File Content Research Articles

RISC-V Hardware Synthesizable Processor Design Test and Verification Using User-Friendly Desktop Application

Although the RISC-V ISA has not been around for long, it is a processor architecture that has been highlighted by many businesses and individuals for its low-cost and rapid pace of development. They are open-source-synthesizable hardware processors with minimal functionality that is ideal for current IoT applications involving simple sensors and actuator controls. Due to some qualities of hardware, they can operate in areas where software programs and applications cannot be used whereas, these software programs that run on such hardware equally help in understanding how hardware operates. This paper, therefore, proposes and discusses the design, implementation, and internal verification and test platform for a Reduced Instruction Set Code-V’s (RISC-V) Instruction Set Architecture (ISA), using an interactive desktop program for a 32-bit single-cycle processor. This paper developed a system that functions as interactive assistance to RISC-V's ISA design and debugger using a more user-friendly desktop UI application. The uniqueness of this design is the flexibility of testing and debugging that is possible through either the software interface or through hardware peripherals such as Universal Asynchronous Receiver/Transmitter (UART) protocols in FPGA or even both. These peripherals allow users to view the contents of the register files and RAM being utilized by the implemented processor on the FPGA. The proposed desktop User Interface program monitors and controls the sequential processing and states of a 32-bit single-cycle RISC-V processor’s operation on an FPGA. Contents of the proposed processor’s registers and memory are displayed alongside other temporal or internal data. Internal components such as Program Counters (PC), Random Access Memory (RAM), are displayed all through the proposed User Interface (UI) program and also through various peripherals on the FPGA board. The software program is implemented using C# programing language through Microsoft Visual Studio 2019 Integrated Development Environment (IDE). The proposed hardware synthesizable processor core is implemented using Verilog Hardware Description Language (HDL) and synthesized with Xilinx Integrated Synthesis Environment (ISE) version 14.7. The proposed processor and its corresponding hardware test modules occupy 6476 Look-Up-Tables (LUT) and operate at a maximum frequency of 49MHz and its operation is verified on a Field Programmable Gate Array (FPGA). The proposed processor and its test platform can serve as a good educational tool as well as a help for processor design engineers both experienced and beginners.

FPGA implementation of a chaos-based image encryption algorithm

With the rapid development of communication networks and the establishment of 5G networks, there is a growing demand for the transmission of images and videos with different sizes and formats. Since these can contain sensitive and personal information, security is of great importance when transferring the contents of such files. Therefore, the use of powerful encryption mechanisms is an absolute requirement to protect the confidentiality of the exchanged data. In this study, we propose an image encryption algorithm with a high level of security. Thus, a chaotic system is proposed, and its state variables have been used to create a new substitution matrix. The importance of this matrix lies both in its use to generate encryption keys and in the encryption algorithm itself. In formulating the proposed encryption algorithm, we adopted the Feistel network in addition to some steps of the Advanced Encryption Standard (AES). The results of the various tests prove that the proposed algorithm guarantees high resistance to statistical and differential attacks and can therefore be used safely in image encryption. The incorporation of various algorithms suggested in this article in the form of IPcore for FPGA platforms amply promotes the use of our cryptosystem in various embedded systems or IoT environments.

Landscape of Automated Log Analysis: A Systematic Literature Review and Mapping Study

Logging is a common practice in software engineering to provide insights into working systems. The main uses of log files have always been failure identification and root cause analysis. In recent years, novel applications of logging have emerged that benefit from automated analysis of log files, for example, real-time monitoring of system health, understanding users’ behavior, and extracting domain knowledge. Although nearly every software system produces log files, the biggest challenge in log analysis is the lack of a common standard for both the content and format of log data. This paper provides a systematic review of recent literature (covering the period between 2000 and June 2021, concentrating primarily on the last five years of this period) related to automated log analysis. Our contribution is three-fold: we present an overview of various research areas in the field; we identify different types of log files that are used in research, and we systematize the content of log files. We believe that this paper serves as a valuable starting point for new researchers in the field, as well as an interesting overview for those looking for other ways of utilizing log information.

