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Images captured in low-light conditions frequently suffer from shortcomings in the quality, contrast, and the luminance, which poses many difficult challenges for both of the automated computer vision systems and in the human observers to discern objects and intricate details within these images because these processes require images with high quality. To address this issue, a wide range of algorithms have been developed with the specific objective of increasing the luminance of such images. In this work, a comprehensive explanation of enhancement algorithms in the field of low-light imaging is provided. We begin by providing an introduction to low-light images, followed by an in-depth exploration of the different algorithms designed to enhance the low-light images. These algorithms include the traditional methods, such as Histogram equalization and the Retinex methods, as well as other traditional enhancement methods. In addition, we delve into the field of the deep learning techniques, which have had an important impact on the field of low-light images enhancement. These approaches include three learning models, including supervised, unsupervised, and semi-supervised learning, each of which plays a crucial role in the improving of the quality of low-light images. In conclusion, low-light image enhancement is an important field in image processing to get the best result. [ABSTRACT FROM AUTHOR]

An emerging paradigm known as "fog computing" improves real-time data processing and analysis by bringing cloud capabilities to the edge of the network. An adaptive scheduling technique is the centre of this study's optimization efforts for fog computing systems. Depending on the level of protection needed, it sorts received tasks into three categories: public, semi-private, and private. Then, it assigns each category to a certain Cloud Data Center (CDC) or Mobile Data Center (MDCs). To guarantee the best possible allocation of tasks, the algorithm considers a number of criteria, such as the quantity of jobs, the capacities of MDCs and CDCs, and communication delays. Examining the efficacy of three scheduling algorithms in homogeneous as well as hetero-geneous fog conditions sheds light on distribution of work, system efficacy and resource management. In order to optimise resource consumption and meet the varied needs of Internet of Things (IoT) applications, this study offers helpful recommendations for designing and operating fog computing infrastructures. [ABSTRACT FROM AUTHOR]

An essential part of digital computer systems are binary adders. Their fundamental carry-propagation process has not changed throughout time, despite the fact that advancements in circuit design, implementation techniques, and logic synthesis tools have substantially improved their structure. By directly communicating the sum bits of earlier bit positions rather than the carry, this study explores the potential of performing addition. A new design space, spanning from ripple-sum to sum-look-ahead adders, is created by transforming binary carry-propagate addition into an equal sum-propagate addition. Carry-propagate adders currently display better features when implemented in established implementation technologies, although having asymptotically comparable area and delay complexity. For the implementation of sum propagate adders, reversible logic gates are suggested in this research. This technique allows for the replacement of the logic gates in the circuit with reversible gates, which reduces latency and area. [ABSTRACT FROM AUTHOR]

Contemporary computer vision systems are typically trained to recognize a limited set of predetermined object categories. This restricted type of supervision limits their applicability and generalization since additional labeled data is needed to indicate any other visual concept. A potential approach that leverages a broader source of supervision involves learning directly from raw text about images. The proposed solution involves implementing a multimodal search in a fashion store using the Contrastive Language Image Pretraining (CLIP) model, which enables vector-based search rather than syntax-based search. CLIP improves product visibility and assists users in obtaining better search results that match their preferences. It is demonstrated that a simple pre-training task of predicting the corresponding image for a given caption is an effective and scalable technique for learning state-of-the-art image representations from scratch using a dataset of (image, text) pairs collected from the internet. Natural language is employed during pre-training to refer to learned visual concepts or describe new ones, enabling zero-shot transfer of the model to downstream tasks. Integration with clustering techniques on the vector space further enhances CLIP's capabilities, facilitating efficient and accurate retrieval of items. By grouping similar fashion items based on visual similarity and semantic relationships, the system enables efficient and accurate retrieval of relevant items. The model can generalize effectively to most tasks without requiring any training on a specific dataset and is frequently on par with a fully supervised baseline. [ABSTRACT FROM AUTHOR]

Statistical Process Control (SPC) is a quality management and improvement methodology that uses statistical techniques to monitor and control processes in order to ensure that they operate consistently and produce products or services that meet specified quality standards. Statistical Process Control (SPC) can also be applied in the context of embedded systems, which are computer systems integrated into various devices and products to perform specific functions. SPC in embedded systems serves a similar purpose as in other domains, but it focuses on monitoring and controlling the performance of the embedded system itself and the processes related to its development and maintenance. This comprehensive survey paper explores recent developments in Statistical Process Control (SPC) methodologies, their applications, and their integration with Thin Film Transistor (TFT) display interfacing, PIC24 microcontroller integration, and touchscreen technology across various domains. We investigate how SPC techniques have been harnessed to enhance quality control, predict faults, optimize processes, and incorporate TFT technology into diverse applications while interfacing with PIC24 microcontrollers. Additionally, we delve into advancements in touchscreen technology, including capacitive and resistive touchscreens. [ABSTRACT FROM AUTHOR]

