Binary Sort Research Articles

Validation of a Thai artificial chatmate designed for cheering up the elderly during the COVID-19 pandemic.

The COVID-19 pandemic severely affected populations of all age groups. The elderly are a high-risk group and are highly vulnerable to COVID-19. Assistive software chatbots can enhance the mental health status of the elderly by providing support and companionship. The objective of this study was to validate a Thai artificial chatmate for the elderly during the COVID-19 pandemic and floods. Chatbot design includes the establishment of a dataset and emotional word vectors in which data consisting of emotional sentences were converted into the word vector form using a pre-trained word2vec model. A word vector was then input into a convolutional neural network (CNN) and trained until the model converges using sentence embedding and similarity word segmentation. Sentence vectors were generated by averaging each word vector using an averaged vector method. For approximate similarity matching, the Annoy library was used to create the indices in tree sorting. Data were collected from 22 elderly and assessed by the Post-Study System Usability Questionnaire (PSSUQ). The study revealed that 72.73% of the respondents found the chatbot easy to learn and use, 63.64% of the respondents found the chatbot can autonomously determine the next course of action, and 59.09% of the respondents believed that troubleshooting guidelines were provided for overcoming errors. The accuracy of the chatbot providing a reasonable response is 56.20±13.99%. Most users were satisfied with the chatbot system. The proposed chatbot provided considerable essential insights into the development of assistance systems for the elderly during the coronavirus pandemic (COVID-19) and during the period of national disasters. The model can be expanded to other applications in the future.

Sorting on Byte-Addressable Storage: The Resurgence of Tree Structure

The tree structure is notably popular for storage and indexing; however, tree-based sorting such as tree sort is rarely used in practice. Nevertheless, with the advent of byte-addressable storage (BAS), the tree structure captures our attention with its write-once property. This property aligns well with BAS's asymmetric read-write characteristics. In this paper, we seek to answer the question: Can tree-based sorting algorithms outperform existing algorithms in the hybrid DRAM-BAS system? To address this, first, we conduct a comprehensive study to assess the compatibility of existing sorting algorithms with such hybrid memory systems and explore the challenges. We then delve into various design dimensions of tree-sort algorithms which leads to an optimized variant, TSort. Finally, a comparative analysis is conducted among three different sets of sorting algorithms, including in-place sorts, external sorts, and tree-based sorts. The results indicate that TSort not only challenges the traditional negative perceptions of the tree structure in sorting but also exhibits excellent performance. It outperforms all other counterparts across diverse datasets, whether uniformly distributed or skewed, in most cases.

Validation of a Thai artificial chatmate designed for cheering up the elderly during the COVID-19 pandemic

Background The COVID-19 pandemic severely affected populations of all age groups. The elderly are a high-risk group and are highly vulnerable to COVID-19. Assistive software chatbots can enhance the mental health status of the elderly by providing support and companionship. The objective of this study was to validate a Thai artificial chatmate for the elderly during the COVID-19 pandemic and floods. Methods Chatbot design includes the establishment of a dataset and emotional word vectors in which data consisting of emotional sentences were converted into the word vector form using a pre-trained word2vec model. A word vector was then input into a convolutional neural network (CNN) and trained until the model converges using sentence embedding and similarity word segmentation. Sentence vectors were generated by averaging each word vector using an averaged vector method. For approximate similarity matching, the Annoy library was used to create the indices in tree sorting. Data were collected from 22 elderly and assessed by the Post-Study System Usability Questionnaire (PSSUQ). Results The study revealed that 72.73% of the respondents found the chatbot easy to learn and use, 63.64% of the respondents found the chatbot can autonomously determine the next course of action, and 59.09% of the respondents believed that troubleshooting guidelines were provided for overcoming errors. The accuracy of the chatbot providing a reasonable response is 56.20±13.99%. Conclusions Most users were satisfied with the chatbot system. The proposed chatbot provided considerable essential insights into the development of assistance systems for the elderly during the coronavirus pandemic (COVID-19) and during the period of national disasters. The model can be expanded to other applications in the future.

