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What does it mean today to study a problem from a computational point of view? We focus on parameterized complexity and on Column 16 “Graph Restrictions and Their Effect” of D.S. Johnson’s Ongoing guide, where several puzzles were proposed in a summary table with 30 graph classes as rows and 11 problems as columns. Several of the 330 entries remain unclassified into Polynomial or NP -complete after 35 years. We provide a full dichotomy for the Steiner Tree column by proving that the problem is NP -complete when restricted to Undirected Path graphs. We revise Johnson’s summary table according to the granularity provided by the parameterized complexity for NP -complete problems.

This article presents a planner for a master dual-arm robot to manipulate tethered tools with the help of an assistant dual-arm robot. The assistant robot assists the master robot by manipulating the tool cable and avoiding collisions. The provided assistance allows the master robot to perform tool placements on the robot workspace table and regrasp it, which would typically fail since cable tension may change the tool positions. It also allows the master robot to perform tool handovers, which would normally cause entanglements or collisions with the cable and the environment without assistance. Simulations and real-world experiments are performed to validate the proposed planner. Experimental results show that with the help of the assistant dual-arm robot and the proposed method, the master robot obtained improved flexibility in working with tethered tools.

Deep neural network (DNN) shows great promise in providing more intelligence to ubiquitous end devices. However, the existing partition-offloading schemes adopt data-parallel or model-parallel collaboration between devices and the cloud, which does not make full use of the resources of end devices for deep-level parallel execution. This paper proposes eDDNN (i.e. enabling Distributed DNN), a collaborative inference scheme over heterogeneous end devices using cross-platform web technology, moving the computation close to ubiquitous end devices, improving resource utilization, and reducing the computing pressure of data centers. eDDNN implements D2D communication and collaborative inference among heterogeneous end devices with WebRTC protocol, divides the data and corresponding DNN model into pieces simultaneously, and then executes inference almost independently by establishing a layer dependency table. Besides, eDDNN provides a dynamic allocation algorithm based on deep reinforcement learning to minimize latency. We conduct experiments on various datasets and DNNs and further employ eDDNN into a mobile web AR application to illustrate the effectiveness. The results show that eDDNN can achieve the latency decrease by 2.98x, reduce mobile energy by 1.8x, and relieve the computing pressure of the edge server by 2.57x, against a typical partition-offloading approach.

In modern SSDs, a flash translation layer (FTL) is the core engine performing the logical-to-physical address translations. However, the increasing capacity of SSDs requires a large DRAM space to hold the mapping table in a page-level FTL. Due to the limited size of built-in DRAM, existing FTL schemes selectively cache some active mapping entries in DRAM, while store the entire mapping table on flash. However, the low cache hit ratio introduced by the traditional mapping entry eviction policy degrades the access performance of SSDs. In this paper, we propose a novel FTL, hot-clusterity FTL (HCFTL), to improve the hit ratio of Cached Mapping Table (CMT) of SSDs with limited cache space. HCFTL clusters mapping entries, which are newly evicted from the cache, into dynamic translation pages (DTPs). Reading entries from DTPs will increase the CMT hit ratio due to spatial and temporal localities. Because the Logical Page Numbers (LPNs) in a DTP are not consecutive, we introduce two different efficient index structures to speedup the lookup of mapping entries in DTPs. Furthermore, to make the DTP index highly accurate, we additionally allocate an auxiliary cache to buffer the mapping entries newly evicted from CMT, and produce dynamic pages with minimum difference between the maximal and the minimal LPNs of entries in those pages. Our experiments show that HCFTL can improve the CMT hit ratio by up to 41.1% and decrease the system response time by up to 33.3%, compared to baseline FTL schemes.

The four-switch buck-boost converter (FSBB) is a preferred choice for the dc-dc applications where the step-up and step-down are needed. In order to reduce the inductor size and improve the efficiency, the zero-voltage switch (ZVS) control schemes with four segments inductor current for FSBB had been investigated in numerous publications. Among these ZVS control schemes, the optimized control variable stored as the huge look-up table data achieved minimum RMS inductor current, and the complex real-time calculation was avoided. However, for the purpose of matching the wide input and output voltage ranges, an external flash was needed for storing the look-up table data; and the large time consumption for invoking the data hazard the dynamic performance significantly. To reduce the storage device cost and meet the demand of transient, a simplified real-time control algorithm is proposed by dividing the operation into the defined DCM and CCM operation featuring the minimum RMS inductor current and ZVS operation during the whole voltage range without complex calculation and mode transient. Finally, a 300W dc-dc prototype is built to verify the theoretical analysis and proposed control scheme with a low-cost real-time digital controller.

Schedule-based fieldbus is applied widely in industrial control. Building schedule table (ST) can affect the time-critical performance for communication greatly. Communication jitters can cause some unexpected results in bus traffic scheduling and longer jitters can even cause severe delay in time-critical application. Communication jitter and evenness in arrangement of variables to be scheduled in micro-cycles in ST were two important issues dealing with the performance. An algorithm to build schedule table based on numerical co-prime method was proposed in this paper. Communication jitter in ST was investigated. Concept dealing with rank of ST was introduced. Numerical co-prime method to evaluate rank of ST was proposed. The algorithm and procedure to build schedule table based on the proposed numerical co-prime method were presented and exemplified in detail. Performance analysis and comparison of the proposed algorithm to HCF/LCM method was presented. It was proved that the proposed algorithm can reduce communication jitter to its minimum value and the longest time consumed to schedule variable in one micro-cycle, and greatly reduce the possibility the time consumed to schedule variables exceeded micro-cycle.