„Rzym a odrodzenie. Z dziejów ideologii rzymskiej”. Uwagi na temat zaginionej książki Borysa Łapickiego

Przedmiot badań: Zawartość teczki archiwalnej zawierającej dokumentację procesu przygotowywania recenzji wydawniczych monografii Borysa Łapickiego, noszącej tytuł Rzym a Odrodzenie. Z dziejów ideologii rzymskiej.
 Cel badawczy: (1) Zaprezentowanie trudności związanych z przeprowadzeniem procesu recenzyjnego monografii Łapickiego, która pomimo podjęcia przez Łódzkie Towarzystwo Naukowe licznych prób uzyskania merytorycznych recenzji zakończyła się niepowodzeniem. (2) Skonfrontowanie napotkanych przez ŁTN trudności z pozycją Łapickiego zajmowaną w polskim powojennym środowisku naukowym. (3) Próba odtworzenia treści monografii.
 Metoda badawcza: Analiza materiału archiwalnego zgromadzonego w zachowanej teczce dokumentującej proces recenzyjny. Rekonstrukcja zachowanych fragmentów monografii.
 Wyniki: (1) Większość kandydatów na recenzentów odmówiła podjęcia się zaproponowanej im funkcji. (2) Recenzenci, którzy przygotowali opinie na temat monografii, pozostawali w znacznym stopniu krytyczni wobec jej treści oraz przyjętej metodologii, jednak żaden nie zdecydował się na wyrażenie negatywnego stanowiska w odniesieniu do jej opublikowania. (3) Brak maszynopisu monografii uniemożliwia jednoznaczną weryfikację ocen recenzentów, lecz zachowane (zrekonstruowane) fragmenty książki pozwalają dostrzec jej istotne wady.1

CFFS: A Persistent Memory File System for Contiguous File Allocation With Fine-Grained Metadata

Extensive research on persistent memory (PM)-aware file systems has led to the development of numerous methods for improving read/write throughput. In particular, accessing or modifying file contents in a similar manner to the memory operations through <i>mmap</i> is a common approach. We designed a file system, CFFS (Contiguous File Allocation with Fine-Grained Metadata File System), to rapidly allocate PM pages to upper layer applications for <i>mmap</i> and to alleviate page fault overheads due to <i>mmap</i>. We optimized the physical contiguity of files in PM to reduce file fragmentation and increase fragment alignment with the goal of reducing software overhead. To achieve this goal, we implemented greedy-based buddy systems and implicit preallocation with a not-most-recently-used (NMRU) policy based on our overall page allocation strategy of considering not only the spatial but also the temporal locality of file access patterns. Furthermore, for efficient and atomic metadata operations, we fully leveraged the byte-addressable property of PM to design fine-grained metadata. CFFS adopts persistent doubly linked lists for directory operations to identify and recover from inconsistencies caused by system failures, doing so without using traditional log mechanisms. In experiments, CFFS showed superior page allocation performance to EXT4-DAX and NOVA did under different PM fragmentation levels. Our allocation algorithm also reduced the cost of page faults for frequently appended files. Finally, CFFS&#x2019;s lightweight directory operations performed excellently in creating and deleting files of various quantities. In summary, the main contribution of the paper is proposing an efficient page allocation algorithm to improve the performance of subsequent <i>mmaps</i>, based on the strategy of considering not only the spatial but also the temporal locality of file access patterns in PM file systems. Another contribution was the fine-grained and log-free method for atomic directory operations.

