Reviewerly/exHarmony huggingface dataset:
Amoeba: Circumventing ML-supported Network Censorship via Adversarial Reinforcement Learning

Embedding covert streams into a cover channel is a common approach to circumventing Internet censorship, due to censors' inability to examine encrypted information in otherwise permitted protocols (Skype, HTTPS, etc.). However, recent advances in machine learning (ML) enable detecting a range of anti-censorship systems by learning distinct statistical patterns hidden in traffic flows. Therefore, designing obfuscation solutions able to generate traffic that is statistically similar to innocuous network activity, in order to deceive ML-based classifiers at line speed, is difficult. In this paper, we formulate a practical adversarial attack strategy against flow classifiers as a method for circumventing censorship. Specifically, we cast the problem of finding adversarial flows that will be misclassified as a sequence generation task, which we solve with Amoeba, a novel reinforcement learning algorithm that we design. Amoeba works by interacting with censoring classifiers without any knowledge of their model structure, but by crafting packets and observing the classifiers' decisions, in order to guide the sequence generation process. Our experiments using data collected from two popular anti-censorship systems demonstrate that Amoeba can effectively shape adversarial flows that have on average 94% attack success rate against a range of ML algorithms. In addition, we show that these adversarial flows are robust in different network environments and possess transferability across various ML models, meaning that once trained against one, our agent can subvert other censoring classifiers without retraining.
PEDAGOGICAL CHARACTERISTICS OF FORMING STUDENTS' SENSE OF LOYALTY TO THE NATIONAL ARMY

During the yeаrs оf indеpendеnce, Uzbekistаn hаs tаken а worthy plаce in the wоrld cоmmunity. Todаy, his аttention in the wоrld is incrеasing. This is especially rеflected in the rеsults of our cоuntry's initiаtives аimed at strеngthening stаbility аnd sеcurity in the regiоn, in the recоgnition by the wоrld cоmmunity оf the grеat succеsses аchieved in the implementаtion of demоcratic and mаrket-bаsed ecоnomic refоrms in оur cоuntry. In this аrticle, the pedаgogical fеаtures of the fоrmation of a sеnse оf loyаlty to the nаtional аrmy amоng studеnt yоuth аre scientificаlly invеstigаted.
Cyber Crime and Its Fear in Women

Cybercrime is a growing problem globally, with women being more vulnerable to its effects than men. Women are particularly susceptible to online harassment, stalking, revenge porn, and identity theft. Despite the prevalence of cybercrime and its adverse effects on women, little is known about how women perceive and respond to these types of crimes. This research study aims to explore the fear of cybercrime among women and the impact it has on their online behavior and daily routines. The paper reviews existing literature on cybercrime and gender, survey data related to attitudes towards cybercrime, and interviews with women on their experiences with cybercrime.
A Figure Skating Jumping Dataset for Replay-Guided Action Quality Assessment

In competitive sports, judges often scrutinize replay videos from multiple views to adjudicate uncertain or contentious actions, and ultimately ascertain the definitive score. Most existing action quality assessment methods regress from a single video or a pairwise exemplar and input videos, which are limited by the viewpoint and zoom scale of videos. To end this, we construct a Replay Figure Skating Jumping dataset (RFSJ), containing additional view information provided by the post-match replay video and fine-grained annotations. We also propose a Replay-Guided approach for action quality assessment, learned by a Triple-Stream Contrastive Transformer and a Temporal Concentration Module. Specifically, besides the pairwise input and exemplar, we contrast the input and its replay by an extra contrastive module. Then the consistency of scores guides the model to learn features of the same action under different views and zoom scales. In addition, based on the fact that errors or highlight moments of athletes are crucial factors affecting scoring, these moments are concentrated in parts of the video rather than a uniform distribution. The proposed temporal concentration module encourages the model to concentrate on these features, then cooperates with the contrastive regression module to obtain an effective scoring mechanism. Extensive experiments demonstrate that our method achieves Spearman's Rank Correlation of 0.9346 on the proposed RFSJ dataset, improving over the existing state-of-the-art methods.
Robot Navigation and Model Development

