Reviewerly/exHarmony huggingface dataset:
Improving Performance in Person Reidentification Using Adaptive Multiple Loss Baseline

Currently, deep learning is the mainstream method to solve the problem of person reidentification. With the rapid development of neural networks in recent years, a number of neural network frameworks have emerged for it, so it is becoming more important to explore a simple and efficient baseline algorithm. In fact, the performance of the same module varies greatly in different positions of the network architecture. After exploring how modules can play a maximum role in the network and studying and summarizing existing algorithms, we designed an adaptive multiple loss baseline (AML) with a simple structure but powerful functions. In this network, we use an adaptive mining sample loss (AMS) and other modules, which can mine more information from input samples at the same time. Based on triplet loss, AMS loss can optimize the distance between the input sample and its positive and negative samples and protect structural information within the sample. During the experiment, we conducted several group tests and confirmed the high performance of AML baseline via the results. AML baseline has outstanding performance in three commonly used datasets. The two indicators of AML baseline on CUHK-03 are 25.7% and 26.8% higher than BagTricks.
The Influence of Social Media Marketing and E-Wom on Purchase Decisions Through Purchase Intention: Study on Ready-to-Eat Food

The focus of this research is to determine the influence of social media marketing on purchase intention, the influence of e-WoM on purchase intention, the influence of purchase intention on purchase decisions, the influence of social media marketing on purchasing decisions, the influence of e-WoM on purchase decisions, and the influence of social media marketing and e-WoM on purchasing decisions through a purchase intention. A questionnaire was used as the data collection instrument in a survey approach. The research sample included 250 people who follow Lokasaji on social media, live in Jabodetabek, are 17 and above, and have purchased Lokasaji products in the last six months. SPSS and LISREL's SEM (Structural Equation Model) were used for data analysis. The results of the hypothesis test show that all hypotheses are accepted.
Face Mask And Social Distance Detection With Alarm Using Deep Learning

The novel coronavirus also called Covid-19 had a huge effect on different sectors in many territories and imposed governments across the world to urge lockdowns to avert novel coronavirus transmission. This little step of wearing a face mask, following social distancing would save plenty of lives as the spread of the novel coronavirus could be mitigated. This theme consists of social distancing noticing and face mask detection for the events of disease like novel coronavirus can be solved by maintaining social distancing as well as wearing/putting on its face mask. This used to develop a Mask Detection using OpenCV, Keras/TensorFlow and also Deep Learning. This System can easily integrated/implemented to various embedded devices with limited computational capacity that uses CNN architecture. System will detect face masks in photos/images and in real-time videos. Social Distancing and wearing masks have become the 2 most popular terms in today's life to keep oneself safe from getting infected from the novel coronavirus. Researchers have concluded that these 2 practises are the warriors against Covid. Governments across the nation are rigorously making efforts to make these 2 practises in action. We as a team came up to a real time solution of detecting distance between humans and detecting persons with no mask covering. This solution was needed as there is a lack of awareness among people about the major precautions which is Mask+Distance. Neither only mask can save, nor only distancing can save you but the aggregation of these two can.
Research on Information Fusion Algorithm Based on Multi-Agent Group Decision Mechanism

Aim at the problem of rough and low precision in the classifier fusion of sorting layer output, an information fusion algorithm based on multi-agent theory is presented. This algorithm proposes based on multi-agent as classifier combination. It applies the collating of individual agent are classified with Clustering Analysis method, according to the result of classification, multi-agent is classified into several groups and the weight coefficient is given to every agent. By building relative matrixes between sort set and sort making order, and classified sort set on relative matrixes, the method constructs an optimization decision making model. According to fused group consensus in rank making. After those are achieved, combination decision is made. According to experiments on speech emotion recognition database, the result of the experience indicates the model is simple and feasible.
Applying Modern Meta-Heuristics in Intelligent Systems

Engineering and business problems are increasingly impenetrable due to the new economics triggered by big data, artificial intelligence, and the Internet of things [...]
EFFECTIVENESS OF SMART TECHNOLOGIES IN CHEMISTRY TEACHING AND LEARNING OF GRADE ELEVENTH STUDENTS IN THE GAMBIA