Deep learning image reconstruction (DLIR) is a most recent computed tomography (CT) image reconstruction method for reducing image noise while maintaining the spatial resolution of the image. It is well-understood that image noise affects the low-contrast detectability (LCD) of the images. We assessed the LCD of DLIR images using parameters of CT number accuracy, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and visual assessment on the low-contrast module in a Catphan phantom and compared it to images reconstructed with filtered-back projection (FBP). We scanned the Catphan 604 phantom (The Phantom Laboratory, USA) with a 512 multi-slice computed tomography (MSCT) scanner. The images were reconstructed with different strengths of the DLIR algorithm (i.e., low, medium, and high). SNR was measured by placing region of interest (ROI) in the center of CTP729 module (i.e. module for measuring CT number uniformity) of the Catphan phantom. CNR was measured by placing two ROIs in the center and a circular object with diameter of 15 mm on CTP730 module (i.e., module for measuring low-contrast detectability) of the Catphan phantom. Low contrast objects were also assessed visually on a 2D viewer software provided by Advantage Workstation Computer System (GE Healthcare, USA). The results show that the CT number for DLIR and FBP algorithms had no significant changes, but the noise levels on DLIR images were reduced compared to those from FBP. The noise levels were reduced to 2.9 HU (or 38.16%) for low-DLIR, 3.74 HU (or 49.21%) for medium-DLIR and 4.7 HU (or 61.84%) for high-DLIRh. Therefore, the SNR improved by 37.5, 49.35 and 61.94% for low-, medium-, and high-DLIR, respectively. The CNR were 0.68, 0.98, 1.2, 1.46 for FBP, low-DLIR, medium-DLIR and high-DLIR, respectively. Compared to CNR from FBP, the CNR improved by 30.61% for low-DLIR, 43.33% for medium-DLIR and 53.42% for high-DLIR. These results corresponded to our visual assessment that LCD is improved as the strength of the DLIR algorithm is increased. In conclusion, it is found that if the strength of the DLIR algorithm increases, then the noise level is reduced and the SNR and CNR are increased. Hence, the DLIR algorithm has a better conspicuity to detect low-contrast objects compared to those from FBP. [ABSTRACT FROM AUTHOR]

Exascale Computing is the next stage of high performance computing system where computer system can perform the operation of 1018Floating point operations per second (FLOPS). Exascale Computing systems are built to give extremely high levels of computational power, making them appropriate for demanding computational activities including data analysis, sophisticated simulations, and scientific research, machine learning any more. Due to high processing capability, ESC has various applications such as climate modeling, nuclear physics, drugs discovery, Artificial Intelligence (AI) etc. Power Management, hardware reliability, software scalability, data flow optimization, and security considerations are few challenges of Exascale Computing. This article provides an overview of operating system; development and the different applications are discussed in Exascale Computing such as genomics, drug discovery, data analysis etc. This research paper also presents advantages and difficulties in Exascale Computing. [ABSTRACT FROM AUTHOR]

Artificial Intelligence is a cutting-edge innovation that might revolutionize K-12 education system. In this literature review, we explore the relationship between AI and K-12 education research. We categorize the findings based on the analysis of several investigative components. We examine the many applications of AI in education and organize them into 24 subcategories in addition to four primary categories: performance, behavior, teaching, and student selection. AI and education have had a tremendous influence on the educational system. It is feasible to teach these systems to become more intelligent, which will enable them to handle challenging issues like purpose, feelings, standards of morality, and behaviour. As a result of individual devices' progress and computer systems, AI has grown so far that it can now be seen in a variety of industries. Moreover, the capacity to connect machine-based technology to other device or machines is significantly responsible for the widespread application of AI. In conclusion, this project highlights the potential of AI for K-12 in the education system. Policymakers and stakeholders should devise a strategy to make learning simpler and more effective by integrating AI technologies into numerous education-related sectors. As a result, teachers may be more effective in the classroom, and students can benefit from higher-quality learning opportunities. This information is crucial for researchers to improve the significance and value of their work forfuture studies. [ABSTRACT FROM AUTHOR]

The person's attitude and emotion can be recognized from their facial expressions. People frequently use their facial expressions to convey their feelings. Music is one item that can alter someone's mood. Lips and eyes serve as more than just sensory receptors; they also let us know how someone is feeling. The article offers a model named Emotion-based Smart Music Recommendation System a computer programmer that makes it easier for users to make playlists and play music. The initiative attemptsto record a person's feelings through their facial expressions and uplift their spirits by playing music that is appropriate for the circumstance. It can gradually settle the user's mind and captures and recognizes the emotion they are expressing; therefore, it typically has a positive impact. Through the use of the computer system's webcam interface, the music player is made to record human emotions. The system takes the user's photo when the application launches. The photo was captured using a webcam. After saving the previouslyacquired image, rendering will begin. The user's mood may alter after some time, and it might or might not change. As a result, the picture is taken after every song or predetermined amount of time. And the image will be sent on to the following stage. Mood modification may occasionally be useful in overcoming depressive and sad circumstances. Expression analysis is capable of reducing the number of health concerns and enhancing user mood. As a result, the suggested system offers a face-based emotion detection systemto identify emotions and play appropriate music can be suggested for IoT platform such as wearable device. [ABSTRACT FROM AUTHOR]

In today's digital world, the usage of computers is inevitable. Poor posture, prolonged exposure to computer screens has been causing a lot of health impacts to everyone who is spending a considerable amount of time in front of the computer screen. Ergonomics is a branch of science that aims to reduce strain, stress, and injury through optimizing workstation design. In this project, certain computer ergonomic designs are employed digitally to mitigate the health effects. We use computer vision to keep the users more health aware while using the computers by keeping track of various factors like the distance between the user's face and the screen, and the user's sitting posture. Also, the famous 20-20-20 rule is implemented digitally which prevents the users from constantly looking at the computer screen by inverting the concept of screen proctoring. The user is motivated to physically move away from the screen at a user-defined time interval by preventing the user from proceeding with his task until the camera detects no person in front of the desk for a certain time-period. The user will be able to track all these activities in a dashboard where all data is visualized in the form of charts and graph. [ABSTRACT FROM AUTHOR]

In higher learning, cloud computing has become a game-changing technology supplying multiple bonuses, including scalability, affordability, and accessibility. In cloud computing systems, work scheduling effectiveness has implications for leveraging the expenditure of resources alongside improving user experience. This study argues a unique architecture for cloud computing in educational sectors grounded on the round-robin scheduling algorithm. The advocated framework's design and implementation are the predominant subjects of this study; the suggested framework's design and implementation are the main topics of this study, which also carries out a thorough performance analysis to assess its success. The study examines the system's typical waiting time and considers an assortment of cloudlets. Results revealed that the round-robin scheduling method significantly decreases waiting times and boosts resource utilization. [ABSTRACT FROM AUTHOR]

