Papan putih maya interaktif (IVBoard): Penilaian tahap interaksi dan kepuasan pengguna

A virtual whiteboard prototype, called Interactive Virtual whiteboard (IVBoard) was developed for online discussion and decision-making purposes. The IVBoard is a Computer-supported Cooperative Work (CSCW) application, built to enable up to 50 users interacting at full duplex mode with the ability to transmit texts, bitmap graphics as well as audio. A multi user server and a multi user interface component were used to enable real time interactions performed among all IVBoard users at a time. The prototype has been used by the academic staffs and students (including the distance learning students) of Universiti Utara Malaysia. After a year period of released, it is incumbent upon us to investigate whether or not the IVBoard is efficient in terms of interaction activities (during the online discussion) and user satisfaction. Thus far, a great deal of attention is given to evaluation, either as a part of the improvement process of the prototype design (formative evaluation) or as a quality assurance mechanism of the IVBoard. The evaluation described in this paper measures (1) user interaction level while using IVBoard, (2) comparison between IVBoard interaction level and traditional discussion, and (3) subjective user satisfaction. Evaluations for (1) and (2) were performed using laboratory experiment, observation, and video recording analysis whereas evaluation for (3) was carried out using questionnaires based on the established user interface evaluation model, QUIS. The results of the above mentioned evaluations are detailed out in this paper

Papan putih maya interaktif (IVBoard):penilaian terhadap interaksi dan kepuasan pengguna

Sebuah prototaip papan putih maya, Interactive Virtual white Board (IVBoard), dibina untuk tujuan perbincangan dan pembuatan keputusan dalam talian pada masa nyata. IVBoard adalah aplikasi Computer-supported Cooperative Work (CSCW) yang dibina untuk membolehkan sehingga 50 pihak berinteraksi secara dupleks penuh dengan keupayaan hantaran teks, grafik bitmap serta audio. Sebuah pelayan berbilang pengguna dan komponen antara muka berbilang pengguna diperlukan untuk membolehkan interaksi masa nyata dilakukan di antara semua pengguna IVBoard pada satu-satu masa. Prototaip ni telah digunakan oleh kakitangan akademik dan segolongan pelajar Universiti Utara Malaysia. Selepas setahun digunakan, timbul keperluan untuk menilai tahap keberkesanannya dari segi peningkatan interaksi semasa perbincangan dan kepuasan pengguna. Ini adalah kerana penilaian menjadi semakin perlu sama ada sebagai sebahagian daripada perbaikan reka bentuk prototaip atau sebagai mekanisme jaminan kualiti IVBoard. Penilaian dalam kertas kerja ini mengukur (1) tahap nteraksi pengguna yang menggunakan IVBoard, (2) membuat perbandingan tahap interaksi melalui IVBoard dengan tahap interaksi melalui perbincangan tradisional, dan (3) menilai kepuasan subjektif pengguna. Penilaian (1) dan (2) menggunakan kaedah uji kaji makmal dengan pemerhatian dan analisis rakaman video, manakala penilaian (3) menggunakan soal selidik dengan model penilaian antara muka pengguna yang telah diiktiraf iaitu QUIS

Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array

This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler-Deb-Thiele\u27s (ZDT\u27s) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously

Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array

This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler-Deb-Thiele\u27s (ZDT\u27s) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously

A hybrid modified method of the sine cosine algorithm using latin hypercube sampling with the cuckoo search algorithm for optimization problems

The metaheuristic algorithm is a popular research area for solving various optimization problems. In this study, we proposed two approaches based on the Sine Cosine Algorithm (SCA), namely, modification and hybridization. First, we attempted to solve the constraints of the original SCA by developing a modified SCA (MSCA) version with an improved identification capability of a random population using the Latin Hypercube Sampling (LHS) technique. MSCA serves to guide SCA in obtaining a better local optimum in the exploitation phase with fast convergence based on an optimum value of the solution. Second, hybridization of the MSCA (HMSCA) and the Cuckoo Search Algorithm (CSA) led to the development of the Hybrid Modified Sine Cosine Algorithm Cuckoo Search Algorithm (HMSCACSA) optimizer, which could search better optimal host nest locations in the global domain. Moreover, the HMSCACSA optimizer was validated over six classical test functions, the IEEE CEC 2017, and the IEEE CEC 2014 benchmark functions. The effectiveness of HMSCACSA was also compared with other hybrid metaheuristics such as the Particle Swarm Optimization–Grey Wolf Optimization (PSOGWO), Particle Swarm Optimization–Artificial Bee Colony (PSOABC), and Particle Swarm Optimization–Gravitational Search Algorithm (PSOGSA). In summary, the proposed HMSCACSA converged 63.89% faster and achieved a shorter Central Processing Unit (CPU) duration by a maximum of up to 43.6% compared to the other hybrid counterparts