Reviewerly/exHarmony huggingface dataset:
Real-World Anomaly Detection in Video Using Spatio-Temporal Features Analysis for Weakly Labelled Data with Auto Label Generation

Detecting anomalies in videos is a complex task due to diverse content, noisy labeling, and a lack of frame-level labeling. To address these challenges in weakly labeled datasets, we propose a novel custom loss function in conjunction with the multi-instance learning (MIL) algorithm. Our approach utilizes the UCF Crime and ShanghaiTech datasets for anomaly detection. The UCF Crime dataset includes labeled videos depicting a range of incidents such as explosions, assaults, and burglaries, while the ShanghaiTech dataset is one of the largest anomaly datasets, with over 400 video clips featuring three different scenes and 130 abnormal events. We generated pseudo labels for videos using the MIL technique to detect frame-level anomalies from video-level annotations, and to train the network to distinguish between normal and abnormal classes. We conducted extensive experiments on the UCF Crime dataset using C3D and I3D features to test our model's performance. For the ShanghaiTech dataset, we used I3D features for training and testing. Our results show that with I3D features, we achieve an 84.6% frame-level AUC score for the UCF Crime dataset and a 92.27% frame-level AUC score for the ShanghaiTech dataset, which are comparable to other methods used for similar datasets.
Leftist Narratives in Tempo Books: Van Dijk’s Critical Discourse Analysis (CDA) Perspective

The text in a narrative has hidden meanings. It is necessary to dismantle and reconstruct the new meanings using critical discourse analysis (CDA). Related to that, this study aims to explore leftist narratives in Indonesia as contained in two books published by Tempo through van Dijk’s perspective of critical discourse analysis (CDA). This study used a descriptive-interpretative method which refers to CDA. The results reveal: First, the structure of the topic’s discourse raises the subject that Tempo is on the leftist side through diction, which depicts them as religious, kind, diligent, intelligent, and having a strong sense of nationalism. Microstructurally, in terms of setting, the leftists are those who were close to Sukarno, often recited the Quran (Muslims), repeatedly discussed with the public, and defended them. While in terms of graphics, Tempo books tend to be printed in red, symbolizing communism. Second, social cognition reporting in Tempo tends to side with the PKI and criticize Suharto concerning the G30S/PKI Movement. The two books reveal the ideological conflict between communism (Russia and China) and capitalism/colonialism (the United States and its allies). Third, from the aspect of context, leftists are innocent people and are the only victims of the regime in power.
Negotiating the challenges in speaking English for Indonesian undergraduate students in an ESL university

In Indonesia, English is not widely used for communication. Hence, Indonesian high school graduates who desire to study abroad may encounter difficulties communicating in English. One of the destination countries Indonesian students choose to study in is Malaysia. When studying in Malaysia, some may transition from EFL (English as a Foreign Language) to ESL (English as a Second Language) speakers as they are required to speak English more frequently, especially in academic contexts. Thus, this study was conducted to investigate the challenges of speaking English for Indonesian undergraduate students, the contributing factors to the challenges, and the strategies used by the students to navigate the challenges. A number of 15 Indonesian EFL undergraduate students still registered as active students in an ESL university in Malaysia participated in this study. Data was collected via semi-structured interviews, transcribed, and thematically analysed. The findings were presented thematically with narrative excerpts to support them. The results indicated some challenges faced when students adjusted themselves in their higher education institution, including their psychological reactions, speaking academic English, and online learning. Therefore, to help EFL students be more prepared to speak English for academic contexts in an ESL environment, stakeholders in the education sector in Indonesia should consider providing more actions to focus on improving the English-speaking skills of students.
The Role of Social Networking Sites in Enhancing Customers’ Satisfaction in UAE Institutions

This study aims to identify the role of social networking sites in enhancing satisfaction among the customers of UAE institutions through the application of the study on the customers of the Roads and Transport Authority within the Emirate of Dubai.The researcher will use the descriptive analytical approach through the distribution of the questionnaire to a random sample of the public dealing with this body through their use of various means of social communication to find out the impact of these means on enhancing their confidence in the Authority.The study reached several recommendations, the most important of which is the need for continuous development of social networking sites in terms of form and content.It also recommended a need to invest in social media to enhance of awareness and guidance towards enhancing respect for the laws and regulations of the Roads and Transport Authority.
Analysis of Fire Simulation on Polyurethane Foam Using FDS in a University Meeting Room

