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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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

Augmented Human (AH) is a research field enhancing human physical abilities or supporting human activity using advanced technologies. As one of the AH approaches, previous studies have attached an actuator to a human body or tools used for an activity. The attached actuators are used to control their movements to support an activity. In this study, instead of attaching actuators, we propose to directly apply noncontact ultrasound force to a lightweight tool to manipulate it. The advantage of using noncontact force is that users do not need to wear a specific device and to process tools used for the activity. As a proof-of-concept system, we developed an ultrasound-based curveball system by which table tennis players can shoot a curveball regardless of their physical ability. In the system, a moving ping-pong ball (PPB) is a target tool for remote manipulation. The system curves the trajectory of a moving PPB by continuously focusing ultrasound on it. Users can control the curve timing and the curve direction (left or right) using a racket-shaped controller. In the user study, we conducted an actual table tennis match using the curveball system and qualitatively confirmed that the player using the system had the upper hand. Another user study using a ball dispenser quantitatively showed that the ultrasound-driven curveball increased the number of mistakes of the opponent player 2.95 times. These results indicate that the proposed concept is feasible.

Generating fluent, coherent, and informative text from structured data is called table-to-text generation. Copying words from the table is a common method to solve the “out-of-vocabulary” problem, but it’s difficult to achieve accurate copying. In order to overcome this problem, we invent an auto-regressive framework based on the transformer that combines a copying mechanism and language modeling to generate target texts. Firstly, to make the model better learn the semantic relevance between table and text, we apply a word transformation method, which incorporates the field and position information into the target text to acquire the position of where to copy. Then we propose two auxiliary learning objectives, namely table-text constraint loss and copy loss. Table-text constraint loss is used to effectively model table inputs, whereas copy loss is exploited to precisely copy word fragments from a table. Furthermore, we improve the text search strategy to reduce the probability of generating incoherent and repetitive sentences. The model is verified by experiments on two datasets and better results are obtained than the baseline model. On WIKIBIO, the result is improved from 45.47 to 46.87 on BLEU and from 41.54 to 42.28 on ROUGE. On ROTOWIRE, the result is increased by 4.29% on CO metric, and 1.93 points higher on BLEU.

Data envelopment analysis (DEA) is a useful tool for measuring the relative efficiencies of participating nations in the Olympic Games. DEA models with restricted multipliers have been used to refine efficiency evaluations by imposing additional information. Existing DEA models for evaluating Olympic medals do not focus on multiplier restrictions regarding input. To fill this research gap, this study incorporates a data fitting technique of medal prediction using ordinary least squares regression in input multiplier restrictions of the conventional DEA model. We show that the efficiency of the proposed model can be decomposed into the achievement ratio of substantial medal total and the unit value index of medals. Such decompositions can be used to analyze the effectiveness of host nations and athlete development initiatives. For an illustrative empirical application, we examine the target that the Brazilian Olympic Committee (BOC) set for the 2016 Summer Olympic Games (Rio 2016). Our results explain the extremely high feasibility of Brazil’s target of being in the top 10 medals table in Rio 2016.

BackgroundThe purpose of this study is to investigate the role of customer clustering in the design of an ethical and targeted marketing model in Internet of Things (IOT) Technology Services Companies.MethodThe research method is applied, exploratory and mixed (qualitative-quantitative). Qualitative section: 15 people of sales and marketing managers of IOT companies, were selected for in-depth interviews by targeted and snowballs methods. In this phase used entropy and VIKOR decision-making techniques. The software used in this phase was Max QDE. Quantitative section: In this phase, all the customers of the studied companies were included, and due to the unlimited nature of the society with Morgan's table, 384 people were selected as the sample size by non-random and available methods. The data collection tool in this section was questionnaire, which used Cronbach's alpha to examine the validity of the questionnaire. In order to analyze the data, the exploratory factor analysis method and Partial least squares structural equation modeling (PLS-SEM) with Smart-PLS2 and Liserl software were used.ResultsQualitative section: In this phase, four clusters were identified: communication factors, ethical and behavioral factors, individual factors and economic factorsQuantitative section: In this phase, the model obtained in the first phase was quantitatively examined and validated and approved.ConclusionThe results showed that four main clusters: communication factors, ethical and behavioral factors, individual factors and economic factors are dimensions of targeted marketing and customers are classified according to their characteristics. So, these companies should pay attention to these items as methods for sales promotion.