Decoupling of tree height and root depth across the globe and the implications for tree mortality during drought events

Tree height (Htree) and root depth (Droot) are the two most critical functional traits for plant ecological strategies. However, the global varying patterns of Htree and Droot and the ecological significance for tree survival under changed climate conditions are less understood. Here, we compiled Htree, Droot, and six root traits related to soil resource absorption for 301 field-grown tree species distributed 776 sites worldwide. The relationships between Htree and Droot across different climate conditions and the implications for tree mortality during drought events were investigated. We found Htree and Droot were often decoupled in angiosperms and gymnosperms among different climate conditions. Greater Htree was prone to occur in warm and moist climates, while greater Droot tended to occur in warm and dry climates with low soil water availability. Phylogenetic analysis revealed that trees have evolved towards smaller Htree but deeper Droot from the deep time. Although dense root structures to some extent contributed to sustaining the resource supply–demand balance of large trees with shallow roots (great Htree/ Droot), the large trees with greater Htree/ Droot were more vulnerable to drought-induced mortality. The findings suggest that the linkage of below- and above-ground reaches has a pivotal role in understanding tree mortality during drought events. The insight will allow more accurate vegetation model prediction for tree sorting processes under climate change scenarios.

Study on classification and retrieval method of e-book resources based on binary sort tree

Study on classification and retrieval method of e-book resources based on binary sort tree

Validation of a Thai artificial chatmate designed for cheering up the elderly during the COVID-19 pandemic

Background: The COVID-19 pandemic severely affected populations of all age groups. The elderly are a high-risk group and are highly vulnerable to COVID-19. Assistive software chatbots can enhance the mental health status of the elderly by providing support and companionship. The objective of this study was to validate a Thai artificial chatmate for the elderly during the COVID-19 pandemic and floods. Methods: Chatbot design includes the establishment of a dataset and emotional word vectors in which data consisting of emotional sentences were converted into the word vector form using a pre-trained word2vec model. A word vector was then input into a convolutional neural network (CNN) and trained until the model converges using sentence embedding and similarity word segmentation. Sentence vectors were generated by averaging each word vector using an averaged vector method. For approximate similarity matching, the Annoy library was used to create the indices in tree sorting. Data were collected from 22 elderly and assessed by the Post-Study System Usability Questionnaire (PSSUQ). Results: The study revealed that 72.73% of the respondents found the chatbot easy to learn and use, 63.64% of the respondents found the chatbot can autonomously determine the next course of action, and 59.09% of the respondents believed that troubleshooting guidelines were provided for overcoming errors. The accuracy of the chatbot providing a reasonable response is 56.20±13.99%. Conclusions: Most users were satisfied with the chatbot system. The proposed chatbot provided considerable essential insights into the development of assistance systems for the elderly during the coronavirus pandemic (COVID-19) and during the period of national disasters. The model can be expanded to other applications in the future.

Oak beams in medieval frameworks: Constraints and advantages for restoration

During the fire of Notre-Dame de Paris, all timber frames coming from the Middle ages period, in the nave and choir, were burnt. It was decided to proceed as possible to an identical reconstruction, but many questions arise about the timber frame. Is wood outdated as a material for beams? Is oak wood the best solution for timber frame? Are we able to find similar long slender oak beams in today French forest? Is it safe to use green wood for the building?In fact, the forested area in France is the same today as in the Middle ages period, but two times higher than during the 19th century. Results from the forest inventory proves that 40 million slender oak trees are available in order to sort around 1500 trees for the restoration.Cathedral heritage provided a demonstration of the high efficiency of carpenter's know-how. Most of oak beams kept their functionality for more than 800 years. This is a nice experimental result for a very long mechanical testing. Wood, emerged as material 300 million years ago as a result of long time evolution, is used to build trees, which are a collection of wooden beams able to resist flexure forces, for a long time.Technical know-how about timber frame is old in human societies and was improved during the Middle ages, but scientific knowledge about wood as an anisotropic material is very recent. The background in mechanics for such material has been developed in early 20th century and observation tools for material structures at the nanometre scale appeared in late 20th century. Wood can be considered as an archetypal high-tech material using polymer-with-additive technology combined to nanostructured fibre-composite within a honeycomb-like micro-structured material. This explains why nature solution for tree beams is very efficient in terms of bending resistance per weight.The mechanical behaviour of wooden beams is highly sensitive to the orientation of the main direction of anisotropy (grain direction) relative to bending forces. Natural beams in trees are built by a kind of 3D printing process so that grain orientation at beam periphery is always optimum. Mechanical bending performance of these beams (round-wood), in spite of branching, is equivalent to the performance of standard clear-wood specimens documented in databases. Squaring at the minimum this round-wood should be done while keeping grain angle closest to zero-degree value, which is performed by specific axe-hewn log squaring. The result is “coarse” slightly curved beams much more resistant than “nicely” straight sawn beams with local grain angle above 10°Using directly green wood in the building process is effective for time of building and energy consumption. The drying of wood induces long deep longitudinal cracks and a reduction in beam section but a bigger increase in wood mechanical performance. If the green frame resists, the dried one will resist all the following years.Finally, today carpenters have kept the building know-how and there are many modern non-destructive techniques available for the best sorting of trees and mechanical evaluation of beams.

