Collision Probability Research Articles

An agile autonomous car driving assistance using hybrid optimization-based kernel support vector convolutional network

In robotic control systems, autonomous car driving is considered a complicated task. The conventional modular techniques necessitate precise localization, planning, and mapping procedures to provide safe driving. These requirements make autonomous car driving tasks computationally ineffective and sensitive to ecological changes. In recent times, the emergence of deep learning-based approaches in autonomous car driving systems provided promising solutions for complex vision task interpretation, localization, and environmental perception. But, they create distribution mismatch issues and require huge perilous interaction information to offer safe driving with the prediction of future collisions. Therefore, to overcome this issue, a novel Modified Kernel Support vector Convolutional based Hybrid Grasshopper Harris hawk (MKSC-HGH) approach is proposed. The proposed MKSC-HGH approach efficiently forecasts the uncertainties of agile autonomous car driving and guides proper navigation details of the track to avoid the possibility of collision with on-road obstacles and fences. This system inputs camera images captured through sensors, car speed, and manual driving data to analyze and predict safety control and probable collision. The prominent feature representing the ability of Modified Convolutional Neural Network (MCNN) and complex boundary encoding process of Kernel Support Vector Machine (KSVM) with hyperparameter tuning operation of Modified Grasshopper Optimization Algorithm based Improved Harris Hawk Optimization (MGOA-IHHO) algorithm made proposed system applicable to predict future states (ie. visual prediction, speed prediction, and collision prediction) more accurately. The efficiency of the proposed MKSC-HGH approach is investigated using evaluation measures namely completion time, average speed, top speed, and laps time. The simulation outcome shows the superiority of the proposed MKSC-HGH approach in predicting agile autonomous car driving over state of art techniques about task performance and sample efficiency.

An analytical method for predicting the structural response of ship side structures by bulbous bow in oblique collision scenarios

ABSTRACT As more and more ships sail on the sea, the probability of collision between ships also increases. At present, researches more on head-on ship collisions than oblique ship collisions. According to statistical data, the probability of oblique ship collision is higher than that of head-on ship collision, and oblique ship collision may cause a wider range of structural damage. Therefore, this paper studies the damage deformation of ship side structures in oblique collision scenarios. In this paper, a simplified analysis method is proposed to predict the structural response of the struck ship’s side structures by bulbous bow in oblique collision scenarios and the analytical results match well with the numerical simulation results, which verifies the accuracy of the simplified analysis method. The simplified analysis method can be used to assess the crashworthiness of ship side structures by bulbous bow in oblique collision scenarios.

Coarse-grained model simulation-guided localized DNA signal amplification probe for miRNA detection

DNA-based enzyme-free signal amplification strategies are widely employed to detect biomarkers in low abundance. To enhance signal amplification, localized DNA reaction units which increases molecular collision probability is commonly utilized. However, the current understanding of the structure-function relationships in localized DNA signal amplification probes is limited, leading to unsatisfied performance. In this study, we introduced a coarse-grained molecular model to simulate the dynamic behavior of two DNA reaction units within a DNA enzyme-free signal amplification circuit called Localized Catalytic Hairpin Assembly (LCHA). We investigated the impact of localized distance and flexibility on reaction performance. The most efficient LCHA probe guided by simulation exhibits sensitivity 28 times greater that of free CHA, with a detection limit of miR-21 reaching 16 pM, while the least effective LCHA probe demonstrated a modest improvement of only 7 times. We successfully employed the optimized probe to differentiate cancer cells from normal cells based on their miR-21 expression levels, showcasing its quantification ability. By elucidating the mechanistic insights and structure-function relationship in our work, we aim to contribute valuable information that can save users' time and reduce costs when designing localized DNA probes. With a comprehensive understanding of how the localization affects probe performance, researchers can now make more informed and efficient decisions during the design process. This work would find broad applications of DNA nanotechnology in biosensing, biocomputing, and bionic robots.

A Q-learning-based distributed queuing Mac protocol for Internet-of-Things networks

Many previous studies showed that some nodes should be in a sleeping state while the traffic is high. These nodes can wake up periodically to transmit data while they have data to transmit. The system throughput will be increased while each node can change between wake-up and sleeping states periodically. If a node can estimate the active rate and wake up at the optimal time, the collision probability decreases. This study proposes a Q-learning-based distributed queuing medium access control (QL-based DQMAC) protocol for Internet-of-Things (IoT) networks. In the proposed QL-based DQMAC, we derive the optimal number of contention IoT nodes. Each node calculates the active rate by itself through the Q-learning algorithm. Then, each node determines whether it will be active or in sleeping mode in the next contention period according to the active rate. Finding the optimal IoT nodes in each contention period decreases the probability of collision. The energy consumption due to the contention and delay for MAC contention is reduced owing to the lower number of contentions. Protocol comparison with other DQMAC protocols shows that the proposed QL-based DQMAC protocol achieves higher performance in IoT networks.