RATIONALE Medication for treatment of COPD is available in many different delivery systems; however, national and international guidelines do not provide recommendations on how to select the optimal system for an individual patient. OBJECTIVES To perform a systematic review of published algorithms for inhaler selection in out-patients with COPD. METHODS PubMed, EMBASE, PsycINFO, Cochrane, and Google Scholar were search for articles on inhaler selection published between January 1, 1990 and March 10, 2021. The results were reviewed for articles containing an algorithm for inhaler selection. The quality of publications containing an algorithm was assessed using the JBI SUMARI text and opinion critical appraisal checklist. Individual steps recommended in the algorithms and the order in which they were considered were extracted independently by the two authors using the JBI text and opinion data extraction tool. Textual syntheses and a table of factors included were used to appraise and compare algorithms. RESULTS The search identified 1016 publications. After removing duplicate studies (n = 409), 607 abstracts were examined. Nine different algorithms or hierarchical recommendations for device selection were identified. All nine publications were considered of good quality. Most algorithms contain only a few decision steps. There were significant differences between the algorithms. None of the algorithms have been validated. Three domains for factors included in the algorithms were identified: patient factors, device attributes, and HCP factors. Patient factors were considered most frequently (19 times) compared with device attributes (10 times) and HCP factors (7 times). Five specific attribute/factors with at least three rankings in different algorithms, were identified as key factors for device selection. CONCLUSION Although the algorithms generally provide step-by-step approaches based on a literature review and/or the experiences of the different authors, none were developed using item generation/reduction methodology nor included input from patients with COPD. There were considerable differences between the algorithms; however, the review identified key factors that should be considered by HCPs when selecting therapy. Registration: PROSPERO (CRD42021244475).

Previous studies have proposed various algorithms such as model predictive control, machine learning, and dynamic programming for ecological adaptive cruise control (ACC). However, industrial application of these algorithms is limited owing to their considerable computational cost. Moreover, there is a tradeoff between the calculation time and optimization results. In this study, a novel optimization method, referred to as quadrant dynamic programming (QDP), for ACC is proposed. QDP is based on regular dynamic programming (DP); it divides the DP table into four quadrants. Most of the computations are performed offline, and expensive hardware is not required to be installed in vehicles. Moreover, the offline computation cost is also reduced to a practical level, whereas the result is globally optimal. The algorithm is validated for reducing the energy consumption of an electric vehicle (EV) via simulations and experiments using our test vehicle. The experimental results also showed the accuracy of the motor and vehicle dynamics models. Compared with the widely used ACC for feedback control, QDP reduced energy consumption by 16.1 % in multi-lane car following scenarios with the same cruising distance and time. The proposed QDP avoided trade-offs between computational cost and optimization results by utilizing offline computation effectively. Moreover, it was proven valid for general ecological ACC applications.

In our day to day life, we face so many decision-making problems. The heavy text data sets and these data sets are increasing drastically in such a way that it reaches to the big data environment. Here, We have not only proposed a framework for big data sentiment analysis on real-time updates in online reviews or text for optimal or best decision selection (for example selection of a restaurant) from existing huge list of N number of restaurants but also implemented our proposed framework as a mathematical algorithm (named as Algorithm 4.1) by using soft computing technique for finding reduct soft set of consolidated review matrix. We further quantified sentiments in three values (1, −1, and 0), either in 1 for (positive/yes/true) or −1 for (negative/no/False) and 0 for (neutral or absence of sentiment) and stored them in a table (named as ternary sentiment table). Then, we have done an entropic calculation on this ternary sentiment table to find the quantity of information stored in its associated rows and columns. This proposed quantification further helps to identify the most important attribute of the table. It helps to decide weight for the different attributes and applying calculated weights to corresponding attributes to obtain the quantified ordered decision-making values.

Digital active gate driving has been shown to effectively manage the switching performance for power devices with the adjustable driving waveforms. However, most of the studies are based on a dedicated test circuit rather than a practical inverter with the sinusoidal output current. In fact, it is the dependency on the load current that makes the design of the gate driving profiles a critical issue. To investigate the digital active gate driver in an inverter application, this paper has applied optimal patterns adapting to time-varying output load current. Prior to the search of optimal patterns, the proper design framework is discussed with three frameworks of different time resolutions. With the proper resolution determined for patterns, multiple optimizations are carried out for different current conditions. In this way, the search for optimal patterns can be completed in an efficient time. Next, a look-up table of optimal switching pattern in correspondence with each certain load current condition was built in advance. According to the output load current, the optimal pattern is selected based on the look-up table. Compared to the conventional constant driving waveform, the power loss has been reduced by 7% with a full optimal look-up table applied.

Traditional tools like NetFlow face great challenges as both the speed and the complexity of the network traffic increase. To keep the pace up, we propose HashFlow for more efficient and accurate collection of flow records. HashFlow keeps large flows in its main flow table and uses an ancillary table to summarize the other flows when the main table is full. With our flow collision resolution and flow record promotion schemes, a flow in the ancillary table is promoted back to the main flow table with a guaranteed probability when it becomes large enough. These operations can be performed highly efficiently, so HashFlow can keep up with ultra-high traffic speed. We implement HashFlow in a Tofino switch, and using traces from different operational networks, we compare its performance against some state-of-the-art flow measurement algorithms. Our experiments show that, for various types of traffic analysis applications, HashFlow consistently demonstrates clearly better performance than its competitors. For example, the performance of HashFlow in flow size estimation, flow size distribution estimation and heavy hitter detection is up to 21, 60 and 35 percent better than those of the best competitors respectively, and these merits of HashFlow come with almost no degradation of throughput.

Despite their superior control performance, active vibration control techniques cannot be widely used in some engineering fields because of their substantial power demand in controlling large-scale structures. As an innovative solution to this problem, an unprecedented self-powered active vibration control system was established in this study. The topological design, working mechanism, and power flow of the proposed system are presented herein. The self-powering ability of the system was confirmed based on a detailed power flow analysis of vibration control processes. A self-powered actively controlled actuator was designed and applied to a scaled active vibration isolation table. The feasibility and effectiveness of the innovative system were successfully validated through a series of analytical, numerical, and experimental investigations. The setup and control strategy of the proposed system can be readily extended to diversified active vibration control applications in various engineering fields.

