Dynamic Packing Research Articles

Template-based text field segmentation for ID documents using dynamic squeezeboxes packing

Template-based text field segmentation for ID documents using dynamic squeezeboxes packing

Capacity planning in logistics corridors: Deep reinforcement learning for the dynamic stochastic temporal bin packing problem

This paper addresses the challenge of managing uncertainty in the daily capacity planning of a terminal in a corridor-based logistics system. Corridor-based logistics systems facilitate the exchange of freight between two distinct regions, usually involving industrial and logistics clusters. In this context, we introduce the dynamic stochastic temporal bin packing problem. It models the assignment of individual containers to carriers’ trucks over discrete time units in real-time. We formulate it as a Markov decision process (MDP). Two distinguishing characteristics of our problem are the stochastic nature of the time-dependent availability of containers, i.e., container delays, and the continuous-time, or dynamic, aspect of the planning, where a container announcement may occur at any time moment during the planning horizon. We introduce an innovative real-time planning algorithm based on Proximal Policy Optimization (PPO), a Deep Reinforcement Learning (DRL) method, to allocate individual containers to eligible carriers in real-time. In addition, we propose some practical heuristics and two novel rolling-horizon batch-planning methods based on (stochastic) mixed-integer programming (MIP), which can be interpreted as computational information relaxation bounds because they delay decision making. The results show that our proposed DRL method outperforms the practical heuristics and effectively scales to larger-sized problems as opposed to the stochastic MIP-based approach, making our DRL method a practically appealing solution.

An online dynamic dual bin packing with lookahead approach for server-to-cell assignment in computer server industry

Efficient production scheduling in computer server industry remains a critical challenge. This challenge becomes particularly acute during the testing phase, where servers are assigned for testing in a modular environment consisting of test banks. Unique characteristics such as online arrival of servers known only over a short time window, skewed arrival pattern, power and cooling compatibility constraints, and dynamic assignment complicate decision making, a situation we observed at our industry partner’s site, which often leads to missing due dates and loss of customer trust. Motivated by this challenge, we introduce an Online Dynamic Dual Bin Packing with Lookahead problem and propose an integer linear programming model that maximizes the number of assigned servers. To efficiently solve this model, we decompose the problem into a set of subproblems for a given lookahead length. A ‘2-phase’ computational framework is proposed that seamlessly integrates mathematical programming with genetic algorithm. Based on realistic data available from a server manufacturer, our findings suggest that solutions are sensitive to (i) the length of the lookahead window, (ii) testing capacity and server arrival pattern, (iii) test processing time requirement, and (iv) physical allocation of servers.

A 119.64 GOPs/W FPGA-Based ResNet50 Mixed-Precision Accelerator Using the Dynamic DSP Packing

A 119.64 GOPs/W FPGA-Based ResNet50 Mixed-Precision Accelerator Using the Dynamic DSP Packing

Circularly Polarized Light Responsive Materials: Design Strategies and Applications.

Circularly polarized light (CPL) with the end of optical vector traveling along circumferential trajectory, shows left- and right-handedness, which transmits chiral information to materials via complicated CPL-matter interactions. Materials with circular dichroism respond to CPL illumination selectively with differential outputs that can be used to design novel photodetectors. Racemic or achiral compounds under CPL go through photodestruction, photoresolution and asymmetric synthesis pathways to generate enantiomeric bias and optical activity. By this strategy, helical polymers and chiral inorganic plasmonic nanostructures are synthesized directly, and their intramolecular folding and subsequent self-assembly are photo-modulable as well. In the aggregated state of self-assembly and liquid crystal phase, helical sense of the dynamic molecular packing is sensitive to enantiomeric bias brought by CPL, enabling the chiral amplification to supramolecular scale. In this review, we aim to systematically summarize and discuss the application-guided design strategies of CPL-responsive materials. Asymmetric synthesis, resolution and property-modulation of small organic compounds, polymers, inorganic nanoparticles, supramolecular assemblies and liquid crystals are highlighted based on the important developments during the last decades. Besides, applications of light-matter interactions including CPL detection and biomedical applications are also referred. This article is protected by copyright. All rights reserved.

Lossless Data Compression for Time-Series Sensor Data Based on Dynamic Bit Packing.

