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Edge computing has become quintessential in commercial, healthcare, and industrial applications. It enables real-time data processing at the edge device, thus reducing the data traffic to the cloud and increasing the processing time efficiency. As an edge device, modern System-on-Chips (SoCs) provide scalability, security, and development in an integrated platform. Intellectual Property (IP) core reuse is a boon in SoCs that bridges the gap between integrated circuit design and fabrication. Such edge devices modeled by vendors are bound to ensure high security to avoid piracy. The proposed architecture provides a two-step authentication utilizing a Finite State Machine (FSM) with a secured key obtained from the newly structured Physical Unclonable Function (PUF) within the same edge device, with the primary goal of verifying several heterogeneous IPs to achieve the least power and energy. Two PUF designs, Anderson Arbiter PUF (AA-PUF) and Balanced AA-PUF, have been proposed for two different placements taking advantage of SoC-based architecture. The PUF characteristics have been experimentally validated with and without majority voting and demonstrate their proximity close to the desired value in ZedBoard. The proposed design is a strong PUF with less than 15% area overhead and power dissipation of 1.982 W for a 64-bit response. The experimental validation has evaluated that the power and energy consumptions are 2.56 W and 2.17 J for 52 heterogeneous IPs. [ABSTRACT FROM AUTHOR]

Flood-susceptibility mapping (FSM) is crucial for effective flood prediction and disaster prevention. Traditional methods of modeling flood vulnerability, such as the Analytical Hierarchy Process (AHP), require weights defined by experts, while machine-learning and deep-learning approaches require extensive datasets. Remote sensing is also limited by the availability of images and weather conditions. We propose a new hybrid strategy integrating deep learning with the HEC–HMS and HEC–RAS physical models to overcome these challenges. In this study, we introduce a Weighted Residual U-Net (W-Res-U-Net) model based on the target of the HEC–HMS and RAS physical simulation without disregarding ground truth points by using two loss functions simultaneously. The W-Res-U-Net was trained on eight sub-basins and tested on five others, demonstrating superior performance with a sensitivity of 71.16%, specificity of 91.14%, and area under the curve (AUC) of 92.95% when validated against physical simulations, as well as a sensitivity of 88.89%, specificity of 93.07%, and AUC of 95.87% when validated against ground truth points. Incorporating a "Sigmoid Focal Loss" function and a dual-loss function improved the realism and performance of the model, achieving higher sensitivity, specificity, and AUC than HEC–RAS alone. This hybrid approach significantly enhances the FSM model, especially with limited real-world data. [ABSTRACT FROM AUTHOR]

Video games are a means of entertainment for everyone, from children to adults. The genre of games now is also very diverse, ranging from adventure, puzzles to storytelling, and even many folk stories have been made into video games by several developers in Indonesia. Starting from folk tales with horror themes such as kuntilanak, legends such as cucumber mas, to folk tales that rarely sound like golden oranges. The folklore video game of buah jeruk emas is a video game that tells of a king who gets a whisper from the gods to get golden oranges. The king then held a competition to get the golden orange fruit. The player must be able to take the golden orange fruit from the enemy in the form of a Non Playable Character (NPC) who will chase the player. In making NPCs, algorithms are used to help play video games. Therefore, the author wants to apply the A * algorithm in the game of golden oranges so that npc can catch up to players according to the planned system. The main method used is A * and then the addition of the FSM method for other methods. The golden orange fruit is a video game using the A * algorithm and the FSM method after testing it can be concluded that it is enough to make the game run. With the results according to the planned system.

Knowledge of aquifer parameters is essential for the management of groundwater resources. Parameters such as porosity and specific yield are among the basic features used to describe the hydrogeological conditions of a region. This study compares the electromagnetic method with geoelectric sounding. The data collection was carried out through a field survey and is used to study and estimate the values of porosity and specific yield of the karst aquifer that feeds five springs: Famaseb (Sp1), Faresban (Sp2), Giyan (Sp3), Ghale Baroodab (Sp4), and Gonbad kabood (Sp5). All these springs are located in the Nahavand Plain, Hamadan Province, west of Iran. Fifteen (15) soundings were obtained upstream of each spring and were used to analyze the results, quantitative and qualitative interpretation of geoelectrical data, logs of subsurface layers, and ranges of true resistivities and their electromagnetic frequencies were determined. The value of the true resistivity was calculated for the saturated and unsaturated layer of each spring, the results were compared with the electromagnetic frequencies, which showed that the results of the two methods used were almost similar. Porosity and specific yield were calculated using Archie's law. It is found that the Faresban spring (Sp2) has maximum porosity of 55% and a specific yield of 0.48 and in contrast to the lowest value of parameters mentioned in the Ghale Baroodab spring (Sp3, porosity 26% and specific yield 0.18). All the estimated values are compatible with the discharge of springs measured in the field and consistent with the geological conditions of the study area. [ABSTRACT FROM AUTHOR]

Hot stamping of high-strength steel plays an increasingly important role as the demand for automotive lightweighting increases. However, the existing hot stamping process faces challenges such as a lack of digital monitoring, limited monitoring scope, unintuitive production data, and untimely analysis of production events. This paper proposes a framework for a hot stamping production monitoring system based on digital twin technology. By exploring key technologies, including finite state machine (FSM) modeling of the production process, collection, and storage of multi-source data, a digital twin monitoring system for the hot stamping line was developed by combining the data with virtual 3D equipment for multi-dimensional information integration. The system can visualize production information from multiple dimensions and reproduce the production process to analyze production events. Finally, the feasibility and effectiveness of the digital twin system were verified through real-world scenarios, providing valuable insights for hot stamping production process monitoring. [ABSTRACT FROM AUTHOR]