The paper explores a novel way to solve the multi-attribute decision-making issues under the hesitant fuzzy environment (HF-MADM) with three-way decision (3WD) theory. Firstly, according to the nature of the relative loss function (RLF), the RLF under the hesitant fuzzy (HF) environment is defined. Then, according to the practical significance of the loss function, this paper establishes the relationship between the loss function and the evaluation value. At the same time, considering that the HF-MADM has multiple attributes and multiple evaluation values, we provide an aggregated loss function via the hesitant fuzzy weight average (HFWA) operator to reflect the overall loss of the alternative. We establish the mixed information table (HF-MADMRLF) based on the overall loss function. Secondly, based on an outranking function and a distance from the positive ideal (PI) solution, this paper defines an estimation on the conditional probability method. Finally, we utilize the presented method to solve actual medical diagnosis of pneumonia (MDP) issue, and prove the validity and applicability of the method through comparison with several representative methods and experimental evaluations.

Mebel Sumber Jati is an organization that sells furniture items like teak closet, teak table, teak wood seats, spring bed, aluminum glass cabinet, sofa, and eating table. The issue is the deals of this organization continues to decrease since the pandemic occurred. That is the reason behind why this organization actually struggles to get new clients. Nonetheless, the organization intends to grow its objective market, particularly during this pandemic. The arrangement is by extending the objective business sectors through Facebook with an online inventory. On Facebook, the organization will combine the photograph items and the cost just as on the online list. The online catalogue will be distributed on the Facebook marketplace page as a connection. The catalog was made using the theory of Bethina Oksen Bendroff, 2021 Therefore, by having a Facebook with an online list, Mebel Sumber Jati will actually be able to extend their new objective market. Keywords: Facebook, Online catalogue, Expanding target market

This study aims to implement the database design used in thesis data processing using Flask. The results of the database design produce four tables, namely the lecturer table is used to store lecturer data, the student table is used to store student data, the title of thesis table is used to store data related to student thesis and the guidance table contains history during guidance with the supervisor, The design of the thesis data processing database was developed using Flask. Flask is a web framework written in Python. Flask serves as the application framework and the interface of the web-based flask application. In this research, the methodology used is to implement database development which consists of system analysis, logical design, physical design and implementation. The database design methodology is carried out by 1. Building a local conceptual data design based on user views, 2. Building and validating local logical data models, 3. Building and validating logical data models, 4. Translating logical data models for the database management system, 5. Designing and implementation of physical representation. The results show that the process of creating a thesis data management database can be done using the Flask framework. The development process using the flask framework includes the process of creating databases, tables and reading, adding, repairing and deleting data. In making the application, the application is divided into 2, namely the application used for database management and the application used to display website-based results that are used to display the results of data processing from the application. Implementation of data structures in the database design and applications used include programming language: Python 3.7.0, framework for displaying web-based data: Flask 1.1.2, and database management system using SQLite.

The English grammar question bank can reserve a large number of special knowledge points and special categories of questions, which is helpful for English learners. Therefore, we design and verify the application effect of an intelligent question bank system. We construct an English grammar knowledge map, which is used to design the system architecture, including basic layer, data layer, service layer, business layer, and user layer. On the basis of the system structure, the index system of the item bank is established, and the functional modules of the system are designed comprehensively. Finally, we design a system database based on MySQL and give the table of knowledge points of English grammar. In order to verify the performance of the designed English grammar intelligent test bank system, a verification experiment is carried out. The experiment selects the accuracy rate of English grammatical feature extraction, recall rate, convergence, and system configuration accuracy. The experimental results show that the proposed system can extract English grammatical features with higher accuracy, and the recall rate is more satisfactory. Compared with the reference systems, the designed system configuration accuracy is higher.