One of the major emerging sectors that has the potential to alter how people live is the smart home. A typical wireless smart home automation system enables one to operate household appliances from a wirelessly connected to a central control unit. For these appliances to work properly together and with the control unit, they typically need to be specially built. One can wirelessly control air conditioners, lights, fans, television sets, security cameras, computer systems, audio/visual equipment, electronic doors, etc. withthe developed system, which can be integrated into a single small unit. One can also turn ON or OFF any appliance that is plugged into an electrical outlet., find out the state of various sensors and make a judgementbased on it. The system is designed to be simple to install, setup, use, and maintain. Soon, voicewill be the main point of contact between people and technology. The issue is the state of the elderly or disabled, who frequently need outside aid to move around and are unable to help themselves. Those who live alone could also want assistance around the house. As a result, a system for voice-controlled wireless control of household appliances is created so that users can carry out specific operations using voice commands. In our present day to day life in smart home devices can be controlled using a single platform like google assistant or Alexa. This paper mainly focuses on developing one product which can be controlledusing multiple devices. This paper is based on the integration of various sensors like LDR sensor, temperature sensor, IR sensor and humidity sensor which collect the information and process the output based on the user commands. It also focuses on developing a universal remote using IR sensor to control multiple devices using a smartphone. [ABSTRACT FROM AUTHOR]

The HL-LHC run is anticipated to start at the end of this decade and will pose a significant challenge for the scale of the HEP software and computing infrastructure. The mission of the U.S. CMS Software & Computing Operations Program is to develop and operate the software and computing resources necessary to process CMS data expeditiously and to enable U.S. physicists to fully participate in the physics of CMS. We have developed a strategic plan to prioritize R&D efforts to reach this goal for the HL-LHC. This plan includes four grand challenges: modernizing physics software and improving algorithms, building infrastructure for exabyte-scale datasets, transforming the scientific data analysis process and transitioning from R&D to operations. We are involved in a variety of R&D projects that fall within these grand challenges. In this talk, we will introduce our four grand challenges and outline the R&D program of the U.S. CMS Software & Computing Operations Program. [ABSTRACT FROM AUTHOR]

The Worldwide LHC Computing Grid (WLCG) is a large-scale collaboration which gathers computing resources from more than 170 computing centers worldwide. To fulfill the requirements of new applications and to improve the long-term sustainability of the grid middleware, newly available solutions are being investigated. Like open-source and commercial players, the HEP community has also recognized the benefits of integrating cloud technologies into the legacy, grid-based workflows. Since March 2021, INFN has entered the field of cloud computing establishing the INFN CLOUD infrastructure. This platform supports scientific computing, software development and training, and serves as an extension of local resources. Among available services, virtual machines, Docker-based deployments, HTCondor (deployed on Kubernetes) or general-purpose Kubernetes clusters can be deployed. An ongoing R&D activity within the ATLAS experiment has the long-term objective to define an operation model which is efficient, versatile and scalable in terms of costs and computing power. As a part of this larger effort, this study investigates the feasibility of an automated, cloud-based data analysis workflow for the ATLAS experiment using INFN CLOUD resources. The scope of this research has been defined in a new INFN R&D project: the INfn Cloud based Atlas aNalysis faciliTy, or INCANT. The long-term objective of INCANT is to provide a cloud-based system to support data preparation and data analysis. As a first project milestone, a proofof-concept has been developed. A Kubernetes cluster equipped with 7 nodes (total 28 vCPU, 56 GB of RAM and 700 GB of non-shared block storage) hosts an HTCondor cluster, federated with INFN's IAM authentication platform, running in specialized Kubernetes pods. HTCondor worker nodes have direct access to CVMFS and EOS (via XRootD) for provisioning software and data, respectively. They are also connected to a NFS shared drive which can optionally be backed by an S3-compatible 2 TB storage. Jobs are submitted to the HTCondor cluster from a satellite, Dockerized submit node which is also federated with INFN's IAM and connected to the same data and software resources. This proof-of-concept is being tested with actual analysis workflows. [ABSTRACT FROM AUTHOR]

Recent years have seen an increasing interest in the environmental impact, especially the carbon footprint, generated by the often large scale computing facilities used by the communities represented at CHEP. As this is a fairly new requirement, this information is not always readily available, especially at universities and similar institutions which do not necessarily see large scale computing provision as their core competency. We present the results of a survey of a large WLCG Tier 2 with respect to power usage and carbon footprint leveraging all sources of information currently available to us. We show that it is possible to estimate the environmental impact with respect to power usage without having to invest in dedicated monitoring equipment. Manufacturers however do not yet provide sufficient information to allow for a detailed analysis of the carbon footprint of equipment manufacture, but even with the available information it is clear that this cannot be ignored. [ABSTRACT FROM AUTHOR]

The Worldwide LHC Computing Grid (WLCG) relies on the network as a critical part of its infrastructure and therefore needs to guarantee effective network usage and prompt detection and resolution of any network issues, including connection failures, congestion, and traffic routing. In this paper, we will describe our ongoing work to proactively analyze, correlate and alert on various network and infrastructure issues. We will discuss the methods and techniques applied, the systems developed, and the challenges with the measurements that make it difficult to easily identify problems or assign those problems to the appropriate location(s). [ABSTRACT FROM AUTHOR]

GlideinWMS is a distributed workload manager that has been used in production for many years to provision resources for experiments like CERN's CMS, many Neutrino experiments, and the OSG. Its security model was based mainly on GSI (Grid Security Infrastructure), using X.509 certificate proxies and VOMS (Virtual Organization Membership Service) extensions. Even when other credentials, like SSH keys, were used to authenticate with resources, proxies were also added all the time, to establish the identity of the requestor and the associated memberships or privileges. This single credential was used for everything and was, often implicitly, forwarded wherever needed. The addition of identity and access tokens and the phase-out of GSI forced us to reconsider the security model of GlideinWMS, to handle multiple credentials which can differ in type, technology, and functionality. Both identity tokens and access tokens are supported. GSI proxies even if no more mandatory, are still used, together with various JWT (JSON Web Token) based tokens and other certificates. The functionality of the credentials, defined by issuer, audience, and scope, also differ: a credential can allow access to a computing resource, or can protect the GlideinWMS framework from tampering, or can grant read or write access to storage, can provide an identity for accounting or auditing, or can provide a combination of any the formers. Furthermore, the tools in use do not include automatic forwarding and renewal of the new credentials so credential lifetime and renewal requirements became part of the discussion as well. In this paper, we will present how GlideinWMS was able to change its design and code to respond to all these changes. [ABSTRACT FROM AUTHOR]

