Reviewerly/exHarmony huggingface dataset:
Do The Companies Owe Corporate Social Responsibility towards Institutions of Higher Education?

With an emphasis on distribution of wealth among the stakeholders and considering environmental sustainability, the companies are required to manage business processes in such a way to provide a positive impact on the society. These companies through their business earn a major profit by operating in the society and various stakeholders are involved and affected from their process directly or indirectly, therefore the companies are expected to spend a part of their profit for the benefits of their stakeholders. Corporate Social Responsibility (CSR) is a concept where big companies consciously combine their economic profit with social well-being and environmental sustainability. India has made legislation in the form of section 135 of Companies Act, 2013 for this purpose. According to this Act, education, gender equality, persons with disability (PwD) and environmental sustainability are some of the areas where the companies can use Corporate Social Responsibility funds through their policies.&#x0D; In response to the law, a large number of companies are performing well and undertaking a large number of projects in areas mentioned under the Schedule VII of the Companies Act, 2013. But the data shows a lot still needs to be done as these large numbers of Companies are spending on education at school level and skill development but higher educational institutions (HEIs) are far away from reaping the benefits of CSR funds. Companies and corporate houses do not consider much about the infrastructural development in HEIs for environmental sustainability, and projects leading to women development.&#x0D; Government is over burdened in looking and sponsoring even the small projects. CSR funding can share this responsibility thereby accelerating the process of development in the institutions.
Web-Based Information System for the Stuff Inventory at UPTD PPD South Bandung Region

The inventory of stuff must be neatly arranged. Using technology supported by an information system, it is hoped that the storage of an item can be neatly arranged. To support broad mobility, a web-based platform is essential. It can provide sufficient integrity for users. This website-based inventory information system is one way to solve problems in the UPTD PPD South Bandung Region. In its design, this system uses qualitative research methods and software development methods of Software Development Life Cycle (SDLC) as well as a system analysis design, namely Data Flow Diagrams (DFD), to determine the flow of the data. The testing was limited to program quality using Blackbox testing to test the program properly.
Implementation of a personal identification system using alveolar bone images

In recent years, personal identification has been performed using antemortem panoramic X-ray images and postmortem-CT images. Using these, we have developed a personal identification method that focuses on the alveolar bone. This study examined the effectiveness of this method and aimed to implement a reproducible system.For personal identification, a total of 633 CT images and panoramic X-ray images belonging to three groups with different conditions were used. These images were 160 sets in the same person group and 96,820 in the other groups. The similarity of alveolar bone images was calculated using the landmark method of Procrustes analysis. The processes were system implemented and the methodology was validated.The ability to identify between the same person group and other person groups showed 0.9769 as the area under the curve (AUC: ROC curve). At the cutoff value of 4.978, there was no false rejection rate, but false acceptance rate was slightly higher.This method was useful as a screening method for personal identification. In addition, system implementation was efficient and reduced human error. In the future, we aim to realize a more efficient personal identification method using distortion-corrected images and including auto-detective landmarks using deep learning.
[Research on "Augmented Reality" Assisted Precise Thoracoscopic Resection of Pulmonary Nodules].

To break with traditional preoperative localization, a porcine animal model to evaluate the safety of augmented reality (AR) assisted localization of solitary pulmonary nodules (SPN) was used. Before the experiment, Microsoft HoloLens AR system was used to bring the CT image into the laboratory after 3D reconstruction. The virtual model was fitted with real body surface markers, and the virtual positioning auxiliary line and auxiliary locator were used to perform puncture positioning before surgery. Data related to actual puncture path and expected planned path were recorded in the experiment. SPSS 26.0 was used to calculate the puncture accuracy under AR assisted positioning, and the results obtained were acceptable in segmentectomy or wedge pneumonectomy. Its feasibility in animal models will also be evaluated, and its safety and efficacy will need to be further studied in clinical trials.
Protection of Documented Information from Falsification Based on Speckle Patterns

The article considers the protection of documented information based on random aperiodic structures. Speckle patterns formed by illuminating a diffuse surface with coherent radiation are proposed as random aperiodic structures. Experimental studies have been carried out on the formation of moiré patterns with various imposition of speckle patterns. It is shown that such moiré patterns can be used to protect and identify documented information.
Single-Sign-On in Smart Homes using Continuous Authentication