In this paper, we propose a bit depth compression (BDC) technique, which performs bit packing by dynamically determining the pack size based on the pattern of the bit depth level of the sensor data, thereby maximally reducing the space wastage that may occur during the bit packing process. The proposed technique can dynamically perform bit packing according to the data's characteristics, which may have many outliers or several multidimensional variations, and therefore has a high compression ratio. Furthermore, the proposed method is a lossless compression technique, which is especially useful as training data in the field of artificial intelligence or in the predictive analysis of data science. The proposed method effectively addresses the spatial inefficiency caused by unpredictable outliers during time-series data compression. Additionally, it offers high compression efficiency, allowing for storage space savings and optimizing network bandwidth utilization while transmitting large volumes of data. In the experiment, the BDC method demonstrated an improvement in the compression ratio of up to 247%, with 30% on average, compared with other compression algorithms. In terms of energy consumption, the proposed BDC also improves data transmission using Bluetooth up to 34%, with 18% on average, compared with other compression algorithms.

Dynamic space packing

Dynamic space packing (DSP) is a random process with sequential addition and removal of identical objects into space. In the lattice version, objects are particles occupying single lattice sites, and adding a particle to a lattice site leads to the removal of particles on neighboring sites. We show that the model is solvable and determine the steady-state occupancy, correlation functions, desorption probabilities, and other statistical features for the DSP of hyper-cubic lattices. We also solve a continuous DSP of balls into .

Real-Time IoV Task Offloading through Dynamic Assignment of SDN Controllers: Algorithmic Approaches and Performance Evaluation

Task offloading in Internet of Vehicles (IoV) is very crucial. The widespread use of IoT applications frequently interacts with the cloud, thereby increasing the load on centralized cloud controllers. Centralized network management in cloud infrastructure is not feasible for the latest IoT trends. Decentralized and decoupled network management in Software Defined Networks (SDN) can enhance IoV services. SDN and IoV coupling can better handle task offloading in ubiquitous and dynamic IoV environments. However, appropriate SDN controller assignment and allotment strategies play a prominent role in IoV communication. In this study, we developed algorithms for SDN controller assignment and allotment namely 1) Next Fit Allotment and Assignment of SDN Controller in IoV (NFAAC), 2) Dynamic Bin Packing Allotment and Assignment of SDN Controller in IoV (DBPAAC), and 3) Dynamic Focused and Bidding Allotment and Assignment algorithm of SDN Controller in IoV (DFBAAC). These algorithms were simulated using open-flow switch controllers. The controllers were modeled as Road Side Units (RSU) that can allocate bandwidth and resource requirements to vehicles on the road. Our results show that our proposed algorithm works efficiently for SDN controller assignment and allocation, outperforming the existing work by a significant improvement of 13.5%. The working of the proposed algorithms are verified, tested, and analytically presented in this study.

Exploring the medicinal potential of Dark Chemical Matters (DCM) to design promising inhibitors for PLpro of SARS-CoV-2 using molecular screening and simulation approaches

The growing concerns and cases of COVID-19 with the appearance of novel variants i.e., BA.2.75. BA.5 and XBB have prompted demand for more effective treatment options that could overcome the risk of immune evasion. For this purpose, discovering novel small molecules to inhibit druggable proteins such as PLpro required for viral pathogenesis, replication, survival, and spread is the best choice. Compounds from the Dark chemical matter (DCM) database is consistently active in various screening tests and offer intriguing possibilities for finding drugs that are extremely selective or active against uncommon targets. Considering the essential role of PLpro, the current study uses DCMdatabase for the identification of potential hits using in silico virtual molecular screening and simulation approaches to inhibit the current and emerging variants of SARS-CoV-2. Our results revealed the 10 best compounds with docking scores between −7.99 to −7.03 kcal/mol better than the control drug (GRL0617) among which DC 5977–0726, DC 6623–2024, DC C879-0379 and DC D135-0154 were observed as the best hits. Structural-dynamics properties such as dynamic stability, protein packing, and residue flexibility demonstrated the pharmacologically favorable properties of these top hits in contrast to GRL0617. The hydrogen bonding half-life revealed that Asp164, Arg166, Tyr264, and Tyr268 have major contributions to the hydrogen bonding during the simulation. However, some of the important hydrogen bonds were missing in the control drug (GRL0617). Finally, the total binding free energy was reported to be −34.41 kcal/mol for GRL0617 (control), −41.03 kcal/mol for the DC5977-0726-PLpro, for the DC6623-2024-Plpro complex the TBE was −48.87 kcal/mol, for the for DCC879-0379-Plpro complex the TBE was −45.66 kcal/mol while for the DCD135-0154-PLpro complex the TBE was calculated to be −40.09 kcal/mol respectively, which shows the stronger potency of these compounds against PLpro and further in in vivo and in vitro test are required for the possible usage as potential drug against SARS-CoV-2.