The challenges resulting from rapid economic growth, urbanization, and increased motorization in developing nations necessitate a comprehensive and sustainable approach to urban public transport planning. While sustainable urban public transport (SUPT) planning offers a solution, the complexity of choosing suitable policy measure options remains a challenge. This study first introduces a decision support framework (DSF) that integrates the sustainable urban public transport manual (SUPTM) adopted for generating the potential SUPT policy measure options, the KonSULT knowledge base applied for providing the performance scores of each measure option for all determined criteria, and the HMADM (including FAHP, FSM, and TOPSIS) technique to create, rank, and select SUPT policy measure options tailored to medium-sized urban areas in developing nations. A case study of Khon Kaen City, Thailand, illustrates the practical application of the framework, resulting in a set of 31 (91.2%) out of the total of 34 ranked policy measure options. Comparing these prioritizations with the city's existing plan reveals a substantial agreement, which suggests the potential applicability of the DSF. Overall, the DSF marks a significant advancement in SUPT planning, which is crucial for shaping efficient, equitable, and environmentally conscious urban mobility in developing countries, which are undergoing transformative change. [ABSTRACT FROM AUTHOR]

Flood-susceptibility mapping (FSM) is crucial for effective flood prediction and disaster prevention. Traditional methods of modeling flood vulnerability, such as the Analytical Hierarchy Process (AHP), require weights defined by experts, while machine-learning and deep-learning approaches require extensive datasets. Remote sensing is also limited by the availability of images and weather conditions. We propose a new hybrid strategy integrating deep learning with the HEC–HMS and HEC–RAS physical models to overcome these challenges. In this study, we introduce a Weighted Residual U-Net (W-Res-U-Net) model based on the target of the HEC–HMS and RAS physical simulation without disregarding ground truth points by using two loss functions simultaneously. The W-Res-U-Net was trained on eight sub-basins and tested on five others, demonstrating superior performance with a sensitivity of 71.16%, specificity of 91.14%, and area under the curve (AUC) of 92.95% when validated against physical simulations, as well as a sensitivity of 88.89%, specificity of 93.07%, and AUC of 95.87% when validated against ground truth points. Incorporating a “Sigmoid Focal Loss” function and a dual-loss function improved the realism and performance of the model, achieving higher sensitivity, specificity, and AUC than HEC–RAS alone. This hybrid approach significantly enhances the FSM model, especially with limited real-world data.

This paper presents a state-of-the-art overview of fine beam steering mechanisms for free-space optical communication on satellites. Precise beam pointing is a critical task for the successful operation of free-space optical communication systems. Based on past research and ongoing projects, the use of fast steering mirrors (FSMs) is still the most popular solution for free-space optical communication applications. Although a variety of commercial off-the-shelf (COTS) FSM solutions exist, there is limited publicly available data on these solutions in the space environment. Three main actuation principles are considered (electro-static force actuated, magnetic force actuated, piezo-effect actuated) and reviewed using available data from past space missions. The article describes the most important criteria in the choice of a fine beam steering solution for free-space optical communication in space. [ABSTRACT FROM AUTHOR]

The process control-oriented threat, which can exploit OT (Operational Technology) vulnerabilities to forcibly insert abnormal control commands or status information, has become one of the most devastating cyber attacks in industrial automation control. To effectively detect this threat, this paper proposes one functional patternrelated anomaly detection approach, which skillfully collaborates the BinSeg (Binary Segmentation) algorithm with FSM (Finite State Machine) to identify anomalies between measuring data and control data. By detecting the change points of measuring data, the BinSeg algorithm is introduced to generate some initial sequence segments, which can be further classified and merged into different functional patterns due to their backward difference means and lengths. After analyzing the pattern association according to the Bayesian network, one functional state transition model based on FSM, which accurately describes the whole control and monitoring process, is constructed as one feasible detection engine. Finally, we use the typical SWaT (SecureWater Treatment) dataset to evaluate theproposedapproach, and the experimental results showthat: for one thing, comparedwithother changepoint detection approaches, the BinSeg algorithm can be more suitable for the optimal sequence segmentation of measuring data due to its highest detection accuracy and least consuming time; for another, the proposed approach exhibits relatively excellent detection ability, because the average detection precision, recall rate and F1-score to identify 10 different attacks can reach 0.872, 0.982 and 0.896, respectively. [ABSTRACT FROM AUTHOR]

A decision support model (DSM) involving a combination of five different prediction models for the environmental effects of transport and the powerful HMADM approach was introduced for the first time to assess the multiple criteria environmental effects of transport in an urban road network of the Khon Kaen Metropolitan Municipality (KKMM) in Khon Kaen City, Thailand. Five mathematical models were adopted to quantify the CO2 emissions (CO2Es), PM2.5 concentration (PM2.5C), CO concentrations (COCs), noise levels (NOLs), and pedestrian accident risk (PAR) values of all road segments in the study area. The FAHP, FSM, and TOPSIS were integrated into the HMADM to estimate the composite transport environmental effect scores (CTEESs) of each road segment. The FAHP was applied to determine the relative weights of each environmental criterion for three land use types, and the FSM was utilized to transform linguistic (fuzzy) scores into numerical (crisp) scores. Both the FAHP and FSM are principally used to deal with uncertain, incomplete, and ambiguous (fuzzy) information that appears during decision-making processes. Finally, TOPSIS was used to estimate the CTEESs of each road segment. An integrated DSM was applied to comprehend and evaluate each individual environmental criterion and the combined environmental criteria for each road segment in the study area. The DSM was employed to rank the problematic locations of all road segments. For instance, the ranking of the top 12 road segments with the greatest CTEESs was 75, 80, 48, 89, 76, 5, 64, 59, 60, 16, 65, and 62. In addition, this DSM can also be used to identify the possible causes of such locations and allocate limited government budgets for the implementation of appropriate remedial measures for resolving such environmental problems due to transport in an urban road network in the study area. [ABSTRACT FROM AUTHOR]

Conventional Maximum Power Point Tracking (MPPT) controllers in photovoltaic (PV) systems are seen to achieve tracking speeds in range of milliseconds. Power-electronic circuits in these systems many-a-time demand faster control actions in microseconds, as they operate at high frequencies, and also, a delay in control action would lead to a corresponding power-loss. Hence, an MPPT controller delivering such fast tracking speeds would improve overall system performance. In this work, an Field Programmable Gate Array (FPGA) based Statechart Controller is developed to perform MPPT control of the PV system. The developed Statechart Controller is tested using software-in-the-loop simulation(SILS) and results are presented. With inputs from a programmable logic controller emulating PV characteristic curves, the Statechart Controller is then deployed in a target FPGA. A comparison between performance with conventional MPPT controller and Statechart Controller is presented and results indicate that the latter is more effective in terms of tracking speeds, determinism, and modularity. [ABSTRACT FROM AUTHOR]

