3D Intrinsic Scene Characteristics Extraction Framework For A Single Image

Three-Dimensional (3D) shape reconstruction is an important area of computer vision research because it has numerous potential applications from entertainment production to industrial inspection and clinical analysis. Existing 3D Intrinsic Scene Characteristics (3D-ISCs) extraction methods for a single image have focused solely on estimating diffuse characteristics, i.e. 3D shape, illumination, and reflectance models, of an object. As a result, they have neglected the specular characteristic, the shiny areas of a glossy surface. In reality, many real-world objects emit both specular and diffuse reflections, and thus the specular component may decrease the performance of the 3D-ISCs methods. This study has developed a framework to extract all of these characteristics. The framework combines a Specular Removal (SR) method and a Shape, Illumination, and Reflectance From Shading (SIRFS) method under a Bidirectional Reflectance Distribution Function (BRDF) model. Since the previous SR methods suffered from hue-saturation ambiguity, they are not suitable for this framework. To solve this problem, two SR methods were developed, evaluated, and compared with the standard SR methods. The proposed SR methods are referred as Chaotic Segmentation (CS) and Sparse Coding (SC) methods. To combine the SR and SIRFS methods, two BRDF models were also developed, evaluated, and compared. These models are referred as Modified Dichromatic Reflectance (MDR) and Modified Blinn-Phong (MBP) models. The performances of the proposed SR methods and the BRDF models for extracting 3D-ISCs were evaluated based on public datasets. The results showed that the SC method was more satisfactory compared to the CS and the benchmark method (iterative method). The accuracies of the diffuse and specular characteristics were improved by 7.6% and 53.5% respectively. Moreover, the combination of SC method and MDR model was capable of outperforming the SIRFS method. The computational speed was 19.2% faster. Meanwhile, the average accuracies of depth, surface normal, illumination, shading, and reflectance were improved by 11.4%, 6.5%, 50.5%, 35.2%, and 5.1% respectively. This study indicates that the specular reflection is an important aspect of 3D reconstruction from a single image. The proposed framework has also made considerable improvements in terms of accuracy and computational time of extracting 3D-ISCs

The Design of Application Architecture of the Institute of Business Based on Enterprise Architecture Planning

Institute of Business (IOB) is committed to achieve its goals, i.e. becomes a place for economics and business as well as computer science developers, and prepare a ready-to-use Human Resources (HR), especially for Timor Leste. At present, IOB does not have an alignment between business processes and information systems owned. Therefore, this paper proposes an architectural design that bridges the alignment. The methods used to build the framework are include Enterprise Architecture Planning (EAP), SWOT, Value Chain, and Mc Farlan Grid. The built frameworks are focused on the needs of the application architecture. The resulted portfolio has 45 applications for various divisions of IOB. In addition, the SWOT analysis shows that IOB's internal and external factors are in the second quadrant. Thus, IOB's position is relatively strong, though it is facing a big challenge. The recommended strategy is the Strengths-Threats (ST) strategy that uses the company’s strength to overcome the threats. This strategy includes improving facilities, adding faculties and departments, developing academic information systems, improving the quality of learning, and improving the human resources quality

Automated visual inspection (AVI) research for quality control in metal stamping manufacturing

This paper presents a set of techniques in Automated Visual Inspection (A Vl) system to perform qnality control for metal stamping industry. AV/ system is aim to confirm whether a product match its quality standard and requirement or not. The system consists of 2D image sensor, lighting system, computer, image processing routines, networking, and handling mechanism. The system is expected to be integrated in the over all process in industry. This paper is focusing to the algorithm aspects of the A VJ system. ft consists of digital image acquisition, noise reduction, edge detection, feature extraction and classification. The result shows the potential implementation to improve the quality control in manufacturing environment

Sistem Pendukung Keputusan Dalam Penempatan Karyawan Baru Di PT. Multi Jasa Cemara Dengan Menggunakan Metode AHP dan TOPSIS

