Reviewerly/exHarmony huggingface dataset:
A Fast Topological Parallel Algorithm for Traversing Large Datasets

This work presents a parallel implementation of a graph-generating algorithm designed to be straightforwardly adapted to traverse large datasets. This new approach has been validated in a correlated scenario known as the word ladder problem. The new parallel algorithm induces the same topological structure proposed by its serial version and also builds the shortest path between any pair of words to be connected by a ladder of words. The implemented parallelism paradigm is the Multiple Instruction Stream - Multiple Data Stream (MIMD) and the test suite embraces 23-word ladder instances whose intermediate words were extracted from a dictionary of 183,719 words (dataset). The word morph quality (the shortest path between two input words) and the word morph performance (CPU time) were evaluated against a serial implementation of the original algorithm. The proposed parallel algorithm generated the optimal solution for each pair of words tested, that is, the minimum word ladder connecting an initial word to a final word was found. Thus, there was no negative impact on the quality of the solutions comparing them with those obtained through the serial ANG algorithm. However, there was an outstanding improvement considering the CPU time required to build the word ladder solutions. In fact, the time improvement was up to 99.85%, and speedups greater than 2.0X were achieved with the parallel algorithm.
A Trust Management System for the Nigerian Cyber-health Community

Trust is a basic requirement for the acceptance and adoption of new services related to health care, and therefore, vital in ensuring that the integrity of shared patient information among multi-care providers is preserved and that no one has tampered with it. The cyber-health community in Nigeria is in its infant stage with health care systems and services being mostly fragmented, disjointed, and heterogeneous with strong local autonomy and distributed among several healthcare givers platforms. There is the need for a trust management structure for guaranteed privacy and confidentiality to mitigate vulnerabilities to privacy thefts. In this paper, we developed an efficient Trust Management System that hybridized Real-Time Integrity Check (RTIC) and Dynamic Trust Negotiation (DTN) premised on the Confidentiality, Integrity, and Availability (CIA) model of information security. This was achieved through the design and implementation of an indigenous and generic architectural framework and model for a secured Trust Management System with the use of the advanced encryption standard (AES-256) algorithm for securing health records during transmission. The developed system achieved Reliabity score, Accuracy and Availability of 0.97, 91.30% and 96.52% respectively.
Evaluating the Scalability of Matrix Factorization and Neighborhood Based Recommender Systems

Recommendation Systems are everywhere, from offline shopping malls to major e-commerce websites, all use recommendation systems to enhance customer experience and grow profit. With a growing customer base, the requirement to store their interest, behavior and respond accordingly requires plenty of scalability. Thus, it is very important for companies to select a scalable recommender system, which can provide the recommendations not just accurately but with low latency as well. This paper focuses on the comparison between the four methods KMeans, KNN, SVD, and SVD++ to find out the better algorithm in terms of scalability. We have analyzed the methods on different parameters i.e., Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Precision, Recall and Running Time (Scalability). Results are elaborated such that selection becomes quite easy depending upon the user requirements.
Identification of a Plasmid: Transformation v1

Protocol for the identification of a plasmid by using transformation of E. Coli
PERANCANGAN SISTEM PENGATURAN LAMPU TAMAN KOTA KISARAN MENGGUNAKAN KENDALI KOMPUTER

City park lights are lighting or lighting that can display the beauty of city parks at night. Most city governments often find it difficult to control their city park lights so that the lighting in city parks is erratic and irregular. In this case, it is very necessary to build an arrangement or control of city park lights such as traffic light based on digitalism to automatic control using computerization. The research method used is the SDLC (System Development Life Cycle) method. By building a simulation system for controlling city park lights using the Visual Basic programming language, it can be useful for city governments in controlling city park lights efficiently and effectively.
Perancangan Aplikasi Pengolahan Data Kelompok Tani Ternak Provinsi NTB

The Department of Animal Husbandry and Animal Health is one of the government agencies of West Nusa Tenggara Province which has the task of improving the welfare of the community and reducing poverty in West Nusa Tenggara Province by providing grants in the form of livestock assistance or other assistance, assistance is given to livestock farmer groups in all regencies/cities throughout the province. -NTB has criteria that have been determined by the Animal Husbandry and Animal Health Service of the Province of NTB, the assistance provided is sourced from the Provincial Revenue and Expenditure Budget (APBD) and the State Revenue and Expenditure Budget (APBN), because the process of providing assistance through the selection of submitted proposals manually by livestock farmer groups with three processes that become important points, namely recapitulation, validation and verification which takes a long time and the lack of information related to the development of livestock farmer groups in all regions of NTB that have received assistance, therefore an application or application is needed. u an information system that can assist the Department of Animal Husbandry and Animal Health of the Province of NTB in processing livestock farmer group data, ranking as a good decision maker..
Design, Modeling, and Analysis of Memory Allocation Policies for Rack-Scale Memory Disaggregation