This chapter discusses in detail about the navigation and the control model development for robot’s autonomous navigation. Before discussing the model development, let’s first discuss what navigation is? Navigation is the task of guiding a robotic vehicle/ robotic manipulator toward a desired goal in a given environment (Corke, 2017). Unlike the robotic vehicle, the human navigation task is more complex due to the following reasons, such as dealing with alternative (favorite, convenient) routes compared to planned routes, live obstacles, different environments, human safety, etc. When humans need to plan their navigation task, they have their start and end location with them and a map of the given environment. These days people have Google Maps to perform their navigation tasks. Additionally, human cognizance plays a skillful role in deciding the set of motions to reach the destination or dynamically altering the navigation strategy in case of some obstructions while reaching the destination. The robot navigation task can be quite complex because it requires lots of sensory input and highend processors to achieve the navigation task. When dealing with a lot more input information, however, with the current state of the art, the robot navigation is not at par with human navigation and cognizance level. The environment also plays a vital role in deciding the complexity of robotic navigation tasks. Since the current research is oriented towards the orchard environment, which is structured and systematic, therefore we use a mapbased navigation approach like humans to reduce the complexity of navigation tasks.
A Theoretical Review of the Internal Control Measures in Preventing E-Banking Frauds in the Nigerian Banking Sector

The developments in the field of information technology have changed banking business and the manner in which its customers transact significantly, bringing about more reliance on electronic banking transactions fondly referred to as “e-banking transactions”. This has also changed the kind of risk both the banks and its customers are faced with, resulting in some significant losses reported; and calling for the need for sound internal control systems that can be applied on e-banking activities to reduce losses and inherent risk. This paper is a theoretical review of the expected characteristics of the internal control system required to combat e-banking fraud in the Nigerian Banking Sector. Related concepts, theories and studies around internal control and electronic banking and fraud were reviewed. To reduce the losses attributed to e-banking frauds, the internal control system over e-banking transactions and activities should not be postmortem like the traditional banking services, but among others, be online real-time, generating alerts as transactions occur, having a combination of proactive and reactive techniques and should automatically generate audit trails. The paper recommends that the Central Bank of Nigeria (CBN) as the apex regulator of the sector should biannually review the controls put in place by the banks to check e-banking transactions for adequacy, and apply appropriate sanctions where necessary. Technology is constantly evolving, hence, the need for consistent review of processes and procedures by the banks, who should continuously sensitize its customers on safeguarding access credentials, while creating avenues for immediate reporting and account restriction in the event of suspicious activities.
Behavioral Biometrics for Continuous Authentication on Mobile Devices: Anomaly Detection through Keystroke Dynamics with Machine Learning

The popularity of mobile devices generates the need for security solutions to ensure user identity. One approach to deal with this scenario is behavioral biometric for continuous authentication (BBCA), which has become increasingly known with advances in hardware and data science technologies. However, this approach still lacks greater robustness in how to model the user’s behavioral biometrics as well as maximize the effectiveness of this authentication. It is particularly important to note in this context that this paper presents an approach to BBCA using machine learning (ML) techniques integrated with sliding windows. Accordingly, biometric data collected from keystroke dynamics typing activities on mobile devices were used to identify genuine users, random (unskilled) imposters and skilled imposters. The ML models for impostor identification followed an anomaly detection (AD) approach, where only genuine data is available at training time. In addition, the use of sliding windows allowed the inclusion of the temporal dimension of the task. The results obtained indicate that the proposed solution has a practical feasibility in terms of its suitability to perform user identification, specifically, the KNN model stood out by achieving a superior performance in the value window 4. In this configuration, it achieved a score of 94% for the F1-score metric in the random imposter scenario, and 93% in the skilled imposter scenario.
Characteristics of Flow Hydrophysics Variables and Flood Potential Around Kuala Jengki Estuary Manado City

Flood disasters along the river resulted from damage to flood barrier construction along the river bank. The damage to the flood retaining wall is technically caused by the very large hydrophysical parameters of the river flow. In theory, the flow mass density parameter shows the concentration of sediment transported through one cross-section. As a result of changes in the volume of sediment transport, there will be an increase in flow energy, followed by changes in large water masses, and this is seen as a destructive force component in some equivalent places or riverbanks, which can physically be formulated in the form of a model function. It is important to do a map of the hydrophysical character variable flow and flood potential along Kuala Jengki estuary Manado City, it is important to do because the estuary is often flooded. Measurement of the hydrophysical variable mass flow density was carried out at a depth of 0.6 rivers at high and low tides. The mass density of the flow is the mass of water containing transport sediment divided by its volume. The mass of water (sample) is measured using a scale, while the volume is measured using a measuring cup or another container that has a volume measurement. For the presentation of density data profiles and other analytical purposes, the measured data were reproduced using linear interpolation techniques. The mass density data modeling was carried out using an experimental function iteration technique containing constants. The results of the research at high tide, the position which is approximately 275 meters at measurement points 10 to 13 at a distance of 675 meters to 950 meters becomes a location that is very prone to river lip damage if there is a rise in water level due to high rainfall, or a position where it becomes flood-prone when the flow density increases, along with an increase in the volume of river water, which is followed by changes in river flow velocity carrying various types of sediment. At a distance of 165 meters at low tide, the measurement position is between 10 and 13, there is an increase in large flow discharge accompanied by an increase in flow velocity that carries flow mass (mass density) with various types of sediment transport. In this condition, the location which is 165 meters away according to the model map becomes prone to river lip damage, which means that it is a location that has the potential for flooding. In contrast to measurement positions 5 and 6 at high tide, there is a significant increase in the low mass density, while at low tide this condition does not occur, this is because the flow velocity at low tide does not change significantly, causing the mass flow density to be relatively the same.
K-12 Teachers’ Implementation of Standards-Based Grading in the Classroom: A Quantitative Study