In this paper, a novel Asymptotic Probability Estimation (APE) method is proposed to estimate the probability of correlated rare failure events for complex integrated systems containing a large number of replicated cells. The key idea is to approximate the failure rate of the entire system by solving a set of nonlinear equations derived from a general analytical model. An error refinement method based on Look-up Table (LUT) is further developed to improve numerical stability and, hence, reduce estimation error. Furthermore, a statistical algorithm based on re-sampling is developed to accurately estimate the confidence interval of APE. Our numerical experiments demonstrate that compared to the state-of-the-art method, APE can reduce the estimation error by up to 30× without increasing the computational cost.

The availability of Software Defined Network’s (SDNs) flow rule entry in the flow table is considered a key factor in the timely delivery of a certain flow. The controller is approached for instructions on how to deal with the flow when the rule for such flow is missing. The controller then updates the flow table accordingly at the switch so that flow could be dealt with locally. It becomes problematic when no rule is defined yet at the controller by the application plane. In most of these cases, such a situation is handled by programming the controller with wildcard rules. However, handling many flows at once under wildcard rules severely hampers the network performance. Flow rules formation by the application plane is sometimes critical and time-consuming which increases the latency ratio by creating a bottleneck at the switch level. To avoid the bottlenecks due to rule absence, in this paper, rather than waiting for the application plane’s response and putting the pending traffic flows in the buffer, which may be dropped, the controller is programmed in a way that has the built-in mechanism of self-flow rule formation. This atomized mechanism is based on the previously available traces of the same flows when they were forwarded on the network using the wildcard rules. To assess the performance of the proposed work, it is emulated and benchmarked with the latest research. The results show considerable performance achievement.

With the popularization of various applications of the Internet of Things (IoT), a large number of smart devices are connected to the IoT to form an interconnected network. Because the amount of network data generated by IoT devices is huge, data owners prefer to outsource these data to the cloud for releasing them from the local storage burden. Meanwhile, in order to protect the privacy of the network data generated by IoT devices, data owners usually encrypt them before outsourcing them to the cloud. Phrase search encryption plays an important role in the IoT-based applications. To the best of our knowledge, all existing phrase search encryption schemes cannot work when user makes spelling errors. In addition, many existing phrase search encryption schemes build the secure index based on the relative position of keywords, which may lead to inaccurate search results. In order to address these problems, we propose an intelligent fuzzy phrase search scheme over encrypted network data for IoT. In this scheme, we construct a fuzzy keyword set for each distinct keyword, which can efficiently address the spelling mistakes. Moreover, we build the binary matrix for the document collection, which can quickly achieve multi-keyword search. In order to accurately determine whether the keywords in the query phrases are consecutive, we build the look-up table for each document. Experimental result shows that the proposed scheme achieves high efficiency and accuracy.

Background: The vibration control loop is the key technology adopt to improve the control performance of the vibration table, which is set outside of the hydraulic vibration table servo control loop. However, the huge number of signal processing work prompts high demands on the calculation ability of the vibration controller. One kind of multi-CPU embedded vibration controller constructed by Digital Signal Processor (DSP) is proposed considering the working principle of the hydraulic vibration table and the Power Spectrum Density (PSD) reproduction process. The embedded controller consists of an acquisition unit, a calculation unit, and a monitoring unit distributes vibration control tasks to the different processing unit to realize distributed algorithm calculations. Every processing unit uses dual-port memory to accomplish data interaction between each other. The development of the embedded controller provides a benchmark engineering case for the design of the hydraulic vibration table vibration controller. Objective: This article focuses on the development of the multi-CPU embedded vibration controller and the distributed calculations. Meanwhile, the power spectrum density experiment is carried out to verify the performance of the hydraulic vibration embedded controller. Methods: 1) The structure of the hydraulic vibration table control system is given, that is, two closed-loop controls. The bandwidth of the system is further broadened by the vibration control of the outer loop. Besides, the accuracy of vibration control is also improved. Then, the development needs of the vibration controller are put forward according to the detailed process of the power spectrum density replication. 2) An arithmetic processing unit is formed by using TI C2000 series DSP to calculate a large number of signal processing and a signal acquisition unit at high speed. In order to improve signal processing efficiency, the signal acquisition unit is used to perform preprocessing calculations (data acquisition and filtering) and vibration control calculations in a distributed manner. 3) Processing speed is further improved by taking full advantage of DSP software sources include lots of library functions and optimized assembly library functions. 4) The friendly operation of the controller and the safety monitoring of the experiment process are realized by the industrial computer served as the human-computer interaction unit. 5) Multi-CPU data sharing is achieved through using dual-port RAM to realize. Results: Through experiments, the developed embedded controller is fully estimated. The experiment shows that the developed hydraulic vibration table can realize real-time vibration control. Concerning the acceleration power spectrum density reproduction experiment, 256 acceleration response samples are calculated, and the update time is 4ms. The tracking accuracy of the timedomain waveform is controlled within 0.3%. Conclusion: The use of the developed embedded controller with signal conditioning equipment can achieve real-time control of the hydraulic vibration table, but the performance of the embedded controller can be promoted in advance, and the performance improvement of the hydraulic vibration table embedded controller can be studied from the following aspects: 1) The Fourier calculation is executed by the acquisition unit to share the calculation workload of the calculation unit; 2) The computing unit uses a signal processor chip with better performance, although this will bring development difficulties; 3) The monitoring computer can use an embedded controller with superior performance instead of an industrial computer to reduce the size, improve the performance; 4) The DSP real-time operating system should be used, and the task scheduling of vibration control experiments should be optimized.

