Alignment Process Research Articles

64‐4: Invited Paper: High Contrast Ratio ADS LCD Using Negative Liquid Crystal Material

Mini‐LED technology is becoming a mainly driving force in the development of LCD industry. Only using excellent spatial viewing angle characteristics, high picture quality and high contrast ratio LCD panel, Mini‐LED can maximize its effectiveness in improving image quality and has the strength to challenge the dominance of OLED in the high‐end market. As we known, ADS technology belongs to plane field switching display mode, taking into account the excellent wide‐angle characteristics and excellent image quality, has been widely used in mobile phone, tablet, notebook, monitor and TV, the only shortcoming is the low contrast ratio (CR), just at 1000‐1200:1. This paper aims to introduce the development of ultra‐high contrast ADS LCD panel and its implementation method. By using low scattering coefficient negative liquid crystal, fine rubbing alignment process, and fine calibrated POL attachment process, an ultra‐high contrast ratio of CR 3000‐3500:1 is achieved for the first time on ADS panel. The slow response time of negative liquid crystal is improved by balancing the operating voltage (Vop) and adjusting the Cell gap, while the decrease in transmittance caused by lower Cell gap can be overcome by the spectral aperture pixel (SAP) design. All the techniques described in this paper are applicable to various types of plane field switching panels. The paper also concludes with a discussion and outlook on how to further improve the contrast ratio of ADS‐like panel.

Intercultural Communication: Hampering and Facilitating Factors in International Business

Abstract Objective This paper aims at uncovering the hampering and facilitating factors in intercultural communication that professionals encounter in their business relationships. Methodology The data collection process involved conducting individual interviews and two rounds of focus groups with professionals who shared their experiences in working with another culture. The transcripts were analyzed using Thematic Analysis (Braun & Clarke, 2012) with the assistance of Atlas.ti 9. Findings The key challenges that emerged were differences in communication styles: too direct versus too indirect; misunderstandings and misconceptions when communicating in non-native languages; differences in business customs, such as separating business from private life versus blurred business and personal relationships; differences in decision-making and stereotyping. Value Added We offer a new perspective about existing models and theories of intercultural dimensions, highlighting the risks they entail when superficially generalized. Our paper contributes to professional practice by illustrating how language, differences in the communication style, business etiquette and stereotyping can prevent successful interactions. We show that business English may facilitate international communication but may easily become a source of misinterpretation. Recommendations Intercultural flexibility can play a fundamental role in contextualizing communication and providing true meaning to businesses exchanges. Adjusting language, focusing on building trustful relationships and creating alignment processes can all be instrumental for more effective and successful business communication. Future research with business professionals from diverse cultural backgrounds would enrich our understanding of intercultural business communication.

Distributed Alignment Processes With Samples of Group Average

Reaching agreement despite noise in communication is a fundamental problem in multi-agent systems. Here we study this problem under an idealized model, where it is assumed that agents can sense the general tendency in the system. More specifically, we consider $n$ agents, each being associated with a real-valued number. In each round, each agent receives a noisy measurement of the average value, and then updates its value, which is in turn perturbed by random drift. We assume that both noises in measurements and drift follow Gaussian distributions. What should be the updating policy of agents if their goal is to minimize the expected deviation of the agents' values from the average value? We prove that a distributed weighted-average algorithm optimally minimizes this deviation for each agent, and for any round. Interestingly, this optimality holds even in the centralized setting, where a master agent can gather all the agents' measurements and instruct a move to each agent.We find this result surprising since it can be shown that the total measurements obtained by all agents contain strictly more information about the deviation of Agent $i$ from the average value, than the information contained in the measurements obtained by Agent $i$ alone. Although this information is relevant for Agent $i$, it is not processed by it when running a weighted-average algorithm. Nevertheless, the weighted-average algorithm is optimal, since by running it, other agents manage to fully process this information in a way that perfectly benefits Agent $i$.Finally, we also analyze the drift of the center of mass and show that no distributed algorithm can achieve drift that is as small as the one that can be achieved by the best centralized algorithm. In light of this, we also show that the drift associated with our weighted-average algorithm incurs a relatively small overhead over the best possible drift in the centralized setting.