Abstract Memory disaggregation architecture is an emerging alternative to the traditional server architecture to address the issue of memory under-utilization in data centers. Memory disaggregation offers a large pool of remote memory connected via high-speed network fabric, thereby allows independent upgrade of memory components. Disaggregated design gives better adaptability of servers to the ever-increasing memory requirement from applications, such as HPC workload, video and big data analytics. However, disaggregrated memory architectures cause significantly large memory access latency due to the limited speed of interconnects currently used. In this paper, we propose a rack-scale disaggregated memory architecture and discuss the various software/hardware design aspects for such an architecture. We analyze the remote memory access latency in this architecture and observe that a significant part of the latency arises out of not only the interconnect, but also due to the contention at the queues of remote memory. To address this issue, we propose two-phase memory allocation policies for disaggregated memory environments that could significantly reduce the average memory access latency, compared to the conventional policies. We built a simulator that uses a trace-based front-end module and a cycle-accurate memory simulator to evaluate the memory access latency in a disaggregated memory system. We conduct experiments with different allocation policies across various benchmarks, representing applications with diverse memory access patterns. Our study shows encouraging results toward adoption of rack-scale memory disaggregation with acceptable memory latency, that could further be reduced with other system-level optimizations.
The Impact of Virtual Reality Technology Characteristics on Purchase Intention in Luxury Fashion amidst Millennials in Thailand

Using virtual reality (VR) technologies has allowed bridging the gap between brand engagement and consumer experiences. Commonly, the factors that has a significant impact on consumer engagement tend to include autonomy, rewards, absorption, competition factors; which is expected to boost millennials use of VR technology. In this study, the scholar aims to investigate the impact of these factors of VR technology of millennial’s purchasing behaviour, particularly luxury fashion purchasing behaviour. This study employs the use of a quantitative approach in performing the research. A close-ended questionnaire was designed and distributed to collect data from a total of 200 sample respondents. The data were validated and missing data were removed with the final data being 200 sample. Our findings revealed that variables including autonomy, absorption, competition, and consumer enjoyment has a positive significant impact on the intention to purchase luxury products amidst consumers. This study's methodology has methodically outlined how to assist customers in having fun and making their online purchasing more enjoyable which influences their purchase intention.
Parallel Design of SFO Optimization Algorithm Based on FPGA

Abstract Taking a lot of time to solve optimization problems has become a challenge for metaheuristic algorithms. Due to independence of the metaheuristics components, parallel processing is a good option to reduce the computational time and to find high quality solutions that are close to the optimum with an acceptable cost. One of these metaheuristic algorithms is the Sailfish Optimizer (SFO) which inspired by a group of hunting sailfish. The SFO algorithm uses a simple method to provide a dynamic balance between exploration and exploitation phases, creates a swarm diversity, avoids local optima, and guarantees high convergence speed. It has been shown that the SFO algorithm outperforms various state-of-art metaheuristic algorithms for multimodal and high dimensional benchmark functions and complicated real-world optimization problems in terms of accuracy and speed by CPU and GPU implementation. In this paper, to speedup this algorithm and increase its performance we propose a reconfigurable hardware version of SFO implemented on Field Programmable Gate Array (FPGA). The FPGA-based SFO can be a very good option in many applications with massive calculations. Due to the inherent parallelism and high computing capabilities of FPGA, the SFO algorithm gain optimum computational time despite the complexity of optimization problems. We have compared the performance of the proposed FPGA-based SFO with its CPU and GPU implementation and some other metaheuristic algorithms. The results show the FPGA implementation is considerably faster than the CPU and GPU implementation. Also, it outperforms other compared FPGA-based metaheuristic algorithms in terms of execution time and convergence speed.
Gesture Recognition Based Virtual Mouse and Keyboard