Summary The expense of creating exhaust ventilation in a gross anatomy laboratory can be an impediment to gross anatomical education, especially in locations with little availability of funds (e.g., developing countries). Thus, the need for inexpensive yet effective exhaust ventilation is important for gross anatomical education. This study details the creation of a downdraft ventilation table that cost less than 200 USD to build, was built with commonly available materials (i.e., lumber, tarps, rebar, corrugated steel, staples, and screws), was built by one person with little difficulty in a matter of hours, was relatively light weight (75.2 kg fully-assembled), and was easy to transport. Further, the table was structurally sound and handled a load of at least 331 kg without damage. The table was affixed to a simple local exhaust ventilation system that cost ∼300 USD and generated an exhaust flow of 3099 m3/h from the table. The table was capable of removing all airborne formaldehyde (0.00 ppm) despite a pool of 100% formalin placed 20.3 cm above the table. Furthermore, the height of the table could easily be adapted for handicapped accessibility and for individuals who are shorter or taller than average. The downdraft system also has applications beyond the gross anatomy laboratory (e.g., exhaust ventilation for embalming, manufacturing, and clinical/surgical aerosol-generating procedures). This report represents a proof-of-concept: a downdraft table that costs less than 200 USD can be built easily and paired effectively with an inexpensive local exhaust ventilation system at a total expense of approximately 500 USD. This report marks an improvement in gross anatomy laboratory safety and accessibility.

The clotheslines used by the community are still in manual form so people still have to lift the clothesline directly. People who have a lot of interests or who work will not have time to lift the clothesline directly so they have to leave their more important work. People are still confused about how to lift clotheslines with the uncertain weather when there are other jobs or traveling. Based on these problems, a prototype model of an automatic clothesline was built using an Android-based Arduino Uno, this is to lighten and shorten the time in lifting clotheslines or drying clothes when the weather is changing. The purpose of this research is to make a tool that can help reduce household chores, especially drying clothes automatically using LDR sensors and rain sensors and can be controlled by cellphones. An automatic clothesline tool has been designed using an Android-based Arduino. In making the prototype using the LDR sensor as a light detector, using a water/rain sensor as a rainwater detector and using a servo motor to open and close the clothesline roof, and use the HC-05 Bluetooth module to move the clothesline roof with a cellphone using bluetooth which is controlled with an Arduino microcontroller. UNO which functions as a data processing center. After testing this tool works well, the sensor will check the weather outside whether it is sunny or rainy. When the weather is sunny or hot outside, the roof of the clothesline will automatically open and if it is raining outside, the roof of the clothesline will automatically close. When the water sensor and LDR sensor do not work or experience problems, the automatic clothesline can be controlled with a smartphone that is connected to the HC-05 Bluetooth module. The result of this research is that the automatic clothes drying device using Arduino Uno can ease household chores when drying clothes and based on the test results with the blackbox table the tool runs 100% as desired.

During Covid-19, manufacturing industries have faced problems due to lack of Remote Access system for manufacturing operation whereas IT sector has had a tremendous increase by leveraging the Remote Access system. In this paper, a Remote Access system is formed by integrating the existing technology such as SCADA (Supervisory Control and Data Acquisition), Microcontroller, OPC server, Internet, Sensor, and Actuator which facilitate controlling and monitoring manufacturing operation remotely. Sensor send operation data to Cloud via microcontroller (Arduino). Cloud computing processes the data and provides information to user in analytical form such as chat, graph, table etc., via HMI (Human Machine Interface). Through HMI the user monitors and controls the manufacturing operation by sending signal to actuator via microcontroller. This process integrated Human intelligent with machine capability. Viability of the proposed methodology is validated through simulation model design on Proteus and Wonderware Intouch. To find features and issues of Remote Access system we have done analysis of the simulation model and work done by different author in similar field. From this study, we realise that the Remote Access system is possible but it will not be effective until the infrastructure of IIoT (Industry Internet of Things) is developed.

Few studies of conflict analysis have analyzed the conflict situations from the perspective of the consistency degree of cliques. Quantifying the conflict degree is instructive for weakening or resolving conflicts. In this paper, we propose the improved Pawlak model of conflict analysis, a common consistency measurement is introduced to quantify the consistency degree of cliques, which explains the internal causes of conflict situation from a new perspective. In addition, the proposed consistency measurement reflects the fit between feasible strategy and clique, which inspires us to formulate the criteria for selecting feasible strategies in a three-valued situation table. Moreover, considering that many-valued ratings are more powerful and effective to describe vague information, a novel model of fuzzy conflict analysis is established with a fuzzy conflict function and a fuzzy consistency measurement in a fuzzy situation table, which could degenerate into the improved Pawlak model of conflict analysis. The criteria of selecting feasible strategies is illustrated by an NBA labor negotiation. Finally, the performance of proposed models is compared with other advanced models.

Global supply chains are kept viable through the information shared through billions of electronic documents, many of which extensively use tables to display critical information. Making effective supply chain decisions requires the extraction of data from these tables which is hindered by the variations in layouts and styles of tables. In this paper, we propose Table Det: a deep learning based methodology to solve table detection and table image classification in data sheet images in a single inference as the first stage of the table text extraction pipeline. TableDet utilizes Cascade R-CNN with Complete IOU (CIOU) loss and a deformable convolution backbone as its underlying architecture to capture the variations in scales and orientations of tables. It also detects text and figures to enhance its table detection performance. We demonstrate the effectiveness of training TableDet with a dual-step transfer learning process and fine-tuning it with Table Aware Cutout (TAC) augmentation strategy. We achieved the highest F1 score for table detection against state-of-the-art solutions on ICDAR 2013 (complete set), ICDAR 2017 (test set) and ICDAR 2019 (test set) with 100%, 99.3% and 95.1% respectively. For the table image classification task we attained 100% recall and above 85% precision on three test sets. This classification capability ensures that all images with tables would be promoted to the next step in the table text extraction pipeline, with a small number of images without tables making it through.