Modern ubiquitous computing environments are increasingly populated with smart devices that need to know the identity of users interacting with them. At the same time, the number of authentications that a user needs to perform increases, as nowadays devices such as smart TVs require authentication which was not the case in earlier times. Even for single-person households, the need to authenticate against present smart devices in the environment appears at regular intervals, ranging from TVs to voice assistants, to gaming consoles. To reduce the need for repeated authentication, we explore the concept of a system that allows the sharing of users’ authenticated identity information between smart devices, similar to the concept of Single-Sign-On on the internet. Following a preliminary field study, we show that such a system can decrease the number of necessary authentications in a ubiquitous computing environment by 84.4%, increasing usability and security.
GAS DETERMINATION USING ARTIFICIAL NEURAL NETWORKS

The recognition of various gases has been performed - part of the tasks solved by these systems. For this purpose, various types of classifiers are used, among which artificial neural networks are widely used. They are used to classify various types of smokes, fires, aromas, gases, etc. These systems use metal oxide gas sensors, which are widely used due to their high sensitivity, low cost and short duration of the chemical reaction. When training the network, a three-dimensional approximation of the sensor characteristics is carried out.
Character Formation Through Meaningful Relationships in Learning Interactions at Islamic Higher Education

This study aims to describe the use of language features in relation to meaning in the form of antonyms, synonyms, and hyponyms in teaching interactions at IAIN Palopo. The research was conducted using a descriptive qualitative approach that uses data sources from narratives or interactions that take place in learning. The data is from words and phrases containing meaningful relationships obtained using a recording instrument (Handycam). Then, the data is classified and analyzed using description, interpretation, and explanation techniques. The study results show that the language features of meaning relations used in teaching interactions at IAIN Palopo are represented as antonyms, synonyms, and hyponyms. Each type of meaning relation shows the meaning of euphemization aspects, sensory aspects, experiential values, relational values, and expressive values. Furthermore, each aspect generally aims to express ideas through meaningful characters that affirm, explain, and convince the object of study to achieve competence..
Retrieval dynamics in resolving relational inconsistency during verbal analogical reasoning.

Reasoning about verbal analogies requires selective retrieval of relevant relational information. A consequence of this may be that inhibitory processes in memory cause reduced recall of information associated with analogy-irrelevant relations. The current experiments apply the retrieval-induced forgetting framework to investigate the potential role of such inhibitory processes in analogical reasoning. Participants studied verbal analogies in A-B :: C-D form. Then, half of the A-B pairs from the study phase appeared in verbal analogy problems but with a new C term (A-B :: C-?), and half the items did not appear in verbal analogy problems. A final recall test was then administered for all the original analogies. When the new C term in the analogical reasoning phase conveyed a new relation that was inconsistent with the original relation, reduced recall for items appearing in analogies was observed (Experiment 1). However, when the new C term conveyed a relation that was consistent with the original relation, no forgetting effect was observed (Experiment 1). This forgetting effect occurred even when a hint of the original relation was provided at final recall (Experiment 2). These results indicate that reasoning about analogies may involve inhibitory processes that help reduce competition among competing relations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Rank Learning-Based Code Readability Assessment with Siamese Neural Networks

Automatically assessing code readability is a relatively new challenge that has attracted growing attention from the software engineering community. In this paper, we outline the idea to regard code readability assessment as a learning-to-rank task. Specifically, we design a pairwise ranking model with siamese neural networks, which takes as input a code pair and outputs their readability ranking order. We have evaluated our approach on three publicly available datasets. The result is promising, with an accuracy of 83.5%, a precision of 86.1%, a recall of 81.6%, an F-measure of 83.6% and an AUC of 83.4%.
Anomaly Detection System for Assembly Cells Using Skeletal Information

In response to problems associated with the shortage of factory workers, the demand for efficiency maximization by eliminating wasted work has recently become stronger. Moreover, to ensure compliance with product quality, the demand for reliable work execution is also increasing. To address these demands, we have developed a deviation detection system for human work that achieves higher efficiency and manufacturing quality through digitalization of product proofs. We implemented our system to extract skeletal information during work and compared it with a reference series. The evaluation results showed that the proposed system could achieve a detection rate of 92% (target > =90%) for behaviors deviating from the reference operation.
A Descriptive Analysis of Movement Patterns of Wh-Questions in Urdu and English Language