Chemistry education in The Gambia is challenged by a lack of laboratory and human resources.The consequences have been unsatisfactory learning outcomes in the Gambian secondary school system.Smartboards, Smart notebook software, and touchscreen laptops were considered to influence learning outcomes.Therefore, a comparison was made between this method and the traditional method.The study used the randomized pre-test-post-test group design to select 284 students by convenient sampling and place them in each experimental and control group.While the experimental group was taught using multifunctional approaches, the social constructivism paradigm, and smart learning objects, the control group was taught using traditional methods, laboratory equipment, and worksheet problem-solving.The effectiveness of the teaching methods was determined by the mean scores on pre-tests and post-tests.Pre-test mean ranks on academic achievement computed using the Mann-Whitney U test indicated no significant difference between the experimental and the control group.However, in the post-test, there was a significant difference (p = 0.003) between the groups, favouring the experimental group.In addition, a higher mean rank was found in the experimental group than in the control group on concept knowledge and application.The results support the current use of modern technology in science teaching and imply that smart technologies can lead to better learning outcomes in the Gambian context if they were to be used extensively in the secondary school system.However, a further study that will determine the level of effectiveness of each of the methods of teaching by comparing the difference between pre-test and post-test scores for each group may be needed in the future, as this will indicate a better measure of the effectiveness of the methods in enhancing students' academic performances.
Digital contact tracing in epidemics: fast tracking the future

The COVID pandemic has brought unprecedented changes in the current healthcare model, more as a necessity than by choice. The rapid unraveling of the pandemic has fast tracked the use of technology and artificial intelligence in healthcare systems by identifying and implementing more efficient processes to mitigate the crisis. Digital contact tracing technology (DCTT) has been hailed as the savior for opening up the community towards some semblance to the previous normal. Understanding contact tracing as both a proactive tool in the containing of an epidemics and as a reactive tool in limiting damages after spread is of utmost importance before taking a call into its effectiveness and implication on privacy of the individuals involved. The current pandemic response is like building a plane during its flight, and hence the risks involved in understanding the disease and mitigating the problems due to the novel nature of the disease needs to be done in real time. The political and social outcries on the use of DCTT are enough reasons for caution in applying previously unperfected technologies in diseases whose natural course has not yet been fully understood. The relationship between epidemics and contact tracing, conventional contact tracing, DCTT, different models of DCTT used during the current epidemic, limitations of DCTT and the future of incorporating DCTT into healthcare systems from the view of epidemiology and patient safety will be the primary focus of this article.
Binocular Stereo Matching Based on SGM and Flood Filling Algorithm

Abstract The SGM algorithm was weak in matching the occluded area and parallax discontinuity area in stereo matching, and it was easy to produce more voids. To address this question, the paper proposes a parallax optimizati-on algorithm based on SGM algorithm combined with flood filling and median smoothing. The algorithm fills the missing parallax values based on the parallax values at the edges of the voids and achieves the repair of the missing parallax in the parallax map without raising a large computational effort. The proposed algorithm has also been qua-ntitatively analyzed on the Middlebury stereo matching dataset using three evaluation metrics: root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (MSSIM). The experimental results show that the improvement and optimization of the SGM algorithm can effectively fill the voids in the parallax map and reduce the noise of the image, and the matching accuracy of parallax maps is improved by an average of 9%.
Non-EFL Students' Ability in Writing Simple Sentences of Descriptive Paragraphs

The objective of this study is to know the students’ ability in writing English simple sentences. This research is descriptive qualitative. The result shows that students have understanding of how to construct simple sentences in several formulas such as Subject + Verb + Complement (S + V + C), Subject + Verb + Adverb (S + V + Adv), Subject + Verb + Object (S + V + Object), and Subject + Verb + Object + Adverb (S + V + O + Adverb). But, besides using simple sentences, the students also still use other sentence forms to support information in their paragraphs such as 1) compound sentences by using the coordinating conjunction for example “so”, ”but”, and “and”. 2) complex sentence by using the coordinating conjunction for example “after”, “before”, “so that”, “if”, “that”, “because”, “even though”, “although”, “when, “while”. 3) compound-complex sentence by using both coordinating conjunction and subordinating conjunction”. Therefore, the teachers/lecturers need to give understanding more to the students that 1) a simple sentence has one independent clause and expresses one idea/topic. 2) simple sentence must have a subject-verb combination, but the subject can be compound or more than one. 3) simple sentence can have a compound verb. 4) simple sentences can only have one subject-verb combination and commas are not used. The students must be able to understand and know the subject, predicate (verb) and nouns, adjectives, and adverbs that will give a complete meaning. So that those who read will understand what they want to convey through the sentence.
ANALYSIZING ERRORS OF INFLECTIONAL AFFIXES ON STUDENTS’ WRITINGS

