This paper proposed an algorithm to evaluate hole properties automatically. The proposed algorithm analyzes probe path, reference data, measurement data, and tolerance data to evaluate hole properties based on tolerance data ISO 2768. The proposed algorithms was verified experimentally by implementing to holes evaluation software which is developed by phyton programming. A 3D product model with two different hole was designed to validate the proposed algorithm. according to the experiment result, proposed algorithm can evaluate hole properties properly with quality control sheet format as output. Then, the proposed algorithm experiment is compared with manual evaluation.

In this paper, the development of inspection code generator for hole cylindrical feature evaluation is reported. The development process aims to enable on-machine measurement process through Computer Aided Inspection Planning (CAIP) software. A CNC machine equipped with touch probe measuring tool is utilized in this research as an object for On-Machine Measurement (OMM) System. The hole feature as measurement object were defined from feature recognition process. An algorithm to construct inspection path planning was developed according to hole feature measurement point. Inspection path planning define touching point, retract point, clearance ratio, and retract distance from the measurement point. The inspection path planning is transformed into inspection code based on Heidenhain iTNC 30i controller code standard. The Inspection code were experimentally executed in the DMG 50U CNC Machine to validate the path planning. Renishaw touch probe were used to measure the hole feature dimension and position. The OMM result was compared to the vernier and measurement result. The experiment result shows that the proposed method has accurate equal inspection result to the vernier.

In the last decade, the era of the Industrial Revolution 4.0 began. Technology played a major role in almost all industrial revolutions. So, computers and manufacturing systems will be able to collaborate. One of the pillars of the fourth Industrial Revolution is crowdsensing. Several experiments in the fields of society, infrastructure, agriculture, and health have used it. Crowdsensing in the health sector can help gather a substantial source of data on general public health conditions. However, most crowdsensing techniques rely on only one communication protocol. This method can cause problems if a system failure occurs. Besides that, another consideration is that the crowdsensing users consist of several communication protocols. As a result, we present a multi-communication protocol gateway architecture for crowdsensing that addresses the aforementioned issues by combining two communication protocols, such as HTTP and MQTT, into a single gateway. This gateway serves to receive data from sensor nodes before transmitting it to an IoT platform on a cloud server. The test results show that the MQTT protocol has better performance than the HTTP protocol in the delay test. The MQTT protocol delay reaches 0.113 seconds and the HTTP protocol delay is 0.717 seconds. In addition, the gateway is also able to receive data properly even though both protocols are run simultaneously.

APIs are critical for digital transformation as well as the establishment and development of new business models. They are the foundation of application economics which allows for quicker, better, and less expensive development. In security perspective, OWASP released its first API security report in 2019 which finally differentiate the security risk categories between API and web application. In recent years, there have been many incidents of cyber attacks related to API, while the implementation of the API itself is growing in popularity among organizations. Therefore, the need to understand APIs from a security perspective should be taken seriously and considered as an integral part of the software development life cycle. In this research, we proposed an API security learning environment called Vulnerable Academic Information System (VAIS) based on the OWASP API Security Risks with containerization deployment plan and gamification technique to provide a fun yet challenging environment for people in understanding the API security in a legal environment.

APIs are critical for digital transformation as well as the establishment and development of new business models. They are the foundation of application economics which allows for quicker, better, and less expensive development. In security perspective, OWASP released its first API security report in 2019 which finally differentiate the security risk categories between API and web application. In recent years, there have been many incidents of cyber attacks related to API, while the implementation of the API itself is growing in popularity among organizations. Therefore, the need to understand APIs from a security perspective should be taken seriously and considered as an integral part of the software development life cycle. In this research, we proposed an API security learning environment called Vulnerable Academic Information System (VAIS) based on the OWASP API Security Risks with containerization deployment plan and gamification technique to provide a fun yet challenging environment for people in understanding the API security in a legal environment.

Nowadays, computer-based tests are commonly used since a pandemic made educational institutions hold exams from home and it made computer-based tests application demand increasing time by time. This situation leads to the need for applications that can run on any device, secure from cheating and compatible with poor internet connection. Our proposed system able to improve security and deception issues in the examination. In this paper we also introduce distributed online computer-based test for English test that made our software can share questions-data to another instance securely.

This paper proposed an algorithm to recognize intersection cylindrical feature, especially counterbore and countersink geometry. The proposed algorithm analyzes 3D solid drawing in term STEP format to find intersection cylindrical feature based on a specific properties of counterbore and countersink geometry. The proposed algorithms was verified experimentally by implementing to holes inspector (HECTOR) software. A 3D product model with five different hole was designed to validate the proposed algorithm. according to the experiment result, counterbore and countersink on the 3D specimen product is properly recognized by the proposed algorithm.

The global data footprint doubles every few years. Organizations struggle to gain meaningful insights from the rapidly growing volumes of data to use this ever-increasing data. Organizations need to manage capacity placement and data governance requirements with speed and flexibility, and minimal costs to reduce capital expenditure. One of the limitations is that traditional storage still has a customer’s need to spend on capital expenditure. The customer needs to pay more every year for maintenance. Many companies consider moving internal data out of their data centers or migrating their data into the cloud. And also, this cloud technology can make the customer no need to worry about the scalability of their resource. Furthermore, the customer only needs to pay for what the customer use on the cloud. Unfortunately, until now, a user does not have many options to deploy object storage solutions across on-premise data centers and the cloud with high–performance capabilities. Storage Gateway is a hybrid cloud storage service that can give users access from their on-premises to virtually cloud storage with unlimited scalability. This Storage Gateway can connect between cloud storage and on-premises site seamlessly. This gateway system can interact with cloud storage services more simply while boosting performance and reducing cost. This paper aims to study the influence of the implementation and optimization of Storage Gateway as a heterogeneous integrator between premise and cloud storage. Also, the Network factor is using optimized by CDN Enabled to reduce upload latency between on-premise to Bucket. Tests are carried out using direct measurement methods to measures Throughput, Latency, and cost-efficiency.