PSO-CALBA: Particle Swarm Optimization Based Content-Aware Load Balancing Algorithm in Cloud Computing Environment

Cloud computing provides hosted services (i.e., servers, storage, bandwidth, and software) over the internet. The key benefits of cloud computing are scalability, efficiency, and cost reduction. The key challenge in cloud computing is the even distribution of workload across numerous heterogeneous servers. Several Cloud scheduling and load-balancing techniques have been proposed in the literature. These techniques include heuristic-based, meta-heuristics-based, and hybrid algorithms. However, most of the current cloud scheduling and load balancing schemes are not content-aware (i.e., they are not considering the content-type of user tasks). The literature studies show that the content type of tasks can significantly improve the balanced distribution of workload. In this paper, a novel hybrid approach named Particle Swarm Optimization based Content-Aware Load Balancing Algorithm (PSO-CALBA) is proposed. PSO-CALBA scheduling scheme combines machine learning and meta-heuristic algorithm that performs classification utilizing file content type. The SVM classifier is used to classify users' tasks into different content types like video, audio, image, and text. Particle Swarm Optimization (PSO) based meta-heuristic algorithm is used to map user's tasks on Cloud. The proposed approach has been implemented and evaluated using a renowned Cloudsim simulation kit and compared with ACOFTF and DFTF. The proposed study shows significant improvement in terms of makespan, degree of imbalance (DI).

New Collaborative Caching Scheme for D2D Content Sharing in 5G

Device-to-Device (D2D) content sharing is an excellent solution to offload the traffic from the core 5G networks and backhaul links. Caching the most popular files at the network edge and in users’ devices to support user proximity services in 5G helps to offload traffic in the core network and increases the cache hit probability. D2D communication in 5G can be utilized to share the cached files between a pair of devices with a minimal involvement from the base station. This paper presents a collaborative content caching scheme with the primary objective to maximize the overall system offloading gain and the cache hit probability in downloading the popular file contents. The proposed system model exploits the social-networking concept within the WiFi Direct radio range, assuming the cell structure present in a densely populated area such as a university campus or an auditorium. The performance of the proposed cache scheme is evaluated through extensive simulations taking into consideration the device mobility and disconnection, and the results are presented.

Blockchain Document Forwarding and Proof Method Based on NDN Network

The digitization of the national economy and the development of the national network have rapidly increased the amount of data, and research in content storage and forwarding is significant. The existing methods of storing certificates and distributing file content entirely rely on the judgment made by the router, and the forwarding process does not consider the security and legality of the data; at the same time, the traditional peer-to-peer (P2P) forwarding network files cannot be effectively reused, and additional security mechanisms are introduced. It affects the performance of the network itself. To improve the overall network performance, optimize the file forwarding process, and ensure the security of content and the verification of historical information, this paper proposes a method for document content storage and distribution that integrates blockchain technology and Named Data Network (NDN). The advantages of data signature encryption, reverse path forwarding of content, and flexible routing improves the overall performance of the forwarding network. Combined with blockchain decentralization technology, the documents and transaction processes can be stored on the chain to ensure the actual security of the forwarding process. In addition, this paper restricts the forwarding process in the NDN network without making any judgments through smart contract rules to ensure the security of confidential files during the forwarding process and, at the same time, limit the forwarding scope of irrelevant junk files in the private network. Finally, experiments prove that the method proposed in this paper can effectively improve the network&#x2019;s overall performance, optimize the forwarding process, and make rule judgments on the forwarding process of specific files to ensure the security of files.

Fresh, Fair and Energy-Efficient Content Provision in a Private and Cache-Enabled UAV Network

In this paper, we investigate a private and cache-enabled unmanned aerial vehicle (UAV) network for content provision. Aiming at delivering fresh, fair, and energy-efficient content files to terrestrial users, we formulate a joint UAV caching, UAV trajectory, and UAV transmit power optimization problem. This problem is confirmed to be a sequential decision problem with mixed-integer non-convex constraints, which is intractable directly. To this end, we propose a novel algorithm based on the techniques of subproblem decomposition and convex approximation. Particularly, we first propose to decompose the sequential decision problem into multiple repeated optimization subproblems via a Lyapunov technique. Next, an iterative optimization scheme incorporating a successive convex approximation (SCA) technique is explored to tackle the challenging mixed-integer non-convex subproblems. Besides, we analyze the convergence and computational complexity of the proposed algorithm and derive the theoretical value of the expected peak age of information (PAoI) to estimate the content freshness. Simulation results demonstrate that the proposed algorithm can achieve the expected PAoI close to the theoretical value and is more 22.11% and 70.51% energy-efficient and fairer than benchmark algorithms.