The introduction of green plants in indoor spaces has raised a great amount of interest motivated by plants’ supposed capacity to improve the quality of indoor built environments. Subsequent studies have covered a broad range of topics, testing plants in indoor environments for their climate-mitigating effects, acoustic benefits, potential energy savings and the enhancement of the indoor microbial communities. Despite the diversity of focus in these studies, no major breakthroughs have been made involving the use of plants in indoor environments after nearly thirty years of research. To identify major inconsistencies and gaps in the research, this review, of an explorative nature, presents an analysis of plant-related parameters reported in 31 cases of experimental research involving the use of plants in indoor environments. The papers were identified by searching the online databases Google Scholar, ResearchGate, Scopus and MDPI and were selected based on their relevance to the topic and diversity of focus. Two classifications in table form provide an overview of the 38 plant-related parameters used in the reviewed research. The conclusions drawn from the analysis of the tables highlight a strongly anthropocentric frame of reference across the majority of the studies, which prioritize human and experimental convenience above plant physiology, and display an overall scarcity and inconsistency in the plant-related parameters reported.

In our time, the written language is undergoing significant changes, which is associated with the emergence of new technology, equipped with special tools for remote communication. With the help of gadgets, you can send a message at any time without making any efforts, however, this communication format is increasingly reflected in the structure of the statements themselves: they are becoming shorter and more capacious in content, while regulatory requirements, as a rule, are not observed. With the emergence of the sphere of Internet communications we began to observe the transformation of the main types of communication: the boundaries between written and oral forms are increasingly blurred, which is especially clearly seen in the analysis of messages in blogs, chat rooms, on forums when discussing any legislative or regulatory acts. Internet communication is becoming a new form of perception of the general picture of the world, the language game predetermines the trajectory of changing the consciousness of Internet users. In order to identify problem areas in this area, a sociological study was carried out, the results of which are presented in the table.

Motion analysis in sports can help athletes and coaches as material for evaluating movement in improving movement and improving athlete performance with a predetermined training program. The purpose of this study was to analyze the motion of the topspin technique in table tennis. This research is a qualitative research by describing the results of the video analysis of the topspin technique movement which is accessed from youtube, then using the Kinovea application instrument. The subjects in this study were the top ranked players, which consisted of five of the best male athletes at the world level in the table tennis game. Based on the analysis data above, it was found that the average bending of the elbow at the ready position was 92.80, the swing position before hitting the ball was 142.40, when hitting the ball was 117.80, and after hitting the ball was 73.40. The results of the average elbow distance from the center point when the ready position is 68.728 cm, when the swing position before hitting the ball is 23.532 cm, when hitting the ball with a distance of 50.88 cm and during further motion 150.768 cm. The results of the analysis of the inclination angle of the body when the ready position is 161.60, when swinging the hand 152.60, when hitting the ball 150.60, and for further motion with a body inclination of 1660. The results of the analysis of the bending of the right leg when the position is 149.80, the position of swinging the right leg 125.40, and when the ball hits it forms an angle of 125.60 and when it continues to move 42.60. The average results of the analysis of the left leg bending angle when the ready position is 151.20, the swinging position with the left leg bending is 126.20, in the position of the ball hitting an angle of 130.40, and accompanied by a follow-up motion to form the left foot angle of 1460. The average foot distance when hitting the topspin, in the ready position is 186 cm, during the backswing the foot distance is 196.638 cm, and when hitting the ball is 198.81 cm, and accompanied by a follow-up motion of 195.886 cm. Biomechanical analysis of the topspin technique from several stages starting from the ready position to the advanced motion carried out by each athlete according to their respective body anatomy and following the position when hitting the ball.Analisis biomekanika teknik topspin pada permainan tenis mejaAbstrakAnalisis gerak pada olahraga dapat membantu atlet dan pelatih sebagai bahan evaluasi gerakan dalam memperbaiki gerakan dan meningkatkan performa atlet dengan program latihan yang telah ditentukan. Tujuan penelitian ini ialah menganalisis gerak teknik topspin dalam permainan tenis meja. Penelitian ini merupakan penelitian kualitatif dengan mendeskripsikan hasil analisis video gerakan teknik topspin yang diakses dari youtube, kemudian menggunakan instrumen aplikasi Kinovea. Subyek dalam penelitian ini men top ranked players yang berjumlah lima orang atlet putra terbaik ditingkat dunia pada permainan tenis meja. Berdasarkan dari data analisis diatas ditemukan nilai rerata tekukan siku pada saat posisi siap 92,80, posisi ayunan sebelum memukul bola 142,40, saat memukul bola 117,80, dan sesudah memukul bola sebesar 73,40. Hasil rerata jarak siku dari titik pusat saat posisi siap 68,728 cm, saat posisi ayunan sebelum memukul bola 23,532 cm, saat memukul bola dengan jarak 50,88 cm dan saat gerak lanjutan 150,768 cm. Hasil analisis sudut kecondongan tubuh saat posisi siap 161,60, saat mengayunkan tangan 152,60, saat memukul bola 150,60, dan untuk gerak lanjutan dengan kecondongan tubuh 1660. Hasil analisis tekukan kaki kanan saat posisi 149,80, posisi mengayunkan kaki kanan 125,40, dan saat perkenaan bola membentuk sudut 125,60 dan saat gerak lanjutan 42,60. Hasil rerata analisis sudut tekukan kaki kiri saat posisi siap 151,20, posisi mengayungkan tangan dengan tekukan kaki kiri 126,20, pada posisis perkenaan bola membentuk sudut 130,40, serta diiringi dengan gerak lanjutan membentuk sudut kaki kiri 1460. Hasil rerata jarak kaki saat melakukan pukulan topspin, pada posisi siap 186cm, saat backswing jarak kaki 196,638 cm, dan saat perkenaan bola 198,81 cm, serta di iringi gerak lanjutan 195,886 cm. Analisis biomekanik teknik topspin dari beberapa tahapan dimulai dari posisi siap hingga gerak lanjutan yang dilakukan masing-masing atlet sesuai anatomi tubuh masing-masing serta mengikuti posisi saat perkenaan bola.