On data reduction for dynamic vector bin packing

We study a dynamic vector bin packing (DVBP) problem. We show hardness for shrinking arbitrary DVBP instances to size polynomial in the number of request types or in the maximal number of requests overlapping in time. We also present a simple polynomial-time data reduction algorithm that allows to recover (1+ε)-approximate solutions for arbitrary ε>0. It shrinks instances from Microsoft Azure and Huawei Cloud by an order of magnitude for ε=0.02.

High-throughput thermal denaturation of tryptophanyl-tRNA synthetase combinatorial mutants reveals high-order energetic coupling determinants of conformational stability.

Landscape descriptions provide a framework for identifying functionally significant dynamic linkages in proteins but cannot supply details. Rate measurements of combinatorial mutations can implicate dynamic linkages in catalysis. A major difficulty is filtering dynamic linkages from the vastly more numerous static interactions that stabilize domain folding. The Geobacillus stearothermophilus (TrpRS) D1 switch is such a dynamic packing motif; it links domain movement to catalysis and specificity. We describe Thermofluor and far UV circular dichroism melting curves for all 16 D1 switch variants to determine their higher-order impact on unliganded TrpRS stability. A prominent transition at intermediate temperatures in TrpRS thermal denaturation is molten globule formation. Combinatorial analysis of thermal melting transcends the protein landscape in four significant respects: (i) bioinformatic methods identify dynamic linkages from coordinates of multiple conformational states. (ii) Relative mutant melting temperatures, δTM, are proportional to free energy changes. (iii) Structural analysis of thermal melting implicates unexpected coupling between the D1 switch packing and regions of high local frustration. Those segments develop molten globular characteristics at the point of greatest complementarity to the chemical transition state and are the first TrpRS structures to melt. (iv) Residue F37 stabilizes both native and molten globular states; its higher-order interactions modify the relative intrinsic impacts of mutations to other D1 switch residues from those estimated for single point mutants. The D1 switch is a central component of an escapement mechanism essential to free energy transduction. These conclusions begin to relate the escapement mechanism to differential TrpRS conformational stabilities.

On the degree of dynamical packing in the Kepler multiplanet systems

ABSTRACT Current planet formation theories rely on initially compact orbital configurations undergoing a (possibly extended) phase of giant impacts following the dispersal of the dissipative protoplanetary disc. The orbital architectures of observed mature exoplanet systems have likely been strongly sculpted by chaotic dynamics, instabilities, and giant impacts. One possible signature of systems continually reshaped by instabilities and mergers is their dynamical packing. Early Kepler data showed that many multiplanet systems are maximally packed – placing an additional planet between an observed pair would make the system unstable. However, this result relied on placing the inserted planet in the most optimistic configuration for stability (e.g. circular orbits). While this would be appropriate in an ordered and dissipative picture of planet formation (i.e. planets dampen into their most stable configurations), we argue that this best-case scenario for stability is rarely realized due to the strongly chaotic nature of planet formation. Consequently, the degree of dynamical packing in multiplanet systems under a realistic formation model is likely significantly higher than previously realized. We examine the full Kepler multiplanet sample through this new lens, showing that $\sim 60{{-}}95~{{\ \rm per\ cent}}$ of Kepler multiplanet systems are strongly packed and that dynamical packing increases with multiplicity. This may be a signature of dynamical sculpting or of undetected planets, showing that dynamical packing is an important metric that can be incorporated into planet formation modelling or when searching for unseen planets.

Dynamic Bin Packing with Predictions

The MinUsageTime Dynamic Bin Packing (DBP) problem aims to minimize the accumulated bin usage time for packing a sequence of items into bins. It is often used to model job dispatching for optimizing the busy time of servers, where the items and bins match the jobs and servers respectively. It is known that the competitiveness of MinUsageTime DBP has tight bounds of Θ(√, log μ) and Θ(μ) in the clairvoyant and non-clairvoyant settings respectively, where μ is the max/min duration ratio of all items. In practice, the information about items' durations (i.e., job lengths) obtained via predictions is usually prone to errors. In this paper, we study the MinUsageTime DBP problem with predictions of items' durations. We find that an existing O(√ log μ)-competitive clairvoyant algorithm, if using predicted durations rather than real durations for packing, does not provide any bounded performance guarantee when the predictions are adversarially bad. We develop a new online algorithm with a competitive ratio of {O(∈2 √ log(∈2 μ)}, O(μ) (where ε is the maximum multiplicative error of prediction among all items), achieving O(√ log μ) consistency (competitiveness under perfect predictions where ∈ = 1) and O(μ) robustness (competitiveness under terrible predictions), both of which are asymptotically optimal.