The present study highlights the differences and similarities between Urdu and English language based on Wh-movement. According to Manetta (2010), Hindi-Urdu exhibits a feature-driven overt Wh-movement to Spec vp, a point from which movement of Wh-word might gain clausal scope. The extent and nature of driven overt Wh-movement will be speculated in the present study by drawing a comparison between Urdu and English language. The use of scope marking to interrogate out of finite complements is contended to postulate a homogeneous idea of the following components involved in the construction of questions in two languages: the propensity of Wh-expressions to appear in preverbal position, the potential of overt long movement, and the employment of Wh-expressions in preverbal point. The study exclaims that Urdu is an in-situ language as it bears the presence of Wh-word at canonical position whereas English is not an in-situ language because it does not bear the presence of Wh-word at middle or end positions. Further, the movement of Wh-words in English is regulatory while the movement of K-words is totally non-regulatory in Urdu language. This study will further help researchers in exploring the movement of Wh-expression in Punjabi language and its similarities with Urdu Wh-movement.
Policy on the Efficient use of Robotics in the Automobile Parts Industry

Globally, automobile companies are converting labor-intensive processes to automated processes to secure competitiveness and reduce costs. In 2020, Korea was the fifth largest automobile producer; however, it faced a population decline and rising labor costs. Korean auto parts companies are in a dilemma-whether to adopt manufacturing robots and have trouble due to financial burden or suffer the lack of technology. Hence, Korean auto parts companies often receive national policy funding to adopt manufacturing robots. Therefore, for sustainable policy support, the efficiency and productivity of manufacturing robot adoption must be analyzed considering government policy support. We divided the activities of automobile parts companies into operating activity and financing activity consisting of production and sales. Moreover, we used the Dynamic Network Slacks-Based Measure (DNSBM) model. This study used KIS-VALUE data from Korea. The analysis results revealed that the overall efficiency (0.3822) was low because of the low efficiency of operating activity productivity (0.4342) and the gap between operating activity productivity and financing activity efficiency (0.7702). Moreover, the total factor productivity (0.9534) decreased because of decreases in operating activity productivity (0.9507) and financing activity productivity (0.9841). From 2016 to 2020, when the manufacturing robot adoption policy was implemented, the difference in corporate efficiency according to policy support was significant. Korea’s manufacturing robot adoption policy contributes to the improvement of corporate competitiveness. This study presents the objective evidence necessary for future policy establishment to direct resource readjustment of Korean auto parts companies and analyze past policy.
ASSESSMENT OF SEDIMENT QUALITY DUE TO HEAVY METAL CONTAMINATION IN MARINE SEDIMENTS ALONG THE NORTHWEST COAST OF SABAH, MALAYSIA

Heavy metal contents along the Northwest coast of Sabah were determined to interpret the contamination level in the marine sediment. The metal abundance is regulated by the physico-chemical properties such as the average sediment pH (7.82, 9.00 and 8.99), organic matter (0.62%, 1.60%, and 2.27%), moisture content (25.00%, 29.70%, and 15.00%) and sandy texture in Kota Belud, Kudat and Mantanani Island, respectively. The major elements show Ca&gt;Fe&gt;Mg&gt;Al&gt;Mn for all study sites, while the heavy metals show Ni&gt;Cr&gt;Zn&gt;Cu&gt;Co&gt;Pb, Cr&gt;Ni&gt;Zn&gt;Cu&gt;Pb&gt;Co and Zn&gt;Pb&gt;Cr&gt;Ni, for Kota Belud, Kudat and Mantanani Island, respectively. The contamination degree of heavy metals was evaluated using the Sediment Quality Assessment (SQA). The SQA parameters indicated none to moderate contamination in Kota Belud that shows Class 0, Class 1 and Class 2 contamination. The parameters also indicated none to low contamination in Kudat and Mantanani Island that show only Class 0 contamination. The enrichment factor (EF) suggested minor to moderately severe metal enrichment by anthropogenic sources in Kota Belud, whereas only minor enrichment in Kudat and Mantanani Island. The modified contamination degree (mCd&lt;1.5) and pollution load index (0≤PLI&lt;1) indicating only low pollution level in the marine sediments for all study sites. The objectives of this study are to determine the physico-chemical parameters of sediments, estimate the heavy metal contents and evaluate the sediment quality.
(Im)politeness Strategies Used in Vice -Presidential Candidates Debate Between Mike Pence and Sen. Kamala Harris