The digital transformation of business in the light of opportunities and focusing on the challenges posed by the introduction of Big Data in enterprises allows for a more accurate reflection of the internal and external environmental stimuli. Intuition ceases to be present in the decision-making process, and decision-making becomes strictly data-based. Thus, the precondition for data-based decision-making is relevant data in digital form, resulting from data processing. Datafication is the process by which subjects, objects and procedures are transformed into digital data. Only after data collection can other natural steps occur to acquire knowledge to improve the company's results if we move in the industry's functioning context. The task of finding a set of attributes (selecting attributes from a set of available attributes) so that a suitable alternative can be determined in its decision-making is analogous to the task of classification. Decision trees are suitable for solving such a task. We verified the proposed method in the case of logistics tasks. The analysis subject was tasks from logistics and 80 well-described quantitative methods used in logistics to solve them. The result of the analysis is a matrix (table), in which the rows contain the values of individual attributes defining a specific logistic task. The columns contain the values of the given attribute for different tasks. We used Incremental Wrapper Subset Selection IWSS package Weka 3.8.4 to select attributes. The resulting classification model is suitable for use in DSS. The analysis of logistics tasks and the subsequent design of a classification model made it possible to reveal the contours of the relationship between the characteristics of a logistics problem explicitly expressed through a set of attributes and the classes of methods used to solve them.

The amazing progresses achieved in both data collecting and transferring have confronted us with a vast volume of stored and transient data. Analyzing such data can result in valuable knowledge providing a competitive advantage in support of decision-making. However, the high volume of the data makes it impossible to analyze such data manually. Data mining methods have been developed to automate this process. These methods extract useful knowledge from a massive amount of data. The vast majority of available methods focus on finding different types of patterns from various kinds of data whereas a few of them pay enough attention to the usability of mined patterns. Subsequently, there is a noticeable gap between delivered patterns and business expectations. Actionable Knowledge Discovery (AKD) is motivated to narrow this gap. Up to now, many AKD methods have been proposed. However, there is no comprehensive survey summarizing different aspects of such methods. Moreover, the lack of clear definitions and boundaries in this area makes it challenging to detect comparable methods. This paper aims at clarifying definitions and boundaries of AKD area. In this regard, some viewpoints are defined, and AKD methods are categorized by use of them. In addition, AKD methods are reviewed, and finally, a characterization table is presented that concludes the survey and can be used for studying different methods in AKD area.