Cloudscheduler is a system to manage resources of local and remote compute clouds and makes those resources available to HTCondor pools. It examines the resource needs of idle jobs, then starts virtual machines (VMs), sized accordingly, on allowed clouds with available resources. Using yaml files, cloudscheduler then provisions the VMs during the boot process with all necessary tools needed to register with HTCondor and run the experiment's jobs. Although we have run cloudscheduler in its first version for ATLAS and Belle-II workloads successfully for more than 10 years, we developed cloudscheduler version 2 (CSV2), a complete overhaul and modernization of cloudscheduler. The new system is used successfully in production for Belle-II, ATLAS, DUNE, and BABAR. In addition to using cloudscheduler version 2 as a WLCG site, we also run it as a service for other WLCG sites, and the Canadian Advanced Network for Astronomical Research (CANFAR) group uses its own instance of CSV2 for their astronomy workloads. In this paper, we report on our experience in operating CSV2 for different experiment's jobs, running on up to 10,000 cores across all experiments and clouds in North America, Australia, and Europe. We will also report on how to correctly account for the resource usage in the WLCG APEL system, how the monitoring works, as well as on the integration of different clouds and how to use resources opportunistically. [ABSTRACT FROM AUTHOR]

Predicting the performance of various infrastructure design options in complex federated infrastructures with computing sites distributed over a wide area network that support a plethora of users and workflows, such as the Worldwide LHC Computing Grid (WLCG), is not trivial. Due to the complexity and size of these infrastructures, it is not feasible to deploy experimental test-beds at large scales merely for the purpose of comparing and evaluating alternate designs. An alternative is to study the behaviours of these systems using simulation. This approach has been used successfully in the past to identify efficient and practical infrastructure designs for High Energy Physics (HEP). A prominent example is the Monarc simulation framework, which was used to study the initial structure of the WLCG. New simulation capabilities are needed to simulate large-scale heterogeneous computing systems with complex networks, data access and caching patterns. A modern tool to simulate HEP workloads that execute on distributed computing infrastructures based on the SimGrid and WRENCH simulation frameworks is outlined. Studies of its accuracy and scalability are presented using HEP as a case-study. Hypothetical adjustments to prevailing computing architectures in HEP are studied providing insights into the dynamics of a part of the WLCG and candidates for improvements. [ABSTRACT FROM AUTHOR]

DIRAC is the interware for building and operating large scale distributed computing systems. It is adopted by multiple collaborations from various scientific domains for implementing their computing models. DIRAC provides a framework and a rich set of ready-to-use services for Workload, Data and Production Management tasks of small, medium and large scientific communities having different computing requirements. The base functionality can be easily extended by custom components supporting community specific workflows. DIRAC is at the same time an aging project, and a new DiracX project is taking shape for replacing DIRAC in the long term. This contribution will highlight DIRAC's current, upcoming and planned capabilities and technologies, and how the transition to DiracX will take place. Examples include, but are not limited to, adoption of security tokens and interactions with Identity Provider services, integration of Clouds and High Performance Computers, interface with Rucio, improved monitoring and deployment procedures. [ABSTRACT FROM AUTHOR]

The CERN Tape Archive (CTA) is the successor to CASTOR and the tape backend to EOS. It was designed to meet the needs of archival storage of data from LHC Run–3 and other experimental programmes at CERN. In the wider Worldwide LHC Computing Grid (WLCG), the tape software landscape is quite heterogeneous, but we are entering a period of consolidation. A number of sites have reevaluated their options and are choosing CTA for their future tape archival storage needs. However, CTA's original mandate imposed several design constraints which are not necessarily optimal for external sites. In this contribution, we show how CERN has engaged with the wider HEP community and collaborated on improvements which allow CTA to be adopted more widely. We detail community contributions to allow CTA to be used as the tape backend for dCache; to facilitate migrations from other tape systems such as OSM and Enstore; and improvements to CTA building and packaging to remove CERN-specific dependencies and to allow easy distribution to external sites. Finally, we present a roadmap for the community edition of CTA. [ABSTRACT FROM AUTHOR]

The quick development of technology not only makes life easier but also raises several security concerns, so cyber security has become very important and vital research area, rather an inevitable part of computer system. Still, various research being done on the development of effective intrusion detection system (IDS). An IDS is one of the suspicious network activities. An IDS is used to identify many types of malicious actions that can undermine a computer system's protection and confidence. Recently, ensemble algorithms are applied in IDS in order to identify and classify the security threats. In this paper author intends to do a brief review of various Ensemble learning Algorithms in ML, which are most frequently used in IDS for several applications; with specific interest in dataset and metric. This work provides broad study and investigation on current literature, the gap for improving and creating efficient IDS can be determined. [ABSTRACT FROM AUTHOR]

The purpose of the article is to reveal the possibilities of information modeling of technological processes of effective info communication systems, which makes it possible to improve the reliability and quality of systems. To achieve this goal, the following tasks were solved. As a rule, service order flows are assumed to be Poisson, which is not true in all cases; therefore, it is necessary to consider a modification of the Kolmogorov equation in order to obtain a system of equations that is valid for any dispersions, which will allow them to be used in any supply chains. It is shown that the information approach to modeling systems allows in real conditions to refine the algorithm or to simplify and speed up the procedure for finding a solution using the queuing chain method. Such chains can be associated with both purely production (technological) processes and information processing processes in telecommunications and computer systems. Therefore, the model developed in the article will allow changing the conditions for setting the task of upgrading the network and finding the optimal solution. The method is shown to be promising, since it is designed for the effective use of technical means in the construction of info communication systems. [ABSTRACT FROM AUTHOR]