Today, computer vision has advanced to the point where a machine can recognise its owner by running a straight forward picture processing application. People are employing this in this period of growth because vision in a variety of everyday activities, including Face Recognition, Color Detection, Autopilot Cars, etc. In this project, computer vision, or a camera, is utilised to recognise hand gestures to create a virtual mouse and keyboard. The computer's camera will scan the image of various hand gestures made by a user, and the computer's mouse cursor will move and even carry out various functions using various movements in accordance with the gestures. Similar to how some other motions can be used to access keyboard features.Without a wire or other external devices, it will function as a virtual mouse and keyboard. The project's webcam is its sole piece of hardware, and Python is used to code on the Anaconda platform. This project uses cutting-edge Machine Learning and Computer Vision algorithms to recognise hand movements, and it operates without the need for any additional hardware. Index Terms - Face Recognition, Machine Learning, Virtual Mouse And Keyboard, Anaconda Platform
Analysis of Public Opinion on the Network of Burst Events based on the PH-LSTM Neural Network

Due to the high-speed development of the Internet today, once a burst event occurs, it will attract the general public‘s attention in a short time and spread rapidly on the Internet, which will lead to the formation of large-scale network public opinion on emergencies. We can accurately judge the development trend of bursts and provide a reference for emergency supervisory departments to deal with public opinion crises by predicting the trend of public opinion on the network of emergencies. To address the issues of a single prediction model's low prediction accuracy and the large influence of social media factors on public opinion trend, an opinion prediction method integrating social media influence and LSTM neural network is proposed, and a PH-LSTM (Post Hot-Long Short-Term Memory) neural network is built. Firstly, the influencing factors of online public opinion are introduced, including the posting hotness and user influence of fused social media influence and the growth rate of events. Secondly, the LSTM neural network is improved to design a PH-LSTM prediction model with three hidden layers, and the PH-LSTM model is used in the quantitative prediction of unexpected events. Model’s validity was verified through experiments, and it was confirmed that the model has a good fitting and prediction effect on the trend of online public opinion of unexpected events.
The Modern Scientific Proofs and their Authenticity in Criminal Evidence: Literature Review

This research seeks to review the growing literature on modern criminal evidence and the role of technological advancement in forensic science.We reviewed 114 forensic science studies based on a systematic literature review approach.The studies provide supporting evidence that technological advancement has permitted improved progress on modern criminal evidence.The analysis cybercrime and related offenses pose a global danger to many private and corporate entities around the world.Some nations (e.g., Algeria) have adopted the notion of proof-free prosecution, which means that there is no exception to the rule in modern criminal legislation comparison as a result of the necessity to adapt and cope with changes in all parts of one's existence.Also, conventional crimes, such as fraud and money laundering, have been creatively changed into new forms by the rising popularity of the Internet.Fruitful directions for further studies and implications for policymakers were discussed.
The New Federal Public Access Memo and What it Might Mean for Federally Funded Researchers

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Can we improve the prognosis of HER2+ Breast cancers in Low income countries: The Moroccan experience

Background: Breast cancer is a frequent heterogeneous disease among women, studies using gene microarray technology changed the way invasive breast cancers are categorized, it can now be classified at least in 4 classes: Luminal A, Luminal B, Basal like, HER2+; the immunohistochemical analyses of expression of estrogen receptor(ER), progesterone receptor(PR), and human epidermal growth factor receptor 2(HER2), are widely used to divide into these 4 breast cancer subtypes. The aim of this study is to demonstrate the impact of an optimal care on the prognosis of tumors that were previously worst prognosis ones in LMIC.
Perancangan Smart Locker dengan Implementasi Sistem IoT dan Aplikasi Mobile Android

A locker is a storage facility that can be seen at several public facilities such as public swimming pools, a library, and sports facilities like a gymnasium. Most lockers at public facilities still use conventional locking techniques. This has a negative impact in terms of effectiveness, efficiency, and security. Therefore, a QR-Code-based system that is integrated with the android application has been created to function for monitoring availability, borrowing lockers, and opening and locking lockers through the android application. Smart locker system using ESP32 as microcontroller and network that used to receive data sent from android application. When data is received, ESP32 will respond by activating the relay which controls the magnetic lock that replaced the conventional lock, while the android application is created for monitoring locker availability, borrowing lockers, and opening and locking lockers through the android application. This test is carried out for this application, which refers to the ISO 25010 standard with aspects of functional suitability, usability, and compatibility. The results of testing aspects of functional suitability and compatibility get 100 percent feasibility percentage results. Then for usability, it shows that from the 10-point questionnaire distributed to respondents, the percentage of feasibility results is 78.98 percent which is included in the acceptable category, this shows that the mobile application has good quality. The system test was done by pressing the button in the android application at the same time with two different devices and having a time difference while opening the lockers with a time average of 0.874 seconds.
The Relevance of Information Behaviour For Nurses Working With Government Hospitals In Kerala