Intricacies in image steganography and innovative directions

With the advancement in digital communication and data sets getting huge due to computerisation of data gathering worldwide, the need for data security in transmission also increases. Cryptography and steganography are well known methods available to provide security where the former use techniques that control information in order to cipher or hide their presence and the latter concentrates on data concealment. Steganography is the practice of masking data especially multimedia data within another data. Visual contents get more importance from people compared to audio contents and moreover visual content file is huge when compared to audio file thereby helping increase robustness of the hiding algorithms. In this paper, we consider three domains in which the image steganography algorithms are proposed along with the experimentation results on USC-SIPI image database which prove the betterment of the algorithms as compared with the traditional algorithms. We propose to use rule based LSB substitution method in spatial domain, XOR based hiding in frequency domain and data encryption standard based embedding in wavelet domain. We find that the proposed algorithms have a better PSNR value averaging close to 53 after embedding the secret data, while the existing algorithms has values of around 50.

Research on Route Pre-caching Based on Content Type Awareness

In order to improve cache hit efficiency and reduce network response delay in Vehicular Named Data Networking (VNDN) environment, a routing strategy based on content type awareness and a collaborative content pre-caching strategy based on content popularity prediction for probabilistic caching were proposed. Firstly, an appropriate route-forwarding strategy is selected according to the message characteristics and whether the destination node is known. Then, unsupervised learning topic model Latent Dirichlet Allocation (LDA) is used to dynamically predict the request preference of vehicle users. Secondly, the topological relationship between different devices in the Internet of vehicles and the predicted vehicle user preferences are used to accurately and effectively predict the popularity of content, so as to reduce the redundancy of content files cached by network devices and maximize the cache hit ratio. Simulation results show that compared with other content caching strategies, this content pre-caching strategy can effectively improve cache performance.

Fast Processing RNA-Seq on Multicore Processor

RNA Sequencing (RNA-Seq) is the sequencing and analysis of transcriptomes. The main purpose of RNA-Seq analysis is to find out the presence and quantity of RNA in an experimental sample under a specific condition. Essentially, RNA raw sequence data was massive. It can be as big as hundreds of Gigabytes (GB). This massive data always makes the processing time become longer and take several days. A multicore processor can speed up a program by separating the tasks and running the tasks’ errands concurrently. Hence, a multicore processor will be a suitable choice to overcome this problem. Therefore, this study aims to use an Intel multicore processor to improve the RNA-Seq speed and analyze RNA-Seq analysis's performance with a multiprocessor. This study only processed RNA-Seq from quality control analysis until sorted the BAM (Binary Alignment/Map) file content. Three different sizes of RNA paired end has been used to make the comparison. The final experiment results showed that the implementation of RNA-Seq on an Intel multicore processor could achieve a higher speedup. The total processing time of RNA-Seq with the largest size of RNA raw sequence data (66.3 Megabytes) decreased from 317.638 seconds to 211.916 seconds. The reduced processing time was 105 seconds and near to 2 minutes. Furthermore, for the smallest RNA raw sequence data size, the total processing time decreased from 212.380 seconds to 163.961 seconds which reduced 48 seconds.