Inferring a functional specification from an existing digital design is a challenge that is suitable with reverse-engineering methods. One of the most widely used functional specification formats is a finite state machine (FSM). This article studies the possibility of blind passive specification mining for a digital device, where the device is treated as a "black box". The presented approach treats an input and output signal waveform as the transition graph of an incomplete deterministic FSM and learns the FSM through FSM minimization. It employs a Boolean satisfiability problem (SAT) solver to find a minimal FSM that complies with observed object behavior. The known approach to identifying state machines in discrete event systems is adapted to operate with variables in the form of coloring and transition tables. The developed implementation produces a synthesizable specification in hardware description language (HDL) and a state diagram in unified modeling language (UML). The proposed approach for inferring an FSM from a waveform trace can serve as a supplementary tool during reverse engineering to provide developers with meaningful insight regarding the analyzed device. The presented case study defines metrics of successful FSM inference and applies them to a synthetic FSM and a real-world example FSM to demonstrate the applicability of the approach. [ABSTRACT FROM AUTHOR]

Wavefront distortion caused by atmospheric turbulence can be described as different types of aberrations, such as piston, tilt, defocusing, astigmatism, coma and so on. The operation of dual deformable mirrors can have mutual coupling effects, which affect the correction effect of wavefront distortion. This study combines a fast-steering mirror (FSM) and a deformable mirror (DM) to form a dual-deformable-mirrors wavefront correction system, and proposes a decoupling algorithm that can correct any specified aberration. In this decoupling algorithm, both the FSM and the DM are controlled using the mode method, and the specific corrected aberrations are obtained based on a limited matrix. The compensation ability of the DM is directly characterized by the mode coefficients of the aberrations, which can achieve independent correction of any order of aberrations and effectively reduce the coupling effect of the dual-deformable-mirrors wavefront correction system. An adaptive optical dual-deformable-mirrors wavefront correction system experiment was built to verify the decoupling algorithm. When the DM corrects the 3rd-, 10th-, and 25th-order aberrations, and the FSM only corrects the 1st- and 2nd-order aberrations, the coupling coefficients are approximately 1.17 × 1 0 − 3 , 1.814 × 1 0 − 2 and 7.81 × 1 0 − 3 , respectively, and their magnitude reaches 10−2 and below 10−2, respectively. The experimental results show that the decoupling algorithm can effectively suppress the coupling effect between the FSM and the DM. [ABSTRACT FROM AUTHOR]

Piezoelectric fast steering mirror (PZT FSM) is the core component of the fine tracking system for space laser communication, and its actuator is a piezoelectric ceramic. Consequently, there is a hysteretic nonlinear disturbance throughout the entire range of the FSM's steering. To enhance the fine tracking system's performance, this paper innovatively analyzes and verifies the effect of the PZT FSM hysteresis characteristics on the error suppression bandwidth of the fine tracking system. Firstly, the rate-dependent hysteresis model is established by serially connecting the Prandtl–Ishlinskii (P-I) model with the dynamic linear mode. The inverse model is designed as a feedforward controller, followed by the conduction of open-loop feedforward compensation experiments. Subsequently, we propose a compound control method based on the rate-dependent hysteresis mode and conduct a simulation analysis. Finally, the experimental platform for the fine tracking system is set up, and the optimization effect of compensating for hysteresis nonlinearity on the fine tracking system is verified. The experimental results show that the nonlinearity of the PZT FSM is improved by 30% in the middle- and high-frequency ranges, and the error suppression bandwidth of the fine tracking system is improved by 41.7%. This effectively enhances the fine tracking system's error suppression capability. [ABSTRACT FROM AUTHOR]

In COCOMO II, the primary input for estimating development effort in person month (PM), duration, and cost is the size of the software. Until now, there are two ways to get the size, namely (1) size is estimated using a line of code of software, and (2) size is estimated using unadjusted function points (UFP), which is one of the functional size measurements (FSM). In this study, we added a new way to obtain the size as the primary input in COCOMO II, namely with COSMIC function points (CFP). CFP has several advantages compared to other FSMs, including UFP. Therefore, like UFP, CFP is converted first to LOC, so the conversion equation must be obtained first. We applied four models to get the conversion functions: Ordinary least squares regression (OLSR), support vector regression (SVR) with linear, polynomial, and Gaussian kernel functions. The four models were applied using a dataset from small-scale business application software in Java. The results showed that PM estimation using the CFP model as the primary input produced better accuracy based on MMRE and Pred (0.25), namely 17%-19% and 67%-80%, than the UFP model on the COCOMO II of 135% and 10%. [ABSTRACT FROM AUTHOR]

The purpose of this study is to examine the effects of motivational qualities of music elicited by two primary types of music sources (i.e., self-selected music and facility-selected music) on consumer emotional and cognitive responses in a fitness facility environment. The concept of motivational qualities of music was aligned with Mehrabian and Russell's stimulus-organism-response (SOR) theory. A survey was administered to self-paced fitness customers (n = 183) who were exposed to either type of music in a natural field experiment setting. SEM was utilised for hypothesis evaluation. The three hypotheses were confirmed: that SSM provides a greater degree of motivation for fitness facility customers than FSM; that higher perception of motivational qualities of music led to greater arousal and pleasure, and that the greater their pleasure and arousal, the greater their satisfaction with their exercise experience. [ABSTRACT FROM AUTHOR]

Hardware obfuscating is a proactive design-for-trust technique against IC supply chain threats, i.e., IP piracy and overproduction. Many studies have evaluated numerous techniques for obfuscation purposes. Nevertheless, de-obfuscation attacks have demonstrated their insufficiency. This paper proposes a register-transfer (RT) level finite-state-machine (FSM) obfuscation technique called ReTrustFSM that allows designers to obfuscate at the earliest possible stage. ReTrustFSM combines three types of secrecy: explicit external secrecy via an external key, implicit external secrecy based on specific clock cycles, and internal secrecy through a concealed FSM transition function. So, the robustness of ReTrustFSM relies on the external key, the external primary input patterns, and the cycle accuracy of applying such external stimuli. Additionally, ReTrustFSM defines a cohesive relationship between the features of Boolean problems and the required time for de-obfuscation, ensuring a maximum execution time for oracle-guided de-obfuscation attacks. Various attacks are employed to test ReTrustFSM’s robustness, including structural and machine learning attacks, functional I/O queries (BMC), and FSM attacks. We have also analyzed the corruptibility and overhead of design-under-obfuscation. Our experimental results demonstrate the robustness of ReTrustFSM at acceptable overhead/corruption while resisting such threat models.

