Wrong Target Research Articles

Supporting Early Language by Supporting Systemic Solutions

A large body of research shows connections between infants’ and toddlers’ home language input and a wide range of receptive and expressive early language skills. Some facets of caretaker input and early language skills are associated with socioeconomic status (SES), though not all. Given the complexity of language learning, language use, and its many pathways of connection to SES, testing causal links between these dimensions is difficult at best. Interventions aimed at changing parent language use have seen mixed success, in part because “language infusions” generally fail to target underlying challenges facing underresourced families, and perhaps because parent language is the wrong target. System-level interventions such as paid parental leave and expansion and enrichment of childcare and early education options hold greater promise for improving families’ lives, with positive repercussions for a broad range of family and child outcomes, including linguistic ones.

Analisis Kinerja Lurah terhadap Pembangunan Daerah dan Otonomi Daerah di Kelurahan Binaraga, Kecamatan Rantau Utara, Kabupaten Labuhanbatu

The purpose of this research was to describe how the ward Binaraga , Rantau Utara Subdistrict, Labuhan Batu regency carries out the duties as outlined in government regulation Number 73 of 2005 concerning sub-districts related to tasks that should be carried out by the government, namely (a). implementation of sub-district government activities; (b). community empowerment; (c). Community service; (d). implementation of peace and general agreement; (e). maintenance of public service infrastructure and facilities; and (P). This research uses a qualitative approach with data collection techniques of interviews, observation, document review. The object studied is the performance of the village head towards regional development and regional autonomy. Based on this research, the task that has been fully carried out effectively is the community service task in the area of ​​improving stabilizer infrastructure. Meanwhile, the assistance tasks are the same, but the PKH and BLT programs have not been fully implemented fairly, where when the assistance is distributed there is still a wrong target

SISTEM PENDUKUNG KEPUTUSAN PENERIMA BERAS MISKIN (RASKIN) DENGAN METODE WEIGHTED PRODUCT BERBASIS WEB PADA KELURAHAN PLELEN

The Plelen Subdistrict Office is one of the government offices in Batang district, Central Java, which implements the RASKIN program, where the selection of prospective RASKIN recipients is still recorded manually. So that residents who should receive assistance will receive it according to the required criteria and will no longer be the wrong target for RASKIN recipients. Therefore, there is a need for a Decision Support System that can make it easier for sub-district employees to make decisions for residents who receive Poor Rice (RASKIN). With the existence of a decision support system (DSS), the aim is to make decisions more quickly and accurately. One method used is Weighted Product. The Weighted Product method is a method of determining order (priority) in multicriteria analysis and uses a multiplication technique to connect attribute ratings, where the rating of each attribute must first be raised to the power of the weight of the attribute in question.

Rethinking the Holocene temperature conundrum

Recent scholarship argues for more research to resolve the ‘Holocene temperature conundrum’, an apparent discrepancy between decreasing proxy-reconstructed and increasing model-simulated long-term temperature trends during the late Holocene. Here, we argue that the observed proxy-model offset likely results from inappropriate comparisons of different seasonal and spatial signals in the reconstructed and simulated palaeo-data. Since proxy archives have been used to reconstruct global annual mean temperatures, they have been compared against model simulations of the same seasonal and spatial domains. However, we suggest that most of the proxy-based large-scale reconstructions are biased towards Northern Hemisphere summer temperatures, and as such model comparisons have predominantly focused on the wrong target data. Further to advancing our understanding of long-term temperature trends, we recommend prioritising the refinement of proxy networks and climate reconstructions to preserve the full spectrum of naturally forced, interannual to multi-millennial variations needed to contextualise recent anthropogenic changes against past Holocene ranges.