MotivationClustering is a fundamental task in the analysis of nucleotide sequences. Despite the exponential increase in the size of sequence databases of homologous genes, few methods exist to cluster divergent sequences. Traditional clustering methods have mostly focused on optimizing high speed clustering of highly similar sequences. We develop a phylogenetic clustering method which infers ancestral sequences for a set of initial clusters and then uses a greedy algorithm to cluster sequences.ResultsWe describe a clustering program AncestralClust, which is developed for clustering divergent sequences. We compare this method with other state-of-the-art clustering methods using datasets of homologous sequences from different species. We show that, in divergent datasets, AncestralClust has higher accuracy and more even cluster sizes than current popular methods.Availability and implementationAncestralClust is an Open Source program available at https://github.com/lpipes/ancestralclust.Contactlpipes@berkeley.eduSupplementary informationSupplementary figures and table are available online.

Nowadays, many people have left their country’s traditions and cultures due to advancement of technologies. Indonesia is rich in diversity, also its traditional games that are an inseparable part of Indonesian culture that should be preserved. Traditional games are almost unknown and abandoned as children lack early knowledge because parents and teachers disregard their important role in teaching these games to children. Traditional games are not up- to-date and are replaced by modern and digital games. Moreover, children nowadays have less free time and are physically less active. Additionally, there are less fields to play nowadays. This project aims to re-introduce Indonesian traditional games by creating an interactive multiplayer table game about Gobak Sodor for Indonesian children from Generation Z, especially those around 9-12 years old. It also aims to overcome misconceptions that traditional games are not fun and increase interest on traditional games. The research methodology was done through literature studies, qualitative methods including site visits and in-depth interviews. Overall, the game can be a fun playing experience that can be played in limited space and time to re-introduce traditional games to children and encourage them to preserve Indonesian culture.

This report from the field concerns a collaborative project which resulted in successfully adding the Cyrillic fields to about 30,000 Ukrainian bibliographic records in OCLC WorldCat, the world’s largest online catalogue. Historically, the Ukrainian records in English-speaking libraries were only provided in transliteration according to the Library of Congress Romanization Table. However, the current standards also require the original script, such as the Ukrainian Kyrylytsia. While automating the Cyrillicization of Ukrainian legacy records is theoretically straightforward, in practice it faced more than one challenge, from poor quality of transliteration to the historical changes in Ukrainian orthography. The report presents the OCLC Ukrainian Cyrillicization project and discusses the steps in its implementation as an example of a successful collaboration in the areas of bibliographic automation, Ukrainian philology and culture, Slavic cataloguing, and linguistics.

While input-output examples are a natural form of specification for program synthesis engines, they can be imprecise for domains such as table transformations. In this paper, we investigate how extracting readily-available information about the user intent behind these input-output examples helps speed up synthesis and reduce overfitting. We present Gauss, a synthesis algorithm for table transformations that accepts partial input-output examples, along with user intent graphs. Gauss includes a novel conflict-resolution reasoning algorithm over graphs that enables it to learn from mistakes made during the search and use that knowledge to explore the space of programs even faster. It also ensures the final program is consistent with the user intent specification, reducing overfitting. We implement Gauss for the domain of table transformations (supporting Pandas and R), and compare it to three state-of-the-art synthesizers accepting only input-output examples. We find that it is able to reduce the search space by 56×, 73× and 664× on average, resulting in 7×, 26× and 7× speedups in synthesis times on average, respectively.

Privacy-preserving data publishing is a process of releasing the anonymized dataset for various purposes of analysis and research. Earlier, researchers have dealt with datasets considering it would contain only one record for an individual [1:1 dataset], which is uncompromising in various applications. Later, many researchers concentrate on the dataset, where an individual has multiple records [1:M dataset]. In the paper, a model f-slip was proposed that can address the various attacks such as Background Knowledge (bk) attack, Multiple Sensitive attribute correlation attack (MSAcorr), Quasi-identifier correlation attack(QIcorr), Non-membership correlation attack(NMcorr) and Membership correlation attack(Mcorr) in 1:M dataset and the solutions for the attacks. In f-slip, the anatomization was performed to divide the raw table into two sub-tables (1) quasi-identifier and (2) sensitive attributes. The correlation of sensitive attributes is computed to anonymize the sensitive attributes without breaking the linking relationship. Further, the quasi-identifier table was divided and k-anonymity was implemented on it. An efficient anonymization technique, frequency-slicing, was also developed to anonymize the sensitive attributes. The novel approach in the f-slip model is the slicing of records according to the frequency of occurrences of sensitive attribute values in each sub-table. The workload experiment proves that the f-slip model is consistent as the number of records increases. Extensive experiments were performed on a real-world dataset Informs and proved that the f-slip model outstrips the state-of-the-art techniques in terms of utility loss, efficiency and also acquires an optimal balance between privacy and utility.