Penerapan Fungsi Hash dengan Algoritma RIPEMD-128 Pada Aplikasi Duplicate PDF Scanner

The development of the digital world era continues to grow and is increasing. Many industries have switched to digital technology such as photos, videos, music, and so on. Of course, this change brings many benefits in terms of speed and data access. Ease of accessing the internet also has a major impact on human life. The ease of accessing documents online is very helpful if you want to find and download pdf documents online. With this convenience, many of the same pdf files are downloaded more than once. This will definitely burden the storage space. To distinguish one pdf file from another, it is done by viewing and reading the contents of the pdf file. This is very inconvenient and time consuming. To overcome this, we need a practical way that can be used to search for the same pdf document so that it can delete duplicate pdf files. One way that can be used to overcome this problem is to use a hash function. The hash function in cryptography is a very important tool in various cryptographic applications, for example in digital signature formation, authentication, and so on. Since the discovery of the MD4 hash algorithm by Ron Rivest, many other hash algorithms have been developed based on the principles of this algorithm. One of them is the RIPEMD-128 algorithm. RIPEMD-128 is an iterative hash function that operates on 32-bit words. By using a hash function, the identity of the pdf file can be generated. If the pdf files are the same it will produce the same hash value as well. This will make it easier to group the same pdf documents so that it will speed up the process of deleting the same pdf files. With the pdf file scanner application, pdf files will be searched for all folders and will group pdf files based on the same hash value. So that it will be easier for users to delete the same pdf file.

APPLICATION OF A FUZZY LOGIC SYSTEM TO DETERMINE THE RESOURCE OF AN ASYNCHRONOUS MOTOR

The article analyzes the method for determining the resource of an asynchronous motor through the use of fuzzy logic, explains the structure of the developed Fuzzy Logic System and the results of experiments on determining the resource of an asynchronous motor. The problems that are necessary to solve unambiguously determine the remaining resource of an asynchronous motor are formulated. In this paper, the developed fuzzy logic system will allow us to reasonably determine the residual life of an asynchronous motor based on the results of measuring the no-load current, air gap, insulation resistance, power factor, winding resistance at direct current, stator winding insulation absorption coefficient, stator winding insulation polarization coefficient, insulation modulus, stator temperature and bearing condition assessment. The results obtained during their implementation will help prevent failure of the asynchronous motor and reduce material damage associated with downtime of technological equipment, elimination of the consequences of accidents and repair of the failed electric motor itself. A method for determining the remaining resource of an asynchronous motor is developed using a fuzzy logic system in the Matlab software environment and the FuzzyLogic package. A fuzzy logic system is developed for determining the remaining resource of an asynchronous motor. A detailed study of the results of computer modeling is carried out , which indicate that the fuzzy logic system for determining the remaining resource of an asynchronous motor functions properly and is ready for operation. A fuzzy logic system normalizer is developed for determining the remaining resource of an asynchronous motor. The launch of the file content in the Matlab command line is analyzed in detail, which showed the result of the entire system of non-clear logic at minimum, maximum and average values of control parameters.

In-Depth Analysis of Ransom Note Files

During recent years, many papers have been published on ransomware, but to the best of our knowledge, no previous academic studies have been conducted on ransom note files. In this paper, we present the results of a depth study on filenames and the content of ransom files. We propose a prototype to identify the ransom files. Then we explore how the filenames and the content of these files can minimize the risk of ransomware encryption of some specified ransomware or increase the effectiveness of some ransomware detection tools. To achieve these objectives, two approaches are discussed in this paper. The first uses Latent Semantic Analysis (LSA) to check similarities between the contents of files. The second uses some Machine Learning models to classify the filenames into two classes—ransom filenames and benign filenames.

The application framework of big data technology in the COVID-19 epidemic emergency management in local government\u2014a case study of Hainan Province, China