Standards-based grading (SBG) is a grading system in which each student is given a set of grades, each reflecting their proficiency in relation to a specific skill. The present study examined K-12 teachers’ implementation of SBG practices in a small, suburban Illinois district, as well as their perceptions and confidence in implementing SBG. It also examined these teachers’ prior formal and informal opportunities to learn about SBG, and how both pre-service and in-service opportunities to learn relate to their implementation of SBG grading. Results provide evidence of mixed levels of teacher SBG implementation, mixed teacher perceptions of SBG, and mixed teacher confidence in implementing such practices. In addition, the study finds that teachers’ opportunities to learn about SBG practices were extremely limited. However, both pre-service and in-service opportunities to learn about SBG related to SBG implementation and these relationships were mediated by teachers’ confidence in implementing SBG.
Hardware-efficient convolution algorithms for CNN accelerators: A brief review

The Convolutional Neural Network (CNN) is a technology of vast importance in image processing and computer vision applications. The bottleneck of CNNs is the multidimensional convolution, which often demands accelerator hardware. The convolution algorithms these accelerators use directly affect the ratio between speed increase and hardware resource consumption during scaling, a metric known as hardware efficiency. The lower this metric, the more power and area are spent on minor performance improvements. In this review, we analyze the potential for hardware efficiency in the current proven algorithms used in convolutional layers: im2col convolution used by most modern applications, Toom-Cook convolution, and FFT convolution. Our analysis reveals the inefficiency of im2col convolution regarding hardware scaling and confirms the potential for hardware-efficient applications using Toom-Cook and FFT convolutions, each with its caveats. Further, we identify possible hardware applications for these algorithms, which may be expanded upon in future works.
SISAP 2023 Indexing Challenge – Learned Metric Index

This submission into the SISAP Indexing Challenge examines the experimental setup and performance of the Learned Metric Index, which uses an architecture of interconnected learned models to answer similarity queries. An inherent part of this design is a great deal of flexibility in the implementation, such as the choice of particular machine learning models, or their arrangement in the overall architecture of the index. Therefore, for the sake of transparency and reproducibility, this report thoroughly describes the details of the specific Learned Metric Index implementation used to tackle the challenge.
A Survey on “Sentiment Analysis of E-commerce Website’s Reviews”

Abstract: Sentiment analysis, a vital component of natural language processing, has gained significant relevance in the realm of ecommerce websites. In this digital age, where consumers heavily rely on online reviews to inform their purchase decisions, understanding and harnessing sentiment in ecommerce reviews is paramount. This abstract explores the utilization of sentiment analysis techniques to extract valuable insights from customer feedback, offering a panoramic view of its applications, challenges, and implications. We delve into keyword extraction, sentiment polarity classification, and the integration of sentiment analysis into recommendation systems. This paper also examines the evolving role of sentiment analysis in enhancing user experiences, brand reputation management, and product development. By decoding the sentiments hidden within ecommerce website reviews, businesses can strategically adapt, improve customer satisfaction, and thrive in a highly competitive online marketplace
Evaluasi Kapasitas Drainase Kelurahan Klasuur Kota Sorong Menggunakan EPA - SWMM