The paper proposes the method of reduced matrix D-trees, which is an improved version of the method of matrix d-trees. This method is a further development of the application of one of the subcircuit methods, the so-called d-tree method, to the symbolic analysis of linear circuits with constant parameters The method of reduced matrix D-trees, like the d-tree method, provides a significant reduction in the required computer time for modeling circuits, which has a mathematical meaning, consisting in the bringing out of similar terms in the formed complex symbolic expressions. Since there are, in fact, many symbolic terms in such expressions, this reduction in time is due to such factoring. The method is illustrated using a model of a long line consisting of a cascade connection of a large number of elementary links. The results of the computer simulation are also presented. [ABSTRACT FROM AUTHOR]

This article presents numerical analysis of typical folded-plate structures by the finite strip method (FSM) taking into account geometrical and material nonlinearity. Harmonic coupled FSM is used for geometrical nonlinear analysis, whereas rheological-dynamical analogy for the analysis of softening behavior. The efficiency of this novel method is demonstrated on the structures that are experimentally investigated and described in cited literature. [ABSTRACT FROM AUTHOR]

Wavefront distortion caused by atmospheric turbulence can be described as different types of aberrations, such as piston, tilt, defocusing, astigmatism, coma and so on. The operation of dual deformable mirrors can have mutual coupling effects, which affect the correction effect of wavefront distortion. This study combines a fast-steering mirror (FSM) and a deformable mirror (DM) to form a dual-deformable-mirrors wavefront correction system, and proposes a decoupling algorithm that can correct any specified aberration. In this decoupling algorithm, both the FSM and the DM are controlled using the mode method, and the specific corrected aberrations are obtained based on a limited matrix. The compensation ability of the DM is directly characterized by the mode coefficients of the aberrations, which can achieve independent correction of any order of aberrations and effectively reduce the coupling effect of the dual-deformable-mirrors wavefront correction system. An adaptive optical dual-deformable-mirrors wavefront correction system experiment was built to verify the decoupling algorithm. When the DM corrects the 3rd-, 10th-, and 25th-order aberrations, and the FSM only corrects the 1st- and 2nd-order aberrations, the coupling coefficients are approximately 1.17×10−3, 1.814×10−2 and 7.81×10−3, respectively, and their magnitude reaches 10−2 and below 10−2, respectively. The experimental results show that the decoupling algorithm can effectively suppress the coupling effect between the FSM and the DM.

Piezoelectric fast steering mirror (PZT FSM) is the core component of the fine tracking system for space laser communication, and its actuator is a piezoelectric ceramic. Consequently, there is a hysteretic nonlinear disturbance throughout the entire range of the FSM’s steering. To enhance the fine tracking system’s performance, this paper innovatively analyzes and verifies the effect of the PZT FSM hysteresis characteristics on the error suppression bandwidth of the fine tracking system. Firstly, the rate-dependent hysteresis model is established by serially connecting the Prandtl–Ishlinskii (P-I) model with the dynamic linear mode. The inverse model is designed as a feedforward controller, followed by the conduction of open-loop feedforward compensation experiments. Subsequently, we propose a compound control method based on the rate-dependent hysteresis mode and conduct a simulation analysis. Finally, the experimental platform for the fine tracking system is set up, and the optimization effect of compensating for hysteresis nonlinearity on the fine tracking system is verified. The experimental results show that the nonlinearity of the PZT FSM is improved by 30% in the middle- and high-frequency ranges, and the error suppression bandwidth of the fine tracking system is improved by 41.7%. This effectively enhances the fine tracking system’s error suppression capability.

To ensure sanitation for all by 2030, fecal sludge collection services in low-income urban areas with no sewer connections need improvement. One of the major issues is the gap between low-income households' willingness to pay and the cost of emptying services in low-income areas. One way of lowering the cost of these services is through process optimization. In this regard, we conducted a time and motion study to better understand the bottlenecks associated with the collection of fecal waste from different types of on-site sanitation facilities. Our results show that emptying pit latrines, which make up 53% of the market for emptying services in Kigali, takes twice as long as emptying septic tanks. 33% of households that requested the service were located in an informal settlement with no access to road and could only be served by a semi-mechanized method which required use of barrels, and a portable pump. In general, interventions related to minimizing trash disposal in pits and septic tanks can go a long way in making the emptying process more time- and cost-efficient. Additionally, developing effective and efficient pumping technologies that are suitable for use in inaccessible areas should be prioritized. HIGHLIGHTS Pit-emptying process time varies depending on the type of pit and on the type of emptying method used.; By applying time and motion study, we can improve fecal sludge collection process duration.;

Saat ini, hampir semua perangkat elektronik menggunakan prosesor di dalamnya. Dalam sebuah prosesor, terdapat bagian control unit yang berfungsi mengatur operasi dari komponen-komponen di dalam prosesor. Control unit merupakan sebuah mesin keadaan terbatas atau disebut finite state machine (FSM). Rangkaian FSM dapat disintesis secara manual ataupun secara otomatis menggunakan bahasa abstraksi Verilog. Dalam penelitian ini, dibuat sebuah aplikasi yang dapat membantu pengguna merancang FSM dan selanjutnya menyimpannya dalam format Verilog. Aplikasi yang dibuat secara fungsional dapat berjalan dengan kesesuaian 100% dan mampu untuk membuat rancangan Verilog untuk FSM dengan berbagai model dan teknik pengkodean state. Simulasi modul Verilog yang dihasilkan juga sesuai dengan spesifikasi rangkaian FSM yang dirancang.