Strong Host-Guest Dependence on the Emissive Properties of MOF-5 and [Zn2(BTTB)(DMF)2•(H2O)3]n.

3D-[Zn4O(1,4-BDC)3•x(solvent)]n (MOF-5; BDC = 1,4-benzodicarboxylate) and 3D-[Zn2(BTTB)(DMF)2•(H2O)3]n (MOF-D; BTTB = 4,4',4″,4‴-benzene-1,2,4,5-tetrayltetrabenzoate) have been investigated by means of steady-state UV-visible and fluorescence and time-resolved emission spectroscopy, as a function of solvent and power of the excitation irradiation. The low-temperature X-ray structures (173 K) were permitted to locate solvent molecules (here H2O) in the lattice. They were found distributed in the middle in the voids with no evidence of specific interactions (H-bond, coulombic, and dipole-dipole) with the framework. The fluorescence decays of the ligands (ππ* excited state), τF, for the host-guest composites MOF-5@solvent and MOF-D@solvent (solvent = air, MeCN, EtCN, MeOH, EtOH, and DMF) were found bi-exponential (short τF1 (ps), and long τF2 (ns)) with one important feature: upon cooling from 298 to 77 K, MOF-5's τF1 decreases and τF2 increases, while the opposite trend is generally observed in MOF-D. The low values for τF1 (ps) in MOF-5 are associated with the augmented probability of solvent-ligand collisions leading to nonradiative deactivation, which upon cooling to 77 K increases further as the scaffolding contracts. The augmentation in τF2 is readily associated with the increased rigidity of the ligands that are not submitted to this effect (at the surface of the MOF and as pendent groups). For the low emitter MOF-D, the reversed situation is noted but not as clearly due to the uncertainties in the data. Upon increasing the excitation flux, the fluorescence intensity increases linearly with the laser power indicating the absence of singlet-singlet annihilation, inferring the absence of efficient exciton migration. This observation is explained by the small absorptivity coefficients, which leads to a small J spectral overlap between absorption and fluorescence according to the Forster and Dexter theories, and consequently, a small rate for energy migration. This conclusion drastically changes the perception of the photocatalytic mechanism of MOF-5 and other MOFs exhibiting similar absorption features (i.e., no antenna effect).

Experimental study on the removal of submicron droplets by fibrous filter media in a sound field

The acoustic agglomeration technology is proposed as pretreatment to effectively reduce the concentration of particles produced in the industrial process, thus to improve the filtration efficiency of subsequent filter devices. However, the removal of submicron droplets by sound waves has not yet received attention. In this paper, a new method is proposed for high-efficient filtration of submicron droplets based on sound waves. According to the entrainment mechanism of sound waves on the submicron droplets, a sound field is introduced in the filtration system to enhance the collision probability between the droplets and the fibers in filter materials. The effects of sound pressure level (SPL) and sound frequency on the droplet removal were experimentally investigated at different filtration gas velocities. The results show that there is no shift for the upstream particle size distribution, however, the downstream droplet concentration decreases when the sound field is introduced. The effect of the sound field on filtration performance is determined by the vibration amplitude and the vibration period of the droplets. In the SPL range of 130–145 dB, the improvement of the filtration performance is better with the increase of the SPL for a fixed sound frequency. In the frequency range of 500–900 Hz, the optimal filtration performance of the filter material is obtained at 700 Hz. When the filtration gas velocity is between 0.2 and 0.4 m/s, the improvement of the filtration performance gradually weakens as the filtration velocity increases. Furthermore, the reduction of the downstream droplet concentration is more significant for low-efficient filters or those with fewer layers under the same condition in the sound field.