The article discusses the types and structure of neural networks, problems and prospects for the construction of intelligent onboard measuring, computing and control systems of modern spacecraft based on artificial neural networks. It also provides methods for learning the capabilities of a multilayer perceptron in data classification, designing and implementing a data classification system based on a multilayer perceptron model with one or more hidden layers, and comparing the results obtained with different network parameter settings. The training of a multilayer perceptron is understood as the process of adapting the network to the presented reference samples by modifying the weight coefficients of connections between neurons. Training a multilayer perceptron by the method of error backpropagation involves a forward and backward pass through all layers of the network: Methods for hardware implementation of multilayer perceptron's with dynamically tunable channels of weight coefficients are shown. [ABSTRACT FROM AUTHOR]

In the age of social media and online offers, many criminal offenses are also occurring nowadays. Cybercrime refers to crimes committed online or through the internet. Such attacks are carried out intentionally, which is why they are classified as criminal offenses. According to data on cybercrime, as of January 2021, Google has registered approximately two million domains that are used for phishing. In 2019, roughly 93.6% of the malware that was discovered was polymorphic, which means that it continuously modified the code in order to avoid being discovered. As more people use information and communication technologies, the rate of cybercrime has skyrocketed. Many nations throughout the globe have implemented safeguards to protect their computer systems. This has led to the discussion of cyber-crimes in many countries. Some countries have incorporated cybercrime into their national law. Therefore, the goal of this research was to use a descriptive and relational approach to bibliometric analysis to show how cybercrime research has changed over time, how its ideas have changed, and how its themes have changed since it was first conducted. In light of this, the terms "cybercrime" and "crime" are both used in the title, and the term "law" is included in the Title, Abstract, and Author keyword fields. This was done to limit the publication to English-language journals and proceeding sources. The results of this investigation yielded 82 linked articles published between 2000 and 2022. As a direct result, the sources, authors, institutions, and nations with the highest productivity rates were determined. In addition, patterns of collaboration among various actors were analyzed. Computers, cyberwar, and national security are driving themes in cybercrime research. They represent frequently treated topics that make up the mainstream research and are, therefore, essential for the formation of a disciplinary core. [ABSTRACT FROM AUTHOR]

The article deals with the main databases ORACLE and PostgreSQL. The experience of their application in various fields is analyzed. The main user criteria are illustrated, according to which it is desirable to select and use these databases. It is shown that ORACLE is preferable to use for complex, unique, as a rule, corporate control systems, where high reliability and efficiency are required, and PostgreSQL will find its place for many small and medium-sized control systems with a small computing resource, compatible with other databases, where required. open source. [ABSTRACT FROM AUTHOR]

This paper proposes a syllabus for training students from schools or universities, as well as specialists with different educational backgrounds on the Internet of Things (IoT) discipline. The topics of lectures and lab (practical) exercises are presented. Step by step the main points of the themes are synthesized. IoT computer systems development is described, too. The algorithms of corresponding programs are suggested. In these lectures and laboratory exercises, the experience of the authors is used, as well as similar syllabuses from several universities. [ABSTRACT FROM AUTHOR]

The problem of utilizing machine learning in cyber security is complicated to resolve it. The explanation for this is not straightforward because developments in the sector have led to the opening so many opportunities. That is difficult to select the ones that are the greatest and most effective for making decisions and putting them into action. In addition, intruders can utilize technology of this kind to launch attacks against computer systems. The purpose of this research is to investigate the application of machine learning in the context of cyber defense and cyber-attacks. In addition, present a model of an attack driven by machine learning. [ABSTRACT FROM AUTHOR]

Research development of Unmanned Combat Aerial Vehicle (UCAV) or fixed wing Combat Drone requires an accurate weapon scoring system for shooting training assessments to determine the type and capability of the rocket weapon to be used. The current camera-based rocket fire assessment method is only to determine the position of the rocket's impact point on the target, resulting in the pattern of combat training being limited to one shooting heading. The orientation of the rocket shooting practice with only one heading will result in the dependence of the UCAV pilot in carrying out the attack, it will be difficult to carry out firing patterns from various directions. One of the reasons for this is that the camera calibration method for the target area of the shot used is not yet oriented to multi-heading shots. This study aims to produce a method of weapon scoring system for the purposes of UCAV which is focused on calibrating the camera with computer vision for the area of the shot where the attack source is multi-heading. This study proposes a method of Clockwise-elliptical calibration using computer vision for monitoring and evaluating air to ground shooting exercises using high speed weapons. The method generates five main steps, i.e Input Video, Determination of 5 Main Points, Selection of Target Areas in the Image, Object Shape Transformation, and Calculation. The result succeeded in informing the position of the rocket explosion point and its distance from the center point and the angle of the rocket, the accuracy of the shape of the rocket trajectory to the impact point according to geo coordinates, sourced from variations in shot headings. [ABSTRACT FROM AUTHOR]

This article describes the experience of using the Maple computer algebra system and Maplet interactive applications built on its basis in the educational process in the study of mathematical induction in the preparation of future teachers of mathematics and computer science. The authors analyzed the scientific literature on the use of information technology in the study of discrete mathematics. Maplets interactive applications have been improved for conducting practical classes on the study of mathematical logic within the framework of the discipline "Discrete Mathematics". The Maple computer algebra system is used, designed for computer modeling of processes used in performing actions to prove equalities (sum), divisibility and inequalities using the method of mathematical induction. Questioning, observation, performance of control work, as well as analytical and interactive methods of the Maple computer algebra system were used as research methods. The results and analysis of the conducted experiments on the implementation of proofs, using the Maple system, checking equalities, divisibility and inequalities are presented. The theoretical and/or practical significance of the work is related to the evaluation of the effectiveness of the use of computer modeling and experimentation in Maple, a number of advantages are identified that improve the quality of the educational process and evaluate them. [ABSTRACT FROM AUTHOR]