In Bresenham's line drawing algorithm, the points of an n-dimensional raster that have to be selected are determined forming a close approximation to a straight line existed between two points. It is widely used for drawing line primitives in a bitmap image (for example: on a computer screen), since only integer addition, subtraction and bit shifting are used. These three operations are cheap concerning standard computer architectures. In addition, it is an incremental error algorithm. It is among the oldest algorithms that have been developed in computer graphics. An extension to the original algorithm may lead to draw circles. This research deals with the Bresenham’s line and circle drawing algorithm based on FPGA hardware platform. The shapes on the VGA screen are displayed via internal VGA port that is built in the device.

The removal of excreta or faecal sludge from full pit latrines – pit emptying – is essential to extend the life of the sanitation technology, especially for the millions of users living in the dense, urban areas of the Global South. Unfortunately, pit-emptying is rarely practiced due to factors related to accessibility, disgust, and importantly, cost. We examined the impact of two different types of vouchers distributed in Blantyre, Malawi, to understand if and how subsidies could increase the practice of pit emptying in low-income areas. We found that pit emptying businesses were able to game the system to charge more money on top of the discount in the first study in which 21% vouchers were redeemed from 252 distributed. In a follow-up study, 25% vouchers were redeemed from 400 distributed with more rigorous subsidy targeting and structuring. We discuss why complex drivers for subsidy adoption among low-income households require further research.

Resource recovery and reuse (RRR) of fecal sludge (FS) from onsite sanitation systems describes the concept of turning human waste into valuable end products. However, studies on peoples' perceptions of FS-derived products are still limited. Guided by the knowledge, attitudes and practices framework, and data from a survey of 395 households, focus group discussions and key informant interviews, this article explores how residents in three unplanned settlements of Dar es Salaam, Tanzania view FS RRR (FS-RRR). Results indicate that residents' knowledge about FS-RRR is moderately low. Moreover, residents generally have negative attitudes toward using FS-derived products, except for those not directly consumed, such as biogas or FS-briquettes. Additionally, only a few residents have engaged in any FS-RRR practices. We conclude that to increase local acceptance of FS-RRR will require significant efforts by a multitude of actors, not least to dispel myths linked to human waste, but also to raise awareness and demonstrate the benefits and safety of FS-derived products. The Tanzanian government must take the lead in this process and should start by prioritizing the improvement of fecal sludge management (FSM) to enable such a shift. HIGHLIGHTS The existing knowledge, attitudes and practices on fecal sludge resource recovery and reuse among residents were explored in three selected unplanned settlements.; Low-to-moderate knowledge of resource recovery and negative attitudes have been identified.; Training, awareness campaigns, public participation and private sector involvement are recommended.;

This paper proposes a Finite State Machine (FSM) testing technique based on deep neural network (DNN). This technique verifies the correctness of an implementation FSM-B of a specification FSM-A. Using the back-propagation algorithm, a deep neural network is trained with the input–output patterns for a given set of transition functions that specify an FSM. Initially, for FSM-A, the input patterns and the corresponding output patterns (I/O pairs) are generated. Then most of the patterns are used to train the DNN. Once the training is over, the DNN is validated with the remaining I/O pairs (around 20%). The model can be used for verifying the correctness of FSM-B after training and validation of the DNN. Some inputs are applied to FSM-B and the generated output patterns are compared with the predicted values of the proposed DNN. The difference of accuracy percentages between FSM-A and FSM-B is recorded and zero difference between them indicates the fault-free condition of the implementation FSM-B. To check the effectiveness of the scheme, the output- and state-type faults are injected to derive mutant FSMs. Experimental results performed on the MCNC FSM benchmarks prove the efficacy of the proposed method. Only a few numbers of tests are needed to detect the presence of anomaly, if any. Hence, the test time reduces significantly — resulting in an average test time reduction of 85.67% compared to the conventional techniques. To the best of our knowledge, for the first time a DNN-driven testing scheme is being proposed. [ABSTRACT FROM AUTHOR]

Facial occlusions like sunglasses, masks, caps etc. have severe consequences when reconstructing the partially occluded regions of a facial image. This paper proposes a novel hybrid machine learning approach for occlusion removal based on Structural Similarity Index Measure (SSIM) and Principal Component Analysis (PCA), called SSIM_PCA. The proposed system comprises two stages. In the first stage, a Face Similar Matrix (FSM) guided by the Structural Similarity Index Measure is generated to provide the necessary information to recover from the lost regions of the face image. The FSM generates Related Face (RF) images similar to the probe image. In the second stage, these RF images are considered as related information and used as input data to generate eigenspaces using PCA to reconstruct the occluded face region exploiting the relationship between the occluded region and related face images, which contain relevant data to recover from the occluded area. Experimental results with five standard datasets viz. Caspeal-R1, IMFDB, and FEI have proven that the proposed method works well under illumination changes and occlusion of facial images. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new gait planning method for a multi-legged robot which has only 1 degree-of-freedom in each leg and has a passive body joint between two body segments. We firstly introduce the Finite State Machine (FSM) to the undulatory gait planning method of the 2n-legged robot. Then, the undulatory gait sequence for straight line motion is achieved by undulations motion. The idea that legged locomotion is achievable by less actuation of 2n-legged robot as well as the gait planning methods are verified finally by simulations and experiments.