The polyurethane foam material is commonly used and marketed in two forms, namely flexible and rigid. Flexible foam is used as a cushion, with various applications for commercial products such as chair support. Therefore, this study aims to describe the occurrence of a fire situation in a university room filled with many polyurethane foam chairs. It also aims to provide awareness regarding potential flame hazards, by using a fire modelling method with FDS. The results showed that fires on PU foam materials produced a high HRR and a wide spread of flame and smoke. From this context, the harmful effects of the fire on the room occupants were emphasized. The results obtained are expected to support the theory of compartment fire, flame distribution in solid materials, PU Foam inferno behaviour, etc. It is also expected to provide additional fire protection and evacuation training for room occupants.
A Qualitative Study of the Perception of Alcohol Dependence Syndrome Patients and Their Perspective towards Cognitive Therapy

Background: In the management of patients with alcohol dependence, the emphasis has been made on the appropriate use of treatment to prevent relapse.Patients' own perceptions of alcohol use and their experiences during treatment have not often been sought.Here, we aimed to see the patient's perception in relation to their alcohol use along with their perception towards received cognitive therapy sessions.Method: A total of 28 male patients from the outpatient department were screened.The data sources were handwritten notes taken by the therapist during individual therapy sessions and individual semi-structured interview conducted at the termination of therapy.The narrative data were analyzed for identification of the major theme using grounded theory analysis.Results: Patients attribute their drinking to factors external to them, they also had a number of misconceptions related to alcohol.The major theme of self-defectiveness and incompetency were common among the patients.Their attitude towards medication and counseling was not favorable.The social environment was perceived non-sympathetic.Cognitive therapy perceived as enhancing their knowledge of addiction but at the same time, found difficult for selfuse.Conclusion: Patients describe their attitude towards alcohol and other problem.Their perspective towards alcohol use and in self and social context helps us to understand that which kind of cognition compel someone towards drinking and why.This view is also central to informing the debate on the use of cognitive therapy in alcohol dependence and modifying the mode of delivery for these patients.
Quality Measurement of Mobile Based Academic Information System at Vocational High School

&lt;span id="docs-internal-guid-7dba97e8-7fff-c66c-56c4-8ca7b5a8a555"&gt;&lt;span&gt;The &lt;/span&gt;&lt;span&gt;Academic Information System (AIS) is a computerized system that aids in the management of teaching and learning activities. &lt;/span&gt;&lt;span&gt;The aim of this research is to ensure the quality of academic information systems to guarantee the functionality and to find out whether it meets the ISO 25010 quality standard. Testing was conducted using 4 of 8 characteristics of the ISO 25010, namely functional suitability, portability, usability, and performance efficiency. 490 respondents consisting of grade 1 to grade 3 students from various majors at one of state vocational high school in Manado were involved in collecting questionnaire data. Several measurement tools are used in this research, such as Page Speed tools, and also Yslow tools. For the instrument itself to analyze the usability is using USE Questionnaire. As the conclusion, the application system was meet the ISO/IEC 25010 standard with functional characteristic is 84.7% (very high), portability aspect is 100%, usability condition is 90%. For the performance efficiency aspect scores 93.7 and 0.907 for time speed parameters.&lt;/span&gt;&lt;/span&gt;
Youtube For Developing Technological Skill

There are many teachers do not have skill on operating computer specially to make materials interesting for their students. This study was to improve the technological skills of students, particularly those who teach online. In this study, we attempted to determine how students may utilize YouTube as a medium to strengthen their technological skills. This study was carried out by us with the help of students who took the Education Management Course as the subject of study. The data collection technique used in this study was observation sheets, which were then used to answer the formulation of how the student responses related to the video-making project in the Education Management Course uploaded on YouTube; then, to answer the formulation of how the student’s activities on Education Management, we asked students to complete their video projects and upload them on YouTube; and to answer the formulation of whether the use of YouTube can develop technological skills of students, observation sheets was used. This study concludes that respondents are able to edit and upload video about Education Management on YouTube.
Classification Academic Data using Machine Learning for Decision Making Process

One of the qualities of higher education is determined by the success rate of student learning. Assessment of student success rates is based on student graduation on time. Sultan Syarif Kasim State Islamic University Riau is one of the state universities in Riau, with a total of 30,000 students. Of all the active students, there are some who are not. Students who are not active in this case will affect the timeliness of their graduation. The university always evaluates the performance of its students to find out information related to the factors that cause students to become inactive so that they are more likely to drop out and what data affect students being able to graduate on time. The evaluation results are stored in an academic database so that the data can later be used as supporting data when making decisions by the university. This research used data science concepts to explore and extract data sets from databases to find models or patterns, as well as new insights that can be used as tools for decision-making. After the data was explored, machine learning concepts were used to identify and classify the data. The method used was the Decision Tree Method. The results of the study found that these two concepts can provide the expected results. Based on the test results, it is known that the attribute that influences the success of student studies is the grade point average (GPA), where the accuracy of the maximum recognition rate is 88.19%.&#x0D; Keywords : Data science; Decision Tree; Graduate on Time; Machine Learning;
Linguistic landscape in Malaysia: The case of language choice used in signboards