Positioning with celestial bodies (celestial navigation) is the art of determining on the surface of the earth based on measurements of celestial bodies which have guided sailors for hundreds of years. Astronomical positioning methods or celestial body navigation are becoming increasingly obsolete and rarely used. The fact is that today, along with technological advances, seafarers prefer to use electronic navigation tools such as the Global Positioning System (GPS). The the International Convention on Standard of Training, Certification and Watchkeeping for Seafarers (STCW) amended 2011, requires all officers on board responsible for navigation to be able to determine the height of celestial bodies, the Line of Position (LOP) and the position of the ship. In general, there are 2 methods of determining the navigation position of celestial bodies, namely by calculating the Sight Reduction Table. This research discusses the accuracy of determining the height of the solar count by comparing the accuracy of the 2 methods. The method used is descriptive comparative based on field research with a qualitative approach. The technique of collecting data was done by means of observation, documentation and literature study. The purpose of this research is to test the accuracy of each calculation method, namely the calculation of the Sailing List (DIP) and the Sight Reduction Table (SRT). The results obtained in this study are the high calculation accuracy calculation method of calculating shipping science lists is more accurate with testing which is further discussed in this study.

Extracting data from user-friendly HTML tables is difficult because of their different layouts, formats, and encoding problems. In this article, we present a new proposal that first applies several pre-processing heuristics to clean the tables, then performs functional analysis, and finally applies some post-processing heuristics to produce the output. Our most important contribution is regarding functional analysis, which we address by projecting the cells onto a high-dimensional feature space in which a standard clustering technique is used to make the meta-data cells apart from the data cells. We experimented with two large repositories of real-world HTML tables and our results confirm that our proposal can extract data from them with an F 1 score of 89.50 % in just 0.09 CPU seconds per table. We confronted our proposal with several competitors and the statistical analysis confirmed its superiority in terms of effectiveness, while it keeps very competitive in terms of efficiency.

In this article, we present key tenets of good experimental design and provide some practical considerations for industrial marketing researchers. We first discuss how experiments have the ability to assess causal claims. Next, we provide an experimental taxonomy table, which brings out the value and limitations of different types of experiments and maps the various goals of business marketing research within each category. Here, we pay particular attention to field experiments since they provide experimental realism by measuring respondents' actual behavior. We also provide a thorough discussion on important practical issues such as questions on experimental design, sample size, and how to involve business organizations in the implementing steps. The paper concludes by stressing the importance of combining data types (e.g., field plus laboratory experiments) and by offering methodological advice on how to analyze experimental data in marketing.

This investigation was conducted to move forward the security of the vigenère cypher calculation by tending to the key conveyance issue and the most key issue within the calculation if cryptoanalysts effectively got it. The working demonstrates employments a 512-bit Electronic Code Book (ECB). The essential key utilized was a 512-bit arbitrary key. The randomized encoding table was also generated by the Blum Blum Shub calculation employing a scrambler key. The RSA calculation was utilized to scramble 512-bits random keys and scrambler keys. It comes about to appear that the proposed calculation does not include a key dissemination issue. With a randomized encoding table, the 512-bits arbitrary key cannot be utilized to unscramble the ciphertext off chance that cryptanalysis did not know the mixed table utilized. The preparing time appeared the proportion of the contrast of the vigenère cypher calculation. The proposed calculation was not as well essentially distinctive, and the longer the message was handled, the proportion of the time distinction possessed was moreover getting closer to one, which implies the distinction was not critical. The coming about ciphertext was too exceptionally secure, where the coming about ciphertext was irregular since the key utilized was random, and there were 3.75 x 10126 keys combination. This algorithm can be an alternative algorithm that is fast, safe, and easy to implement