Electronic Engineering

When a live streaming video is delivered over a peerto-peer (P2P) network, the chunk delay is always a problem of great concern. A serious chunk delay can produce obvious discontinuity of the streaming video, resulting in low satisfaction of the service. Video on P2P is divided into several chunks and distributed to the peers. Each chunk has its own playback time deadline. The playback time of a delayed chunk is overlapped with that of the next chunk. Traditionally, fast forwarding and uniform frame skipping are the two methods used to deal with the chunk delay problem. However, they may easily produce the effect of perceptual discontinuity and perceived by a viewer. This paper proposes a frame dropping method based on frame loss visibility information in order to maintain visual continuity of the video. The frame with lower loss visibility will be dropped first. In a previous work, the idea of loss visibility was applied by a router to develop a frame dropping strategy when network congestion occurs. In this work, we apply it to the chunk-level playback controller in P2P network. The number of frames to be dropped is dependent on the value of chunk delay. The main difference between the proposed approach and the traditional methods is that different frames could be chosen and dropped. A viewer's satisfaction is evaluated by using the way of subjective video quality assessment. The proposed method produces higher MOS (mean opinion score) than that of the two traditional methods.

When a live streaming video is delivered over a peerto-peer (P2P) network, the chunk delay is always a problem of great concern. A serious chunk delay can produce obvious discontinuity of the streaming video, resulting in low satisfaction of the service. Video on P2P is divided into several chunks and distributed to the peers. Each chunk has its own playback time deadline. The playback time of a delayed chunk is overlapped with that of the next chunk. Traditionally, fast forwarding and uniform frame skipping are the two methods used to deal with the chunk delay problem. However, they may easily produce the effect of perceptual discontinuity and perceived by a viewer. This paper proposes a frame dropping method based on frame loss visibility information in order to maintain visual continuity of the video. The frame with lower loss visibility will be dropped first. In a previous work, the idea of loss visibility was applied by a router to develop a frame dropping strategy when network congestion occurs. In this work, we apply it to the chunk-level playback controller in P2P network. The number of frames to be dropped is dependent on the value of chunk delay. The main difference between the proposed approach and the traditional methods is that different frames could be chosen and dropped. A viewer's satisfaction is evaluated by using the way of subjective video quality assessment. The proposed method produces higher MOS (mean opinion score) than that of the two traditional methods.

Polyhedral oligomeric silsesquioxane (POSS) was synthesized via the hydrolytic condensation of c-aminopropyltrimethoxysilane in the tetrahydrofuran solution catalyzed by concentrated hydrochloric acid and was further used as the grafting agent to react with graphite oxide (GO). The grafted product, which referred to as POSS-g-GO, was used to modify epoxy resin (EP) matrix. The epoxy/POSS-g-GO nanocomposites were fabricated using ultrasonication and the cast molding method and confirmed by Fourier transform infrared spectroscopy, X-ray diffraction, dynamic mechanical analysis (DMA), and thermogravimetric analysis techniques. The results revealed that the incorporation of a small amount of POSSg-GO caused a significant improvement in ultimate tensile strength, impact strength and roughness. With 2 wt% POSS-g-GO ultimate tensile strength and flexural strength of the composites were improved by 24.8 and 56.6 %, respectively. The impact strength was 42.97 kJ/m 2 , which is 2.5 times higher than that of the pure EP (17.49 kJ/m 2). The DMA results showed that the moduli of the nanocomposites in glass and rubbery states were significantly higher than those of the control epoxy. It indicated that incorporation of POSS-g-GO into epoxy networks was the efficient load transfer between the POSS-g-GO additives and epoxy matrix through covalent links. Morphological structure of the impact fracture surface of the epoxy/POSSg-GO composites was observed by scanning electron microscope, as well.

Abstrak Kualitas sumber daya manusia merupakan salah satu faktor penunjang untuk meningkatkan produktivitas kinerja suatu instansi perusahaan. Sumber daya manusia yang berkompetensi tinggi dapat mendukung tingkat kinerja, dengan penilaian kinerja maka akan didapat prestasi yang dicapai setiap karyawan. Untuk memperoleh informasi yang cepat dan akurat prestasi karyawan yang tepat memenuhi kriteria yang diharapkan. Untuk mengetahui hal tersebut, dengan suatu metode pengambilan keputusan multikriteria dengan memecahkan situasi kompleks dan tidak terstruktur kedalam bagian-bagian dan menyusunnya dengan menggunakan metode Vlse Kriterijumska Optimizajica I Kompromisno Resenje (VIKOR) pada Sistem Pendukung Keputusan (SPK) maka penentuan karyawan berprestasi dapat dihitung berdasarkan perhitungan dari bobot kriteria masing-masing, sehingga dapat memilih karyawan berprestasi di dalam perusahaan secara cepat. Abstract The quality of human resources is one of the supporting factors to improve the productivity of a company's performance. Highly competent human resources can support the level of performance, with performance appraisal it will get the achievements achieved by each employee. To obtain fast and accurate information the employee's exact accomplishment meets the expected criteria. To find that out, with a multicriteria decision-making method by solving complex and unstructured situations into sections and compiling them using the Vise Kriterijumska Optimizajica I Kompromisno Resenje (VIKOR) method on Decision Support System (SPK), the determination of achieving employees can be calculated based on calculation of the weight of each criterion, so it can select employees achievers in the company quickly. 1. PENDAHULUAN Teknologi informasi semakin berkembang dalam segala aspek kehidupan yang pada penerapannya dapat mempermudah pekerjaan manusia. Kualitas sumber daya manusia merupakan salah satu faktor penunjang untuk meningkatkan produktivitas kinerja suatu instansi perusahaan. Maka dari itu sumber daya manusia yang berkompetensi tinggi dapat mendukung tingkat kinerja, dengan penilaian kinerja akan diketahui prestasi yang dicapai setiap karyawan, hal ini memudahkan instansi untuk pertimbangan dalam menentukan karyawan terbaik. Manusia dalam kehidupan sehari-hari sering menemui masalah dalam pengambilan keputusan. Masalah yang muncul dapat berskala besar atau kecil yang sangat berpengaruh dalam hasil keputusan. Seorang pimpinan benar-benar harus selektif dalam mengambil keputusan untuk pemilihan karyawan terbaiknya. Sekarang pengembangan system dapat membantu menentukan alternatif terbaik dalam suatu permasalahan, yaitu sistem pendukung keputusan (SPK). Di dalam sistem pendukung keputusan terdapat alternatif, kriteria dan bobot yang digunakan untuk menentukan suatu solusi terbaik[1]. Sistem Pendukung Keputusan merupakan suatu system terkomputerisasi dan dirancang untuk menigkatkan efektivitas dalam pengambilan keputusan untuk memecahkan masalah yang bersifat semi terstruktur maupun tidak terstruktur sehingga dalam proses pengambilan keputusan yang dilakukan dapat lebih berkualitas. Ada beberapa metode yang termasuk dalam sistem pendukung keputusan diantaranya, Analitycal Hierarchy Proses (AHP), Simple Additive Weighting (SAW), Weighted Product (WP), TOPSIS, Simple Multi Atribute Rating Technique (SMART) dan lain-lainnya[2][3][4]. 2. TEORITIS 2.1 Sistem Pendukung Keputusan Sistem Pendukung Keputusan (SPK) atau Decision Support System (DSS) merupakan sistem yang mampu memberikan kemampuan pemecahan masalah maupun kemampuan pengkomunikasian untuk masalah dengan kondisi semi terstruktur dan tak terstruktur[5][6].