This paper presents a novel benchmark called the Asterisk Test that characterizes a hand's fingers' ability to translate an object on a table in eight linear directions, without moving the wrist, in a controller, object, and hand agnostic manner. The benchmark also enables a measure of the symmetry~(about the plane's principal axes) of the hand's ability to maneuver objects. The Asterisk Test's utility is demonstrated on two generic robot hand designs: a parallel jaw gripper and a two-linked, two fingered gripper. The method to analyze the test data in order to evaluate the hand is also provided. We conclude with a comparison of this benchmark to previous dexterity measures, such as manipulability. We also discuss how improved performance in this benchmark is indicative of simpler hand control.

In this letter, we introduce acentralized planner with low computational cost to schedule the motions of multiple Automated Guided Vehicles (AGVs) at the intersection of pre-defined polynomial curves. In particular, we find that the collision conditions between two AGVs along polynomial paths can be formulated as a set of polynomial inequalities. Furthermore, by solving these inequalities, the continuous boundaries of potential collision areas for vehicles can be determined offline and stored in a table. During the online phase, by also taking into account the priority setup among AGVs, the planner will use efficient table lookup to determine a list of intermediate goals for each AGV to move toward based on their real-time position feedback. In this way, the multiple robots are able to navigate on polynomial guide paths safely and efficiently at the crossroad, and the performance of our approach is demonstrated in a number of simulated scenarios. Videos of the experiments are available at https://sites.google.com/view/zqzhang/agvsplanner .

Low-rate Denial of Service (LDoS) attacks cause severe destructiveness to network security. Consequently, the implementation of detection and defense against them is a concern among the research communities. But it is formidable to deploy extension modules to detect and mitigate attacks online in traditional networks, because devices are deficient of flexibility and scalability. To address the problem, we design and implement an online attack detection and mitigation system (ADMS) framework via the scalable and programmable Software Defined Networking (SDN). ADMS is installed on SDN controllers and conforms to the OpenFlow policy without extra devices. ADMS consists of two modules: the two-phase detection module and the mitigation module. The two-phase detection module combines the new port traffic feature and the Lightgbm classifier based on flow table statistics traffic to precisely detect LDoS attacks. The mitigation module utilizes the novel Sequence Matching based Dynamic Series Analysing (SMDSA) algorithm to locate the attacker, and efficiently mitigates attack traffic by packet filter. The SMDSA algorithm distinguishes the victim port from benign ports by calculating the anomaly score of each port. Our evaluation on a prototype implementation of ADMS shows that the framework is able to precisely identify and efficiently mitigate LDoS attacks in real-time.

Small scale organizations strive to achieve maximum output with limited availability of resources. An effective plant layout plays a significant role in enhancing the overall productivity and efficiency of an organization. Using a fixture for holding a job ensures accurate alignment and reduces defects in finished components. This paper discusses the implementation of an optimized plant layout and designing a fixture for welding of pipes. The existing plant layout had unused spaces and unscientific arrangements of machines. There was a need for a fixture which would reduce the defects caused due to alignment errors during welding. This could be achieved by the use of a fixture table, supporting unit and clamping unit. The use of weld-fixture reduced the rework from the existing 10% to 5%. The proposed plant layout computed using CRAFT simulation tool reduced the material travel distance. This resulted in the reduction of material handling costs by 15%.

The conception and treatment of complex classifications or typologies (as hierarchical tables), mainly of nature components, has for long constituted a major concern for researchers. Hence, several codification methods were developed in order to address and facilitate the management of such tables. Most of these methods uses alphanumeric codes, that remain specific to each case (type of entity), in the sense that their transposition to other cases is rarely feasible. This article proposes a new standardized codification method, applicable to various hierarchical schemas. Implemented in the development of a complex system of biodiversity data management, this method consists in creating for each table a fixed number of levels, coded using the same type of strings, based on ’numeric characters’. This method makes it possible to manage different tables with the same module and facilitates the automatic incrementation and updating of the code (=position). The new model has the advantage of offering possibilities to generate, update or delete a code, without disrupting the codes of the other elements, in addition to the gain in response time of the requests. It gives hope that in some cases (as geo-databases) to merge different tables whose merger was not previously obvious.

Visualizing data in sports videos is gaining traction in sports analytics, given its ability to communicate insights and explicate player strategies engagingly. However, augmenting sports videos with such data visualizations is challenging, especially for sports analysts, as it requires considerable expertise in video editing. To ease the creation process, we present a design space that characterizes augmented sports videos at an element-level (what the constituents are) and clip-level (how those constituents are organized). We do so by systematically reviewing 233 examples of augmented sports videos collected from TV channels, teams, and leagues. The design space guides selection of data insights and visualizations for various purposes. Informed by the design space and close collaboration with domain experts, we design VisCommentator, a fast prototyping tool, to eases the creation of augmented table tennis videos by leveraging machine learning-based data extractors and design space-based visualization recommendations. With VisCommentator, sports analysts can create an augmented video by selecting the data to visualize instead of manually drawing the graphical marks. Our system can be generalized to other racket sports (e.g., tennis, badminton) once the underlying datasets and models are available. A user study with seven domain experts shows high satisfaction with our system, confirms that the participants can reproduce augmented sports videos in a short period, and provides insightful implications into future improvements and opportunities.

Aims: Across higher education, systems and policies explicitly address the impact of research. This paper contributes to the impact and engagement discussion from a regional, rural and remote perspective. We focus on how impact and engagement fit with regional, rural and remote research and explore strategies that can be employed to enhance impact and engagement in a rural health research context. Context: The impact agenda in Australia is a response to a worldwide call for demonstrable change or potential for change resulting from university research. As funding models evolve to integrate impact, there are increased pressures for universities and academics to plan for, evidence and report on it. The current lack of focus on impact in regional, rural and remote research may further disadvantage regional, rural and remote researchers’ prospects for career progression and funding opportunities. Approach: Ignoring or avoiding impact will marginalise rural researchers and research. We discuss the definitions of impact and engagement as they apply to rural research and argue that engagement and impact must be commensurate with employment conditions. To platform regional, rural and remote impact, we provide strategies to assist researchers and administrators in building impact and engagement into their research and academic culture. Conclusion: The message to researchers is that impact is here to stay. The high levels of rural engagement can lead to impact, but we need to be clever at providing clear evidence to make that visible.

