An Enhanced List Based Packet Classifier for Performance Isolation in Internet Protocol Storage Area Networks

Consolidation of storage into IP SANs (Internet protocol storage area network) has led to a combination of multiple workloads of varying demands and importance. To ensure that users get their Service level objective (SLO) a technique for isolating workloads is required. Solutions that exist include cache partitioning and throttling of workloads. However, all these techniques require workloads to be classified in order to be isolated. Previous works on performance isolation overlooked the classification process as a source of overhead in implementing performance isolation. However, it’s known that linear search based classifiers search linearly for rules that match packets in order to classify flows which results in delays among other problems especially when rules are many. This paper looks at the various limitation of list based classifiers. In addition, the paper proposes a technique that includes rule sorting, rule partitioning and building a tree rule firewall to reduce the cost of matching packets to rules during classification. Experiments were used to evaluate the proposed solution against the existing solutions and proved that the linear search based classification process could result in performance degradation if not optimized. The results of the experiments showed that the proposed solution when implemented would considerably reduce the time required for matching packets to their classes during classification as evident in the throughput and latency experienced.

Improved Generalized Cross-Validation and Unbiased Predictive Risk Estimator Methods Using the RGSVD: Application to Inversion of Potential Field Data

The inversion of potential field data has widely utilized the generalized cross-validation (GCV) and the unbiased predictive risk estimator (UPRE) methods to determine the regularization parameter. However, these two methods are time-consuming and it is difficult for them to determine the optimal linear search range including the optimal regularization. To solve these problems, this article improves the GCV and UPRE methods using the RGSVD (randomized generalized singular value decomposition) algorithm. The improved methods first use the randomized algorithm to compute an approximate generalized singular value decomposition (GSVD) with less computational time. Then, the optimal linear search range is determined based on the generalized singular values. Finally, the GCV and the UPRE functions are efficiently computed on the basis of the results from the RGSVD algorithm. In this way, the GCV and UPRE methods using the RGSVD algorithm are able to determine the optimal regularization parameter fast and effectively. One comparative test shows the effectiveness and efficiency of the GCV and the UPRE methods using the RGSVD algorithm.

LINEAR SEARCH ALGORITHM TO BE SOLVED BY PARAMETER LOOP

There are common occasions for finding out required optional data or element from the given algebra of sets and any kind of systems when we are solving practical and informatics tasks. In order to solve these types of tasks or issues, students or researchers have to know about the methodologies for basic understanding which are called tasks for searching. This process is very important as for finding out basic understanding and methodologies, having detailed knowledge of algorithms and searching methods, although there are modern specific technologies and automatic programming systems. When searching methods are programmedfor informatics tasks, necessary abilities such as seeking essential or import of program language operators and making analysis indifference among characterful solving should be owned by students or specialists. Therefore,I set my purpose of thesis of organizing linear searching algorithms by the parameter loop of the programming language C during the discovering process of identifying differences, patterns, and internal core of linear searching methodologies.

"ANYWORD" BILINGUAL DICTIONARY: DESIGN AND IMPLEMENTATION OF LINEAR SEARCH ALGORITHMS IN ANDROID-BASED OPEN-SOURCE APPLICATIONS

<p class="Abstract"><span lang="EN-US">Kemajuan teknologi informasi pada masa saat ini, membuat penyebaran informasi semakin cepat dan akurat. Hal tersebut membuat tempat penyampaian informasi menjadi penting terkait dengan informasinya. Penelitian ini membuat template aplikasi "AnyWord" kamus dua bahasa berbasis Android yang bersifat fully open-source code. Penelitian ini dirasa perlu karena belum tersedianya template aplikasi kamus yang ringan dan mudah dioperasikan serta bersifat gratis untuk digunakan oleh umum. Pengembangan aplikasi menggunakan model waterfall dan menggunakan perangkat lunak Android Studio dan SQLite. Untuk melakukan uji coba aplikasi, peneliti memilih menggunakan beberapa istilah geometri berbahasa Inggris dari http://www.mathwords.com/. Istilah geometri dipilih karena penerapannya pada jurusan lain misalnya di jurusan sistem informasi, geometri dipelajari oleh mahasiswa saat mempelajari AutoCad, Desain UI / UX, dan lain-lain. Validasi dilakukan secara daring kepada seorang ahli pemrogaman. Selanjutya ujicoba aplikasi dilakukan juga secara daring kepada 20 mahasiswa di lingkungan kampus. Hasil rata-rata keduanya adalah 90,27%. Jadi sesuai dengan skala Likert, aplikasi "AnyWord" layak dan dapat digunakan oleh umum. </span></p>

