Implementation of Barcode Technology to Logistics Processes of a Company

The article focuses on expanding the use of barcodes in selected logistics activities in a company. Our study discusses the application of barcode technology to selected logistics activities in the company in order to address the error rate in these activities and to control ownership of this technology in other logistics activities within the company during the COVID-19. The priority of the testing phase was to point out the elimination of errors in the original versus the newly proposed solution for the company on 10 products. In the test phase, the 10 products with the highest turnover in the company were used to point out the elimination of errors in various logistics activities, especially the time saved compared to the work of human personnel in the company. The company has this technology at its disposal, in the parent company as well as in the subsidiary. It was only a matter of expanding the use and applicability of this technology as well as other possibilities for research hypotheses, which we outlined at the end of the article. In this article, we focus on RFID and barcode technologies, since the company initially considered using RFID technology, however, chose the use of barcodes because it was an already known work technology. The current situation affected with COVID-19 disease requires many advantages and disadvantages of both technologies.

Writer Identification Based on Hand Writing using Artificial Neural Network

Humans are social beings who depend on social interaction. Social interaction that is often used is communication. Communication is one of the bridges to connect social relations between humans. Communication can be delivered in two ways, namely verbal or nonverbal. Handwriting is an example of nonverbal communication using paper and writing utensils. Each individual's writing has its own uniqueness so that handwriting often becomes the character or characteristic of the author. The handwriting pattern usually becomes a character for the writer so that people who recognize the writing will easily guess the ownership of the related handwriting. However, handwriting is often used by irresponsible people in the form of handwriting falsification. The acts of writing falcification often occur in the workplace or even in the field of education. This is one of the driving factors for creating a reliable system in tracking someone's handwriting based on their ownership. In this study, we will discuss the identification of a person's handwriting based on their ownership. The output of this research is in the form of ID from the author and accuracy in the form of percentage of system reliability in identifying. The results of this study are expected to have a good impact on all parties, in order to minimize plagiarism. Identification of handwriting to be built consists of two main processes, namely the training phase and the testing phase. At the training stage, the handwritten image is subjected to several processes, namely threshold, wavelet conversion, and then will be trained using the Backpropagation Artificial Neural Network. In the testing phase, the process is the same as in the training phase, but at the end of the process, a comparison will be made between the image data that has been stored during training with a comparison image. Backpropagation ANN can work optimally if it is trained using input data that has determined the size, learning rate, parameters, and the number of nodes on the network. It is expected that the offered method can work optimally so that it produces an accurate percentage in order to minimize handwriting falcification.

Development of an affective database made of interactive virtual environments

Despite the great potential of Virtual Reality (VR) to arouse emotions, there are no VR affective databases available as it happens for pictures, videos, and sounds. In this paper, we describe the validation of ten affective interactive Virtual Environments (VEs) designed to be used in Virtual Reality. These environments are related to five emotions. The testing phase included using two different experimental setups to deliver the overall experience. The setup did not include any immersive VR technology, because of the ongoing COVID-19 pandemic, but the VEs were designed to run on stereoscopic visual displays. We collected measures related to the participants’ emotional experience based on six discrete emotional categories plus neutrality and we included an assessment of the sense of presence related to the different experiences. The results showed how the scenarios can be differentiated according to the emotion aroused. Finally, the comparison between the two experimental setups demonstrated high reliability of the experience and strong adaptability of the scenarios to different contexts of use.

Prototyping, Testing, and Redesign of a Three-Wheel Trekking Wheelchair for Accessible Tourism Applications

This work is part of the project called “Gölem project”, started in 2017, about special devices developed to enable the so-called Accessible Tourism. This project aims to design and develop a trekking wheelchair for people with impaired mobility. After an initial phase of design and prototyping, the testing phase has now begun. The objective is to validate several aspects of the design, concerning basic kinematics and dynamics, passenger comfort and physical effort of the carriers. This paper describes the development of qualitative tests for drivability and balance validation of this first prototype. At this stage, a list of features to be investigated was made, suitable trekking paths were chosen, and qualitative experimental field tests were performed. Then, the design of the prototype was modified according to these first experimental results, to improve the wheelchair characteristics. The prototype is now undergoing the modification phase, then further testing will be performed with the use of specific instrumental devices to evaluate the wheelchair itself and to perform the kinematic, dynamical, and comfort characterization.