CompreTAP: Feasibility and reliability of a new language comprehension mapping task via preoperative navigated transcranial magnetic stimulation

ObjectiveStimulation-based language mapping approaches that are used pre- and intraoperatively employ predominantly overt language tasks requiring sufficient language production abilities. Yet, these production-based setups are often not feasible in brain tumor patients with severe expressive aphasia. This pilot study evaluated the feasibility and reliability of a newly developed language comprehension task with preoperative navigated transcranial magnetic stimulation (nTMS). MethodsFifteen healthy subjects and six brain tumor patients with severe expressive aphasia unable to perform classic overt naming tasks underwent preoperative nTMS language mapping based on an auditory single-word Comprehension TAsk for Perioperative mapping (CompreTAP). Comprehension was probed by button-press responses to auditory stimuli, hence not requiring overt language responses. Positive comprehension areas were identified when stimulation elicited an incorrect or delayed button press. Error categories, case-wise cortical error rate distribution and inter-rater reliability between two experienced specialists were examined. ResultsOverall, the new setup showed to be feasible. Comprehension-disruptions induced by nTMS manifested in no responses, delayed or hesitant responses, searching behavior or selection of wrong target items across all patients and controls and could be performed even in patients with severe expressive aphasia. The analysis agreement between both specialists was substantial for classifying comprehension-positive and -negative sites. Extensive left-hemispheric individual cortical comprehension sites were identified for all patients. Apart from one case presenting with transient worsening of aphasic symptoms, pre-existing language deficits did not aggravate if results were used for subsequent surgical planning. ConclusionEmploying this new comprehension-based nTMS setup allowed to identify language relevant cortical sites in all healthy subjects and severely aphasic patients who were thus far precluded from classic production-based mapping. This pilot study, moreover, provides first indications that the CompreTAP mapping results may support the preservation of residual language function if used for subsequent surgical planning.

Perspektif Opini Pelanggan pada Aplikasi MyPertamina menggunakan Metode Latent Dirichlet Allocation (LDA)

Fluctuations in world oil prices are one of the major factors affecting the country's economic growth, including Indonesia. The government issued a fuel subsidy program, but the program was used by the wrong target and caused the government budget to swell. The solution is to provide programs to the right targets, the government created the MyPertamina application. MyPertamina's application reviews need to be further analyzed and researched to find out the customer's perspective on the application and help the government improve its work program. This study proposes the LDA (Latent Dirichlet Allocation) topic modeling method to analyze user reviews of the MyPertamina application. The methodology used in this research is starting with a literature study, data collection, data preprocessing, sentiment analysis, and topic modeling using LDA. The results of the analysis show that there are several negative reviews with most reviews being positive. This indicates that the MyPertamina application is a good program and right on target in distributing subsidized fuel. Based on the results of the analysis, the are some suggestions about improving application performance in the registration process and adding payment options through e-wallets other than LinkAja or m-banking. The conclusion of the perspective user, the MyPertamina application is effective in controlling subsidized fuel purchases and several user suggestions need to improve regarding registration and payment.

OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling

LIDAR point clouds are less affected by the weather and possess more depth of field than 2D images. However, sparsity and disorder of point clouds bring challenges for 3D object tracking due to the difficulty in detecting and encoding. In addition, ineffective candidate proposals increase the phenomenon of the loss of target tracking or wrong target tracking. In this paper, we propose an Orientation-variant Siamese 3D object tracking network that utilizes a Detection based Sampling module to generate candidate proposals (OS-DS tracker). The Detection based Sampling module is used to cut the excessive and useless proposals. And the multivariate Gaussian sampling generates the candidate proposals when the objects are not detected. Concretely, we first pre-train PointRCNN Network to globally detect objects from LIDAR point clouds. Then the 3D detected objects are refined by Candidate Regions Sampling to generate candidate proposals. Meanwhile, to make the feature vectors more discriminative, we design an Orientation-variant Siamese Auto-encoder, i.e., tracking loss regress to the intersection over union (IOU) of the template box and the candidate region boxes. Our method is tested on the KITTI dataset and the SHIP Tracking dataset. Compared with the previous state-of-the-arts, the proposed method outperforms in vessel tracking with 5.2%/2.1% improvement in Success and Precision.