Erratum to ‘Oak beams in medieval frameworks: Constraints and advantages for restoration’ [Journal of Cultural Heritage Volume 56C (July-August 2022) 108-117

• Wood is always a top material for beams. • 40 million of slender young oak trees are available in French forest. • Round-wood squared at the minimum keeps the high resistance of trunks. • Using green wood is the fastest and most energy-saving method. • High tech modern techniques can be used for the best sorting of trees. During the fire of Notre-Dame de Paris, all timber frames coming from the Middle ages period, in the nave and choir, were burnt. It was decided to proceed as possible to an identical reconstruction, but many questions arise about the timber frame. Is wood outdated as a material for beams? Is oak wood the best solution for timber frame? Are we able to find similar long slender oak beams in today French forest? Is it safe to use green wood for the building? In fact, the forested area in France is the same today as in the Middle ages period, but two times higher than during the 19th century. Results from the forest inventory proves that 40 million slender oak trees are available in order to sort around 1500 trees for the restoration. Cathedral heritage provided a demonstration of the high efficiency of carpenter's know-how. Most of oak beams kept their functionality for more than 800 years. This is a nice experimental result for a very long mechanical testing. Wood, emerged as material 300 million years ago as a result of long time evolution, is used to build trees, which are a collection of wooden beams able to resist flexure forces, for a long time. Technical know-how about timber frame is old in human societies and was improved during the Middle ages, but scientific knowledge about wood as an anisotropic material is very recent. The background in mechanics for such material has been developed in early 20th century and observation tools for material structures at the nanometre scale appeared in late 20th century. Wood can be considered as an archetypal high-tech material using polymer-with-additive technology combined to nanostructured fibre-composite within a honeycomb-like micro-structured material. This explains why nature solution for tree beams is very efficient in terms of bending resistance per weight. The mechanical behaviour of wooden beams is highly sensitive to the orientation of the main direction of anisotropy (grain direction) relative to bending forces. Natural beams in trees are built by a kind of 3D printing process so that grain orientation at beam periphery is always optimum. Mechanical bending performance of these beams (round-wood), in spite of branching, is equivalent to the performance of standard clear-wood specimens documented in databases. Squaring at the minimum this round-wood should be done while keeping grain angle closest to zero-degree value, which is performed by specific axe-hewn log squaring. The result is “coarse” slightly curved beams much more resistant than “nicely” straight sawn beams with local grain angle above 10° Using directly green wood in the building process is effective for time of building and energy consumption. The drying of wood induces long deep longitudinal cracks and a reduction in beam section but a bigger increase in wood mechanical performance. If the green frame resists, the dried one will resist all the following years. Finally, today carpenters have kept the building know-how and there are many modern non-destructive techniques available for the best sorting of trees and mechanical evaluation of beams.

A shuffled cellular evolutionary grey wolf optimizer for flexible job shop scheduling problem with tree-structure job precedence constraints

Along with the growing demands for customized products and small batch production, the flexible job shop manufacturing environment becomes increasingly popular. Efficient flexible job shop scheduling plays a crucial role in making quick responses to production orders with low volume and high variety. When producing complex assembly products that are comprised of multiple and multilevel intermediate parts organized as tree-structure Bills-Of-Materials (BOMs), jobs get restricted by hierarchical precedence constraints due to dependencies between manufactured parts. To cope with this condition, this paper formulates a flexible job shop scheduling problem with job precedence constraints (FJSSP-JPC). A novel shuffled cellular evolutionary grey wolf optimizer (SCEGWO) is proposed to solve FJSSP-JPC with the objective of minimizing makespan. Schedule solutions are encoded as elaborately designed triple-vectors involving the information of job sequencing, grouped operation sequencing and machine assignment, while the satisfactions of job precedence constraints are guaranteed by binary sort tree-based repair mechanism. In SCEGWO, each individual interacts with its topological cellular neighborhood by conducting a micro discrete variant of grey wolf optimizer (GWO), causing that the whole population is decomposed into multiple subpopulations which communicate by the neighborhood overlapping. Extensive experimental results demonstrate that the components of SCEGWO are effective and the proposed SCEGWO outperforms other competing algorithms significantly on the addressed problem.