Experimental Study on Water-Rock Interaction Characteristics of Unconsolidated Sandstone during CO2 Multicomponent Thermal Fluid Injection

According to the reservoir characteristics and the current situation of CO2 utilization during thermal recovery in an unconsolidated sandstone heavy oil reservoir, the mechanism and law of porosity and permeability change in an unconsolidated sandstone heavy oil reservoir during CO2+steam and CO2+steam+ sodium alpha-olefin sulfonate (AOS) injection were studied by combining a static monomineral water-rock reaction and a dynamic polymineral sand pack displacement experiment. In the static water-rock reaction between CO2 and monomineral of reservoir rock, the dissolution degree of monomineral at 200°C is greater than that at 100°C and 300°C, and the order of mineral dissolution is illite, montmorillonite, kaolinite, and quartz. Besides, the dissolution rate of single rock minerals decreased significantly in the system of CO2 with AOS. In the polymineral sand pack displacement experiment, the porosity gradually decreases by CO2 multicomponent thermal fluid, and the permeability first decreases and then increases by CO2 multicomponent thermal fluid, but the permeability change is only about 0.5% by CO2+steam+ AOS, which is mainly attributed to the adsorption of AOS on the rock surface, and it is confirmed in the infrared spectrum of unconsolidated sand after displacement. This also shows that CO2+steam+AOS can stabilize the rock skeleton structure of the reservoir and prevent the deterioration of heterogeneity in the subsequent development of thermal recovery of heavy oil reservoirs; therefore, the CO2 multicomponent thermal fluid with chemical agents can improve the damage of a single CO2 thermal fluid to the reservoir.

Numerical investigation on the droplet entrainment from gas sheared liquid film of hydroxyl-terminated polybutadiene/paraffin fuels

Hydroxyl-terminated polybutadiene (HTPB)/paraffin fuels applied in hybrid rocket motors enjoy high regression rates and excellent mechanical properties; however, the special microscopic structure of the fuels leads to more complex droplet entrainment mechanisms. The two-dimensional heterogeneous HTPB/paraffin fuels geometry model was established by a dynamic packing algorithm. Dynamic evolution characteristics of a liquid film disturbed by the interaction between HTPB and paraffin were investigated by numerical calculation, and the controlling mechanism of droplet entrainment in a hot shear flow was explored. The results showed that the motion of high-strength HTPB fragments in the liquid film distorted the structure of interfacial wave and generated uncommon rough waves with an averaged wavelength of up to 9.05 mm, for the fuel containing 60 wt. % paraffin. Additionally, there were three pathways of droplet entrainment, i.e., rupturing of paraffin-coated HTPB filaments, splashing at the crest of paraffin wavelets, and the breakup of paraffin ligaments. However, periodic interfacial wavelets were generated for the fuel with a 30 wt. % content of paraffin due to the damping of HTPB, and most of the entrained droplets were generated when the exposed molten paraffin flowed to both ends of the fuel slab. The diameter of entrained droplets was in the range of 0.02–0.74 mm, and it was shown to be positively correlated with the paraffin content, the temperature of shear flow, and the mass flux of shear flow.

Dynamic Bin Packing with Predictions

The MinUsageTime Dynamic Bin Packing (DBP) problem aims to minimize the accumulated bin usage time for packing a sequence of items into bins. It is often used to model job dispatching for optimizing the busy time of servers, where the items and bins match the jobs and servers respectively. It is known that the competitiveness of MinUsageTime DBP has tight bounds of Θ(√łog μ ) and Θ(μ) in the clairvoyant and non-clairvoyant settings respectively, where μ is the max/min duration ratio of all items. In practice, the information about the items' durations (i.e., job lengths) obtained via predictions is usually prone to errors. In this paper, we study the MinUsageTime DBP problem with predictions of the items' durations. We find that an existing O(√łog μ )-competitive clairvoyant algorithm, if using predicted durations rather than real durations for packing, does not provide any bounded performance guarantee when the predictions are adversarially bad. We develop a new online algorithm with a competitive ratio of minØ(ε^2 √łog(ε^2 μ) ), O(μ) (where ε is the maximum multiplicative error of prediction among all items), achieving O(√łog μ) consistency (competitiveness under perfect predictions where ε = 1) and O(μ) robustness (competitiveness under terrible predictions), both of which are asymptotically optimal.