This research aimed to identify what error of inflectional affixes was the most frequently appeared on students’ writings and what error of inflectional affixes was the least frequently appeared on students’ writings. The approach of research was qualitative method with descriptive analysis to analyze the data. The data were taken from students’ writings made by 111 second semester students of Indonusa Polytechnic Surakarta majoring in health information management. This research was to perform the percentage of error of inflectional affixes on students’ writings. The percentage of plural -s/es was 58,46 %, third person present singular -s/es was 20 %, past tense –ed was 6,15 %, past participle -en/ed was 6,15 %, progressive –ing was 3,08 %, possessive –‘s was 3,08 %, superlative –est was 1,68 % and comparative –er was 1,40 %. Referring to the percentages of the research, the researcher concluded that the error of inflectional affixes which the most frequently appeared was plural –s/es with the percentage 58,46 %, and the error of inflectional affixes which the least frequently appeared was comparative –er with the percentage 1,40 %. Mastering inflectional affixes is important in order to make precise sentences. Therefore, students should perform well in applying inflectional affixes.
An Analysis of Phonological, Morphological and Syntactical Errors on Teachers’ Talk in EFL Classroom

This study investigated the teachers’ talk errors from phonological, morphological and syntactical aspects committed by EFL teachers during classroom instruction. It employed descriptive qualitative research. Through recording and transcription of teachers’ classroom meetings, the researcher found that the errors of teachers' talk occurred 96 times and the phonological errors dominated the teachers’ talk errors. It reached 55.2 % or occurred 53 times. The phonological errors covered the mispronouncing of pure vowels, diphthongs, triphthongs and some consonants. Furthermore, the second type of error was syntactical errors. They were committed 34 times or reached 35.4%. the errors comprised the incorrect word order and sentence structure or the misuse of tense. Meanwhile, the morphological errors were done 9 times or only reached 9.4 %. The errors included the misuse of verb, noun and pronoun.&#x0D; The result of the study revealed that the EFL teachers who are supposed to be role models in using proper English, frequently make errors during classroom interaction. so that the result of the study is significant and expected to be able to raise the awareness of the EFL teachers about the importance of teacher talk in classroom interaction.
Cybersecurity and Privacy Aspects of Smart Contracts in the Energy Domain

&lt;p&gt;Smart contracts (SCs) are a set of logical procedures that can be run by individual peers participating within a Distributed Ledger Technology (DLT) network. By design, smart contracts inherit many of the benefits of DLT, including its immutability, scalability and security properties. Nevertheless, they may introduce additional attack vectors, which can lead to cybersecurity explorations that could jeopardize the end-application's ability to operate as intended or result in data leaks, and privacy violations. In this work an exploration of known problems, and possible attack scenarios will be presented. This is followed by a set of proposed best practices and mitigation strategies that are intended to assist developers, researchers and other relevant stakeholders to develop secure SC implementations. &lt;/p&gt;
PELATIHAN MEMBUAT MEDIA PEMBELAJARAN BAGI GURU PAI MENGGUNAKAN APLIKASI CANVA DESA SEGARAJAYA

Teachers have an important role in the process of teaching and learning activities. But unfortunately in this online learning there are still many teachers who have difficulty in making learning patterns through content media. Due to lack of references and several other factors. Therefore, the readiness of teachers to face the digital era in the world of education is very necessary, so that teachers are ready to use digital technology as the main learning platform. By conducting training to make learning videos through the Canva application because it is very important for teachers to do. The goal is for teachers to be able to make videos that are interesting, interactive, easy to understand and useful. In addition, continue to encourage a sense of enthusiasm to teach under any circumstances. The method used is socialization, training and evaluation. The existence of training activities to make learning media can improve the ability of teachers to provide material and teachers are also increasingly able to use technology, are able to make learning videos through YouTube and can implement the Canva application and get new references.
Shanakht-Net: Person Re-identification using Inertial Sensors data generated by Smart-wearables from Daily Activities

&lt;p&gt;An important component of an automated surveillance environment is person re-identification. The problem is often addressed using data received from vision sensors using appearance-based features, which are heavily reliant on visual cues such as colour, texture, and so on, limiting the reliability of re-identification of an individual. Much research has been performed to solve the problem of re-identification utilising human gait using inertial measurement units (IMU) data, which is thought to be unique and offer a distinct biometric signature that is especially ideal for re-ID in uncontrolled conditions. The locomotive activity of walking was the primary emphasis. The current study utilised not only locomotive activities but also non-locomotive activities of daily living. The data was obtained from the WISDM lab. The data is collected while engaging in six distinct everyday activities. The dataset was originally gathered for the purpose of Human Activity Recognition. Nonetheless, each person is given a unique ID. This information was utilised to re-identify the individual. The dataset consists of data of 36 volunteers. Shanakht-Net, a novel convolutional neural network, is introduced. The F1-score obtained is 93\%. Precision, recall, and accuracy are assessed and reported as well.&lt;/p&gt;
CHARACTERIZATION OF CORNER POSITIVE MATRICES: HOPFIELD NEURAL NETWORK: NP HARD PROBLEMS