EVALUASI KEMAMPUAN LAHAN UNTUK PERTANIAN DI KABUPATEN MAJELENGKA, JAWA BARAT

Abstrak:Pencarian data curah hujan dan suhu Kabupaten Majalengka, Jawa Barat dimaksudkan agar dalam pendayagunaan lahan yang digunakan sesuai dengan kemampuannya. Tujuan dari penelitian ini adalah untuk mengetahui kemampuan lahan di Kabupaten Majalengka berdasarkan curah hujan dan suhu serta mengevaluasi kesesuaian antara penggunaan penggunaan lahan. Penelitian ini menggunakan metode kualitatif Pada penelitian ini menggunakan bahan berupa data curah hujan dan suhu serta komoditas unggulan di daerah Majalengka, Jawa Barat. Selama periode tahun 2010-2019 data curah hujan di Kabupaten Majalengka dengan curah hujan tahunan terendah yaitu sebesar 1.457 mm/tahun yang terjadi pada tahun 2019 dan tertinggi sebesar yaitu sebesar 7.170 mm/tahun pada tahun 2014 periode tahun 2010-2019 rata-rata suhu Kabupaten Majalengka yaitu 27°C hingga 27.7°C. Suhu udara dan curah hujan tersebut masih cocok untuk tanaman-tanaman seperti padi sawah, jagung, kacang kedelai padi sawah, jagung dan kacang kedelai. Kata Kunci: evaluasi kemampuan lahan, curah hujan, suhu, Majalengka, komoditas unggul The search for rainfall and temperature data in Majalengka Regency, West Java is intended to make use of the land in accordance with its capabilities. The purpose of this study is to find out about the ability of land in Majalengka Regency based on rainfall and temperature and evaluate the suitability between land use in the form of superior commodity crops and land capability that has been determined. This study uses data search or searching methods, in the search method there are two ways, namely by linear search and binary search. In this study using material in the form of rainfall and temperature data and leading commodities in the majalengka area, west Java. During the 2010-2019 period rainfall data in Majalengka Regency with the lowest annual rainfall was 1,457 mm / year which occurred in 2019 and the highest amounted to 7,170 mm / year in 2014 the period 2010-2019 the average temperature of the Regency Majalengka is 27 ° C to 27.7 ° C. The temperature and rainfall are still suitable for plants such as lowland rice, corn, soybean, lowland rice, corn and soybeans.

Study the Best PenTest Algorithm for Blind SQL Injection Attacks

<p>There are several types of SQL injection attacks. One of the most popular SQL Injection Attacks is Blind SQL. This attack is performed by exploiting a gap in the database server when executing query words. If the server responds to an invalid query, the attacker will then reverse the engineering part of the SQL query, which is obtained from the error message of the server. The process of generating a blind SQL injection attack is complicated. As a result, a Pentester often requires a long time to penetrate the database server. This research provides solutions to the problems above by developing the automation of a blind SQL injection attack. The method used in this research is to generate keywords, such as the database name and table name so that the attacker can retrieve information about the user name and password. This research also compares several search algorithms, such as linear search, binary search, and interpolation search for generating the keywords of the attack. Automation of the Blind SQL Injection was successfully developed, and the performance of the keywords generation for each algorithm was also successfully measured, i.e., 1.7852 seconds for Binary Search, 1.789 seconds for interpolation and 1.902 seconds for Linear Search.</p>

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

In this paper, we study Reinforcement Learning from Demonstrations (RLfD) that improves the exploration efficiency of Reinforcement Learning (RL) by providing expert demonstrations. Most of existing RLfD methods require demonstrations to be perfect and sufficient, which yet is unrealistic to meet in practice. To work on imperfect demonstrations, we first define an imperfect expert setting for RLfD in a formal way, and then point out that previous methods suffer from two issues in terms of optimality and convergence, respectively. Upon the theoretical findings we have derived, we tackle these two issues by regarding the expert guidance as a soft constraint on regulating the policy exploration of the agent, which eventually leads to a constrained optimization problem. We further demonstrate that such problem is able to be addressed efficiently by performing a local linear search on its dual form. Considerable empirical evaluations on a comprehensive collection of benchmarks indicate our method attains consistent improvement over other RLfD counterparts.

English Myanmar Dictionary System by Using Linear and Binary Search Techniques

This paper is aimed to develop a searching method based on binary search and linear search as well as to understand the finding of search methods. The system searches the desired word for English to English and English to Myanmar. The system may help the English may help the English Language user enable to know the desired word of English and Myanmar meaning. The system output is searching word of English meaning, Myanmar meaning, part of speech, searching time and step. And also, the system finds cross reference and user's unknown word by using binary search and linear search of searching algorithm. This system is implemented by using ASP.NET platform.

Optimasi Learning Rate Neural Network Backpropagation Dengan Search Direction Conjugate Gradient Pada Electrocardiogram

This paper develops a Neural network (NN) using conjugate gradient (CG). The modification of this method is in defining the direction of linear search. The conjugate gradient method has several methods to determine the steep size such as the Fletcher-Reeves, Dixon, Polak-Ribere, Hestene Steifel, and Dai-Yuan methods by using discrete electrocardiogram data. Conjugate gradients are used to update learning rates on neural networks by using different steep sizes. While the gradient search direction is used to update the weight on the NN. The results show that using Polak-Ribere get an optimal error, but the direction of the weighting search on NN widens and causes epoch on NN training is getting longer. But Hestene Steifel, and Dai-Yua could not find the gradient search direction so they could not update the weights and cause errors and epochs to infinity.