24003/emitter.v10i1.667
Authors:Herti Miawarni, Eko Setijadi, Tri Arief Sardjono, Vincentius Raki Mahindara, Mauridhi Hery Purnomo Pages: 31 - 46 Abstract: Telemonitoring of human physiological data helps detect emergency occurrences for subsequent medical diagnosis in daily living environments. One of the fatal emergencies in falling incidents. The goal of this paper is to detect significant incidents such as falls. The fall detection system is essential for human body movement investigation for medical practitioners, researchers, and healthcare businesses. Accelerometers have been presented as a practical, low-cost, and dependable approach for detecting and predicting outpatient movements in the user. The accurate detection of body movements based on accelerometer data enables the creation of more dependable systems for incorporating long-term development in physiological remarks. This research describes an accelerometer-based platform for detecting users' body movement when they fall. The ADXL345, MMA8451q, and ITG3200 body sensors capture activity data, subsequently classified into 15 fall incident classes based on SisFall dataset. Falling incidents classification is performed using Long Short-Term Memory results in best AUC-ROC value of 97.7% and best calculation time of 6.16 seconds. Meanwhile, Support Vector Machines results in the best AUC-ROC value of 98.5% and best calculation times of 17.05 seconds. PubDate: 2022-04-12 DOI: 10.24003/emitter.v10i1.639
Authors:Adhi Dharma Wibawa, Arni Muarifah Amri, Arbintoro Mas, Syahrul Iman Pages: 47 - 62 Abstract: Opening job vacancies using the Internet will receive many applications quickly. Manually filtering resumes takes a lot of time and incurs huge costs. In addition, this manual screening process tends to be inaccurate due to fatigue conditions and fails in obtaining the right candidate for the job. This paper proposed a solution to automatically generate the most suitable candidate from the application document. In this study, 126 application documents from a private company were used for the experiment. The documents consist of 41 documents for Human Resource and Development (HRD) staff, 42 documents for IT (Data Developer), and 43 documents for the Marketing position. Text Processing is implemented to extract relevant information such as skills, education, experiences from the unstructured resumes and summarize each application. A specific dictionary for each vacancy is generated based on terms used in each profession. Two methods are implemented and compared to match and score the application document, namely Document Vector and N-gram analysis. The highest the score obtained by one document, the highest the possibility of application to be accepted. The two methods’ results are then validated by the real selection process by the company. The highest accuracy was achieved by the N-Gram method in IT vacancy with 87,5%, while the Document Vector showed 75% accuracy. For Marketing staff vacancy, both methods achieved the same accuracy as 78%. In HRD staff vacancy, the N-Gram method showed 68%, while Document Vector showed 74%. In conclusion, overall the N-gram method showed slightly better accuracy compared to the Document Vector method. PubDate: 2022-04-26 DOI: 10.24003/emitter.v10i1.679
Authors:Usman Habib Khan, Muhammad Naeem Ahmed Khan, Aamir Mehmood Mirza, MUHAMMAD AKRAM, Shariqa Fakhar, Shumaila Hussain, Irfan Ahmed Magsi, Raja Asif Wagan Pages: 63 - 82 Abstract: Testing of mobile applications (apps) has its quirks as numerous events are required to be tested. Mobile apps testing, being an evolving domain, carries certain challenges that should be accounted for in the overall testing process. Since smartphone apps are moderate in size so we consider that model-based testing (MBT) using state machines and statecharts could be a promising option for ensuring maximum coverage and completeness of test cases. Using model-based testing approach, we can automate the tedious phase of test case generation, which not only saves time of the overall testing process but also minimizes defects and ensures maximum test case coverage and completeness. In this paper, we explore and model the most critical modules of the mobile app for generating test cases to ascertain the efficiency and impact of using model-based testing. Test cases for the targeted model of the application under test were generated on a real device. The experimental results indicate that our framework reduced the time required to execute all the generated test cases by 50%. Experimental setup and results are reported herein. PubDate: 2022-04-26 DOI: 10.24003/emitter.v10i1.628
Authors:Junior Milembolo Miantezila, Victor Adewuyi, Eunice Owoola Pages: 83 - 101 Abstract: Considered in this work are the radiation aspects of a radio-frequency wireless power transfer system. Using the halfwave dipole as a candidate of choice, the current distribution on the antenna is first evaluated and presented using the versatile electromagnetic numerical Method of Moment technique (MoM). Using the current distribution obtained from the kernel of integration, the radiation fields for the single dipole element was obtained. Also, the analysis is extended to uniformly space linear antenna arrays using broadside and ordinary endfire arrays as candidates of interest. The simulation results for the broadside and endfire arrays were presented for 5, 6, 7, 10, 20 and 30 array elements at 0.3, 0.4 and 0.5 inter-element spacing. The peak directivity of broadside array occurs at 30 elements, 0.5λ spacing, and exceeds endfire array peak directivity by 11.27%. In addition to the advantage of an improved directivity achieved by the 7-element broadside array, an improved peak sidelobe level (PSLL) with the lowest PSLL for 7, 20, and 30 elements broadside array occurring at -12.0534 dB, -12.4298 dB, -12.6642 dB, -13.2246 dB, and -13.2747 dB respectively. PubDate: 2022-04-26 DOI: 10.24003/emitter.v10i1.638
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