The adoption, in 2001, in Budapest, of the Council of Europe Convention on Cybercrime brought an important step forward in the prevention and combatting cyber-related crimes, through the creation of a special indictment (art. 6) against the production, sale, procurement for use, import, distribution, import or making available of devices, computer programs, passwords or any other such data with the scope to further illegal access to a computer system, interception without right of a computer data transmission, an illegal data interference or an illegal system interference, offences comprised in the art. 2 to 5 of the Convention. Although the offence in art. 6 represents the „mean-crime" in relation with the further commission of the above mentioned crimes against the confidentiality, integrity and availability of computer data and systems („purpose-crimes"), the nowadays Cybercrime phenomenon shows that the misuse of the devices and computer programs actually exceeds the legal boundaries of art. 2 to 5, and (technically) impacts much of the other forms of cyber-related or cyber-enabled offences, especially in the FinTech area, electronic payment, blockchain, cryptocurrency etc. Taking into consideration the proliferation of illegal activities against personal information, confidential data or access credentials, especially the commercialization, especially in Dark Web, of codes, passwords, hacking tools, malware and other present or future cutting-edge system interference technologies, thus posing a great danger to the whole cyber-ecosystem, an improvement of art. 6, and of all the correspondent (related) articles in the special laws or the criminal codes adopted by the signatory countries, would contribute to the creation of an extensive and much comprehensive legal tool in the prevention and efficiently combating cybercrimes. [ABSTRACT FROM AUTHOR]

According to the World Health Organization, there are approximately 285 million blind people around the world. Those people faced challenges in their life, especially when reading a book. This paper is aims to test and evaluation the audio reading system (which is use to help the blind person to read the book) with new dataset which consist of 161 image, 8 font size, mono and color image, and different views. The system is test and discussion from the aspects: accurate, Font size and type, and more reliable. According to the results (on our dataset (image type, 161 images)), the characteristics of the system is efficient and accurate real time system with cloud computing and the accuracy increase while the font size increase, whereas the accuracy of font size 30 is 100% and of 12 is 80%. [ABSTRACT FROM AUTHOR]

Mostly, the Personnel Information Applications required the human name as a full term in all human resources submissions. The full name attribute consists of five parts: First name, Second name, Third name, Fourth name, and Family name. Most queries require to display the name of any person in a variety form to reply the requested demand of this type of information, this type of requests involves amount of storage in both memory and a secondary storage, in addition to significant CPU processing time [1]. In this paper an attempt to optimize the storage requirements and processing time requested to deal with person full name efficiently. Due to the processing name as, composite attributes need some attention during all stages that concerns this type of data such as: insertion, update, arrange, delete, truncate...etc. In most human resources applications, name of an individual starting of his/her birth date need to be recorded correctly in many applications: Either social and business, and must be kept in save and secure places, even after the person death. Normally person name in most computer system is a variable size field and usually it requires range of characters between 20 – 40 characters: each character require one byte. The experiment of the suggested method shows significant reduction in both storage and processing time, where for a dataset of 6904 persons full name requires 2000 Parts Names in the index Names, while if the number of records in the application reach several millions records the size of index will remain approximately constant. The optimization factor in storage very high and it might be exceed 98%, and it is proportional to the numbers records volume of the information in a database files, and the limit of integer type of two Bytes (uint) which can accommodate number of part names code equal to (216 – 1), for value range between 0-65535. Also, the optimization will directly affect the processing time in both off line and on-line applications systems, especially nowadays the computer technology have been offered a power of parallel processing in both Hardware and Software. [ABSTRACT FROM AUTHOR]

The article highlights the role and features of the study of the functioning of the English language in higher education. The state of education in the Republic of Uzbekistan and the development trends of society are the most effective problems of the advanced development of the education system based on computer technology and the creation of a unified educational information environment. With the rapid development of science and the rapid updating of information, it is impossible to study all your lifetime, it is important to develop an interest in obtaining knowledge for continuous self-education. The main objective of the training is to achieve a new modern quality in the upbringing of the modern, young generation. [ABSTRACT FROM AUTHOR]

A robotic arm is an artificial arm designed to carry out specific activities. For many non-human scenarios where human communication is impossible, there are more and more reasons to construct robotic arms nowadays. People pick up things without thinking about the procedures necessary, and robotic arms that are controlled manually via wired and wireless technology are also used. The goal of this study is to regulate the robotic arm's angle using an Arduino UNO board, an ultrasonic sensor, and a digital controller connected to a computer system. The robotic arm has five degrees of freedom (DOF), five joints, and servo motors at each one. Servo motors can control their position with the aid of a microcontroller. This Servo motor enables the Robotic Arm to position the necessary link at the proper angle. A rotary encoder can be used to measure the angle feedback. The goal of this research work is to introduce the level of intelligence that may be used by industries to decrease human mistake rates while also improving manufacturing and processing's quality and speed of output. The main benefit of the robotic arm is that it can operate in dangerous conditions that are unsuitable for people, such as high temperatures and pressure. It is simple to update and modify the Robotic Arms. The entire cost and risk of workplace injuries are decreased by the robotic arm. Experimental verification has been made of the designed robotic arm's functionality. Results from the simulation are shown and discussed. [ABSTRACT FROM AUTHOR]

Multi-core processor with hierarchical multilevel cache helps to reduce memory access time and also lower down the speed gap between primary memory and processor. Many replacement policy has been designed to improve the last level cache and an effective replacement policy helps to optimize the usage of last level cache with respect to different high level intensive workload in a multi-core computer system. In this manuscript we have designed an augmented replacement strategy Recency timer count Re-Reference Interval Prediction (RTC_RRIP). The RTC_RRIP policy uses recency time prefilter which accelerates the re-reference interval prediction accuracy to minimize number of cache misses and miss penalty. We perform analysis using GEM 5 simulator and uses some traces from CPU2017 benchmarks application program to compare RTC_RRIP with existing LRU and hawkeye policy. We reveal that RTC_RRIP is showing better performance over LRU and Hawkeye in terms of hit rate and execution time. [ABSTRACT FROM AUTHOR]