Politeness is necessary for the way people socialize. However, some people choose to communicate impolitely despite knowing that it’s inappropriate. This study aims to find out how people use impoliteness strategies in communication, and identify the impoliteness strategies used in the Vice-Presidential United States of Amerika candidates debate between Mike Pence and Sen. Kamala Harris on October 8th, 2020, while also figuring out the purpose of using these strategies in the debate. For this reason, to identify the use of impoliteness strategies, the researcher used Jonathan Culpeper's (2005) theory of impoliteness strategies and a qualitative approach to analyze the data. The data was taken from a YouTube video entitled “Full Debate: Vice President Mike Pence and Sen. Kamala Harris | WSJ” posted by the Wall Street Journal on October 8, 2020. The results of this study revealed that four out of five impolite strategies were used, with negative impoliteness as the most commonly used strategy. The other four strategies are bald on record impoliteness, positive impoliteness, negative impoliteness, and sarcasm and mock politeness. Meanwhile, withholding politeness was never used in the debate.
The Community Manipulation through Big Brother’s Tyranny in George Orwell’s Nineteen Eighty Four

This research aimed on some instruments or agencies that implemented in constracting the community engineering in Orwell’s Nineteen Eighty Four, describe the logic used and present the community engineering carried out the novel. The writer then uses library research and sosiology literature as method in analyzing the novel. The data were collected by using note taking technique which exists in Nineteen Eighty-Four accord with the pages. Then, all the quotation classified and analyzed based on the case that had beeen arround by each moment/event in that novel. After doing the considerable study, the writer finds basically the bad effect of human engineering to the society. The over control by agents were bringing individuals’ loss of human nature and a critical thinking faculty and the diminished capacity for self expression. So, finally the human being is not exists as a human with high level values, in fact in this novel, human is less than the animal.
The Efficacy of Using Round Robin Technique in Teaching Speaking to Indonesian English as Foreign Language (EFL) Students

This research aims at finding out the efficacy of using round robin technique in teaching speaking especially to Indonesian English as Foreign Language (EFL) students. The main question of this research: Is the use of round robin technique effective in teaching speaking to Indonesian EFL students? The research can be an addition to the persisting teaching speaking in English. The research was conducted in August 2022. This research was conducted at First semester students of the English Study Program of Nusa Cendana University, Kupang. The population of this research was First semester students of the English Study Program of Nusa Cendana University, Kupang in the 2021/2022 academic year. The number population is 160 in four classes. The research used a pre-experimental method with a pre-test and post-test design. The pre-test was given to find out the basic ability of the students in mastering speaking and the post-test given to find out the students’ improvement in mastering speaking after giving the treatment by using round robin technique. The findings show that using round robin technique is effective in teaching speaking to Indonesian EFL students. It is supported by the result of the significance test through SPSS 20 program that the P was 0.00. Therefore, it is recommended to use the round robin technique in developing students’ speaking of Indonesian EFL students
The Correlation between Vocational Students’ Speaking Anxiety and Speaking Performances in Learning English

Speaking is one of English skills that needs to be mastered by the students because it is the most fundamental element to build a communication. However, speaking has the complexity that can difficult the students to learn English and reach the goal. This study aims to find out about the correlation between vocational students’ speaking anxiety and speaking performances in learning English. This study also find out about their speaking anxiety level, type of speaking anxiety, and their speaking ability in learning English. A correlational study used to conduct this research. The researcher collected the data through FLCAS questionnaire that consists of 24 statements and the students’ speaking performance score. The researcher distributed the questionnaire to 70 students of SMK PGRI 3 Malang. After analyzing the findings with SPSS version 24 and Microsoft Excel, the result shows that there is a negative correlation between students’ speaking anxiety and speaking performances in learning English. It is correlated at -0.192 which means it is in a very weak correlation. In addition, the students’ speaking anxiety level is identified in moderate level. The dominant type of speaking anxiety they have is communication apprehension and their speaking ability is categorized in a very good level.
Automatically Prepare Training Data for YOLO Using Robotic In-Hand Observation and Synthesis

Deep learning methods have recently exhibited impressive performance in object detection. However, such methods needed much training data to achieve high recognition accuracy, which was time-consuming and required considerable manual work like labeling images. In this paper, we automatically prepare training data using robots. Considering the low efficiency and high energy consumption in robot motion, we proposed combining robotic in-hand observation and data synthesis to enlarge the limited data set collected by the robot. We first used a robot with a depth sensor to collect images of objects held in the robot's hands and segment the object pictures. Then, we used a copy-paste method to synthesize the segmented objects with rack backgrounds. The collected and synthetic images are combined to train a deep detection neural network. We conducted experiments to compare YOLOv5x detectors trained with images collected using the proposed method and several other methods. The results showed that combined observation and synthetic images led to comparable performance to manual data preparation. They provided a good guide on optimizing data configurations and parameter settings for training detectors. The proposed method required only a single process and was a low-cost way to produce the combined data. Interested readers may find the data sets and trained models from the following GitHub repository: github.com/wrslab/tubedet