PERFORMANCE APPRAISAL OF TREAP AND HEAP SORT ALGORITHMS

The task of storing items to allow for fast access to an item given its key is an ubiquitous problem in many organizations. Treap as a method uses key and priority for searching in databases. When the keys are drawn from a large totally ordered set, the choice of storing the items is usually some sort of search tree. The simplest form of such tree is a binary search tree. In this tree, a set X of n items is stored at the nodes of a rooted binary tree in which some item y ϵ X is chosen to be stored at the root of the tree. Heap as data structure is an array object that can be viewed as a nearly complete binary tree in which each node of the tree corresponds to an element of the array that stores the value in the node. Both algorithms were subjected to sorting under the same experimental environment and conditions. This was implemented by means of threads which call each of the two methods simultaneously. The server keeps records of individual search time which was the basis of the comparison. It was discovered that treap was faster than heap sort in sorting and searching for elements using systems with homogenous properties.
 

Deep learning approach for plant leaf detection

There are several sorts of trees in the natural environment, and it tends to be hard to recognize them. Botanists and the individuals who study plants anyway can distinguish the sort of tree initially by utilizing the characteristics of the leaf. Machine learning is utilized to automatically classify leaf types. Concentrated widely in 2012, this is a quickly developing field dependent on profound learning. Profound learning is itself a self-learning method utilized on a lot of information, and late improvements in equipment and huge information have made this strategy increasingly down to earth. We propose a classify leaves using the CNN model, which is often used when applying deep learning to image processing.

СПЕЦІАЛЬНЕ ЗАСТОСУВАННЯ ВЛАСНОЇ РОЗРОБКИ ДЛЯ ДЕМОНСТРАЦІЇ І ПОРІВНЯННЯ АЛГОРИТМІВ СОРТУВАННЯ ТА ПОШУКУ ДАНИХ

У статті наведено опис спеціального застосування власної розробки, яке дозволяє студентам, що вивчають алгоритми сортування та пошуку даних, спостерігати за процесом і проводити аналіз переваг і недоліків низки методів для кращого розуміння принципів їх функціонування. Розглянуто деякі алгоритми сортування та пошуку даних, проаналізовано існуючі програмні системи (інтернет-сайти) для розв’язування поставленої завдачі, їх особливості, переваги та недоліки. Виконано розробку об'єктно-орієнтованої моделі програмної системи з використанням засобів візуального моделювання UML (подані діаграми варіантів використання і діаграма класів) та функціональної моделі в нотації BPWin (перший і другий рівні). Перераховано доступні алгоритми: бульбашкове сортування, сортування вставками, сортування вибором, сортування злиттям, швидке сортування, шейкерне сортування, сортування гнома, сортування Шелла, бінарне сортування, послідовний пошук, бінарний пошук. Оскільки реальний час роботи алгоритму на сучасному комп'ютері є занадто малим, і користувач не встигне зрозуміти принципів його роботи, було прийнято рішення додати затримку після кожного кроку, що істотно збільшило час під час демонстрації роботи алгоритму. Наведено приклади використання розробленого застосування: введення даних і демонстрація роботи алгоритму сортування обмінами, порівняння алгоритмів сортування для випадкового заповнення масиву з 25000 елементів за критеріями «Час роботи» і «Кількість ітерацій». Відзначено можливість зміни мови інтерфейсу. Описано використання довідкової системи. Розглянуто типову послідовність роботи з розробленим застосуванням. Зроблено висновок, що створене застосування може стати додатковим елементом інформаційно-комунікативних засобів навчання при викладенні відповідних дисциплін – наприклад, «Алгоритми і структури даних» для спеціальностей галузі 12 «Інформаційні технології».