Novel Drill Bit Analysis to Delay and Mitigate Fixed Cutter Thermal Damage

As oil and gas wells become deeper, drilling longer intervals is becoming a major milestone for drill bit companies, as the process comes with a variety of challenges affecting the durability of drill bits. Among the major challenges are thermal and impact damage in polycrystalline diamond compact (PDC) cutters, which can significantly affect the performance and longevity of a drill bit. While cutter technology development remains an important arena to address said challenges, there exists a need to also address these through the design process. This paper presents the development and deployment of a new drill bit analysis method that addresses thermal damage by optimizing the design, which has been field validated across the globe. The analysis involves estimating the thermal input load and the available cooling rate for every cutter on a drill bit during drilling conditions. The data is then used to optimize and apply changes to the design. The analysis considers all the critical and relevant operational parameters to calculate these indices. The outcome of the so-called thermal index analysis enables the design team to make informed decisions to improve the design of the drill bit and to minimize the extent of thermal damage in cutters. The improvements made in the design include changes in cutting structure to affect cutting forces and, eventually, the thermal input load during the drilling process. This stage in practice can bring down the temperature of the cutting edge by 20%, as calculated analytically. Another major change that can affect the results is hydraulic design of the bit, which includes the location of the nozzles as well as their orientation and size. In test cases, the cooling rate improved by 50% while keeping the same flow rate though the bit. Several field trials have validated the correlation of thermal index analysis to drill bit dulls. This analysis is now in the field evaluation and testing phase, where it is being used during the design process to improve bits with thermal damage. The field-testing phase has been primarily conducted in thermally challenging applications across the Middle East, North Africa region, and in West Texas.

Using Data Augmentation and Time-Scale Modification to Improve ASR of Children’s Speech in Noisy Environments

Current ASR systems show poor performance in recognition of children’s speech in noisy environments because recognizers are typically trained with clean adults’ speech and therefore there are two mismatches between training and testing phases (i.e., clean speech in training vs. noisy speech in testing and adult speech in training vs. child speech in testing). This article studies methods to tackle the effects of these two mismatches in recognition of noisy children’s speech by investigating two techniques: data augmentation and time-scale modification. In the former, clean training data of adult speakers are corrupted with additive noise in order to obtain training data that better correspond to the noisy testing conditions. In the latter, the fundamental frequency (F0) and speaking rate of children’s speech are modified in the testing phase in order to reduce differences in the prosodic characteristics between the testing data of child speakers and the training data of adult speakers. A standard ASR system based on DNN–HMM was built and the effects of data augmentation, F0 modification, and speaking rate modification on word error rate (WER) were evaluated first separately and then by combining all three techniques. The experiments were conducted using children’s speech corrupted with additive noise of four different noise types in four different signal-to-noise (SNR) categories. The results show that the combination of all three techniques yielded the best ASR performance. As an example, the WER value averaged over all four noise types in the SNR category of 5 dB dropped from 32.30% to 12.09% when the baseline system, in which no data augmentation or time-scale modification were used, was replaced with a recognizer that was built using a combination of all three techniques. In summary, in recognizing noisy children’s speech with ASR systems trained with clean adult speech, considerable improvements in the recognition performance can be achieved by combining data augmentation based on noise addition in the system training phase and time-scale modification based on modifying F0 and speaking rate of children’s speech in the testing phase.

Effective Combination of Bert Model and Cross-Sentence Contexts in Aspect Extraction

The Aspect Extraction (AE) field investigates in collecting words which are sentiment aspects in sentences and documents. Despite the pandemic, the number of products purchased online is still growing, which means that the number of product reviews and comments is also increasing rapidly, so the role of the task is gradually crucial. Extract aspects in the text is a difficult task, that requires algorithms capable of deep capturing the semantics of the text. In this work, we combine two models of the two research groups, with the first using the BERT algorithm with multiple concatenated layers and the second using the strategies to enrich the dataset by itself in the training or testing phase. The source code is available on github.com, researchers can run it through scripts, modify it for further research also. https://github.com/leanhkhoi/AE_BERT_CROSS_SENTENCES

Software Security: Role in SDLC

This research emphasizes mainly on the need for software security. Softwares are developing at a faster pace so it is required to impose security on them in order to secure them from cybercrimes. Softwares have been facing problems by the attackers who are constantly kept on breaching the Data. Therefore this survey comprises the phases that are an integral part of the SDLC from the security point of views such as Design and testing phase. Moreover, it quests upon the data related to threats and attacks. Not only this, but it also involves the prerequisites that have to be determined before developing the software like, what are the approaches that should be followed and what are the best suitable designs to secure the software?

What is a Library Website, Anyway? Reconsidering Dominant Conceptual Models

In late 2019, Thompson Rivers University embarked on a multi-phase website usability project beginning with a website user survey, to be followed shortly afterward by usability testing and interviews. While the survey was completed as planned, the COVID-19 pandemic closed the library and interrupted the usability testing phase. This interruption and the frantic website changes that followed led me to consider survey findings within the context of differing conceptual models of the library website as a whole. This study explores a number of conceptual models of the library website in further depth, considering evidence from both the existing literature and the user survey in addition to the researcher’s own experience making post-COVID website updates. Particular models that are examined include Website as Research Portal, Website as Extension or Representation of the physical library, and Website as Library Branch. Each of these conceptual models has different implications on priorities, structure, purpose, and resource allocation. Rather than considering the models of library employees superior or more advanced than those of students, I contend that an awareness of myriad ways to understand the website can best bridge the gap between library employees and other users. The study concludes that while there is no perfect model of the library website, considering and communicating our models may sharpen collegial decision-making structures and create greater unity of purpose within the library.