The need for and the use of different data assimilation techniques to improve the quality of streamflow forecast is now well established. In this paper, the goal is to demonstrate the power of a new class of methods known as the forward sensitivity method (FSM) which is based on the temporal evolution of model sensitivities with respect to the control variables consisting of initial conditions and parameters. FSM operates in two phases: the first phase provides a simple algorithm for placing observations at or near where the square of forward sensitivities attains their maximum values. Using only this selected subset of observations in a weighted least squares method, the second phase then provides an estimate of the unknown elements of the control variables. In this paper, FSM based assimilation is applied to a simple class of two parameter model in a medium‐sized agriculture dominant watershed lying in the Krishna River Basin, India. Four assimilation scenarios were tested to determine the effect of assimilating only sensitive observations as well as the impact of temporally evolving initial condition sensitivity. Sensitivity results showed that observations during the monsoon time alone are enough for assimilation purposes, which has helped in reducing the computational time greatly. Assimilation and forecast results also indicated that the scenarios which assimilated only sensitive observations are better in estimating daily streamflow. From the obtained results, it is concluded that FSM based assimilation has significant potential to improve the streamflow simulations, especially in places where data availability remains a major challenge. Key Points: The potential of assimilating only sensitive soil moisture observations on streamflow forecast was demonstrated using a novel forward sensitivity method (FSM) methodImpact of temporally evolving sensitivity of initial condition on hydrological model performance during assimilation was determinedThe sensitivity‐based soil moisture assimilation was effective up to 45 lead days during streamflow forecast [ABSTRACT FROM AUTHOR]

The removal of excreta or faecal sludge from full pit latrines – pit emptying – is essential to extend the life of the sanitation technology, especially for the millions of users living in the dense, urban areas of the Global South. Unfortunately, pit-emptying is rarely practiced due to factors related to accessibility, disgust, and importantly, cost. We examined the impact of two different types of vouchers distributed in Blantyre, Malawi, to understand if and how subsidies could increase the practice of pit emptying in low-income areas. We found that pit emptying businesses were able to game the system to charge more money on top of the discount in the first study in which 21% vouchers were redeemed from 252 distributed. In a follow-up study, 25% vouchers were redeemed from 400 distributed with more rigorous subsidy targeting and structuring. We discuss why complex drivers for subsidy adoption among low-income households require further research. [ABSTRACT FROM AUTHOR]

• A dedicated hardware system to quantify physical labor during walk and run. • This hardware has the capacity to detect walk cycles. • The proposed hardware system can distinguish between walk and run. • A dynamic diet chart preparation system based on calorie consumption by the body. • The system allows the user to provide food affinity during diet chart preparation. At the beginning of human civilization, human being needs to undergo immense physical labor to survive. During those days high-calorie diet was essential. However, the evolution of technology has changed the scenario and much lesser amount of physical labor is required to survive in modern hi-tech days, requiring less amount of calorie. The excess calorie gets deposited in the body in the form of white fat. As a consequence, obesity appears as an epidemic all over the world. Long term obesity causes many diseases like heart attack, stroke, diabetes, and many other ailments. It is tough for people, who honestly want to check their obesity by controlling food habits, to continue a static diet chart with fixed restricted foods for a long time. Most of the time, people give up such restrictions on food. It will be very useful if a system exists, that will generate a dynamic diet chart based on calorie spend by the body. This research describes a system that will generate a dynamic diet chart based on calorie spend by the body and other data like user's BMI, food preferences, etc. In this system, user can tailor his/her diet chart by changing daily physical activities (activities that burn calories). The main contributions of the proposed system are as follows: • A dedicated hardware system to quantify physical labor during walking and running throughout the day from feet pressure changes along with walk cycle detection. • The proposed hardware system can distinguish between walk and run. • A dynamic diet chart preparation system, where the user has the provision to plan his/her diet chart with food affinity. The entire work is divided into two modules; the first one focuses on the hardware design to detect and quantify physical activities during "walking" and "running". These data are used in the second part. The second part contains calorie calculation along with the preparation of a dynamic diet chart with food affinity. In the hardware design, an Application Specific Integrated Circuit (ASIC) is proposed to measure the physical activity during "walking" and "running". At the time of hardware logic synthesis, VHDL and FPGA are used. Experimental results show that the proposed hardware provides more accurate results than a pedometer. There is no standard metric to measure the performance of the dynamic diet chart generation system. Competency of the dietitian at the time of setting the parameters, honesty of the users at the time of the interactive session, etc. are the main factors that influence heavily the performance of the dynamic diet chart preparation system. The advantage of dynamic diet chart is that users can modify the diet menu as per their wish, and the system generates a diet chart in such a way that calorie intake (through food items) is maintained properly. In addition to this, the user can plan his future meals. This work is an interdisciplinary work. It is a blending of electronics (FSM), design, and computation for decision making; the computation portion includes software engineering, soft computing, etc. Future plan of this work is to integrate this system with "Cloud" to provide different data analysis related services, like region-wise food habit pattern prediction, health-related statistics, etc. [ABSTRACT FROM AUTHOR]

There is a growing body of evidence from rigorous evaluations demonstrating the effectiveness of education entertainment – ‘edutainment’– interventions in achieving development outcomes. Building on this research, this study presents the results of a pioneering quasi-experimental evaluation of Navrangi Re, a 26-episode television drama aired in India in 2019. The show was the first ever edutainment broadcast on commercial television in India. It aimed to influence sanitation behaviours through changing knowledge and attitudes, increasing risk perception, stimulating conversations, building collective efficacy, and creating social disapproval against poor faecal sludge management practices. The evaluation compared changes in outcomes of those exposed to the TV show with those unexposed, applying differences-in-differences estimation to a panel of 2,959 respondents. Baseline balance tests show high comparability between exposed and unexposed respondents. It found exposure to the drama led to significant changes in most outcomes with 37% of those who watched at least one episode showing behavioural intent to act, rising to 78% of those who had watched at least seven episodes. The show reached 59.6 million unique viewers, confirming drama as an effective, low cost and scalable tool to engage people around faecal sludge management – a critical and hard to address issue. [ABSTRACT FROM AUTHOR]

This article examines the Federated States of Micronesia (FSM) diplomatic relations with China, and its search for greater autonomy through financial and political independence as its current Compact of Free Association with the United States comes up for review in 2023. The article draws on diplomatic histories overlooked in existing analyses of regional diplomacy in which Micronesians explore alternative options for how to best advance their collective future interests. These Micronesian narratives demonstrate that external powers and aid donors should not take their influence for granted, nor necessarily correlate their largesse with local respect. The priorities of Pacific nations are increasingly focused on mitigating the existential threat of climate change to their environments. Avoidable environmental damage to a reef in Pohnpei by the Chinese fishing vessel Ping Da 7 in late 2013 and subsequent refusals to remove the grounded vessel and clean up the damage provide just one example of the FSM having to review their external relations in response to differences between donors' promises and their practice. To maintain healthy relations with the FSM, this article argues that China and the United States need to respect and support the FSM as a sovereign nation with many compatible interests, but also occasional divergences in national priorities. [ABSTRACT FROM AUTHOR]