This study aimed to investigate the languages used in shop signs in three different areas in Semenyih, Selangor, Malaysia. Using a mixed-method approach, this paper identified the preferred language for shop signs in the town of Semenyih, Pelangi Semenyih, and Setia Ecohill, as well as examined the relationship between the language choice in signages and linguistic landscape in Malaysia. A total of 180 signboards was photographed to ensure the impartiality of data collection, and they were coded based on four aspects: full names of the shops in various languages, the business scope of the shops, the number of languages used in shop signs, size of the scripts, and layout of languages highlighted, adopted from the study of Shang and Guo (2017). Questionnaires and interviews with the shop owners were also employed to elicit information about their preferences regarding the language choice for their shop signages, which shed light on the impact of the development in Semenyih towards the choice of shop signages. The findings revealed that, despite the regulations imposed by the local city council (Majlis Perbandaran Kajang (MPKJ) or Kajang Municipal Town Council) on the permissible shop signages, the shop owners still used languages other than the Malay language in their signboards, such as English, Mandarin, and Tamil, with English being the most dominant one. This indicates that, as the towns develop, the linguistic landscape here changes with importance being given to signboards in English compared to Malay.
Surabaya land cover prediction based on Landsat Satellite using the Multi-layer Perceptron Method

Infrastructure development has occurred very rapidly in Surabaya in the last few decades. There is pressure on the need for land use in line with the increase in population. This study aims to analyze changes in land cover with inter-decade analysis and predict land cover in 2021-2030 in Surabaya using the Multi-Layer Perceptron method. The data used in this research is Landsat satellite which is considered good in representing the actual land cover. A decrease in the amount of vegetation occurs every decade in Surabaya, while the number of buildings is increasing and the bodies of water are relatively the same. The Multi-Layer Perceptron method has a good level of accuracy in predicting land cover in the city of Surabaya. In 2021-2030 it is predicted that Surabaya will still experience an increase in the number of buildings and a decrease in the amount of vegetation.
Enhancing Dynamic Hand Gesture Recognition using Feature Concatenation via Multi-Input Hybrid Model

Radar-based hand gesture recognition is an important research area that provides suitable support for various applications, such as human-computer interaction and healthcare monitoring. Several deep learning algorithms for gesture recognition using Impulse Radio Ultra-Wide Band (IR-UWB) have been proposed. Most of them focus on achieving high performance, which requires a huge amount of data. The procedure of acquiring and annotating data remains a complex, costly, and time-consuming task. Moreover, processing a large volume of data usually requires a complex model with very large training parameters, high computation, and memory consumption. To overcome these shortcomings, we propose a simple data processing approach along with a lightweight multi-input hybrid model structure to enhance performance. We aim to improve the existing state-of-the-art results obtained using an available IR-UWB gesture dataset consisting of range-time images of dynamic hand gestures. First, these images are extended using the Sobel filter, which generates low-level feature representations for each sample. These represent the gradient images in the x-direction, the y-direction, and both the x- and y-directions. Next, we apply these representations as inputs to a three-input Convolutional Neural Network- Long Short-Term Memory- Support Vector Machine (CNN-LSTM-SVM) model. Each one is provided to a separate CNN branch and then concatenated for further processing by the LSTM. This combination allows for the automatic extraction of richer spatiotemporal features of the target with no manual engineering approach or prior domain knowledge. To select the optimal classifier for our model and achieve a high recognition rate, the SVM hyperparameters are tuned using the Optuna framework. Our proposed multi-input hybrid model achieved high performance on several parameters, including 98.27% accuracy, 98.30% precision, 98.29% recall, and 98.27% F1-score while ensuring low complexity. Experimental results indicate that the proposed approach improves accuracy and prevents the model from overfitting.
Introduction to the importance of learning English for early childhood and elementary schools age children in Jampang Village, Bogor

This community service activity was motivated by the lack of understanding of early childhood and elementary school age children in Jampang village, Bogor regarded the importance of English competencies. In addition, curriculum changes from 2013 curriculum in which the English was not taught in elementary towards the independent curriculum in which English is subject that starting from elementary. The aim of this activity is to prepare the children as the students to face the independent curriculum by providing an understanding of the importance of English and increasing the basic vocabulary skills. The three stages of implementing this activity are socialization, demonstration or practice about basic vocabulary, and evaluation. The results showed enlargement understanding of the English learning and the participants' ability to master basic English vocabulary.
A comparative study of lexical bundles in accepted and rejected applied linguistic research article introductions