TESS discovery of a super-Earth and two sub-Neptunes orbiting the bright, nearby, Sun-like star HD 22946

We report the Transiting Exoplanet Survey Satellite (TESS) discovery of a three-planet system around the bright Sun-like star HD 22946 (V ≈ 8.3 mag), also known as TIC 100990000, located 63 pc from Earth. The system was observed by TESS in Sectors 3, 4, 30, and 31 and two planet candidates, labeled TESS Objects of Interest (TOIs) 411.01 (planet c) and 411.02 (planet b), were identified on orbits of 9.57 and 4.04 days, respectively. In this work, we validate the two planets and recover an additional single transit-like signal in the light curve, which suggests the presence of a third transiting planet with a longer period of about 46 days. We assess the veracity of the TESS transit signals and use follow-up imaging and time-series photometry to rule out false-positive scenarios, including unresolved binary systems, nearby eclipsing binaries, and contamination of the light curves by background or foreground stars. Parallax measurements from Gaia Early Data Release 3 together with broad-band photometry and spectroscopic follow-up by the TESS FollowUp Observing Program (TFOP) allowed us to constrain the stellar parameters of TOI-411, including its radius of 1.157 ± 0.025 R⊙. Adopting this value, we determined the radii for the three exoplanet candidates and found that planet b is a super-Earth with a radius of 1.48 ± 0.06 R⊕, while planets c and d are sub-Neptunian planets with radii of 2.35 ± 0.08 R⊕ and 2.78 ± 0.13 R⊕ respectively. Using dynamical simulations, we assessed the stability of the system and evaluated the possibility of the presence of other undetected, non-transiting planets by investigating its dynamical packing. We find that the system is dynamically stable and potentially unpacked, with enough space to host at least one more planet between c and d. Finally, given that the star is bright and nearby, we discuss possibilities for detailed mass characterisation of its surrounding worlds and opportunities for the detection of their atmospheres with the James Webb Space Telescope.

Improving the weld lines mechanical properties by combining alternate dynamic packing and rapid heat cycle moulding

This is the first study that investigates the combined effect of alternate dynamic packing and rapid heat cycle moulding (RHCM) on the weld line mechanical properties of glass fibre reinforced thermoplastics. In conventional injection moulding, the outer layers rapidly solidify leaving a superficial weld line that do not recover when applying the dynamic packing. The results show that the thermal effect of RHCM reduces the thickness of the solidified skin layer and allow the alternate dynamic packing to reorient the fibres along the flow direction even in the outer layers. With reference to conventionally moulded tensile specimens made of 35% glass fibre reinforced polypropylene and having a front weld line, the proposed technological combination increased specimens’ strength and stiffness by 201% and 46%, respectively.

A Universal Method for Modeling and Characterizing Non-Circular Packing Systems Based on n-Point Correlation Functions.

A universal method for modeling and characterizing non-circular particles is developed. The n-point correlation functions (n = 1, 2 and 3) are efficiently computed with a GPU parallel computing procedure. An algorithm for dynamic packing of impenetrable non-circular particles is developed based on the fast estimation of overlap information using a one-point correlation function. The packing algorithm is independent of particle shape and proved to be reliable by examples of polygons and super-ellipses. In addition, penetrable packings are generated in an efficient and precise way. Using a two-point correlation function, these non-circular packs are accurately characterized and compared in terms of features such as penetrable and impenetrable, packing fraction and particle shape. In addition, three-point correlation functions are also illustrated and discussed.

The Investigation of Novel Dynamic Packing Technology for Injection Molded Part Quality Control and Its Production Stability by Using Real-Time PVT Control Method

Injection molding is an effective mass production process for plastic, partly due to a number of advantages such as complex shape moldability, material selectivity, and a rapid process cycle. However, highly labor-based conventional production restrains the development of the industry. Experience-driven molding setups are used to trial the mold process, and also for quality checking the molded part for mass production. There is no effective solution for maintaining the production stability and defect-free adjustment. This study aimed to establish scientific packing pressure setup technology to optimize the molded part quality and the stability of consecutive production. The dynamic packing pressure setup technology for molded part quality and the process stability were investigated. This not only achieves the optimization of the packing pressure setup, but the stabilization of quality in mass production. Four major qualities were discussed in this study including tensile strength, regional deviation on shrinkage, total shrinkage, and warpage. The qualities improved by up to 3.9%, 92.9%, 41.9%, and 9.2%, respectively. A series of pilot runs of 300 cycles for two packing pressure control methods were tested to investigate the stability of the qualities. Dynamic packing pressure control improved the weight replication by 54%, reduced total shrinkage by 23%, and improved the warpage by 12%.