&lt;p&gt;In this research paper, the problem of characterization of corner positive matrices ( an open research problem ) is addressed. Based on optimization of energy function associated with Hopfield Neural Network, an algorithmic approach to determine the corner positive definiteness of a symmetric matrix is proposed. It is reasoned that the problem addressed is an NP hard problem.&lt;/p&gt;
Experimental Research of Veles Planetary Rover Performing Simple Construction Tasks

The paper is concerned with the problem of experimental research of Veles planetary rover performing simple construction tasks. The current state of the art in planetary rovers and their research in construction tasks are discussed. The Veles rover solution designed for construction tasks and experimental testbed are described. The experimental testbed included a test room with Moon regolith analogue. Experimental research concerning rover mobility and manipulation tasks were carried out. Experimental research consisted of various scenarios,, including clearing an area that removes boulders and levelling the soil. The complementary scenario for the area preparation was to exchange the tools of the manipulator. In this case, the gripper and the shovel were used as end-effectors for moving objects, both structured or in the form of regolith. Results of selected experimental research are presented and discussed. Finally, directions of future works of the rover are pointed out.
Ontology Data Modeling of Indonesian Medicinal Plants and Efficacy

People use medicinal plants for as early prevention and treating disease. Medicinal plants must be careful not to cause side effects, so knowledge is needed. Medicinal plant knowledge is stored using an ontology data model. In some ontology studies, there are still shortcomings in managing information, namely the absence of a relationship between scientific terms related to medicinal plants and phrases already known to the public. Hence, it is necessary to have this relationship. In other studies, there is no information related to disease protein, so this research also develops ontologies to enrich knowledge about medicinal plants and their efficacy. Based on the results, the developed ontology test can build a relationship between scientific terms of therapeutic pants and phrases that are known to the public. The public also knows which proteins affect a disease, so public knowledge about medicinal plants is getting wider.
INTELLIGENT VIDEO SURVEILLANCE USING DEEP LEARNING

Video surveillance, also known as CCTV (closed-circuit television), is a rapidly growing industry that has been around for more than 30 years and has seen its fair share of technological advancements. In today's world, video surveillance has become an essential component for ensuring public safety. Security can be defined in a variety of ways depending on the context, such as theft detection, violence detection, explosion risk, and so on. The term "security" in crowded public places refers to almost any type of abnormal event.Intelligent video surveillance delivers cutting-edge smart security by recording unexpected activities in homes, offices, and public locations based on the preferences of the user. In the event of an abnormal incident, the video surveillance system will actively respond to detect actions in advance through real-time monitoring and promptly communicate data. The primary focus is on the use of deep learning techniques to provide tracking of a moving target, high-definition picture quality, and night vision technology triggered by motion sensors, which means the system isn't running when nothing is happening at your location, automatic audio and visual detection, video recording initiation, and detection of suspicious activities that can trigger and alert the systems in all climate conditions.Deep learning technology will be used in the data processing model design to visualise data for abnormal activities, and this design also proposes an intelligent surveillance system to quickly and effectively detect activities by sending a video image and an alert message to the web via real-time processing. Recent improvements in computer vision, particularly deep learning approaches, have opened up new possibilities for these systems, enhancing their capabilities and launching new research areas in this field.
CLASSIFICATION OF ONLINE TOXIC COMMENTS USING MACHINE LEARNING ALGORITHMS

Toxic comments are disrespectful, abusive, or unreasonable online comments that usually make other users leave a discussion. The danger of online bullying and harassment affects the free flow of thoughts by restricting the dissenting opinions of people. Sites struggle to promote discussions effectively, leading many communities to limit or close down user comments altogether. This paper will systematically examine the extent of online harassment and classify the content into labels to examine the toxicity as correctly as possible. Here, we will use two machine learning algorithms and apply them to our data to solve the problem of text classification and to identify the best machine learning algorithm based on our evaluation metrics for toxic comments classification. We will aim at examining the toxicity with high accuracy to limit down its adverse effects which will be an incentive for organizations to take the necessary steps
Analysis of Application of Accounting Information Systems Receivable Billing In Increasing The Effectiveness of Cash Receiving In The Company

The objectives to be achieved in this study are to find out the extent of the accounting information system for collecting receivables in increasing the effectiveness of cash receipts implemented by PT. Karunia Indah Delapan Expres. The following actions were done to reach the aims of this study are: 1. perform an analysis of the accounting information system on the collection of receivables applied by PT. Karunia Indah Delapan Express, 2. Analyze the accounting information system for collection of accounts receivable to see if it can support the effectiveness of PT. Karunia Indah Delapan Expres, 3. Identify the problems and causes of problems that PT. Karunia Indah Delapan Expres is facing. From the results of the research and analysis carried out it can be concluded that:1. The slowness of the delivery letter to return to the original branch. 2. The lack of the number of collectors / collection officers of receivables. 3. The number of account numbers in PT. Karunia Indah Delapan Expres Surabaya.