The assurance of quality and reliability of process models and workflows is essential for model driven software development. There are numerous ways to achieve these objectives. One is model checking through which it can be verified that a model satisfies specific logical rules. The model to be checked is usually given as finite state machine. Rules have to be specified at the level required by the model checker. In this work, we develop a model for validating the DNA profiling through finite state.. This enables the research/business process professionals to use model checking techniques and to produce higher quality research/business models for subsequent software development. The approach is demonstrated by validating event-driven process chains. [ABSTRACT FROM AUTHOR]

This research develops Android games by applying the FSM Algorithm (Finite State Machine) for the movement of NPC (Non-Player Character) to produce dynamic movements. The popular and legendary game with the appearance of side scroller is Super Mario Bross and Shovel Knight, the game is the most preferred game of its time to the present, but the game does not apply AI (Artificial Intelligence) so the game seems less challenging. The game is a concept game that is currently rarely used. Based on this, a side scroller-based survival game was created by implementing AI on NPCs on the Android platform. The AI used is the FSM Algorithm which functions to regulate enemy movements. The method used in developing multimedia products of this game uses MDLC (Multimedia Development Life Cycle). Based on the tests that have been carried out, the alpha test results are functionally appropriate and the results of beta testing using UserAcceptence Test (UAT) obtained a value of 86.40% which is declared feasible to use and can be developed. The advantages of this game are the presence of shock elements in the form of landslides, bursts of water, rock rain, and attacks by eagles

A logic synthesis for finite-state machines (FSMs) aimed at programmable array logic (PAL)-based complex programmable logic devices is proposed here. This approach consists of the simultaneous synthesis of a transition function and an output function. The main contribution is the novel multilevel optimization of an FSM. In this process, a new form of graph is used, i.e., a graph of excitations and outputs. This is a generalization of the graph of outputs that has previously been used in the process of technology mapping of multi-output functions in PAL-based programmable structures. The main idea, the theoretical background, and a precise algorithm are illustrated by means of simple examples. The proposed algorithm was compared with other approaches by synthesizing the FSM benchmarks and mapping the solutions to k-term PAL-based logic blocks. The obtained results are compared on the basis of the area (number of logic blocks) and speed (number of logic levels). The proposed approach is especially effective for larger FSMs.

Furosemide (FSM) is commonly used in the treatment of edema associated with congestive cardiac failure, cirrhosis of the liver, renal disease, including the nephrotic syndrome and hypertension. However, in ascites, it is clinically limited due to its frequent dosing and short biological half-life and its prolonged-release preparations are not available. Therefore, the main objective behind the present research work is to develop chitosan coated and conjugated poly (lactic-co-glycolic acid) (PLGA) nanocarriers, to sustain the delivery of FSM with improved systemic circulation. Emulsion-solvent evaporation technique was used for the preparation of nanoparticles. In-vivo pharmacokinetic study showed 2.6, 3.10, and 4.30 folds enhancement in relative availability of FSM for FSM-PLGA, FSM-chitosan-coated-PLGA and FSM-chitosan-conjugated- PLGA nanoparticles, respectively than FSM. The present research work concluded that FSM loaded chitosan conjugated PLGA nanoparticles could enhance the systemic circulation of FSM with improved pharmacokinetics parameters.

In this paper, a method for grounding impedance measurement is proposed. The method is experimentally validated in five substations rated voltage 35/10 kV. Compared to a standard measuring method, the basic benefits of the proposed method are: (a) the current probe is realised in the form of a ground drill (a drill-type electrode designed to be driven into the earth) instead of being used the grounding grid of a next substation, (b) proposed method does not use an overhead line (or a cable line) for purposes to connect remote current probe, (c) the proposed method requires a test signal source whose output power may be in the order 100 W (instead of 1 kW in standard method), and (d) measuring accuracy of the proposed method is the same as in the case when standard method is used.

SNOW-V is a new member in the SNOW family of stream ciphers, hoping to be competitive in the 5G mobile communication system. In this paper, we study the resistance of SNOW-V against bitwise fast correlation attacks by constructing bitwise linear approximations. First, we propose and summarize some efficient algorithms using the slice-like techniques to compute the bitwise linear approximations of certain types of composition functions composed of basic operations like ⊞, ⊕, Permutation, and S-box, which have been widely used in word-oriented stream ciphers such as SNOW-like ciphers. Then, using these algorithms, we find a number of stronger linear approximations for the FSM of the two variants of SNOW-V given in the design document, i.e., SNOW-V σ0 and SNOW-V⊞8, ⊞8. For SNOW-V σ0, where there is no byte-wise permutation, we find some bitwise linear approximations of the FSM with the SEI (Squared Euclidean Imbalance) around 2−37.34 and mount a bitwise fast correlation attack with the time complexity 2251.93 and memory complexity 2244, given 2103.83 keystream outputs, which improves greatly the results in the design document. For SNOW-V⊞8, ⊞8, where both of the two 32-bit adders in the FSM are replaced by 8-bit adders, we find our best bitwise linear approximations of the FSM with the SEI 2−174.14, while the best byte-wise linear approximation in the design document of SNOW-V has the SEI 2−214.80. Finally, we study the security of a closer variant of SNOW-V, denoted by SNOW-V⊞32, ⊞8, where only the 32-bit adder used for updating the first register is replaced by the 8-bit adder, while everything else remains identical. For SNOW-V⊞32, ⊞8, we derive many mask tuples yielding the bitwise linear approximations of the FSM with the SEI larger than 2−184. Using these linear approximations, we mount a fast correlation attack with the time complexity 2377.01 and a memory complexity 2363, given 2253.73 keystream outputs. Note that neither of our attack threatens the security of SNOW-V. We hope our research could further help in understanding bitwise linear approximation attacks and also the structure of SNOW-like stream ciphers.