Investigating the strategic IT alignment process with a dynamic capabilities view: A multiple case study

In the turbulent business environments brought about by the digital age, strategic IT alignment remains at the forefront of managers’ concerns, raising important issues for researchers. One of these issues is to further understand how firms enact their IT alignment processes and what IT and non-IT capabilities are required to support these processes. To understand this issue, we conducted four case studies in small and medium-sized enterprises (SMEs). Anchored in a dynamic capability-based view, our findings unveil how three 2nd-order, six 1st-order dynamic IT alignment capabilities, and other IT and non-IT capabilities coherently interact to support the firm's business objectives.

WMSA 2: a multiple DNA/RNA sequence alignment tool implemented with accurate progressive mode and a fast win-win mode combining the center star and progressive strategies.

Multiple sequence alignment is widely used for sequence analysis, such as identifying important sites and phylogenetic analysis. Traditional methods, such as progressive alignment, are time-consuming. To address this issue, we introduce StarTree, a novel method to fast construct a guide tree by combining sequence clustering and hierarchical clustering. Furthermore, we develop a new heuristic similar region detection algorithm using the FM-index and apply the k-banded dynamic program to the profile alignment. We also introduce a win-win alignment algorithm that applies the central star strategy within the clusters to fast the alignment process, then uses the progressive strategy to align the central-aligned profiles, guaranteeing the final alignment's accuracy. We present WMSA 2 based on these improvements and compare the speed and accuracy with other popular methods. The results show that the guide tree made by the StarTree clustering method can lead to better accuracy than that of PartTree while consuming less time and memory than that of UPGMA and mBed methods on datasets with thousands of sequences. During the alignment of simulated data sets, WMSA 2 can consume less time and memory while ranking at the top of Q and TC scores. The WMSA 2 is still better at the time, and memory efficiency on the real datasets and ranks at the top on the average sum of pairs score. For the alignment of 1 million SARS-CoV-2 genomes, the win-win mode of WMSA 2 significantly decreased the consumption time than the former version. The source code and data are available at https://github.com/malabz/WMSA2.

High accuracy keyway angle identification using VGG16-based learning method

Aligning perforated pipes in different manufacturing workstations is critical for ensuring the quality of the final product in the oil&gas industry. Keyways inside the pipes are typically used for alignment. In order to automate the alignment process using an industrial robot, the keyway angle must be identified accurately. Because the environmental conditions keep changing in the shop floor, current methods cannot satisfy the accurate alignment requirement. Recently, VGG16 has become one of the most effective ways to deal with vision-based problems with different lighting conditions. Therefore, this paper proposes a method based on the VGG-16 architecture to identify the keyway angle to satisfy the manufacturing requirement (angle accuracy <1o) in different lighting conditions. In order to demonstrate the effectiveness of the proposed method, two traditional methods, a commercial vision method, and a geometrical rule based method, are also investigated. The comparisons of the three methods show that the proposed method performs best, yielding an angle error less than 1° in 98.38% of the testing images. The research results indicate that VGG-16 based method has significant potential to improve manufacturing processes.

The Homogenization of Urban Climate Action Discourses

Abstract The diversification of actors in global climate governance may entail risks, but it is also linked to enhanced democratic performance and opportunities for innovation. To what extent has this diversification fostered a parallel multiplication of perspectives in urban climate policy? To answer this question, we analyze the evolution of urban narratives based on 463 international policy documents issued between 1946 and 2020. Our analysis shows that, instead of leading to diversification, the proliferation of actors is accompanied by a growing homogenization of urban narratives. Language appears to become progressively uniform across organizations and over time, with approaches emphasizing multi-actor governance, integrated planning, and co-benefits becoming dominant. Three factors explain this homogenization. First, actors with a long history of involvement in international development exert a significant amount of influence. Second, there is a tendency toward language harmonization in international policy. Third, urban climate narratives stabilize through association with broader policy paradigms. In conclusion, the diversification of actors in international climate policy is mediated by processes of narrative alignment, which foreclose possibilities for divergent thinking.