Improving Economic Management Decisions in Forestry with the SorSim Assortment Model

The sustainable supply of timber is one of the most important forest ecosystem services and a decisive factor determining the long-term profitability of forest enterprises. If timber production is to be economically viable, there must always be a way to analyse forest stands and trees felled for exploitation with regard to the wood assortments they contain. Only then can the expected timber yields, achieved by various silvicultural strategies or actions and different sorting options, be quantified with sufficient accuracy. The SorSim assortment simulator was developed for forest practitioners and forest scientists in Switzerland to realistically simulate the sorting of individual trees and entire forest stands based on defined specifications. SorSim has a simple user interface and comes in a number of different language versions (G, E, F). The software is implemented in Java, making it platform-independent. It can be downloaded for free at (https://www.wsl.ch/en/projects/sortimentsimulator-sorsim.html). This article provides an overview of how the simulator works and demonstrates its potential applications based on a practical and a scientific example. A particular practical advantage is that the composition of the assortments of the planned harvests can be estimated according to quantity and value. When used in strategic planning and especially in research, SorSim provides a basis for analysing either long-term developments in yields from forest stands or silvicultural treatment methods. Based on an even-aged and a selection forest stand, the scientific example shows how strongly the assessment of the advantageousness of two different silvicultural strategies depends on the time when the calculation was made (using historical and current assortment revenues and timber harvesting costs). In particular, the combination of SorSim with timber harvest productivity models enables differentiated forest economic insights. Various approaches for value-based optimisation in the sorting of individual trees and for the optimal allocation of harvesting activities to defined customer demands are currently being examined as further SorSim developments.

ANALISIS PERBANDINGAN KINERJA CART KONVENSIONAL, BAGGING DAN RANDOM FOREST PADA KLASIFIKASI OBJEK: HASIL DARI DUA SIMULASI

The conventional CART method is a nonparametric classification method built on categorical response data. Bagging is one of the popular ensemble methods whereas, Random Forests (RF) is one of the relatively new ensemble methods in the decision tree that is the development of the Bagging method. Unlike Bagging, Random Forest was developed with the idea of adding layers to the random resampling process in Bagging. Therefore, not only randomly sampled sample data to form a classification tree, but also independent variables are randomly selected and newly selected as the best divider when determining the sorting of trees, which is expected to produce more accurate predictions. Based on the above, the authors are interested to study the three methods by comparing the accuracy of classification on binary and non-binary simulation data to understand the effect of the number of sample sizes, the correlation between independent variables, the presence or absence of certain distribution patterns to the accuracy generated classification method. results of the research on simulation data show that the Random Forest ensemble method can improve the accuracy of classification.

A Wireless Electro-Optic Headstage With a 0.13- μm CMOS Custom Integrated DWT Neural Signal Decoder for Closed-Loop Optogenetics.

We present a wireless electro-optic headstage that uses a 0.13- μm CMOS custom integrated circuit (IC) implementing a digital neural decoder (ND-IC) for enabling real-time closed-loop (CL) optogenetics. The ND-IC processes the neural activity data using three digital cores: 1) the detector core detects and extracts the action potential (AP) of individual neurons by using an adaptive threshold; 2) the data compression core compresses the detected AP by using an efficient Symmlet-2 discrete wavelet transform (DWT) processor for decreasing the amount of data to be transmitted by the low-power wireless link; and 3) the classification core sorts the compressed AP into separated clusters on the fly according to their wave shapes. The ND-IC encompasses several innovations: 1) the compression core decreases the complexity from O(n 2) to O(n · log(n)) compared to the previous solutions, while using two times less memory, thanks to the use of a new coefficient sorting tree; and 2) the AP classification core reuses both the compressed DWT coefficients to perform implicit dimensionality reduction, which allows for performing intensive signal processing on-chip, while increasing power and hardware efficiency. This core also reuses the signal standard deviation already computed by the AP detector core as threshold for performing automatic AP sorting. The headstage also introduces innovations by enabling a new wireless CL scheme between the neural data acquisition module and the optical stimulator. Our CL scheme uses the AP sorting and timing information produced by the ND-IC for detecting complex firing patterns within the brain. The headstage is also smaller (1.13 cm 3), lighter (3.0g with a 40mAh battery) and less invasive than the previous solutions, while providing a measured autonomy of 2h40, with the ND-IC. The whole system and the ND-IC are first validated in vivo in the LD thalamus of a Long-Evans rat, and then in freely-moving CL experiments involving a mouse virally expressing ChR2-mCherry in inhibitory neurons of the prelimbic cortex, and the results show that our system works well within an in vivo experimental setting with a freely moving mouse.