This paper investigates the effects of Chongqing’s rural and urban residents and total resident population on economic development based on the residents’ consumption structure and analyses of economic development theories concerned by using the input-output table of Chongqing during 2002–2017 and SDA (Structure Decomposition Analysis) model. The study found that, compared with the previous years, the direct consumption of the primary industry’s unit output to the industrial products has decreased significantly in 2017, while the direct consumption to the tertiary industry has increased significantly; The direct consumption per unit output of the second industry is basically equal to that of the products of the industry, while the direct consumption of the products of the third industry has increased; The direct consumption per unit output value of the tertiary industry is basically equal to that of the primary industry. In the long run, the changes in consumption structure of rural and urban residents and total resident population and the increase in proportion of tertiary industry accelerate the transformation and upgrading of industrial structure. However, the effect of consumption structure on GDP (Gross Domestic Product) varies from year to year. On the whole, the changes of residents’ consumption have a positive effect on GDP (Gross Domestic Product).

Combined-permutation representations (CPRs) for characterizing -skeletons (a benzene skeleton, a Haworth-projected skeleton, a superphane skeleton, and a coronene skeleton) are constructed by starting from respective sets of generators, where the permutation of each generator is combined with a mirror-permutation of 2-cycle to treat both achiral and chiral substituents under the GAP system. Thereby, the CPR of degree 8 (= 6 + 2) for the benzene skeleton, the CPR of degree 14 (= 12 + 2) for the Haworth-projected skeleton, the CPR of degree 14 (= 12 + 2) for the superphane skeleton, the CPR of degree 14 (= 12 + 2) for the coronene skeleton are generated to give primary mark tables (tables of marks) based on these CPRs. These primary mark tables generated by the GAP system are different in the sequence of subgroups from each other, although they stem from the same point group . They are unified into a single standard mark table by means of a newly-devised GAP function MarkTableforUSCI. Moreover, another newly-devised GAP function constructUSCITable is employed to construct a standard USCI-CF (unit-subduced-cycle-index-with-chirality-fittingness) table concordantly. After a set of PCI-CFs (partial cycle indices with chirality fittingness) is calculated for each skeleton, symmetry-itemized combinatorial enumeration is conducted by means of the PCI method of Fujita’s USCI approach (S. Fujita, Symmetry and Combinatorial Enumeration in Chemistry, Springer-Verlag, Berlin-Heidelberg, 1991).

The performance-driven design of SDN architectures leaves many security vulnerabilities, a notable one being the communication bottleneck between the controller and the switches. Functioning as a cache between the controller and the switches, the flow table mitigates this bottleneck by caching flow rules received from the controller at each switch, but is very limited in size due to the high cost and power consumption of the underlying storage medium. It thus presents an easy target for attacks. Observing that many existing defenses are based on simplistic attack models, we develop a model of intelligent attacks that exploit specific cache-like behaviors of the flow table to infer its internal configuration and state, and then design attack parameters accordingly. Our evaluations show that such attacks can accurately expose the internal parameters of the target flow table and cause measurable damage with the minimum effort.

In its current form, the Radiation Oncology Model (RO Model) prioritizes payment cuts over true value-based payment transformation. With significant modifications to the payment methodology, the reporting requirements, and recognition of the unique challenges faced by disadvantaged populations, the RO Model can protect patient access to care, preserve the physician-patient decision-making process, and ensure the delivery of high-quality, efficient radiation therapy treatment. The American Society for Radiation Oncology has spent several years advocating for a meaningful alternative payment model for radiation oncology and continues to push The Center for Medicare and Medicaid Innovation for changes to the RO Model that will recognize these key outcomes.

Understanding the earthquake behavior of structures is the first step towards developing a strategy for earthquake-resilient design and construction of the built environment. The growing number of earthquake simulators (shake tables) globally has allowed researchers to closely study the response of different building types when subjected to simulated earthquake shaking. Typically, such simulators are sophisticated and complex testing apparatus that require high levels of skill and experience for their effective operation and are associated with high costs of installation, operation, maintenance, and repair. In developing countries where there is limited investment in research, the application of such tools to meet the current need for experimental campaigns is generally not feasible, and hence alternative tools and methods are sought. In this context, a detailed review into alternative cost-effective tools and methods such as shock tables, harmonic shake tables, and controlled underground explosions for experimental testing was undertaken and is reported herein. Furthermore, the design, detailing, and construction of a shock table and a harmonic shake table are presented.

The increased flash page sizes cause a large number of subpage requests due to the difference in host and flash I/O units. The subpage requests may degrade the space utilization, response time, and lifetime of NAND flash memories. Addressing the subpage issue, a few studies in the past have proposed merging subpages to generate full pages. Although these subpage schemes may improve performance and lifetime, they incur immense DRAM space for storing the sector information of merged pages. Moreover, they do not consider the update frequencies of the subpages for merging and thus an update request to a subpage causes partial page invalidation, which leads to garbage collection (GC) overhead. To address these issues, our proposed scheme considers the update frequencies of the subpages for merging in order to avoid partial page invalidation, which in turn improves the GC efficiency. Further, the proposed scheme uses a sector information table (SIT) in flash pages to store the fine-grained sector information of merged subpages. In the light of experiment results, our scheme, on average, reduces DRAM footprint, flash writes, and block erasures by 29%, 18%, and 13%, respectively.