Nowadays, to reach a progressive growth although being competitive in the market, the manufacturing industries are using advanced technologies like, cloud computing, internet of things (IoT), artificial intelligence, 3D printer, nano technology, cryogenics, robotics and automation in smart manufacturing sectors. One such subclass of artificial intelligence is a machine learning, which uses computer system for making prediction and to perform definite task without any use of specific instructions to enhance the quality of the product, rate of production, to optimize the processes and its parameters in machining operations. A broad category of manufacturing which is technology driven that utilizes internet connected machines to monitor the performances of manufacturing processes referring as Smart manufacturing. The current paper presents a comprehensive survey and summary of different machine learning algorithms which are being employed in various traditional and non-traditional machining processes and also an outlook of manufacturing paradigm is presented. Subsequently, future directions to machining industry were proposed based on trends and challenges that are accompanying with machine learning. [ABSTRACT FROM AUTHOR]

Tree growth regulation networks are dynamic and stochastic, with feedback that regulates their growth function at different ages. Modelling of the tree growth process poses new challenges due to the large number of trees in the stand and the stochastic nature of their interactions. In this study, we motivate stochastic modeling of tree growth networks and demonstrate the method using a 4-parameter Gompertz type diffusion process and an observed dataset from permanent sample plots. In order to cover a wider range of forest stands, random effects are additionally included in the model. We perform parameters estimation of the fixed-and mixed-effect scenario models for the diameter growth model by an approximated maximum likelihood procedure and using a dataset of longitudinal measurements. The newly developed mathematical model is fitted by determining the numerical values of the parameters in order to best respond to the measurements collected during the experiment. The results are validated using an independent validation dataset. All results are obtained in the Maple computer algebra system. [ABSTRACT FROM AUTHOR]

Somatosensory games can achieve human-computer interaction, without the need for a handle or keyboard, directly using the body to complete the game. As a modern interactive way, its interactive form full of technology to show the shocking effect. This design develops an Arduino-based gesture game simulator, which combines Arduino and PAJ7620 gesture sensor to realize the most critical part of gesture recognition in the gesture game, and displays the recognition result through LED display. By building the hardware circuit and coding the software code, the gesture recognition function of the game is finally realized. The test shows that the gesture recognition device designed in this project can provide different data according to different gestures, and has been realized to interact with computer system, and can be run in various computer applications, which has considerable development prospect. [ABSTRACT FROM AUTHOR]

The load unbalancing problematic is a multi-variable, multi-constraint problem that reduces the effectiveness of computer systems. Overloading and underloading are two forms of load unbalancing that may be remedied with load balancing methods. To the best is no exhaustive, systematically hierarchical classification of existing load balancing strategies despite the critical nature of such methods. There is also a lack of research and consideration in the literature about the causes that lead to the load unbalancing problem. This study provides a comprehensive analysis of the various strategies for load balancing. Highlighting the benefits and drawbacks of current approaches, as well as tackling critical difficulties, is essential for creating effective load balancing algorithms in the future. The research also offers novel ideas for load balancing. [ABSTRACT FROM AUTHOR]

The necessity of microprocessor-based computer hardware systems has increased as a result of the advancement in technology. Now we are able to create any desirable and portable system with emerging technologies. In this paper, we present an Arduino-based computer hardware system that can be used to measure the height of a person with the help of ultrasonic sensors. The ultrasonic sensor detects the height or the distance of the object from the reference level with accuracy. Therefore, the sensor is considered as the key elements of the embedded system. The sensor is interfaced using Arduino Nano board and programmed using Arduino IDE. Other important components are the potentiometer and Liquid Crystal Display (LCD). This method of detecting distance using an ultrasonic sensor is precise, accurate, and effective. The purpose of this project is to create a portable height measurement device that is eco-friendly and cost effective. [ABSTRACT FROM AUTHOR]

In the light of the transformation towards society 5.0 and the post-pandemic resilient movement for SMEs, system and technology development is increasingly being carried out in line with the needs of the business world in implementing enterprise resource planning (ERP) applications. Functional compatibility and performance efficiency are core characteristics that must be possessed by an SME digital system, and as a procedure for evaluating the quality of a software model based on ISO/IEC 25010:2011. It is necessary to conduct a performance assessment such as stress testing which includes the qualification of the system's ability to process information based on the sub-characteristics of a reliable capacity system, such as the number of requests and data concurrency. while the time behavior sub-characteristic assesses the successful connection time and the average time. A cloud computing or intelligent system that SMEs want to implement, such as an ERP application, needs to be tested with this procedure to find out the high performance of services that can be performed by the system simultaneously, as well as the limitations of the system. to avoid possible system downs. Performance efficiency characteristics are also a parameter of platform suitability that can be used by companies effectively with guaranteed quality, and the right system size. In this research, stress testing was carried out on the open-source ERP system, namely Odoo, regarding the level of performance efficiency based on the ISO 25010:2011 standard. [ABSTRACT FROM AUTHOR]

Technologies for blind and low-vision (BLV) people have long been a focus of Human-Computer Interaction (HCI) and accessibility (ASSETS) research. To map and assess this cross-disciplinary field, prior literature reviews have focused on specific BLV research areas (e.g., navigation assistance) or study methodologies (e.g., qualitative methods). In this paper, we provide a more holistic examination, combining both quantitative bibliometric analyses with qualitative assessments. Using keyword queries of terms focused on the human (e.g., people) and their visual status (e.g., blind, low-vision), we first derived a dataset of 880 papers published between 2010-2022 from ACM and IEEE conferences and journals. We then apply a programmatic analysis of this dataset followed by a qualitative analysis of the 100 most-cited papers. Our findings highlight four major research areas: Accessibility at Home & on the Go, Non-Visual Interaction, Orientation & Mobility, and Education. We also capture the diversity of denominations used to refer to the BLV community and their co-occurrences, as well as computer systems targeting both blind and low-vision users with a focus on visual substitution. We close by suggesting areas for future work and hope to stimulate discussions in our field. [ABSTRACT FROM AUTHOR]