Information is a key issue in the information age. The real challenge of this time is not producing information or storing information, but getting people to use information appropriately. Information is a critical resource in the operation and management of organisations. Timely availability of relevant information is vital for effective performance of managerial functions such as planning, organising, leading and controlling. There is a universal assumption that man was born innocent or ignorant and should actively seek knowledge. Information Behaviour is a broad term encompassing the ways individuals articulate their information needs, seek, evaluate, select and use information. In this era of information, it is very relevant for any type of the professionals to have the updated information at the right time in the right mode. The present study concentrates the relevance of information behaviour for nurses, especially working with the Government hospitals in Kerala.
Pengaruh Motivasi Belajar Terhadap Hasil Belajar Siswa pada Mata Pelajaran Instalasi Penerangan Listrik

This research aims to find out how significant the effect of a Learning Motivation on Student Learning Outcomes in the Class XI TITL Electrical Lighting Installation subject at SMK N 1 Padang. This study uses a type of quantitative approach research and is correlational. The subjects in this study were all students of class XI TITL in the 2022/2023 academic year. There were two classes, one class was used for research class and the other class was for research instrument testing. Data collection used a questionnaire and documentation, the questionnaire used a Likert scale score of four which had been expertly validated by an expert lecturer at the Department of Electrical Instruments, after which a trial was carried out and it was distributed to respondents. Data analysis techniques in this study used prerequisite analysis techniques, simple linear regression tests and t-tests to determine the significant effect of the independent variables on the independent variables, as well as the determinant coefficient test to determine the significant magnitude of the independent variables on the dependent variable. The results of this study indicate that there is a significant influence of learning motivation on student learning outcomes in the class XI Electrical Lighting Installation subject at SMK N 1 Padang.
Urban Safety Risk Assessment Technology Based on Risk Correction

In order to effectively manage and control risks and improve the accuracy of urban safety risk assessment, a revised model of urban safety risk based on inherent risk screening is proposed, risk screening standards and industry risk coefficients for different industries are formulated, and a three-level urban safety risk assessment process is established, in which risk assessment subjects, industry management departments and governments (regions) are linked.Risk assessment is carried out through the bottom-up model of "point line surface", overlapping to form industrial and regional risks.Taking A district of a city in the south of China as a sample, the safety risk assessment of accident disaster cities is carried out in a "point line plane" mode.It is clear that the assessment object is the risk point hazard sources of production and business units and public safety areas under the jurisdiction.The results show that this method can systematically and comprehensively find out the key points of urban risk management and control, effectively evaluate the regional risk level, and provide decision-making basis for the hierarchical management and control of urban security risks.
Dark Forest Algorithm: A Novel Metaheuristic Algorithm for Global Optimization Problems

Metaheuristic algorithms, as effective methods for solving optimization problems, have recently attracted considerable attention in science and engineering fields. They are popular and have broad applications owing to their high efficiency and low complexity. These algorithms are generally based on the behaviors observed in nature, physical sciences, or humans. This study proposes a novel metaheuristic algorithm called dark forest algorithm (DFA), which can yield improved optimization results for global optimization problems. In DFA, the population is divided into four groups: highest civilization, advanced civilization, normal civilization, and low civilization. Each civilization has a unique way of iteration. To verify DFA’s capability, the performance of DFA on 35 well-known benchmark functions is compared with that of six other metaheuristic algorithms, including artificial bee colony algorithm, firefly algorithm, grey wolf optimizer, harmony search algorithm, grasshopper optimization algorithm, and whale optimization algorithm. The results show that DFA provides solutions with improved efficiency for problems with low dimensions and outperforms most other algorithms when solving high dimensional problems. DFA is applied to five engineering projects to demonstrate its applicability. The results show that the performance of DFA is competitive to that of current well-known metaheuristic algorithms. Finally, potential upgrading routes for DFA are proposed as possible future developments.
A Look at IR 4.0 in Education

This article describes about industrial revolution 4.0 in education.IR 4.0 stands for fourth industrial revolution.And which is a new level of life.The industrial revolution 4.0 had positive and negative impacts on all aspects of life, including education.The industrial revolution 4.0 can provide many benefits for the achievement of educational goals, with the use of sophisticated machinery which is the implementation of the industrial revolution 4.0.