A race against the clock: Constraining the timing of cometary bombardment relative to Earth’s growth

Comets are considered a potential source of inner solar system volatiles, but the timing of this delivery relative to that of Earth’s accretion is still poorly understood. Measurements of xenon isotopes in comet 67P/Churyumov-Gerasimenko revealed that comets partly contributed to the Earth’s atmosphere. However, there is no conclusive evidence of a significant cometary component in the Earth’s mantle. These geochemical constraints would favor a contribution of comets mainly occurring after the last stages of Earth’s formation. Here, we evaluate whether dynamical simulations satisfy these constraints in the context of an Early Instability model. We perform N-body simulations of the solar system’s dynamic evolution considering an outer disk of 10000 comets, different initial conditions for the inner solar system and assuming that the giant planet instability happened within ≃10 million years of the start of planet formation. Out of 30 simulations, 13 meet a list of criteria for success. We calculate the probability of collision between comets and Earth analogs component embryos through time and estimate the total cometary mass accreted in Earth analogs as a function of time. We determine that the cumulative cometary mass accreted by the Earth analogs during the first 100 million years ranges between 4 ×1021 and 5 ×1024 g. While our results are in excellent agreement with geochemical constraints, we also demonstrate that the contribution of comets on Earth might have been delayed with respect to the timing of the instability, due to a stochastic component of the bombardment. More importantly, we show that it is possible that enough cometary mass has been brought to Earth after it had finished forming so that the xenon constraint is not necessarily in conflict with an Early Instability scenario. Indeed, 2 of the 13 successful simulations provide enough comet delivery after a last giant impact happening later than 30 Myr. However, it appears very likely that a few comets were delivered to Earth early in its accretion history, thus contributing to the mantle’s budget. Finally, we compare the delivery of cometary material on Earth to Venus and Mars. These results emphasize the stochastic nature of the cometary bombardment in the inner solar system.

Membrane-assisted reactive crystallisation for the recovery of dissolved phosphorus in vivianite form from liquid effluents

Novel membrane crystallisation processes resolve the mixing challenge on conventional crystallisers, by providing fixed interfacial area over which supersaturation is controlled for nucleation. Moreover, the membrane surface is thought to reduce interfacial energy and encourage micromixing. In this regard, a novel membraneassisted reactive crystallisation (MARC) process was used in this work for the dissolved phosphorous recovery in form of vivianite crystals from a phosphate-rich solution by means of the dosing of iron (II). To characterise the role of the boundary layer in controlling nucleation, a batch lab-scale system was used for the crystallization tests, and different hydraulic conditions (Reynolds ranging from 105 to 395) and polymeric membranes were tested. The crystallisation process was influenced by the hydraulic conditions, in which a low liquid velocity led to a lower induction time and vivianite supersaturation, and therefore, higher nucleation rates. Membrane properties were characterised to establish their role in the modification of the critical free energy requirement for nucleation, and for the promotion of micromixing, as possible factors that can be used to modify nucleation kinetics. As result, the bulk induction time tended to decrease with the increase in membrane hydrophobicity, roughness, pore size and porosity. Spherical vivianite nanoparticles were always synthesised with a mean size around 35 nm and a narrow distribution independently of the hydraulic conditions and membrane used. Finally, the crystallisation kinetic conformed to a diffusion-dependent nucleation mechanism, in which higher residence times for mixing increased the ion collision probability for nucleation. Importantly, this study demonstrated that MARC is an attractive prospect for nutrient recovery from wastewaters where crystal nucleation can be easily controlled by setting the operational conditions and membrane properties, eliciting considerable process intensification over existing conventional crystalliser.

Dynamic characteristic analysis of riser considering drilling pipe contact collision

As important equipment for deep-sea oil and gas development, risers are subjected not only to external ocean environmental loads but also to internal drilling pipe contact collisions. In this study, a dynamic analysis model of the riser system considering the contact collision of drill pipe in drilling operation is established. Moreover, the contact stiffness method is used to describe the contact collision force between the drill pipe and riser. The model is discretized using the finite element method and solved using the Newmark-β method. The dynamic characteristics of the riser under the action of the marine environment and drilling conditions are analyzed. In addition, the corresponding safety protection measures are put forward for the contact collision between the drill pipe and riser. The results show that the collision force between drill pipe and riser is the largest in the initial period, and the contact form is gradually stable. The distribution of the collision force is basically consistent with that of the bending moment, and the collision force and collision probability are the largest near the water surface and at the flexible joint of the bottom end, which is easy to cause column wear failure. The collision force and collision probability of the drill pipe and riser increase with the increase of platform offset and sea current velocity but decrease with the increase of top tension and bit pressure. The increase of the top tension and the increase of the platform offset will reduce the contact area between the drill pipe and the riser.

Differences in Neurocognitive Functions Between Healthy Controls and Anterior Cruciate Ligament-Reconstructed Male Athletes Who Passed or Failed Return to Sport Criteria: A Preliminary Study.