Juridical Analysis of Sanctions On The Criminal Action Of Narcotics Abuse Goal I According To Law No. 35 Of 2009

Research objectives to find out and analyze; Determination of criminal sanctions against the main perpetrators of class 1 narcotics abuse. Judges' considerations in imposing criminal penalties on class 1 narcotics abuse based on decisions (No2166/pid.sus/2018/PN. Research method; with a descriptive qualitative approach that describes phenomena and incidents in the field at the research location. Data collection techniques: Through field research, library research, and interviews with parties handling cases such as prosecutors, judges, lawyers, and suspects. Conclusion: Application of criminal sanctions against the main perpetrators of class narcotics abuse 1. Application of sanctions to the abuse of narcotics class I committed by Defendant Kurniawan in Decision Number 2166/2018/PN.Tng, the authors conclude that the application of sanctions, in this case, was the wrong target or the wrong person. The Judge's considerations in imposing a criminal offense against narcotics abuse class 1 based on the decision (No 2166/2018/PN.Tng). It is legal and convincing that the decision is correct.

Decision Support System for Program Indonesia Pintar Recipients Using the Fuzzy Multi-Criteria Decision-Making Method

Program Indonesia Pintar (PIP) is the development of Bantuan Siswa Miskin (BSM) program, which covers students from the learning stages of SD or MI, SMP or MTs, SMA or Sekolah Menengah Kejuruan (SMK), the PIP Program is a National Program that aims to eliminate barriers to poor students participating in studying by helping poor students get access to appropriate learning services, avoiding dropping out of school, attracting poor students to return to study, helping students fulfill their desires in upgrading activities. Through the Program Indonesia Pintar (PIP), school-age children from poor households or families can continue to study, do not drop out of school. No recipients are on the wrong target for assistance from the Smart Indonesia Program at SMP Negri 39 Pekanbaru City. The method used in the decision support system is Fuzzy Multi-Criteria Decision Making (FMCDM) which assesses alternative determinants so that they can be used in policy analysis in decision-making. The results of this decision support will help decide the best choice of several substitutes based on the selected criteria.

Effect of Cas9 Protein on the Seed-Target Base Pair of the sgRNA/DNA Hybrid Duplex.

CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein (Cas9) has been widely used for gene editing. Not all guide RNAs can cleave the DNA efficiently remains a major challenge to CRISPR/Cas9-mediated genome engineering. Therefore, understanding how the Cas9 complex successfully and efficiently identifies specific functional targets through base-pairing has great implications for such applications. The 10-nt seed sequence at the 3' end of the guide RNA is critical to target recognition and cleavage. Here, through stretching molecular dynamics simulation, we studied the thermodynamics and kinetics of the binding-dissociation process of the seed base and the target DNA base with the Cas9 protein. The results showed that in the presence of Cas9 protein, the enthalpy change and entropy change in binding-dissociation of the seed base with the target are smaller than those without the Cas9 protein. The reduction of entropy penalty upon association with the protein resulted from the pre-organization of the seed base in an A-form helix, and the reduction of enthalpy change was due to the electrostatic attraction of the positively charged channel with the negative target DNA. The binding barrier coming from the entropy loss and the dissociation barrier resulting from the destruction of the base pair in the presence of Cas9 protein were lower than those without protein, which indicates that the seed region is crucial for efficiently searching the correct target by accelerating the binding rate and dissociating fast from the wrong target.

Traditional Sanctions Against the Button Tribe Elopement in the Labuhan Regional Court Judge

This research aims to explore the application of customary sanctions in eloping cases that are resolved through lawsuits in court through the existence of Decision No. 4 / Pdt.G / 2020 / PN Lbh. The elopement was carried out by a male woman who is a buton tribe outside the buton area. The family of the woman as plaintiff filed a lawsuit for material and immaterial damages, but the lawsuit was declared indible by the Panel of Judges. In this study conducted an in-depth review of whether the plaintiff's lawsuit can be interpreted based on customary law, whether legal considerations and judge's rulings have been oriented to Buton customary law. Research uses normative research methods, with secondary data in the form of primary legal materials and secondary legal materials, as well as court rulings. Analysis of primary legal materials is carried out description, systematization, analysis, interpretation and assessing buton customary law. Legal considerations used by judges include relative competence which in essence the Labuha District Court is not authorized to examine and adjudicate cases a quo because previously customary deliberations have been carried out 3 (three) times in resolving aquo cases, which then imposed customary fines based on buton tribal customs. by indigenous buton tribal figures to Defendant, the reason Plaintiff is not a buton tribe but a kei tribe, therefore does not have the right to file a lawsuit for customary fines buton against Defendant so that the Plaintiff's lawsuit is wrong target, and Defendant is incomplete, there are still people who must act as Defendants or withdrawn Defendants and therefore the lawsuit contains error in persona in the form of plurium litis consortium , in the sense that the lawsuit filed is less.