As one of the educational institutions in the city of Bandung, Igasar Pindad Vocational High School Bandung has begun to utilize information technology, learning support facilities in schools are expected to be able to support the student learning process within the stipulated time period. One of the facilities to support student learning in schools is a computer laboratory. The Computer Laboratory of Software Engineering Vocational High School Igasar Pindad Bandung plays a key role in harnessing students' abilities. An academic educational process that focuses on hands-on activities to develop a Software Engineering specialization at ten grades, eleven grades and twelve grades related to software design, programming and supporting databases. The impact of several existing IT services as the application of information technology systems by only paying attention to temporary needs and the discrepancy between business processes and practicum academic goals, allows the application of information systems to overlap and the existence of sub-systems that are different from one another. Based on these problems, the Computer Laboratory of software engineering at Igasar Pindad Vocational High School Bandung requires enterprise architecture design using the stages in TOGAF ADM. The results of this research will be the blueprint of the architecture that is made. The blueprint that will be made will be an integral part of the development of information systems and technology at the Computer Laboratory of software engineering at Igasar Pindad Vocational High School Bandung. [ABSTRACT FROM AUTHOR]

To assess the potential capabilities of computer systems (CS), indices of the realizability of solving tasks are used. These indices characterize the quality of the systems, taking into account the reliability of the CS and the parameters of the tasks. These estimates become relevant when scalable computer systems are considered. For example, 93% of the TOP 500 supercomputers are cluster-type systems that are scalable. Failures in such systems, which directly depend on the number of computing nodes, significantly reduce the efficiency of solving tasks. The paper presents a description of mathematical model of computer systems with accumulator in group servicing task flow. The mathematical model is based on the methods of queuing theory. The paper offers solutions for calculating indices that allow us to assess the fullness of the accumulator and understand how the size of the group affects the fullness of the one. The obtained analytical solutions are aimed at express analysis of the functioning of CS. [ABSTRACT FROM AUTHOR]

The problem of implementing a gesture control system based on computer vision is an urgent task, since existing approaches do not provide the necessary versatility and performance. Based on system analysis and formalization of objects and processes of gesture control, a structural model of the system is formulated. This model defines the tasks of analysis, processing and storage of information solved by each module. Further, in accordance with research object and the functionality requirements, a functional model is implemented, including procedures for managing applications and simulating the computer mouse movement. The developed models will be further used to implement the gesture control software based on computer vision. [ABSTRACT FROM AUTHOR]

The paper considers a continuous integration server deployed in a virtualized environment as a computational mass service system that handles a uniform stream of software distribution building requests. The authors describe a methodology for solving the problem of predicting the load of a computing system using machine learning methods. The method of data preparing for training the prediction model is presented. The results of the experiment on prediction of the requests stream intensity and computer system load are given. The features of the model, which are expressed in the identification of distinctive qualitative features of the requests stream and the ability to group these features by the degree of their relationship, are demonstrated. The conclusion about applicability of the method and further ways of development is made. [ABSTRACT FROM AUTHOR]

This paper has proposed a single computing engine based on VLC technology for use in real-time to secured image of transmitter and receiver systems implemented on an FPGA in real time. It is proposed that a single computing engine system consist of the following components be implemented: UART control, FIFO buffer, VGA controller, and 128-bits AES algorithm decryption and encryption. An Altera DE1-SoC board is used to implement the design, coded in VHDL, and implemented in Quartz prime 15.1 FPGA using a software platform system architecture. The single computing engine communication via VLC system hardware provides the highest security benefit with excellent image quality and unnoticeable local area communication security features. It has been demonstrated through implementation results that the single computing engine can operate at a maximum clock frequency of Fmax 170.97 MHz and achieve a throughput of 1.367 Mbps with the design single computing engine. [ABSTRACT FROM AUTHOR]

With the evolution of technology, Cyber-Physical Systems(CPS) have become an integral part of human life and have been contributing to every aspect of innovation solving real-world challenges. Cyber-Physical Systems have grown to exist in almost every industrial practice and domain today ranging from Transportation, Healthcare, Automotive, Smart Cities, Energy, Crime prediction to Education. Cloud-Based Technologies on the other hand have been evolving towards providing solutions to a versatile range of computing needs by building on-demand sharable cloud platforms to serve these use-cases of Artificial Intelligence, Big Data, IoT, and Cyber-Physical Systems. Various Industries have got benefitted from this and It has given birth to all new organizational and business models on a large scale. In this article, we provide an overview of recent advancements in computing for Cyber-Physical Systems primarily by highlighting ongoing research and development work in different industrial domains. This article includes elaboration on academic and industry perspectives for different use cases, trends in computing with Cyber-Physical Systems, and the development of cloud tools and technologies. We also attempt to expose some open challenges and research problem statements that need further study and contributions from researchers and industrial experts. [ABSTRACT FROM AUTHOR]

The traditional method of urine color analysis is achieved by visual examination. However, this method has a high level of incompetence and inaccuracy. Complete urinalysis testing has various limitations due to the great number of samples processed, impaired color discrimination by the naked eye, the required time for testing, and the work involved in the prepared sample and processing. Recently, digital color image processing has attracted considerable attention due to it is great sensitivity, rapidity, and facility in which color is measured and translated into numerical values that may be regarded as signals for analysis using the RGB color system and color information is readout. In this review, we present different ways in recent developments in automated urinalysis. This paper reviews the colorimetric sensing, camera, smartphone, and scanner methods and describes their advantages and limitations. [ABSTRACT FROM AUTHOR]