Only 55% of anterior cruciate ligament-reconstructed (ACLR) athletes return to competitive sports. This brings into question the usefulness of current return to sport (RTS) criteria. High cognitive demand of sport environment clarifies the value of incorporating neurocognitive tests when making decisions regarding the time of RTS. This preliminary study aimed to compare the neurocognitive functions between healthy controls and ACLR male athletes who passed or failed RTS criteria. A total of 45 male football players, including 15 ACLR who passed RTS criteria, 15 ACLR who did not pass, and 15 healthy controls participated in this cross-sectional study. The Cambridge Neuropsychological Test Automated Battery was used to measure a battery of neurocognitive tasks, including speed of response, sustained attention, working memory, cognitive flexibility, and response inhibition. The results revealed that compared with both the ACLR-passed and healthy groups, the ACLR-failed group showed greater values of 5-choice movement time (P = .02, P = .01, respectively) but lower values of stop signal reaction time (P = .03, P = .001, respectively) and proportion of successful stops variables (P = .02). In addition, compared with the healthy group, both the ACLR-failed and ACLR-passed groups indicated greater values in between errors (P < .001, P = .008, respectively) and reaction latency variables (P = .002, P = .01, respectively) but lower values of A' (P < .001, P = .007, respectively), probability of hit (P < .001, P = .03, respectively), and percent correct trials variables (P = .006, P = .02, respectively). Our findings indicated deficits in neurocognitive functions in ACLR male athletes. In addition, poor performance in sustained attention, working memory, and cognitive flexibility measures observed in the ACLR-passed group highlighted the necessity for using a multimodal approach via implementation of neurocognitive measures in conjunction with the functional and muscular assessments when making RTS decisions.

Novel Access Methods in Cellular Networks Based on the Analog Bloom Filter

In cellular networks, the User Equipment (UE) often needs to send control information to the base station. For example, to initiate a connection, a UE transmits a Zadoff-Chu (ZC) sequence on a channel called PRACH, where the sequence is randomly selected from up to 64 sequences. Also, a connected UE may send the Scheduling Request (SR) bit on a channel called PUCCH to start an uplink data transmission. In this paper, novel access methods, namely, ABF PRACH and ABF SR, are proposed based on the Analog Bloom Filter (ABF). With ABF PRACH, a UE transmits a pattern, which consists of multiple ZC sequences. The performance is improved, because the number of patterns, currently 2304, is much larger than the number of sequences, resulting in a much lower collision probability. Similarly, with ABF SR, each connected UE is assigned a unique pattern. The system capacity is improved, because the resource is shared by many UEs, instead of dedicated to individual UEs. Both ABF PRACH and ABF SR have been demonstrated in real-world experiments. Simulations show that ABF PRACH significantly outperforms the existing PRACH. Also, ABR SR achieves a 2.52-fold increase of capacity, while maintaining very low error ratios.

Convex risk-bounded continuous-time trajectory planning and tube design in uncertain nonconvex environments

In this paper, we address the trajectory planning problem in uncertain nonconvex static and dynamic environments that contain obstacles with probabilistic location, size, and geometry. To address this problem, we provide a risk-bounded trajectory planning method that looks for continuous-time trajectories with guaranteed bounded risk over the planning time horizon. Risk is defined as the probability of collision with uncertain obstacles. Existing approaches to address risk-bounded trajectory planning problems either are limited to Gaussian uncertainties and convex obstacles or rely on sampling-based methods that need uncertainty samples and time discretization. To address the risk-bounded trajectory planning problem, we leverage the notion of risk contours to transform the risk-bounded planning problem into a deterministic optimization problem. Risk contours are the set of all points in the uncertain environment with guaranteed bounded risk. The obtained deterministic optimization is, in general, nonlinear and nonconvex time-varying optimization. We provide convex methods based on sum-of-squares optimization to efficiently solve the obtained nonconvex time-varying optimization problem and obtain the continuous-time risk-bounded trajectories without time discretization. The provided approach deals with arbitrary (and known) probabilistic uncertainties, nonconvex and nonlinear, static and dynamic obstacles, and is suitable for online trajectory planning problems. In addition, we provide convex methods based on sum-of-squares optimization to build the max-sized tube with respect to its parameterization along the trajectory so that any state inside the tube is guaranteed to have bounded risk.