Over-the-Air Antenna Array Calibration for mmWave Hybrid Beamforming Systems Based on Monte Carlo Markov Chain Method

The antenna phase calibration is critical for the millimeter wave (mmWave) hybrid beamforming communication system. Especially, with the increasing number of antennas being deployed in future massive MIMO systems, it is unrealistic to calibrate each antenna path in a microwave anechoic chamber. This work proposes a phase calibration based on over-the-air (OTA) scheme for mmWave hybrid beamforming systems, where the calibration process is performed automatically by the online signal transmission. The challenge for the OTA-based phase calibration is the imperfect channel estimation due to the phase error. To solve the challenge, we simplify the channel estimation process by integrating the beam alignment and phase calibration process. Consequently, the phase calibration is formatted to an MMSE-criterion based optimization problem solved by the Monte Carlo Markov Chain (MCMC) with probabilistic conversion improved Gibbs sampling method. Furthermore, an alternating iteration algorithm is developed to calibrate phase deviation for both the transmitter and receiver. We also extend our method to solve the joint amplitude and phase calibration problem. According to the simulation result, the calibration results outperform existing methods when the signal-to-noise ratio is less than 15dB. Besides, the proposed method exhibits a high beamforming gain during the calibration process, which paves the way for future massive device deployment in a practical system.

Magnetic field induced alignment of graphene nanoplatelets in epoxy resin to develop model nanocomposite

In this work, a mathematical model is developed to optimize the alignment parameters of Graphene Nanoplatelets (GNP) and Fe3O4-GNP applying a weak DC magnetic field (0.05 T), considering rotation, translation, migration, and slackening mechanisms of the nanoparticle in the epoxy. The characteristic magnetic, viscosity and hydrodynamic parameters required by the mathematic model are determined experimentally by synthesizing the magnetite ferric oxide (Fe3O4) and attaching them to GNP to increase its magnetic susceptibility. A highly aligned Fe3O4-GNP nanocomposite is fabricated at 0.05 T magnetic field and 40 Pa-s dynamic viscosity of epoxy, as evident from the optical image analysis. The mass magnetic susceptibility for the nanoparticles are determined at different magnetic field. Time needed for the alignment process at 0.05 T and viscosity range 10–50 Pa-s are compared among the rotation, chaining, migration and the slackening phenomena. The procedure demonstrated to prepare fully cured nanocomposite with aligned Fe3O4-GNP can be used in advanced structures.

Machine learning performance comparison for main propulsive shafting systems alignment

The ship shaft alignment is crucial to achieve a high-performance propulsion system. This alignment is carried out, still in drydock, by adjusting the bearings' offsets. However, there are numerous available combinations sets of vertical offsets which results in good alignment final condition. Defining an optimum set of vertical displacements is costing shipyards a valuable time. Therefore, this work proposes the use of machine learning algorithms to predict if a given set of offsets, following the mandatory rules in force, should be implemented or not. In this manner, this paper presents a case study where a finite element model of an Anchor Handling Tug Supply (AHTS) vessel’ shaft line was assembled in order to obtain the bearings reactions, shaft line deflections, shear forces, bending moments and, finally, the influence coefficients matrix (ICM). Those data were used to feed machine learning (ML) models based on four different algorithms, namely, K-Nearest-Neighbors, Extremely Randomized Trees, Random Forest and Gradient Boosting in order to solve multiclass classification problems concerning the offset's set to be applied in the alignment of the shaft line. Results showed that the Gradient Boosting and Random Forest algorithms presented the best results, achieving up to 98.1% of precision in one of the 36 scenarios tested, and an average precision above 96.0%. Such results corroborated with the authors' proposal to implement ML techniques as a way to speed up the currently very time-consuming shaft alignment process.