OBJECTIVES There is a pressing need to improve safety and efficiency in the operating room (OR). Postsurgical adverse events, such as surgical site infections and surgical flow disruption, occur at a significant rate in industrial countries where a considerable portion of such complications result in death. The aim of the study was to identify an ideal room design that improves the flow of staff members using risk and safety performance measures. METHODS Operating room designs were compared by using computer simulation modeling to analyze traffic flow inside an OR. The study was conducted in two phases. A historical data set was first created based on surgical flow data obtained from 23 video observations of actual surgical procedures. A detailed simulation-based model was then developed. RESULTS As room size increases, staff members have more available space to maneuver in the room, resulting in more distance walked but far fewer undesirable contacts. An angled table orientation is preferred with the circulating nurse workstation at the foot of the OR table, as it provides more space for staff to move across the room without increasing the number of contacts. Furthermore, when the nurse workstation is near the wall, staff members experience fewer undesirable contacts. CONCLUSIONS Simulation modeling was used to assess the impact of OR layout alternatives on three performance metrics, and the medium-sized OR prototype performs well across the metrics. Future research will consider the relative influence of several factors on traffic-based safety and efficiency performance metrics, resulting in a more predictive simulation design model.

Accurate identification of table grapes is crucial to the harvesting process of the grape picking robot. This paper proposes an efficient grape detection model, YOLO-Grape, to solve the problem of unrecognition or decreased recognition accuracy caused by the complicated growth environment, shadows of branches and leaves, and overlapping grapes. To improve the network recognition accuracy, a down-sampling fusion structure is integrated into the network, and the Mish activation function is used. Meanwhile, an attention mechanism is added to the network, and the non-maximum suppression (NMS) function is replaced with the soft non-maximum suppression (Soft-NMS) function, thereby reducing the missing of predicted boxes due to overlapping grapes. Besides, the depthwise separable convolution is introduced to improve the detection speed of the network. In addition, transfer learning is used in the training process to improve the detection accuracy and generalization ability of the model. On the test data set of 700 grape images, the experimental results show that YOLO-Grape achieves an F1-score of 90.47%, a mAP of 91.08% and a detection speed of 81 frames per second. Compared with Faster-RCNN(Resnet50), SSD300, YOLOv4, and YOLOv4-tiny, the mAP of the YOLO-Grape model is increased by 1.67%, 2.28%, 0.84%, and 6.69%, respectively. The average recognition speeds of the YOLO-Grape model were 31.15, 3.38 and 6.45 times of Faster-RCNN(Resnet50), SSD300, and YOLOv4 respectively. Through four sets of comparative experiments, it is found that the proposed YOLO-Grape model achieves high recognition accuracy for occluded grapes, meeting the requirements of grape picking robots for real-time detection of multiple varieties of table grapes in complex situations.

The technique of backhand topspin against backspin is important for table tennis players to gain more advantages in the confrontation. In this paper, a biomechanical analysis of backhand topspin against backspin was conducted with varsity and non‐varsity male table tennis players from Zhejiang Changzheng Vocational and Technical College. The QUALISYS infrared acquisition system collected the changes in the athletes’ limb movements, and the force platform collected the changes in the athletes’ limb moments in the ball striking process. The results showed that professionally trained athletes were able to achieve greater joint angles and provide greater torques to the shoulder, elbow and wrist joints at the moment of batting. The main purpose of this paper is to provide data reference for the improvement of backhand stroke technique by studying the pattern of limb movements of players when they perform backhand stroke. In summary, in order to improve the backhand technique of hitting backspin, athletes need to focus on training the shoulder, elbow and wrist joints to achieve greater variations of angles and greater torques. The novelty of this paper is collecting the body movements of backhand strokes in a more concise and fast way with the QUALISYS infrared acquisition system.

There are still many parents who do not have sufficient understanding in terms of toddler disease. One way to provide education is the availability of a system that can be used for consultation based on the symptoms of illness experienced by toddlers and the actions needed to overcome them. The system that will be built is an expert system that can relatively provide suggestions for solutions to children's health problems using the Case Based Reasoning (CBR) method. namely an expert system that uses case-based reasoning methods, namely looking for similarities of a disease compared to a disease that has existed before. In this study, the CBR method was combined with a weighting process using the pairwise comparison method which was within the scope of the AHP (Analytic Hierarchy Process) method. In comparing consultations with old diseases that already exist in the system, and looking for similarities from the comparison results, the Sorensen similarity algorithm is used. This study resulted in weights with 3 symptom categories, namely mild symptoms with a weight of 0.09, moderate symptoms with a weight of 0.24 and severe symptoms with a weight of 0.67 and will recommend several diseases with a similarity above 0.5 and diseases with a similarity below 0.5 will be entered into the revise table to find a solution.

Objective This scoping review will assess the literature that documents or utilizes patient journey mapping methodologies in health care settings. It will also examine the reporting processes of studies that use this methodology. Introduction Health care systems are complex and can be challenging for patients to navigate. Using patient journey mapping as a research method promotes a deeper understanding of patient experiences when navigating these systems. Patient journey mapping provides valuable insights into where systems are working well, where gaps in care exist, and how the system could respond to these gaps. Inclusion criteria This review will consider peer-reviewed articles and publicly available academic literature documenting patient journey mapping methodologies. The review will also consider studies providing guidance and recommendations on how to report patient journey mapping studies in health care services and systems. Methods The proposed review will follow JBI guidance for scoping reviews. The following databases will be searched: MEDLINE, Embase, Emcare, PsycINFO, Scopus, Web of Science Core Collection, the Directory of Open Access Journals, Informit, and ProQuest Dissertations and Theses Global. The search will not be limited to year of publication but will be limited to studies reported in English. The PRISMA-ScR extension will be used to document the literature search. Two reviewers will screen titles, abstracts, and full-text articles. An extraction table will be used to extract relevant data from all included articles and to facilitate data analysis.