Ultraviolet treatment (UV-C) is well known for its antimicrobial effects and current research shows that it has the potential to inactivate microorganisms in milk at much lower temperatures than conventional thermal treatment. However, Ultraviolet irradiation may result in adverse effects on milk quality, which arises due to photo oxidation in the presence of oxygen. Limiting the dissolved oxygen content in milk can minimize oxidative damage and thus, result in a better product quality. Nitrogen purging could be an effective method for reducing dissolved oxygen from liquids. The present study evaluates effects of nitrogen purging (prior to UV treatment) on milk quality. It was found that nitrogen purged UV treated milk causes minimal changes to physicochemical properties of milk. [ABSTRACT FROM AUTHOR]

Today's embedded System is complex. An embedded system design project may involve of various engineering field. A rapidly-available and well-defined framework code brings advantages to the team consists of many engineers from various domains. This framework must be easy to use for communication purpose and analysis (model). This paper proposes a design flow based on a model which is high level but precise enough to use in automatic generation of the embedded system framework code. The model is flexible for rapid modification. The event driven paradigm and the FSM are used in the model. The design flow uses the model to generate framework code based on an existing platform. The work presented in this paper produces tool for the generation which is called EBGES. The proposed model describes the system as set of finite state machines (FSM) and events. This model serves for two purposes: (1) to be discussed by the developers/various engineers before deciding the platform and the architecture of the system, (2) to be used for generating the framework code. An automatic code generator is developed to produce a framework code from the model. The framework consists of (1) the FSM for every block, (2) communications between the FSMs, (3) function prototypes (for software) for function used by FSM, (4) interface of hardware module used by the FSMs, (5) instantiation of the platform. The generator software takes the model in form of annotated diagrams which are created schematically using a GUI environment. The diagrams follow UML standard. The outputs are VHDL code for hardware and C code for the software part. Example of calculator application is developed to test the tool and the flow. The generated framework code in the calculator experiment accelerated the development. Up to 51% of the code is generated automatically and 49% of the code is written manually. The result of the experiment shows significantly improvement on design productivity which is the comes from: (1) abstraction of the behavior of subsystems/modules (HW or SW) by hiding unnecessary detail and (2) automatic generation of the framework code. [ABSTRACT FROM AUTHOR]

In this paper, we study the linear approximation of certain composition functions, with applications to SNOW 2.0 and SNOW 3G. We first propose an efficient algorithm to compute the linear approximation of certain composition functions with parallel operations, which has a linear-time complexity for any given mask tuple, and thus allows for a wide range of search for linear approximations. Naturally, we apply this algorithm to compute the linear approximations of the FSM of both SNOW 2.0 and SNOW 3G. For SNOW 2.0, we compute the linear approximation of the FSM for a wide range of linear masks, and obtain some results which enable us to slightly improve the data complexity of the known fast correlation attacks, by using multiple linear approximations and combining a small technique when applying the k-tree algorithm. For SNOW 3G, we make a careful search for the linear approximations of the FSM and obtain many mask tuples which yield high correlations. Using these linear approximations, we mount a fast correlation attack on SNOW 3G and recover the initial state of the LFSR with the total time complexity 2 222.33 and memory complexity 2 221.74 , given 2 220.74 keystream words. Our attack does not pose a threat to the claimed 128-bit security of SNOW 3G. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has become an enabler of smart technologies being a backbone for Internet convergence as devices interact over Internet Protocol based networks. The need for seamless interconnection while maintaining user confidentiality and data integrity cannot be overemphasized as IoT invariably inherits the security threats posed by the Internet. This work presents a dual smart and secured home automation initiative using the finite state machine (FSM). The proposed model was seen to achieve the dual purpose of automating the home while providing a remote security management system. [ABSTRACT FROM AUTHOR]

In the paper there is discussed the problem of constructing and implementation the mathematical models for control algorithms of concurrent processes. For the control object example there was taken an example of 3D Cartesian machine. The control algorithm is mathematically described with use of Finite State Machine methodology in canonical and concurrent variants. Implementation examples are given, problem of resources consumption and operation time is discussed and the conclusion is d drawn. [ABSTRACT FROM AUTHOR]

The main purpose of the paper is to present technology mapping of FSM (finite state machine) oriented to LUT (look-up table)-based FPGA (field-programmable gate array). The combinational part of an automaton, which consists of a transition block and an output block, was mapped in LUT-based logic blocks. In the paper, the idea of carrying out the combinational part of FSM was presented and leads to the reduction of the number of LUTs needed to carry out an automaton. The essence of this method is a simultaneous synthesis of the whole combinational block described in the form of multi-output function. The proposed idea makes it possible to conduct decomposition that may enable to share logic blocks, which can lead to the reduction of using resources of FPGA. The decomposition process was conducted using the analyzed DECOMP system. The effectiveness of the proposed idea of the FSM description was also confirmed by conducting decomposition with the usage of the ABC system. The obtained results prove the efficiency of the proposed synthesis method of FSM in comparison with the separate synthesis of a transition block and an output block. [ABSTRACT FROM AUTHOR]

Modeling transient flow characteristics in a producing gas well has been a problem long over in natural gas industry due to parameter changing during operation. In the past, authors concentrate on application of correlations and steady state approach, but most of their works does not give satisfactory results because the used applications neglect the transient aspect leading to premature closure of most wells. Many existing models are proposed to correct these anomalies using simplified governing equation ignoring the transient aspect of the flow characteristics. A one-dimensional transient compressible model comparing the conservation of mass, momentum and energy has been presented to investigate the transient behavior of flow characteristics in a producing gas well staged at different inclination due to environment change. The model is solved numerically using the implicit Steger-Warming flux vector splitting method (FSM). The work investigates flow characteristics along depth of the well using different wellbore diameter of 0.073m, 0.0883m, at different time and different thermal conductivities. It shows that transient occurs due to the temperature difference between the produced gas and the flow environment while gas pressure increases due to difference between wellbore pressure and reservoir pressure. The result of this work reflect gas flow law and the characteristics of heat transfer in formation. [ABSTRACT FROM AUTHOR]