Magnetic alignment technology for wafer bonding

PurposeWafer bonding is a key process for 3 D advanced packaging of integrated circuits. It requires very high accuracy for the wafer alignment. To solve the problems of large movement stroke, position calibration error and low production efficiency in optical alignment, this paper aims to propose a new wafer magnetic alignment technology (MAT) which is based on tunnel magneto resistance effect. MAT can realize micro distance alignment and reduces the design and manufacturing difficulty of wafer bonding equipment.Design/methodology/approachThe current methods and existing problems of wafer optical alignment are introduced, and the mechanism and realization process of wafer magnetic alignment are proposed. Micro magnetic column (MMC) marks are designed on the wafer by the semiconductor manufacturing process. The mathematical model of the space magnetic field of the MMC is established, and the magnetic field distribution of the MMC alignment is numerically simulated and visualized. The relationship between the alignment accuracy and the MMC diameter, MMC remanence, MMC thickness and sensor measurement height was studied.FindingsThe simulation analysis shows that the overlapping double MMCs can align the wafer with accuracy within 1 µm and can control the bonding distance within the micrometer range to improve the alignment efficiency.Originality/valueMagnetic alignment technology provides a new idea for wafer bonding alignment, which is expected to improve the accuracy and efficiency of wafer bonding.

In-motion initial alignment method using Cayley–Kalman filter on special orthogonal group

Aiming at the in-motion initial alignment problem of strapdown inertial navigation system (SINS), this paper proposed a precise direct in-motion alignment method based on attitude matrix representation and Cayley–Kalman filter on the special orthogonal group. There are two innovations in this paper. First, as an element of the special orthogonal group [Formula: see text], the error attitude matrix is used to construct an in-motion alignment model, and it is transformed into the vector space to represent the attitude error state. The error matrix was used as a state to decrease the influence of the state-dependent problem. Second, this method uses the Cayley transform to replace the Taylor expansion to derive the update equation, which is a no approximation mapping relation to assure accuracy when deriving the filtering algorithm. Simulation and experimental results demonstrate the proposed alignment method has advantages over the existing methods in alignment accuracy and alignment time and performs well in the in-motion alignment process of SINS.

MANSOR: A module alignment method based on neighbor information for scientific workflow

SummaryFinding similar scientific workflow modules that can substitute essential components of the privacy workflows from public repositories to create a personalized workflow is growing in popularity. This is a cost‐effective and error‐free strategy for the scientific community. Currently, module alignment approaches heavily depend on syntactic information such as modules' names and types. However, the contextual semantic information of modules, which encompasses inputs, outputs, and datalinks connecting modules, can also convey their functions. Unfortunately, this information is scarcely utilized during the module alignment process. In this work, we propose a module alignment method based on neighbor information for scientific workflow (MANSOR). Specifically, we present a rule‐based attribute similarity computation approach for calculating initial module‐pair similarity in two workflows. The relation similarity is then employed to iteratively fine‐tune the matching degree with uncertainty of module pairs by considering the contextual semantics until reaching a steady state. After pairwise comparison of workflows, the module alignment results are determined based on their module‐pair similarity. Experimental results on the human‐curated corpus of ratings indicate that MANSOR outperforms the existing state‐of‐the‐art approaches with statistical significance.