BackgroundAs COVID-19 continues to spread globally, traditional emergency management measures are facing many practical limitations. The application of big data analysis technology provides an opportunity for local governments to conduct the COVID-19 epidemic emergency management more scientifically. The present study, based on emergency management lifecycle theory, includes a comprehensive analysis of the application framework of China’s SARS epidemic emergency management lacked the support of big data technology in 2003. In contrast, this study first proposes a more agile and efficient application framework, supported by big data technology, for the COVID-19 epidemic emergency management and then analyses the differences between the two frameworks.MethodsThis study takes Hainan Province, China as its case study by using a file content analysis and semistructured interviews to systematically comprehend the strategy and mechanism of Hainan’s application of big data technology in its COVID-19 epidemic emergency management.ResultsHainan Province adopted big data technology during the four stages, i.e., migration, preparedness, response, and recovery, of its COVID-19 epidemic emergency management. Hainan Province developed advanced big data management mechanisms and technologies for practical epidemic emergency management, thereby verifying the feasibility and value of the big data technology application framework we propose.ConclusionsThis study provides empirical evidence for certain aspects of the theory, mechanism, and technology for local governments in different countries and regions to apply, in a precise, agile, and evidence-based manner, big data technology in their formulations of comprehensive COVID-19 epidemic emergency management strategies.

The Incremental Shuttle Walk Test

The Incremental Shuttle Walk Test

A non-subsampled Shearlet transform based approach for heartbeat sound watermarking

To secure the heartbeat sound exchanged in telemedicine, we propose in this work a blind watermarking approach combining a Non-Subsampled Shearlet Transform and Singular Value Decomposition. This approach allows guaranteeing the patients' successful authentication by integrating a watermark containing the patient's specific information as well as his photography in the audio file. In this approach to decompose the signal into low and high frequencies, a Non-Subsampled Shearlet Transform is performed. Singular value decomposition is then applied to the obtained low frequency components and the watermark bits are integrated by modulating the singular values. The imperceptibility results have typically shown our approach can integrate a satisfactory amount of information while preserving the diagnostic content of the audio file. In addition, the robustness tests demonstrate the proposed approach can efficiently generate a watermark resisting to several attacks. The imperceptibility results have shown our approach can integrate a satisfactory amount of necessary information while preserving the diagnostic content of the audio file. Since the patient informations are embedded in the multimedia file, a watermark extraction will clearly authenticate the potential patient. Since the patient informations are embedded in the multimedia file, a watermark extraction will clearly authenticate the patient.

Timestamp prefix carving for filesystem metadata extraction

While file carving is a popular and effective method for extracting file content from unallocated space in a forensic image, it can be time consuming to carve for the wide variety of possible file signatures. Furthermore, file carving does not connect the discovered file to its filesystem metadata. These limitations of file carving are the advantages of Generic Metadata Time Carving, in which filesystem metadata is searched for by first finding repeated co-located timestamps using a potential timestamp carving algorithm. The potential metadata is verified by a filesystem specific parser, and the pointer within the metadata to the file data may allow for full file recovery. Currently, a limitation of the Generic Metadata Time Carving method is that it will only find metadata records that have multiple equivalent timestamps, thus missing metadata records and files with differing, but very similar, timestamps. Therefore, in order to improve the recall of the Generic Metadata Time Carving methodology, we have designed and implemented a prefix matching potential timestamp carving algorithm. We apply our experiments to realistic NTFS and Ext4 forensic images, in which we compare the precision and recall results for differing prefix lengths. Our results indicate that using prefix-based potential timestamp carving can yield significantly greater recall for extracting filesystem metadata records, with little to no reduction in precision as compared to the original exact potential timestamp carving method.

Empirical Study of Test Case and Test Framework Presence in Public Projects on GitHub

Automated tests are often considered an indicator of project quality. In this paper, we performed a large analysis of 6.3 M public GitHub projects using Java as the primary programming language. We created an overview of tests occurrence in publicly available GitHub projects and the use of test frameworks in them. The results showed that 52% of the projects contain at least one test case. However, there is a large number of example tests that do not represent relevant production code testing. It was also found that there is only a poor correlation between the number of the word “test” in different parts of the project (e.g., file paths, file name, file content, etc.) and the number of test cases, creation date, date of the last commit, number of commits, or number of watchers. Testing framework analysis confirmed that JUnit is the most used testing framework with a 48% share. TestNG, considered the second most popular Java unit testing framework, occurred in only 3% of the projects.