Colored operads, series on colored operads, and combinatorial generating systems

We introduce bud generating systems, which are used for combinatorial generation. They specify sets of various kinds of combinatorial objects, called languages. They can emulate context-free grammars, regular tree grammars, and synchronous grammars, allowing us to work with all these generating systems in a unified way. The theory of bud generating systems uses colored operads. Indeed, an object is generated by a bud generating system if it satisfies a certain equation in a colored operad. To compute the generating series of the languages of bud generating systems, we introduce formal power series on colored operads and several operations on these. Series on colored operads are crucial to express the languages specified by bud generating systems and allow us to enumerate combinatorial objects with respect to some statistics. Some examples of bud generating systems are constructed; in particular to specify some sorts of balanced trees and to obtain recursive formulas enumerating these.

Grouped attribute strength-based image retrieval

Visual attributes, as a bridge between humans and machines, have played an important role in various applications. We focus on attribute-based image retrieval. Unlike early works that either initiate the image search via binary attributes or refine the search results via relative attributes, we propose to realize image retrieval using grouped attribute strength, which are learned from both binary attributes and relative attributes. First, early methods are employed to predict the binary attributes and sort the relative attributes in descending order in different situations. Second, we group the sorted images corresponding to each attribute and combine the learned binary and relative attributes to learn the grouped attribute strength of the images, which result in a new attribute feature vector for each image. Finally, we apply the learned grouped attribute strength to different retrieval models to realize our image retrieval tasks. We demonstrate the approach on LFW-10 and Shoes datasets and show its clear advantages over traditional binary attribute-based retrieval methods.

Optimal selection of pumped hydro storage based renewable energy generator(s) for isolated community using binary sort and search algorithm

In this paper, optimal selection of renewable energy generator(s) for supplying isolated loads in a cost effective and environmentally friendly manner based on the available renewable energy resource within a given location is presented. The selection is based on minimum cost of energy (COE), loss of power supply probability (LPSP) and dump energy. The proposed scheme utilizes binary sort and search algorithm and is implemented in Matlab environment. To test the applicability and effectiveness of the proposed scheme, two scenarios are performed for a typical isolated community not supply with the national grid. The scenarios are based on the two available seasons: the dry season and the rainy season. Simulation results show that during the dry season (October-March), the combination of PV and wind turbine is the best option to meet the village energy need with lowest LPSP of 0.00, COE of 0.2839 $/Wh, dump 5097 Wh and score combination index (SCI) of 8.4. Meanwhile, the best renewable energy generators option for raining season is found to be the combination of PV, wind turbine (WT) and Hydrokinetic turbine (HKT) with the LPSP of 0.000, COE of 0.4047 $/Wh, dump energy of 4871.2 Wh and SCI 9.54.

Level Set Based Path Planning Using a Novel Path Optimization Algorithm for Robots

In order to decrease the path length and control the minimum distance between the path and the obstacles when the level set based path planning algorithm is adopted, a new path optimization algorithm named elastic particle is proposed in this paper. Firstly, the iteration expression of optimization algorithm is deduced by active contour theory. Secondly, to ensure the convergence of algorithm, the relation among each item in the algorithm expression is analyzed and its convergence condition is determined. At last, level set algorithm is improved so that the smoothness of the initial path and the convergence speed of the algorithm are improved. In addition, a method named the nearest boundary distance is put forward to accelerate the operation speed of the algorithm. What’s more, memory pool and binary sort tree are adopted in the code to further reduce the running time of this algorithm. The optimal values of the algorithm parameters are analyzed via the simulation experiment,and its result demonstrates that the new algorithm has greatly optimized the path of algorithm-level set and guaranteed fast running speed and high reliability.

Design prototype detection tools of Porous Tree using microcontroller Arduino Uno R3 and piezoelectric sensor

In the city, many trees are found uprooted and cause accidents and many losses. No exception in the area of Majalengka Regency of West Java Province which can also anytime an accident or disaster caused by fallen trees, where in Majalengka district is logging trees on the street and public places are not done regularly. Based on the above problems, the need for tools that can detect a porous tree, to assist in the sorting of trees which should be felled and not felled by the party who has the authority of the general management of BMCK. Previously created tools to detect porous trees imported from Hungary and Germany, namely Arbosonic3D and Sonic Tomography. This design uses piezoelectric sensors to detect how much pressure is received by fragile and fragile trees, of course the fragile and fragile strength of trees will be different when exposed to the same pressure given the fragile density of fragile and fragile trees, then the data sent to Arduino Uno R3 to be processed into an information. This research produces a means of detecting the loss of a tree for early detection and no falling trees.