Image Style Transfer Based on Dynamic Convolutional Manifold Alignment of Halo Attention

The objective of image style transfer is to render an image with artistic features of a style reference while preserving the details of the content image. With the development of deep learning, many arbitrary style transfer methods have emerged. From the recent arbitrary style transfer algorithms, it has been found that the images generated suffer from the problem of poorly stylized quality. To solve this problem, we propose an arbitrary style transfer algorithm based on halo attention dynamic convolutional manifold alignment. First, the features of the content image and style image are extracted by a pre-trained VGG encoder. Then, the features are extracted by halo attention and dynamic convolution, and then the content feature space and style feature space are aligned by attention operations and spatial perception interpolation. The output is achieved through dynamic convolution and halo attention. During this process, multi-level loss functions are used, and total variation loss is introduced to eliminate noise. The manifold alignment process is then repeated three times. Finally, the pre-trained VGG decoder is used to output the stylized image. The experimental results show that our proposed method can generate high-quality stylized images, achieving values of 33.861, 2.516, and 3.602 for ArtFID, style loss, and content loss, respectively. A qualitative comparison with existing algorithms showed that it achieved good results. In future work, we will aim to make the model lightweight.

Resonant Cavity 4-λ Integrated 4×4 PD-Array for High Optical Alignment Robustness WDM-FSO Communications

We present a newly developed resonant cavity 4-λ integrated two-dimensional 4 × 4 photodetector array (2D-PDA) device and its application for a wavelength-division-multiplexing (WDM) free-space optical (FSO) communication. The 2D-PDA enables direct optical coupling to the FSO beam, simplifying the optical alignment process needed for 10 μm single-mode fiber coupling and reducing the need for beam-tracking function. In the WDM-FSO communication demonstration, a four-wavelength beam in free space was successfully received by 4-different cavity length PD pixels in 4 × 4 PDA with crosstalk between each channel. This paper discusses about the fabrication and characteristic of the 2D-PDA device, in addition to the 25 Gbps/λ FSO communication demonstration using the 4 × 4 2D-PDA. Considering the crosstalk, the bit error rate is discussed in the 2-WDM and 3-WDM FSO communication demonstrations at 25 Gbps/λ.

Kajian Struktur Visual Pada Pasca Produksi Film Eksperimental “Sweet Rahwana”

Experimental Film “Sweet Ravana” is a film artwork that raises about human nature that is translated through puppet approach. To realize the character in accordance with one of the human traits that exist in the puppet characters namely Ravana. Where Ravana is a figure of evil and always thirsty for power. In a movie there are some messages to be conveyed by the author. The message to be conveyed apart from the narrative aspect also through the cinematic aspect. In the experimental film "Sweet Ravana" this message to be conveyed made through shot attraction. Two previously unrelated shots then after going through the alignment process then generate a new meaning. The series of compositions of shots on the film is then the visual structure. Sintagmatik and paradigmatik is a theory that can be used to study the visual structure that exist in the experimental film "Sweet Ravana" with the aim to know the structure of the visual on the process jukstaposisi types of shot selection and editing.

Comparing the Effectiveness of Hashtags in Digital Social Movements: A Case Study of #PercumaLaporPolisi and #PolriSesuaiProsedur in Indonesia

Hashtags are used in digital social movements to mobilize netizens and create social change. This study aims to fill in gaps from previous studies by comparing the hashtags #PercumaLaporPolisi and #PolriSesuaiProsedur, which emerged on Twitter as social movements in response to the rape of three children under ten in East Luwu, South Sulawesi. The study incorporates framing analysis and focuses on the frame alignment process to see the efforts of the hashtags #PercumaLaporPolisi and #PolriSesuaiProsedur on mobilizing social media users. This study uses Social Network Analysis (SNA) to analyze the network structure formed from #PercumaLaporPolisi vs. #PolriSesuaiProsedur hashtags and determine the values of reciprocity, centralization, diameter, density, and modularity. The researcher also uses framing alignment analysis to analyze the tweets collected using Python from October 6-17, 2021, and Netlytic software as a tool. This text compares the effectiveness of two Twitter hashtags, #PercumaLaporPolisi, and #PolriSesuaiProsedur, in mobilizing supporters during a campaign about police policies in Indonesia. Network analysis found that #PolriSesuaiProsedur had a more extensive network, higher density, and more robust framing than #PercumaLaporPolisi, which resulted in a more effective mobilization of supporters. The text emphasizes the importance of precise messaging and framing in hashtag activism. This study compared the success of two hashtags, #PercumaLaporPolisi, and #PolriSesuaiProsedur, and found that #PolriSesuaiProsedur was more successful due to its clear framing. This research highlights the significance of precise framing in hashtags for mobilizing supporters in digital social movements. Future studies could investigate the impact of various hashtags on mobilization.