Multi-word expressions referred to as lexical bundles are the important ‘discourse building blocks’ to construct and signal fluent writing, particularly in an attempt to produce high-quality research articles that can be accepted by reputable journals. A number of studies have reported the use of lexical bundles in various sections of research articles, including introductions as the holder of research rationale. In spite of that, attention is barely paid to the comparison between accepted and rejected manuscripts. With the intention to fill this gap, this study is aimed at investigating whether the manifestation of lexical bundles will differ between the introduction sections of accepted and rejected research articles in applied linguistics. A total of 15 introductions for each data group were analyzed under the frameworks of lexical bundles structures (Biber et al., 2004) and functions (Hyland, 2008). Findings reveal that noun phrase-based and research-oriented bundles were respectively detected as the most prevalent main structure and function in both accepted and rejected data sets. Closer inspection, however, evinced a greater frequency and richer variety of lexical bundles in accepted introductions. Even so, this study confirmed that the two datasets exhibit different subcategories of lexical bundles in numerous cases. Implicationally, the findings of this study may shed further light on the comprehension of lexical bundles use in preparing related future studies.
Effects Of Covid-19 On The Performance Of National Teachers' Colleges In Uganda

Purpose: This study attempted to investigate the effects of COVID-19 on the performance of National Teachers’ Colleges (NTCs) supported by Enabel.Methodology/approach: The study adopted a cross sectional research design. The study population consisted of staff working in the NTCs purposely or randomly selected. The self-administered questionnaire was used to collect the data that was analysed using both descriptive and inferential analysis.Findings: The research findings showed that programmes disruptions (r = 0.496); funding disruptions (r = .403) and capacity gap (r = .556) are moderately significant and positively associated with NTC performance respectively. Overall, the variables studied explain 33.9 percent of the variation in the organizational performance of NTCs.Implications/limitations: The research findings have shown that whereas programme disruptions and capacity gaps significantly contributed to the explanation of performance in NTCs during the lockdown, funding disruptions do not. The study recommends the continued adoption of innovative approaches to realize the objective of quality teacher training and education. Research into the effects of Covid-19 on the students in NTC is recommended, as this current study did not explore the component of students.Originality/value: While the effects of Covid-19 on the education sector have been studied, this has been mainly done at the primary and secondary levels of education in Uganda. This paper has attempted to investigate Covid-19 effects on NTCs supported by Enabel.Keywords: Covid-19; programme disruptions; funding disruptions; capacity gaps; organizational performancePaper type: Research paper
JPEG2000-Based Semantic Image Compression using CNN

Some of the computer vision applications such as understanding, recognition as well as image processing are some areas where AI techniques like convolutional neural network (CNN) have attained great success. AI techniques are not very frequently used in applications like image compression which are a part of low-level vision applications. Intensifying the visual quality of the lossy video/image compression has been a huge obstacle for a very long time. Image processing tasks and image recognition can be addressed with the application of deep learning CNNs as a result of the availability of large training datasets and the recent advances in computing power. This paper consists of a CNN-based novel compression framework comprising of Compact CNN (ComCNN) and Reconstruction CNN (RecCNN) where they are trained concurrently and ideally consolidated into a compression framework, along with MS-ROI (Multi Structure-Region of Interest) mapping which highlights the semiotically notable portions of the image. The framework attains a mean PSNR value of 32.9dB, achieving a gain of 3.52dB and attains mean SSIM value of 0.9262, achieving a gain of 0.0723dB over the other methods when compared using the 6 main test images. Experimental results in the proposed study validate that the architecture substantially surpasses image compression frameworks, that utilized deblocking or denoising post- processing techniques, classified utilizing Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measures (SSIM) with a mean PSNR, SSIM and Compression Ratio of 38.45, 0.9602 and 1.75x respectively for the 50 test images, thus obtaining state-of-art performance for Quality Factor (QF)=5.
MANAJEMEN SURAT MASUK, BUKU TAMU DAN DISPOSISI SURAT DENGAN APLIKASI E-OFFICE PADA BALAI TEKNOLOGI INFORMASI DAN KOMUNIKASI DINAS PENDIDIKAN PROVINSI MALUKU

An information system or e-office application is one of the applications developed with the aim of helping office administration management to be more effective and efficient. As one of the UPT (Technical Implementation Units) within the Maluku Provincial Government, the Education Information and Communication Technology Center develops e-office applications as a form of electronic data management. The system development method used in this study is the Waterfall Model and was developed using the Laravel Framework and MySQL database. This research was conducted with the aim of implementing an e-office application at the Tekkom Office of the Maluku Province Education Office with guest/visitor book features, incoming mail filing, letter disposition, guest/visitor book reports and incoming mail reports. With this application, office administration management such as guest book data and incoming mail can be managed electronically so that it becomes more effective and efficient.