The purpose of this research is to evaluate the condition of existing drainage channels in the area around Jalan Pulau Batanta Kompleks. In addition, it is also to determine the capacity of existing drainage channels to rainfall with a 2-year, 5-year and 10-year plan discharge. Rainfall frequency distribution analysis is carried out using the distribution analysis method, namely the Normal Distribution Method with chi-square calculations and Kolmogorov Smirnov suitability test. Rainfall intensity is calculated using the Mononobe equation and modeling with EPA-SWMM by simulating the drainage network and calculating the flood inundation area. The existing condition of the drainage system in the complex area along Jalan Batanta Island in accommodating the maximum rainfall discharge is still often overflowing, this is obtained from the results of the EPA-SWMM analysis that the channels around Jalan R.A. Kartini overflowed the most in the return periods of 2 years, 5 years, and 10 years with the largest runoff in channel 15. From the results of the evaluation of drainage channels and networks, it is known that the cause of flooding in the area around Jalan Batanta Island Complex is the existence of drainage channels that should accommodate rainwater, due to the large amount of sedimentation, as well as garbage that reduces the capacity of other channels. All channels reviewed have a sub-drainage area of 3.18 Ha with a total length of 7544.33 meters in good condition.
The effect of governance on capital flows in Sub-Saharan African countries

This paper examines the effect of governance in Sub-Saharan African (SSA) countries. Specifically, this study investigates (i) the interacting impact of government efficiency, regulatory quality, and the rule of law alongside other socioeconomic variables to determine foreign capital inflow (FCI) based on each economic SSA bloc; and (ii) the characteristic drivers of FCI, impacting economic growth in the SSA countries. Descriptive statistics, static models, least square dummy variables (LSDVs) and the dynamic system general method of moment (GMM) were employed as the study’s estimating techniques. Based on the result of the LSDV, food security and the rule of law significantly impact FCI in the sub-economic blocs in the region. Only six countries across the four economic blocs responded to food security and the rule of law in the model. The dynamic system-GMM provided evidence of five socioeconomic variables and three governance variables contributing to FCI. The findings revealed (i) regulatory quality and the rule of law are governance variables that significantly impacted FCI; and (ii) food security failed to significantly impact FCI in the SSA region. However, inflation, life expectancy, the human capital index, exchange rate and gross domestic product (GDP) growth impacted FCI significantly. In the aggregate, inflation, regulatory quality, exchange rate and the human capital index exhibited positive relationships, while other variables such as life expectancy, government effectiveness and the rule of law appeared significant but inversely impacted FCI in the SSA region. The key policy implication recommendation from this study is that a good legal framework could moderate the flow of foreign capital in favour of growth as it creates a strong foundation for sustainable economic development in the region.
Processing Measures for the Beautiful Tone of the Electric Guitar

A beautiful tone can not only make the electric guitar present a better performance effect, but also enable the player to immerse himself in the performance atmosphere and convey his performance demands to the audience. However, the factors affecting electric guitar tone include multiple individuals in both software and hardware, such as pickups, string lengths, circuits, paints, and musician's musical aesthetic ability, so it is necessary to apply tone processing methods according to the basic tone requirements, apply differentiated tone processing techniques based on the construction of electric guitars, regulate the tone in steps in accordance with the basic process, and continuously improve the musician's artistic comprehensive literacy.
Scientific and Educational Space and the Sovereign Future of the Russian State

The paper analyzes the actual content of the interdisciplinary concept «scientific and educational space of the Russian Federation», since the ongoing changes in the educational sphere of the Russian state, due to the new realities of the country’s foreign and domestic policy, require scientific justification and understanding. The author determines the tendencies of the development of the educational system of Russia. As a result of the study, it was revealed that the unity of society, the level of its interaction with the State, ideology and culture, being the sides of socio-political formation, are directly dependent on the level of the internal scientific and educational policy of each civilized country. The author concludes that it is necessary to continue using the full potential of the scientific and educational space to unite society, preserve the unity of the general cultural space of the State, prevent national-ethnic conflicts and social tension, taking as an alternative basis the priority of individual rights and minimizing social inequality in order to strengthen the national security of the sovereign Russian state. An urgent component of the vigorous development of Russian civil society should be the state policy in the youth sphere, based on creating conditions for the broad implementation of the potential of young citizens in generating their own future and the future of the sovereign Russian state.
Exploring Co-Presence in Virtual Work: A Literature Review

In recent decades, virtual work has emerged as a prominent paradigm in the world of employment. Within discussions surrounding virtual work, the concept of co-presence has garnered significant attention. Co-presence facilitates virtual workers to feel integrated into their teams and fosters relationships with colleagues. This research undertakes a comprehensive literature review to delve into the concept of co-presence, its crucial determinants, and the implications it holds. A total of 34 journal articles were scrutinized for inclusion based on their alignment with the research topic. The synthesis of these studies reveals that co-presence plays a pivotal role in supporting virtual work. Furthermore, the alignment of co-presence technology with job characteristics emerges as a critical consideration to ensure technology enhances rather than hinders productivity.