Akibat kebutuhan indikator dan data ekonomi secara terkini, maka diperlukan estimasi yang mencerminkan kondisi perekonomian daerah dalam masa pandemi COVID-19. Oleh karena itu, tujuan paper ini adalah untuk menghasilkan estimasi matriks transaksi antar sektor yang merupakan bagian dari tabel input-output. Data yang digunakan dalam penelitian ini adalah tabel input-output tahun 2016 dan PDRB tahun 2020 yang bersumber Badan Pusat Statistik Provinsi Banten. Metode yang digunakan untuk estimasi adalah matrix transformation technique. Hasil penelitian ini menunjukkan metode matrix transformation technique (MTT) mudah diterapkan dengan data yang terbatas. Adapun matriks transaksi antar sektor hasil estimasi dengan MTT mampu menyerap informasi terkini. Walaupun, masih ada informasi lama tentang struktur yang termuat didalamnya. Berdasarkan perbandingan antara matriks transaksi antar sektor tahun 2020 hasil estimasi terhadap matriks transaksi antar sektor tahun 2016, terlihat dampak COVID-19 menurunkan kinerja produksi pada berbagai sektor.

El presente trabajo consiste en el estudio de herramientas que permiten configurar un entorno de simulación o emulación de redes dentro de un mismo sistema facilitando de cierta forma plantear un escenario de red que cuenta con topologías y flujos de tráfico. Específicamente se enfocó en el modelado de tráfico en redes SDN (Redes Definidas por Software) que permite que un solo equipo administre una red en su totalidad, haciéndolo capaz de tolerar cambios en toda la estructura de la red sin necesidad de detener los servicios. Se realiza una investigación bibliográfica de fuentes de carácter documental sobre simuladores que permiten el modelado de redes para determinar la más adecuada; los instrumentos analizadas fueron: NS-3, EstiNet y MiniNet. Posteriormente de acuerdo a la información obtenida y el estudio del mismo, se realizó una tabla comparativa con los parámetros que distinguen a cada una, permitiendo de esta forma concluir de manera idónea la mejor opción para emulación de topologías en ambientes SDN.

The “BENIN TERMINAL” machines are maintained by company technicians who encounter difficulties in the operations carried out on these machines. In fact, it is about improving the procedure for installing and removing engines and gearboxes for BENIN TERMINAL mobile vehicles through the study and design of a single scissor lift table. It has a lifting capacity of 2 tons, a width of 900 mm, a total length of 1900 mm and a maximum height of 2000 mm using a hydraulic system. It works with 12 V batteries, simple and height-adjustable workspace. The lifting table also allows certain operations requiring an average height to be carried out.This device was developed for the BENIN TERMINAL garage in order to reduce the efforts and risks encountered by technicians when installing or removing engines and gearboxes on certain machines, in particular heavy machines such as Reach Stackers and 16ton forklifts.

The purpose of this study is to examine the usage of digital book media in the development of explanatory texts for students in the sixth grade of primary school. The experimental design employed in this study was a one-group pretest-posttest design. Test in command questions is used to collect data, which is then used to produce explanatory texts utilizing digital book media. The paired sample t-test on the SPSS Version 22 system is used for this normality test, and the results are presented in the following table. The results of the study revealed that the pre-test mean was 66.11. In contrast, the post-test mean was 82.78, indicating that the post-test score was more dominant than the pre-test based on descriptive statistical analysis approaches. H0 is rejected, while H1 is approved, indicating an effect of utilizing digital book media on writing skills in the sixth grade of elementary school, according to the findings of the study.

Due to the large variable design space in optimization problems of composite laminates, it remains one of the challenging tasks to develop efficient optimization design methods to improve the design flexibility and efficiency. This work presents a sequential permutation table (SPT) method for the multiobjective optimization design of two-material hybrid composite laminates with simply supported boundary conditions, which maximizes the fundamental frequency and minimizes the cost/weight. Based on the vibration analysis of hybrid composite laminates, the approximate linear regularity of the square of fundamental frequency is derived, and two best ply orientations for the two materials are identified, respectively. By assigning one best ply orientation with maximum fundamental frequency at respective stacking positions, and using another best ply orientation to replace plies in the stacking sequence from the mid-plane to the outermost can lead to the optimum. Two multiobjective optimization problems are employed to verify the SPT method, results are compared with those obtained by heuristic algorithms. The obtained better solutions demonstrate the effectiveness and efficiency of the SPT method and its potentials for optimal design of hybrid composite laminates.

Where the number of new student registrants at the Sinar Harapan Private Vocational School is unstable every year and the school has difficulty predicting how many new student registrants will be in the coming year and preparing extracurricular activities such as English/computer training or the best facilities for new students such as chairs, tables, classrooms and so on, as well as the competitiveness of private schools in the district. banyan. So we need a system that can dig up data and help predict the number of new student registrants, using data mining techniques, namely the Rough Set Algorithm which aims to get a short rule estimate from a table, in this study using student registration data in 2018, 2019, 2020. By applying data mining with the rough set algorithm and carrying out the rough set stages, it can produce decisions in the form of generating rules (knowledge), and the results of the calculation analysis are 152 students to predict the number of students in the coming year.

Fog computing needs, particularly in terms of performance, availability and reliability, are increasing every day due to the rapid growth in the number of connected Internet of Things devices and, consequently, the quantitative explosion in the volume of data generated. This study aims to improve the management of collected data to maximize the performance of Fog computing. To this end, a dynamic architecture for the distributed storage of collected data in Fog environments, based on Fog collaboration, is proposed. Dynamicity is related to the Fog and sensors mobility, but distribution is related to data storage in Fog computing resources. In addition, a supplementary Fog layer and a Fog assignment table are used for a good achievement of the proposed architecture and efficient management of Fog sensor associations. The simulation experiments show that the collaborative distributed storage significantly improves the performance of the Fog in terms of data availability and end-user latency. Subsequently, the proposed solution minimizes the number of queries to the cloud.

In this paper, we present a class of integer code capable of correcting unidirectional solid bursts. A brief implementation in a quad core processor is discussed along with its memory consumption. Further, a comparison is done with linear codes and integer codes correcting similar types of errors. Codes discussed here use integers and table look ups which makes them suitable for software implementation in all processors. Also, these codes can be interleaved without the use of any additional hardware.