TAT: Targeted backdoor attacks against visual object tracking

Visual object tracking (VOT) is a fundamental computer vision task that aims to track a target in a sequence of video frames. It has been broadly adopted in safety- and security-critical applications, such as self-driving systems and traffic control systems. However, the VOT models (i.e., the trackers) that rely on third-party training resources face a severe threat of backdoor attacks, which refer to the type of the attacks that poison a portion of training data and mislead the tracker to track a wrong target. A surge of research interest has arisen in backdoor attacks in the domain of image classification, as a measure to expose the potential security risks of the classifiers and inspire new defense techniques. Despite the prosperity of the research in backdoor attacks in image classification, there still lacks investigation in backdoor attacks against VOT, due to their unique challenges: first, the architecture of a VOT model is much more complicated than that of an image classifier; second, VOT targets a sequence of video frames rather than individual images. To bridge the gap, we propose a novel and effective targeted backdoor attack approach TAT specifically against VOT tasks. In particular, TAT includes a basic version TAT-BA that can achieve effective and stealthy backdoor attacks against VOT trackers, and an advanced version TAT-DA that can evade two representative defense techniques. Our large-scale experimental evaluation demonstrates the effectiveness and the stealthiness of TAT. Moreover, we also demonstrate the performances of TAT-BA under real-world settings and the abilities of TAT-DA to counter defense techniques. The code will be available at https://github.com/MisakaZipi/TAT.

VisionICE: Air–Ground Integrated Intelligent Cognition Visual Enhancement System Based on a UAV

Post-disaster search and rescue is critical to disaster response and recovery efforts and is often conducted in hazardous and challenging environments. However, the existing post-disaster search and rescue operations have problems such as low efficiency, limited search range, difficulty in identifying the nature of the target, and wrong target location. Therefore, this study develops an air–ground integrated intelligent cognition visual enhancement system based on a UAV (VisionICE). The technique combines a portable AR display device, a camera-equipped helmet, and a quadcopter UAV for efficient patrols over a wide area. First, the system utilizes wireless image sensors on the UAV and helmet to capture images from the air and ground views. Using the YOLOv7 algorithm, the cloud server calculates and analyzes these visual data to accurately identify and detect targets. Lastly, the AR display device obtains real-time intelligent cognitive results. The system allows personnel to simultaneously acquire air and ground dual views and achieve brilliant cognitive results and immersive visual experiences in real time. The findings indicate that the system demonstrates significant recognition accuracy and mobility. In contrast to conventional post-disaster search and rescue operations, the system can autonomously identify and track targets of interest, addressing the difficulty of a person needing help to conduct field inspections in particular environments. At the same time, the system can issue potential threat or anomaly alerts to searchers, significantly enhancing their situational awareness capabilities.

Adversarial Reinforced Instruction Attacker for Robust Vision-Language Navigation.

Language instruction plays an essential role in the natural language grounded navigation tasks. However, navigators trained with limited human-annotated instructions may have difficulties in accurately capturing key information from the complicated instruction at different timesteps, leading to poor navigation performance. In this paper, we exploit to train a more robust navigator which is capable of dynamically extracting crucial factors from the long instruction, by using an adversarial attacking paradigm. Specifically, we propose a Dynamic Reinforced Instruction Attacker (DR-Attacker), which learns to mislead the navigator to move to the wrong target by destroying the most instructive information in instructions at different timesteps. By formulating the perturbation generation as a Markov Decision Process, DR-Attacker is optimized by the reinforcement learning algorithm to generate perturbed instructions sequentially during the navigation, according to a learnable attack score. Then, the perturbed instructions, which serve as hard samples, are used for improving the robustness of the navigator with an effective adversarial training strategy and an auxiliary self-supervised reasoning task. Experimental results on both Vision-and-Language Navigation (VLN) and Navigation from Dialog History (NDH) tasks show the superiority of our proposed method over state-of-the-art methods. Moreover, the visualization analysis shows the effectiveness of the proposed DR-Attacker, which can successfully attack crucial information in the instructions at different timesteps. Code is available at https://github.com/expectorlin/DR-Attacker.