Wireless Body Area Network (WBAN) is a health service that consists of small sensors attached to the patient's body to improve health services. Apart from the importance and necessity of the WBAN, there are some problems in WBAN such as inaccurate measurements, hardware failures, discharged sensors, and sensors running out of energy which can cause false alarms and reduce confidence in using the WBAN system for remote health services. This research aims to create a system or modelling to solve anomalous data problems in WBAN health data. The system will process data to produce an analysis of information in an anomalous condition by applying the statistical method using Mahalanobis Distance and the prediction method using SMOreg. The process of collecting data and pre-processing is carried out before completing the detection of anomalous features. The data normalization process is carried out to make the process faster. This approach was tested on a real health dataset on the WBAN sensor. The results of the implementation show that the method produced a high-performance detection ratio (DR), which is above 80%. In addition, the experiment resulted that the size of the sliding window affected the anomaly detection results.

Virtualization and Software-defined Networking (SDN) are emerging technologies that play a major role in cloud computing. Cloud computing provides efficient utilization, high performance, and resource availability on demand. However, virtualization environments are vulnerable to various types of intrusion attacks that involve installing malicious software and denial of services (DoS) attacks. Utilizing SDN technology, makes the idea of SDN-based security applications attractive in the fight against DoS attacks. Network intrusion detection system (IDS) which is used to perform network traffic analysis as a detection system implemented on SDN networks to protect virtualization servers from HTTP DoS attacks. The experimental results show that SDN-based IDS is able to detect and mitigate HTTP DoS attacks effectively.

E-learning is distance learning that uses computer technology, networks of computers and the internet. E-Learning allows students to study via computers in their respective places without having to go to study/lectures in class physically. Moodle is a Learning Management System that is used as a medium for delivering E-Learning. The problem that often arises in e-learning is that in the learning process, students interact more with e-learning media so that teachers will find it difficult to monitor student behavior when using learning media. In fact, students in some cases tend to drop out or attend lesser classes. Moodle can capture student interactions and activities while studying online using log files. From the results of student interactions and activities on e-learning, it can be used to determine their learning style. Identifying student learning styles can improve the performance of the learning process. This research suggests an approach to automatically predicting learning styles based on the Felder and Silverman learning style (FSLSM) model using the Decision Tree algorithm and the ensemble Gradient Boosted Tree method. We've used actual data sets derived from e-learning program log files to perform our work. We use precision and accuracy to assess the results. The results show that our approach is delivering excellent results.

This paper discusses how to monitor the operation of guest OS on the virtualization environment. There are several forensic applications which are useful for analyzing events that run on operating systems specifically memory, CPU, and I/O. We use the LibVMI library to create a new plugin for Drakvuf in order to detect Hang on a guest OS that runs on top of the Xen Hypervisor. The experiment shows that libVMI able to monitor the state of the guest OS. However, the a problem arises when LibVMI start to detect the hang condition. The EPT violation occurs during hang monitoring process.

A network switch is an important network device on a computer network, the role of a switch can determine the good and bad of a network service. In a data center, sometimes it has several switch devices with different capabilities (diversity). For this reason, we need a strategy to carry out the effectiveness of using switch devices on computer networks. One way that can be done to realize this is by choosing the right partner between switches and hosts. The matching theory makes it possible to overcome this problem. In this study, it was simulated using the Stable Marriage Problem (SMP) method. The initial state to determine the ranking of pairs is done by using several attributes that are owned by each switch and host such as interfaces, services on the host, and data traffic on the device. Simulations are performed on mininet using Software-defined networking (SDN).

Computer (server) becomes an essential part of the information system. However, this server always has a possibility to experience a failure. In our previous study, we involve virtual machine technologies to address the failure that occurs on the server. However, this method only covers the recovery of the server from the perspective of the server itself. Our proposed method is to use the concept of software-defined networking to overcome the failure by involving network devices (e.g., switches). The experiment result shows that the concept of SDN is able to maintain the resilience of the server by interrupting the suspicious traffic.

Wireless sensor networks (WSN) consists of large number of sensor nodes with limited energy and computing resources. These facts have highlighted open problem to prolong the lifetime of sensor nodes while still maintaining the functional roles of WSN in reporting important events to a base station. These papers propose an approach for WSN inspired by the concept of immunity-based system where a set of reactions is performed in the appearance of nonself substances called syndromes. The notion of reactive cluster is introduced where only sensor nodes affected by the syndrome appearances need to perform reactions by establishing clusters among them. Since communication costs significant energy, each sensor nodes as an immune cell need to reduce impacts of the syndromes for itself and other sensor nodes in the routing paths to the sink node. It is done establishing adaptive data aggregation strategies. Depend on the critical level of the corresponding syndrome and error of wireless communications that may occur, the length of the aggregation window is adjusted. We show that the proposed approach shows promising results in minimizing dead sensor nodes, avoiding network congestion while still maintaining the functional roles of WSN in reporting important events to the sink node.