PT. Multi Jasa Cemara bergerak dalam bidang jasa kebersihan yang menyediakanbeberapa karyawan untuk membersihkan setiap tempat atau ruangan. Setiap karyawanbaru ditentukan oleh HRD untuk ditempatkan pada area tertentu. Masalah yang biasaterjadi yaitu karyawan baru tidak memahami area kerja yang dikerjakan sehinggapekerjaan menjadi lambat dan kurang memiliki kebersihan, biasanya para supervisorcleaning service hanya menugaskan langsung para karyawannya di area kerja tanpabriefing dan melihat penguasaan area kerja para karyawan yang baru. Sehinggadibutuhkan sebuah cara untuk membantu HRD dalam menentukan area kerja untukkaryawan yang baru. Oleh karena itu penelitian ini membahas penggunaan sistempendukung keputusan menggunakan metode AHP dan TOPSIS untuk keputusanpenempatan karyawan baru di PT. Multi Jasa Cemara

E-Commerce Product Image-Based Recommendation System Kalcare.Com Using Deep Learning

Recommendation systems have now become an important part of a digital service, one example is e-commerce. The facts show that the COVID-19 pandemic has had a significant impact on customers by making them spend more time surfing online to get daily necessities products by shopping on e-commerce sites. With the rapid development of deep learning technology today, of course, it can be used to help in terms of the process of producing a product image-based recommendation system that has a fairly high level of similarity. This study will discuss how to produce an image-based product recommendation system architecture by comparing the results of the application of algorithms 8 pre-trained models that are available and have also been widely used in various studies and the information technology industry. The dataset used is product images sourced from the kalcare.com website. After testing the pre-trained model, then an application prototype was made to be tested then in the final stage of this research a poll was conducted to determine the response and opinion of users to the protopine recommendation system made for e-commerce kalcare.com using deep learning

Graphology analysis for detecting hexaco personality and character through handwriting images by using convolutional neural networks and particle swarm optimization methods

Graphology or handwriting analysis can be used to infer the traits of the writers by examining each stroke, space, pressure, and pattern of the handwriting. In this study, we infer a six-dimensional model of human personality (HEXACO) using a Convolutional Neural Network supported by Particle Swarm Optimization. These personalities include Honesty-Humility, Emotionality, eXtraversion, Agreeableness (versus Anger), Conscientiousness, and Openness to Experience. A digital handwriting sample data of 293 different individuals associated with 36 types of personalities were collected and derived from the HEXACO space. A convolutional neural network model called GraphoNet is built and optimized using Particle Swarm Optimization (PSO). The PSO is used to optimize epoch, minibatch, and droupout parameters on the GraphoNet. Although predicting 32 personalities is quite challenging, the GraphoNet predicts personalities with 71.88% accuracy using epoch 100, minibatch 30 and dropout 52% while standard AlexNet only achieves 25%. Moreover, GraphoNet can work with lower resolution (32 x 32 pixels) compared to standard AlexNet (227 x 227 pixels)

RISK MANAGEMENT OF INFORMATION SYSTEM IN DISKOMINFO STATISTIC AND ENCODING USING NIST SP 800-30

E-Government is a form of government service in digital form that utilizes the internet network which makes government services to the community easy. However, behind the perceived convenience, of course, there will be risks that arise, for example data loss, data theft, mis-access, illegal access, hardware damage, hacking, etc. which will have a negative impact on an organization, including in the Statistics and Encryption Communication and Information Service, XYZ Regency. The most commonly found threats are those that come from humans and electricity. In addition, there are still many sources of threats that have the potential to pose risks that will interfere with the implementation of electronic-based government. From the results of risk measurements that have been carried out based on NIST SP 800-30 By multiplying between the levels determined in the likelihood and impact processes to produce a number to be used as a guide in determining the level of risk, it was found that the risk threats originating from humans are 60% risk with Low level, 30% risk with Medium level, and 10% risk with High level. While the risk derived from electricity was 20% risk with Low level, 20% risk with Medium level, and 60% risk with High level. Lastly sourced from Technical is 34% risk with Low level, 33% Medium level risk, and 33% High level risk. Overall the risk assessment results were 39% risk threats with Low level, 33% risk threat with Medium level, and 28% risk threat with High level