DESAIN PEMBELAJARAN MODEL KEMP DAN IMPLEMENTASINYA DENGAN TEKNIK JIGSAW

Various kinds of events with the development of the times in the world of education today that have an impact on the quality of education. First, there are many teachers who find it difficult and complain in designing or designing learning using learning media so that the wrong target occurs. Second, the negative mindset of the teacher that teaching is troublesome, tiring, and difficult. Third, various kinds of student characters that can cause confusion for teachers, where to start educating them. Fourth, the tight competition in the world of education is the impact of globalization and MEA so that it demands quality education and is judged by the output of its graduates. The author provides answers to the problems presented, namely the application of the Kemp model of learning design with details of setting learning objectives, analyzing student characteristics, identifying materials, determining learning, determining pre-tests, determining teaching and learning activities, coordinating supporting facilities, and evaluating to facilitate teachers in designing effective, efficient and quality learning.

ANALISIS STRATEGI PEMASARAN DALAM MENARIK MINAT NASABAH UNTUK MENGAJUKAN PINJAMAN DANA PADA PT.BPR PARO DANA

Bank Syariah Mandiri Gorontalo branch as one of the sharia banks in Gorontalo Province continues to improve marketing strategies for buyers in order to achieve the wrong target company by increasing the number of partners for BSM Implants financing products. In terms of type selection and financing, BSM Implants is actually quite interesting because this financing product cannot be found in other Islamic banks. This discusses the technique and quality of promotion from the marketing of the implants themselves. The formulation of the problem in this study is whether it can promote the interests proposed by Implants at the Syariah Syariah Bank of Gorontalo Branch. This research was conducted using quantitative methods provided The population in this study was the BSM Implants that made installments in the period 2018. And the sample was as much as 70% obtained from the BSM Implants Implants 2018 installment research fund. This research uses multiple regression analysis method. And has a significant level of 0.05. Data collection methods in this study use the collection, filling out forms, and data collection in accordance with the problems to be collected. The results showed that testing between promotion variables towards interest in financing implants shows that promotion variables are important to interest in BSM implant financing at the Gorontalo branch of Bank Syariah Mandiri.

Describing and Quantifying Wrong-Patient Medication Errors Through a Study of Incident Reports.

PurposeOur aim was to inform a new definition of wrong-patient errors, obtained through an analysis of incident reports related to medication errors.MethodsWe investigated wrong-patient medication errors in incident reports voluntarily reported by medical staff using a web-based incident reporting system from 2015 to 2016 at a university hospital in Japan. Incident report content was separately evaluated by four evaluators using investigational methods for clinical incidents from the Clinical Risk Unit and the Association of Litigation and Risk Management. They investigated whether it was the patient or drug that was incorrectly chosen during wrong-patient errors in drug administration in incident reports and assessed contributory factors which affected the error occurrence. The evaluators integrated the results and interpreted them together.ResultsOut of a total 4337 IRs, only 30 cases (2%) contained wrong-patient errors in medication administration. The cases where the intended drugs were administered to incorrect patients occurred less frequently than cases where the wrong drugs were administered to the intended patients through the investigation of wrong targets. After a discussion, the evaluators concluded that the patient - drug/CPOE screen mismatch, caused by choosing the wrong patient, drug, or CPOE screen (mix-ups), occurred in the wrong-patient medication errors. These errors were caused by three conditions: (1) where two patients/drugs were listed next to one another, (2) where two patients’ last names/drugs’ names were the same, and (3) where the patient/drug/CPOE screen in front of the staff involved was believed to be the correct one. Additionally, these errors also involved insufficient confirmation, which led to failure to detect and correct the mismatch occurrences.ConclusionBased on our study, we propose a new definition of wrong-patient medication errors: they consisted of choosing a wrong target and insufficient confirmation. We will investigate other types of wrong-patient errors to apply this definition.