Improvements in Classical Proportional Navigation Guidance Using Fuzzy Logic

The performance of classical Proportional Navigation guidance is limited against highly maneuvering targets and in presence of measurements noise resulting into large miss distances and lower hit probability. Also, the advanced Augmented PN guidance technique requires target state estimation. In this paper, fuzzy logic has been used to implement PN guidance and Membership Functions of fuzzy logic has been tuned using genetic algorithm. The proposed Fuzzy Based PN (FBPN) guidance gives superior performance than PN and APN in terms of lower miss distance, higher hit ratio and better ability to handle measurement noise at all target attack aspects. Deterministic simulations have proved the superior performance and robustness of proposed scheme for various conditions such as step target maneuver upto 9g, weaving maneuver and presence of measurement noise. Further, Monte Carlo simulations have proved that proposed scheme enhances interception performance in realistic scenarios by improving the hit ratio upto 48% and rms miss distance upto 41%. Limitations of APN scheme in terms of target state estimation is also mitigated in the proposed guidance scheme. Finally, global asymptotic stability of fuzzy homing guidance loop is proved using circle criterion.

Conceptual Design of Artificial Intelligence Powered Automated Space Debris Remover (ASDR)

The focus of this research article is the application of AI technology for space debris removal. With the increasing number of non-functional artificial objects orbiting Earth, commonly known as space debris or junk, the need to address this issue has become crucial. Currently, there are over 200,000 such objects posing a significant threat to operational satellites and space missions. To mitigate this risk, we propose the utilization of AI-trained robotic systems to safely de-orbit space debris, thereby reducing the probability of collisions and potential damage. This research paper introduces the concept of employing AI and robotics technology to achieve this objective, with a specific emphasis on targeting Point Nemo as a designated disposal location. By harnessing the capabilities of AI, we can effectively identify and track space debris, enabling the robotic system to navigate and remove debris from critical orbital paths safely. Furthermore, the re-entry trajectory directed towards Point Nemo ensures that approximately 95% of the debris will burn up upon atmospheric re-entry, thus minimizing any potential risks to human life and property.

Experimental and numerical analysis on electrolytic bubble group dynamics in the aluminum electrolysis process using the slotted anode

The CuSO4 aqueous solution electrolysis experiment is conducted to investigate the electrical bubble dynamics using the slotted anode to reveal the gas removal mechanism. A three-dimensional transient mathematical model coupled discrete phase model (DPM) − discrete-continuum transition model (DCTM) − volume of fluid (VOF) method is developed to track the dispersed bubble trajectory, bridge the dispersed bubble to continuous gas, and resolve the deformed bubble surface, respectively. The slotted anode decreases the bubble diameter compared with the traditional anode because the slot shortens the bubble motion distance to decrease the bubble residence time. The slot width smaller than the detached bubble diameter can limit the bubble deformation. Increasing current plays a dual role in bubble motion in the experiment: it accelerates the bubble coalescence process but decreases the bubble collision probability. The longitudinal slot is more conducive to reducing the maximum bubble coverage and increasing the bubble release frequency than the transverse slot.

Stellar Collisions in Galactic Nuclei: Impact on Destructive Events Near a Supermassive Black Hole

The centers of galaxies host both a supermassive black hole and a dense stellar cluster. Such an environment should lead to stellar collisions, possibly at very high velocities so that the total energy involved is of the same order as supernova explosions. We present a simplified numerical analysis of the destructive stellar collision rate in a cluster similar to that of the Milky Way. The analysis includes an effective average two-body relaxation Monte Carlo scheme and general relativistic effects, as used by Sari & Fargione, to which we added explicit tracking of local probabilities for stellar collisions. We also consider stars which are injected into the stellar cluster after being disrupted from a binary system by the supermassive black hole. Such stars are captured in the vicinity of the black hole and enhance the expected collision rate. In our results we examine the rate and energetic distribution function of high-velocity stellar collisions, and compare them self-consistently with the other destructive processes which occur in the galactic center, namely tidal disruptions and extreme mass ratio inspirals.