E-Learning Effectiveness Analysis in Developing Countries: East Nusa Tenggara, Indonesia Perspective

The adoption of e-learning in developing countries like Indonesian Universities have been focused in urban areas like the big cities, especially in Java island. There is a lack of development of e-learning in a remote city like Kupang East Nusa Tenggara Indonesia which is located far away from the capital city. This research aims to assess the effectiveness of e-learning by analyzing three factors in one of the higher institution in Kupang city, i.e. Sekolah Tinggi Kesehatan Citra Mandiri Husada Kupang (STIKes CHMK). The factors include culture, technology and infrastructure, and content satisfaction. The data were collected using questionnaires. Research shows that with proper preparation for e-learning, the acceptance of e-learning in rural areas is significantly high. This finding suggests that e-learning can greatly benefit the students like Kupang city in developing countries

PENGEMBANGAN APLIKASI MENTALFIRST BERBASIS ANDROID SEBAGAI MEDIA DETEKSI AWAL PTSD DAN MEDIA INFORMASI SEPUTAR PTSD

Trauma merupakan tekanan emosional dan psikologis yang pada umumnya karena kejadian yang tidak menyenangkan atau pengalaman yang berkaitan dengan kekerasan. Secara umum, ada banyak faktor yang bisa menyebabkan seseorang mengalami trauma, termasuk peristiwa menyedihkan, mengguncang jiwa, hingga mengancam nyawa. Ini karena kejadian traumatis dapat menyebabkan gangguan streess pasca trauma (PTSD). Untuk mengatasi kesulitan ini, peneliti melakukan pengembangan sebuah aplikasi berbasis Android yang berfungsi sebagai media deteksi awal PTSD dan juga sebagai media informasi yang berkaitan dengan penanganan PTSD. Aplikasi ini dikembangkan menggunakan metode Test Driven Development dan menggunakan Kotlin dan XML sebagai bahasa pemograman dan layouting aplikasi serta, menggunakan Firebase sebagai back end nya. Test Driven Development sendiri merupakan pengembangan perangkat lunak yang menekankan testing sebelum coding  yang dimana menggunakan pendekatan Agile dan Extreme Programming.Dengan pengujian Black Box Testing aplikasi dapat berjalan dengan baik dan aplikasi ini memiliki nilai SUS (System Usability Scale) rata-rata sebesar 89.75. Aplikasi telah dipublikasi ke dalam Play Store dengan status pengujian terbuka. Dengan demikian, aplikasi “MentalFirst” ini diharapkan dapat membantu masyarakat dapat melakukan deteksi awal dan mendapatkan informasi yang berkaitan dengan PTSD

Design Application of Augmented Reality-Based Computer Device Assembly Practicum Modules

The adaptation and use of digital technology have presented various opportunities and challenges for actors involved in educational services, i.e., colleges, educators, and students. Augmented reality has recently emerged as one of the digital technologies that have attracted the attention of many academies and practitioners; in addition, AR technology has brought about a change in the way users and machines interact that can teach and direct students to handle the topic of lessons differently and more proactively. This study aims to design and build an android-based Augmented Reality (AR) computer hardware assembly practicum module application as an alternative learning media in the computer hardware device assembly practicum module, which is expected in a learning activity to be more exciting and increase students' skills about computer assembly through AR technology can be one of the solutions to overcome the practicum module which was previously still in the form of a textbook and was not yet technology-based. The research method used is the Multimedia Development Life Cycle (MDLC), which consists of six stages, namely concept, design, material, collection, assembly, testing, and distribution. The results of the practicum module application with Augmented Reality technology can be run on mobile devices with an Android operating system for version 5.1 and above, and this module has a feature that can introduce 3-D objects of hardware devices and simulate the assembly of hardware devices 3D objects 3D IC processor components and mainboards that are driven with the touch of a finger by pairing elements (Drag and Drop)