Opioids and cancer survival: are we looking in the wrong place?

There is a controversial narrative in the anaesthetic literature suggesting that anaesthetic technique (including opioids) may be detrimental to survival after tumour resection. The initial observations were retrospective. Several prospective studies are ongoing; one in breast cancer has reported no adverse outcome. The evidence for an effect of opioids stems from three pieces of information: (1) opioids depress the immune system, (2) opioids potentially promote angiogenesis, and (3) opioids potentially support tumour growth. Although the evidence for (2)/(3) is unclear, combinations of these effects are beneficial to tumours and potentially promote metastatic reseeding. Accepted wisdom suggests that opioid effects are driven by opioid receptor activation but the presence of opioid receptors on immune cells for example is unlikely. Immune cells, vascular endothelium and a range of tumour cells express Toll-like receptor 4 (TLR4) receptors (for Gram-negative bacterial wall components), and there is growing evidence for opioids interacting with this alternative receptor; and for some there is paradoxical naloxone sensitivity. Is the focus on opioid receptors and cancer the wrong target? TLR4 receptor activation produces immune activation, stimulates angiogenesis, and supports tumour survival. We know that some opioids are more immune suppressive than others (there is no such comparative information for angiogenesis and tumour survival); this may correlate with TLR4 activation. If there are clusters of opioids that have more opioid than TLR4 profiles and vice versa, this may influence outcome. If this is the case, then evidence-based advice could be given for perioperative use in the oncology-anaesthesia setting.

TuSeSy: An Intelligent Turntable Servo System for Tracking Aircraft and Parachutes Automatically

Tracking aircraft and parachutes plays a vital role in airdrop experiments. It is necessary to study a parachute’s open state and flight trajectory. More scholars are looking into how to efficiently and accurately obtain parachute deformation data and trajectory data. At present, the actual data collection primarily involves experimenters holding high-definition high-speed cameras to track and shoot parachutes to obtain the image sequences of the parachutes during the airdrop process. However, these methods cannot obtain the trajectories of the parachutes and they are susceptible to interference from human factors. In this paper, we designed TuSeSy, an intelligent turntable servo system that can track the aircraft and parachutes in airdrop tests automatically. Specifically, TuSeSy generates the control commands according to the differences between the actual taken images and the inferred images by tracking algorithms (so as to actually track the target). In addition, we propose an effective multi-target tracking switch algorithm based on the image frame difference and optical flow, to achieve real-time switching from the aircraft to the parachute in an airdrop test. To evaluate the performance of TuSeSy, we conducted extensive experiments; the experimental results show that TuSeSy not only solves the problem of wrong target tracking, but it also reduces computational overhead. Moreover, the multi-target tracking switch algorithm has higher computing efficiency and reliability compared to other tracking switch approaches, ensuring the practical applications of the turntable servo system.

Cross-subject spatial filter transfer method for SSVEP-EEG feature recognition

Objective. Steady-state visual evoked potential (SSVEP) is an important control method of the brain–computer interface (BCI) system. The development of an efficient SSVEP feature decoding algorithm is the core issue in SSVEP-BCI. It has been proposed to use user training data to reduce the spontaneous electroencephalogram activity interference on SSVEP response, thereby improving the feature recognition accuracy of the SSVEP signal. Nevertheless, the tedious data collection process increases the mental fatigue of the user and severely affects the applicability of the BCI system. Approach. A cross-subject spatial filter transfer (CSSFT) method that transfer the existing user model with good SSVEP response to the new user test data without collecting any training data from the new user is proposed. Main results. Experimental results demonstrate that the transfer model increases the distinction of the feature discriminant coefficient between the gaze following target and the non-gaze following target and accurately identifies the wrong target in the fundamental algorithm model. The public datasets show that the CSSFT method significantly increases the recognition performance of canonical correlation analysis (CCA) and filter bank CCA. Additionally, when the data used to calculate the transfer model contains one data block only, the CSSFT method retains its effective feature recognition capabilities. Significance. The proposed method requires no tedious data calibration process for new users, provides an effective technical solution for the transfer of the cross-subject model, and has potential application value for promoting the application of the BCI system.