Project portfolio modeling for theregional dual education development

The aim of the article is to present a method of project portfolio management for the regional development of dual education under conditions of uncertainty using expert methods. In the project portfolio management standard, portfolio formation is represented by a group of alignment processes, but their practical application in a specific subject area remains at the discretion of the developer. For the design and development of software systems, visual process models are developed for a specific subject area. The article presents the development of a complex system of dual education through the formation of a portfolio of projects. The data obtained allowed to determine that the portfolio management methodology can be successfully implemented in Ukrainian dual education. To improve the processes of portfolio management, a practical implementation of the processes of portfolio formation in the IDEF0 notation was carried out. A simplified algorithm for forming a project portfolio has been developed, which allows increasing the speed of response to changes in portfolio managementin educational sphere. The proposed solution of the educational system development through portfolio using expert methods that are distinguished by the application of the Pareto rule forbuilding a scenario for the system development. On the basis of the developed methodology for forming a portfolio of innovative projects, the process of optimizing the efficiency of the portfolio of innovative projects with determining their individual priorities is studied on the example. The application of the developed procedures for planning the portfolio management of the dual education system in the central region of Ukraine is demonstrated. The results obtained have made it possible to make sure that the system development management in conditions of incomplete information covers the areas of process management, and helps to minimize the impact of uncertainty on the efficiency of the portfolio of projectsimplementation.

Capture of stars into gaseous discs around massive black holes: alignment, circularization, and growth

ABSTRACT The majority of massive black holes (MBHs) likely hosted gas discs during their lifetimes. These could either be long-lived active galactic nuclei (AGN) discs, or shorter-lived discs formed following singular gas infall events, as was likely the case in our own Galactic Centre. Stars and compact objects in such environments are therefore expected to interact with the gaseous disc as they go through it, and potentially become aligned and fully embedded within it. The interactions of embedded stars with the gas could give rise to a plethora of physical processes affecting the stars, including growth through accretion of gas, migration in the disc, stellar captures, and mergers with other stars. The impact of such processes strongly depends on the population of stars that eventually align with the disc and become embedded in it. Here we make use of analytic tools to analyze the alignment process, accounting for both geometric drag and gas dynamical friction. We find that up to $\sim \! 50~{{\ \rm per\ cent}}$ of main sequence stars and stellar mass black holes in the central 0.1 pc can align with AGN disc in the Galactic Centre and similar galactic nuclei. The orbits of aligned stars are typically circularized and are prograde with respect to the AGN disc. Furthermore, alignment and accretion are intimately linked, and the capture of stars by an AGN disc can potentially explain the origin of the young stellar disc in the Galactic Centre with a top-heavy mass function, even without the need for a star-formation event.

Interorganizational Sensemaking of the Transition Toward a Circular Value Chain.

The transition toward the circular economy requires stakeholders to collaborate along value chains. Yet, such collaborations are considerably challenging. Given the paradigmatic change, stakeholders face high levels of uncertainty and also need to align on a common way forward. We extend research on interorganizational sensemaking and the circular economy by exploring the process of interorganizational alignment in a European consortium of over 150 companies representing the value chain for flexible packaging with the objective to transform the value chain from linear to circular. We find that the interorganizational sensemaking process unfolds across three levels-organization, value chain, and ecosystem-which provide different reference frames for the process. We provide insights into how these frames, power dynamics, and identity considerations influence this process. Our findings highlight the importance of considering interdependencies between stakeholders and a collective reconceptualization of the established value chain to successfully transition toward a circular one.