Pembangunan dan penilaian sistem 'template' soal selidik berasaskan web (e-templete questionnaire)

Kajian ini dijaiankan bagi meninjau keboiehgunaan dan tahap mesra pengguna terhadap g-?e?77p/a/g soal selidik. Fokus utama kajian ini adaiah (i) menilai tahap keboiehgunaan <?-/<?/7?/?/<3/<? soal-selidik daiam pembangunan soal selidik secara atas talian sebagai instrumen penyeiidikan, (ii) menilai tahap keboiehgunaan g-Zgnzp/a/g soal selidik yang dibangunkan untuk proses pengumpuian data penyeiidikan, (iii) menilai tahap keselamatan g-fgwzp/a/e soal selidik yang dibangunkan, (iv) menilai tahap mesra pengguna g-Zg/wp/a/g, (v) menilai tahap keberkesanan g-fgnzp/a/g soal selidik dan (vi) menilai sama ada terdapat perbezaan yang signifikan di antara persepsi peiajar dan pensyarah terhadap tahap keberkesanan e-?g77zp/afe soal selidik berkenaan. Rekabentuk kajian yang dijaiankan adaiah berbentuk kajian tinjauan dan melibatkan kedua-dua kaedah kualitatif dan kuantitatif. Responden kajian ini terdiri daripada 10 orang pensyarah, 10 orang kakitangan am dan 30 orang peiajar yang terlibat dengan aktiviti penyeiidikan. Instrumen kajian yang digunakan adaiah borang soal selidik dan temubual. Kajian ini mengambil kira aspek keberkesanan g-re772p/a?g yang merangkumi tahap keboiehgunaan sistem berkenaan daiam pembangunan borang soal selidik secara atas talian, keboiehgunaan sistem daiam aspek pengumpuian data, tahap keselamatan data dan tahap mesra pengguna. Kajian ini menguji sama ada terdapat perbezaan persepsi peiajar dan pensyarah terhadap tahap keberkesanan g-Zgnzp/a/g yang dibangunkan. Hasil daripada kajian mendapati tahap keboiehgunaan daiam pembangunan soal selidik berada pada tahap tinggi iaitu dengan memperoleh skor min = 3.97 . Tahap keboiehgunaan untuk aktiviti pengumpuian data memperoleh skor min = 4.03. Manakala untuk tahap keselamatan skor min yang diperoleh adaiah 3.95. Bagi tahap mesra pengguna skor min yang diterima adaiah 3.85. Akhir sekali, tahap keberkesanan g-/g/Mp/a/rg memperoleh skor min 3.95. Kajian juga mendapati bahawa tidak terdapat perbezaan yang signifikan antara persepsi peiajar dan pensyarah terhadap g-/gHzp/a7g yang dibangunkan. Pembangun mencadangkan supaya laman web g-?gmp/a?g ini dapat dimumikan lagi dengan penambahan fungsi untuk menganalisis data. Ini kerana fungsi berkenaan tidak dapat dibangunkan

MOFSocialNet: Exploiting Metal-Organic Framework Relationships via Social Network Analysis

The number of metal-organic frameworks (MOF) as well as the number of applications of this material are growing rapidly. With the number of characterized compounds exceeding 100,000, manual sorting becomes impossible. At the same time, the increasing computer power and established use of automated machine learning approaches makes data science tools available, that provide an overview of the MOF chemical space and support the selection of suitable MOFs for a desired application. Among the different data science tools, graph theory approaches, where data generated from numerous real-world applications is represented as a graph (network) of interconnected objects, has been widely used in a variety of scientific fields such as social sciences, health informatics, biological sciences, agricultural sciences and economics. We describe the application of a particular graph theory approach known as social network analysis to MOF materials and highlight the importance of community (group) detection and graph node centrality. In this first application of the social network analysis approach to MOF chemical space, we created MOFSocialNet. This social network is based on the geometrical descriptors of MOFs available in the CoRE-MOFs database. MOFSocialNet can discover communities with similar MOFs structures and identify the most representative MOFs within a given community. In addition, analysis of MOFSocialNet using social network analysis methods can predict MOF properties more accurately than conventional ML tools. The latter advantage is demonstrated for the prediction of gas storage properties, the most important property of these porous reticular network

On the Potential of the Excluded Volume and Auto-Correlation as Neuromorphometric Descriptors

This work investigates at what degree two neuromorphometric measurements, namely the autocorrelation and the excluded volume of a neuronal cell can influence the characterization and classification of such a type of cells. While the autocorrelation function presents good potential for quantifying the dendrite-dendrite connectivity of cells in mosaic tilings, the excluded volume, i.e. the amount of the surround space which is geometrically not accessible to an axon or dendrite, provides a complementary characterization of the cell connectivity. The potential of such approaches is illustrated with respect to real neuronal cells.Comment: 15 pages, 6 figure

Geodesic network method for flows between two rough surfaces in contact

A discrete network method based on previous asymptotic analysis for computing fluid flows between confined rough surfaces is proposed. This random heterogeneous geodesic network method could be either applied to surfaces described by a continuous random field or finely discretized on a regular grid. This method tackles the difficult problem of fluid transport between rough surfaces in close contact. We describe the principle of the method as well as detail its numerical implementation and performances. Macroscopic conductances are computed and analyzed far from the geometrical percolation threshold. Numerical results are successfully compared with the effective medium approximation, the application of which is also studied analytically