Prediction-based channel assignment for minimizing channel switching in mobile WBANs

As the world’s population rises, the healthcare system experiences significant changes. Wireless body area network (WBAN) is an emerging technology that has considerable impact on medical and non-medical applications. However, two crucial challenges in WBANs are interference minimization and channel assignment. High interference may increase collision probability, transmission delay, and energy consumption. Multichannel schemes are proposed to reduce the data transmission latency and improve the system throughput by allowing simultaneous transmission of sensors in coexisting WBANs. When WBAN users move, they need to switch the channels frequently to avoid potential channel conflicts and to maintain the Quality of Service (QoS). However, frequent switching may raise energy consumption and aggravate delay. Existing multichannel assignment schemes failed to perform well in highly dynamic and densely deployed WBANs environments. In contrast to existing studies, this paper proposes a Prediction-based Channel Assignment (PCA) algorithm that selects the channels for WBANs to remain valid for future time instances and thus minimizes the delay and number of channel switches for dynamic and coexisting WBANs. When a WBAN needs to switch a channel, the proposed method predicts the future neighbors of that WBAN based on its history. It explores the channel information of present and future neighbors to select a suitable channel with higher resilience in a dynamic environment. Thus, our algorithm minimizes channel interference by avoiding unnecessary channel switching. We have used machine learning algorithms to predict the future neighbors of a WBAN. Experiment results show that the proposed algorithm performs better than an existing algorithm and random channel assignment in delay and throughput.

The Atomic Observation of the Structural Change Process in Pt Networks in Air Using Environmental Cell Scanning Transmission Electron Microscopy.

The structural change in Pt networks composed of multiple chain connections among grains was observed in air at 1 atm using atomic-resolution environmental cell scanning transmission electron microscopy. An aberration-corrected incident electron probe with a wide convergence angle made it possible to increase the depth resolution that contributes to enhancing the signal-to-noise ratio of Pt network samples in air in an environmental cell, resulting in the achievement of atomic-resolution imaging. The exposure of the Pt networks to gas molecules under Brownian motion, stimulated by electron beams in the air, increases the collision probability between gas molecules and Pt networks, and the Pt networks are more intensely stressed from all directions than in a situation without electron irradiation. By increasing the electron beam dose rate, the structural change of the Pt networks became significant. Dynamic observation on an atomic scale suggested that the structural change of the networks was not attributed to the surface atomic-diffusion-induced step motion but mainly caused by the movement and deformation of unstable grains and grain boundaries. The oxidized surface layers may be one of the factors hindering the surface atomic step motion, mitigating the change in the size of the grains and grain boundaries.

Radial mixing and segregation of binary density ellipsoids in a rotating drum

In this paper, the Discrete Element Method (DEM) is applied to investigate the radial mixing and segregation of a binary mixture of ellipsoids with different densities in a rotating drum. The ellipsoidal particles are constructed with multi-sphere model, and the periodic boundary condition is adopted. The influences of aspect ratio and density ratio on the mixing quality and final segregation extent are examined. Simulation results show that, light particles are inclined to occupy at the periphery of the granular bed, whereas heavy ones concentrate in the center area. As particle aspect ratio deviates from unity, i.e. oblate or prolate shape, the mixing index is increased and final segregation degree is decreased. It is discovered that convective mixing is predominant over diffusion for any given particle shape (oblate, spherical, prolate). The prolate particles (AR=4.0) reveal the highest compactness of a binary mixture system in the rotating drum. Particle translation is the main movement mode and ellipsoids are more easily to rotate. Particle shape affects collision probability and strength, and ellipsoidal particles need more energy to be driven. The reduction of density ratio of light to heavy particles does inevitably contribute to a greater segregation degree. The results also indicate that the initial states of binary mixtures do not affect the final segregation patterns.

Solid state cationization reaction of microporous starch with betaine hydrochloride under repeated heating/cooling cycles: Design of a green approach for corn starch modification

In this research, the cationization process of microporous starch with betaine hydrochloride (BHC) in the presence of H3PO4 (as a catalyst) under heating/cooling cycles was reported for the first time. Granular microporous starch was initially prepared from normal corn starch (NS) through amyloglucosidase treatment. Then, solid state cationization reaction of microporous starch (MS) with betaine hydrochloride (BHC) was performed under repeated dry-heat modification. The cationic microporous starch showed higher substitution degree (0.031) and reaction efficiency (89.1 %) in comparison with cationic starch based on NS (0.021, 60.3 %), which this can be attributed to the increased probability of effective collision between BHC molecules and starch granules after enzymatic treatment. The analysis of cationic starches by FTIR and 13C NMR confirmed the presence of cationic functional groups on starch chains. Further examinations on the modified starches by single and dual treatments were accomplished with respect to morphology, particle size distribution, X-ray powder diffraction (XRD), colour parameters, zeta potential, amylose content, viscosity, solubility, and swelling power. The greenness of the suggested dual treatment (score: 82) in this work was evaluated and compared to a conventional method reported in literature (score: 67) on the preparation of cationic starches.